Miracle-dz/UniFAR-FTUs huggingface dataset:
Biostratigraphy of the Endothiodon Assemblage Zone (Beaufort Group, Karoo Supergroup), South Africa

The Endothiodon Assemblage Zone is the third oldest tetrapod biozone of the Beaufort Group (Adelaide Subgroup, Karoo Supergroup). It is situated between the underlying Tapinocephalus and overlying Cistecephalus assemblage zones and in the southwestern part of the basin corresponds to the majority of the Poortjie and Hoedemaker members of the Teekloof Formation. It is characterised by the dicynodont genus Endothiodon, especially in the lower part of assemblage zone, and records early ecosystem recovery from the Capitanian mass extinction. It also contains the lowest occurrence in the Karoo Basin of cynodont therapsids, eutherocephalians, bidentalian dicynodonts, and diapsids. The biozone reaches a maximum thickness of around 250 m in the southwestern part of the basin. We propose a two-fold subdivision into a lower Lycosuchus - Eunotosaurus Subzone (equivalent to the upper two-thirds of the former Pristerognathus Assemblage Zone) and an upper Tropidostoma - Gorgonops Subzone (equivalent to the former Tropidostoma Assemblage Zone), with the contact deﬁned by the ﬁrst appearance of Tropidostoma dubium. The Endothiodon Assemblage Zone is terminated by the ﬁrst appearance of Aulacephalodon bainii.
Research on SLAM Drift Reduction Mechanism Based on Point Cloud Segmentation Semantic Information

This paper combines the semantic segmentation of scenes with Simultaneous localization and Mapping (SLAM) technology to build a three-dimensional semantic map. The input sequence is selected by ORB-SLAM for key frame selection, and the scene’s semantic segmentation is performed in the corresponding point cloud data. We use a new 3D segmentation framework, which can effectively simulate the local structure of point cloud. A drift reduction mechanism based on semantic constraints and Bundle Adjustment (BA) constraints was proposed. This mechanism considers the three-dimensional objects, feature points and camera pose for semantic recognition in the scene, and integrates them into the back-end BA to optimize them. The final experimental results show that compared with the current popular ORB-SLAM, this mechanism can reduce the system’s translation drift error by 18.8%.
Impetus and influences of Online Learning Interaction based on Non-English Lecturers’ Perspectives in global class program

The purpose of this paper aimed to investigate the impetus and influences of executing Online Learning Interaction in the Global Class Program. There were sixteen university lecturers involved in this study. Data were collected through an online survey using Google form. The analysis of data used descriptive analysis using percentages. The results indicate that Online Learning Interaction carried out in English classrooms resulted in positive effects for university lecturers. The most influential effect of executing Online Learning Interaction to facilitate lessons in English was aiding to enhance technological skills in learning. Then, the second biggest effect was facilitating to transformation global vision or mindset of the lecturers. The third and fourth places were improving the effectiveness of communication in learning and enhance delivering skills. Moreover, the study indicates that ICT satisfaction in learning was the dominant motive to execute Online Learning Interaction in English Classroom contexts.
Treatment patterns of patients with multiple sclerosis in Guangzhou, China

Background & Objective: Disease-modifying treatments (DMTs) for multiple sclerosis (MS) are widely used in Western countries. In China, however, the current treatment patterns of MS patients are not well characterized. This is to explore the gap between the current treatments in Guangzhou, Southern China and those given in Western countries. Methods: We performed a survey of MS patients at department of neurology, a tertiary MS referral centre in Guangzhou, concerning treatments of MS in Southern China. The clinical data in patients were collected. The initial treatment, drug withdrawal or switching profile, and therapeutic effect of existing treatments in MS patients were analyzed. Results: The ratio of MS patients who receive DMTs in Guangzhou China is extremely low. Among the 178 patients studied, only 28.09% received initial treatment with DMTs. MS patients who receive initial treatment with first-line DMTs have higher drug withdrawal rates (32.6%) and drug switching rates (30.43%) than those of western populations. The main reasons for withdrawal of first-line DMTs were doctor’s advice (maintenance of remission)(40.00%), economic burden(20.00%), and no channels to buy drugs(13.33%). In MS patients initially treated with first-line DMTs who switched to other drugs, a gap between treatments was common (8/14; 57.14%). There were 18 patients with highly active MS receiving treatment with rituximab. Annual relapse rate after treatment significantly decreased than that before treatment (0.74 vs. 1.50 , P < 0.001). Conclusions: DMTs for MS in Guangzhou, Southern China appear to lag behind those in Western countries. Much work is needed to improve drug accessibility and affordability of DMTs in China. Rituximab is an option for highly active MS in limited medical-resource countries.
Zoonotic emergence of coronavirus: a potential public risk for Latin America

Coronaviruses are common throughout the world and six of them can make humans sick. Some coronaviruses have existed for a long time and commonly cause mild to moderate illnesses around the world. However, the two most recent coronaviruses, SARS-Coronavirus (SARS-CoV) and Mers-Coronavirus (MERS-CoV) frequently cause severe disease. However, with the exception of the previous coronaviruses, its role in respiratory disease in humans is still a matter of debate. In a multicentre study, where some countries in Latin America and Australia were considered, among others, which included 6.266 pediatric patients with symptoms compatible with influenza; the highest prevalence was Rhinovirus /Enterovirus (42%) and Coronaviruses was only 6%.
Controlling Switched Dc-Dc Converter Using ANFIS in Comparison with PID Controller

The non-linear behaviour of the Dc-Dc converters which appears mainly because of different causes such as disturbances, aging of materials, source instability which makes control process as a difficult task to overcome, many control techniques are employed such as PID controllers which works under linear operating conditions and fails with non-linear systems, so in order to reach a good dynamics, good performance and a good insensitivity to perturbations and parameter uncertainties, an artificial intelligence control strategy namely ANFIS has been used which does not need the mathematical model of the plant and automatically overcome the changing conditions as well. In this paper, a MATLAB/Simulink inspection is established to design a prototype model for such a converter with two different control principles (PID, and ANFIS) for Comparative purposes. In ANFIS controller two input parameters and one output (error signal, and rate of change in error) are considered, this voltage controller ensures better dynamic behaviour and superior performance compared to PID controller in regulating the output voltage.
Self-adjustment of candidate counsellor student who is forced in taking a guidance and counselling department

The research aims to determine the process and self-adjustment factors of guidance and counseling students to be able to maintain their status as students of guidance and counseling. This study uses a qualitative approach to the type of case study research and data collection techniques using observation and interviews. The results showed that students A, B, C, and D claimed to be forced to take the direction of guidance and counseling. Until the third semester of students A and B were able to adjust themselves, students A and B considered this a fate that must be lived and reacted with grace and even now they felt solid with the direction of guidance and counseling. While students C and D have not been able to adjust because they are unable to live it. Students C and D look for alternative roads by moving majors as desired.
Microaffirmations as a tool to support the process of inclusive education

The main question that guides this work concerns the intentional use of microaffirmations in support of the inclusive education process. We will describe how microaffirmations can help to achieve significant goals for inclusive education both inside and outside the classroom (Ainscow 2015; Messiou et al., 2016). Specifically, attention will be focused on how support and recognition communicated through microaffirmations can improve sense of belonging as an essential element of creating safe spaces for learning (Mitchell, 2014). The theoretical overview provided here sets the groundwork for a research study, to be implemented in Italy and the United States, where inclusion and microaffirmation is the binomial investigated.
Graphene derivatives potentiate the activity of antibiotics against Enterococcus faecium, Klebsiella pneumoniae and Escherichia coli

Antibiotic resistance in bacteria is developing at a faster rate than new antibiotics can be discovered. This study investigated the antimicrobial activity of several carbon-based derivative compounds alone and in combination with clinically relevant antibiotics against key ESKAPE pathogens Enterococcus faecium, Klebsiella pneumoniae and Escherichia coli. Three compounds, graphite, graphene and graphene oxide, in conjunction with ciprofloxacin (CIP), chloramphenicol (CHL) and piperacillin/tazobactam (TZP) were examined using fractional inhibitory concentration (FIC) testing. CIP combined with graphene demonstrated additive antimicrobial activity against E. faecium compared to individual application. Furthermore, CIP supplemented with graphene, graphene oxide or graphite showed additive activity with ∑FIC values of 1.0 against K. pneumoniae, whereas only TZP showed ∑FIC values <1.0 with graphene oxide. For E. coli, the antibiotic activity of CIP was enhanced with graphene, graphene oxide or graphite, whereas only graphite and graphene enhanced the activity of CHL and TZP respectively. Graphite and graphene oxide caused significant antagonism (∑FIC ˃ 4.0) in conjunction with TZP against E. coli. In conclusion, the results demonstrate the potential to supplement clinically relevant antibiotics with carbon-based graphene, graphene oxide derivative or graphite for use as an additive supplement for novel systemic or topical treatment solutions against key priority pathogens.
Privacy-Preserving Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data

Abstract-Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. Cloud computing provides individuals and enterprises massive computing power and scalable storage capacities to support a variety of big data applications in domains like health care and scientific research, therefore more and more data owners are involved to outsource their data on cloud servers for great convenience in data management and mining. Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. However, sensitive data should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document retrieval. In this paper, we present a secure multi-keyword ranked search scheme over encrypted cloud data. We investigate the Multi-keyword top-k search problem for data encryption against privacy breaches, and attempt to identify an efficient and secure solution to this problem. Specifically, for the privacy concern of query data, we construct a database query search method.
Research on Target-Driven Navigation of Mobile Robot Based on Deep Reinforcement Learning and Preprocessing Layer

Recently, with the rise of deep reinforcement learning model, robot navigation based on this method has a huge advantage compared with traditional slam method, which has attracted extensive attention. However, when the navigation algorithm trained in the virtual environment is transferred to the real environment, the navigation performance of the robot will decline sharply because of the great difference between the virtual environment and the real environment. In order to improve the navigation ability of mobile robot, this paper implements a mobile robot navigation system based on deep reinforcement learning without environment map and only visual input. At the same time, in order to solve the problem of poor generalization ability of deep reinforcement learning from virtual environment to real environment, this paper proposes a preprocessing layer with knowledge and combines it with deep reinforcement learning module. The combined algorithm model alleviates the performance fault problem caused by the migration algorithm and the performance difference between virtual sensor and real sensor. At the end of this paper, a navigation experiment based on the turtlebot is designed, which proves that the deep reinforcement learning algorithm with the preprocessing layer can alleviate the performance fault problem caused by the migration algorithm, and have a certain ability of obstacle avoidance and avoidance without the environment map.
Caractérisation physico-chimique des films multicouches de polyélectrolytes à base de polysaccharides et de polypeptides en vue d'applications dans le domaine des biomatériaux

Les multicouches de poyelectrolytes, systemes auto-assembles par adsorptions successives de polycations et de polyanions, ouvrent des perspectives dans le domaine de la fonctionnalisation des biomateriaux. L’objectif du present travail a concerne le developpement d’un biomateriau multistratifie a base de films multicouches et de gels d’alginate. Les exigences de biocompatibilite et de biodegradabilite nous ont orientee vers des multicouches a base de polypeptides et de polysaccharides. Nos travaux s’articulent autour de trois axes principaux : (i) Tout d’abord, nous avons compare le comportement des complexes en solution afin de comprendre comment ils interviennent lors de la construction des films multicouches. Cette etude suggere la possibilite de predire, par un simple melange des deux polyelectrolytes de signes opposes, s’ils sont susceptibles ou non de former un film multicouche sous certaines conditions de force ionique. (ii) Dans un deuxieme temps, nous nous sommes interesses a l’influence du changement de force ionique du surnageant sur le film multicouche PLL/HA preforme. Nous avons montre que l’augmentation ou la diminution de la force ionique induit respectivement un gonflement ou un degonflement du film, accompagne d’une liberation des polyelectrolytes avec l’apparition de cavites dans certains cas. Ces changements de force ionique conduisent a la dissolution du film. (iii) Le troisieme volet a consiste a determiner les meilleures conditions permettant d’elaborer, par la methode de pulverisation, un biomateriau multi-stratifie en vue d’application dans le domaine de l’ingenierie tissulaire. Ainsi, des films multicouches a base de polypeptides et de polysaccharides ont ete superposes avec des gels d’alginates. Les films multicouches joueraient le role de reservoir de principes actifs et les gels d’alginate contiendraient des cellules.
Highly Active Transition Metal-Promoted CuCeMgAlO Mixed Oxide Catalysts Obtained from Multicationic LDH Precursors for the Total Oxidation of Methane

To improve the catalytic performance of an active layered double hydroxide (LDH)-derived CuCeMgAlO mixed oxide catalyst in the total oxidation of methane, it was promoted with different transition-metal cations. Thus, two series of multicationic mixed oxides were prepared by the thermal decomposition at 750 °C of their corresponding LDH precursors synthesized by coprecipitation at constant pH of 10 under ambient atmosphere. The first series of catalysts consisted of four M(3)CuCeMgAlO mixed oxides containing 3 at. % M (M = Mn, Fe, Co, Ni), 15 at. % Cu, 10 at. % Ce (at.% with respect to cations), and with Mg/Al atomic ratio fixed to 3. The second series consisted of four Co(x)CuCeMgAlO mixed oxides with x = 1, 3, 6, and 9 at. % Co, while keeping constant the Cu and Ce contents and the Mg/Al atomic ratio. All the mixed oxides were characterized by powder X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM) coupled with X-ray energy dispersion analysis (EDX), X-ray photoelectron spectroscopy (XPS), nitrogen adsorption-desorption at −196 °C, temperature-programmed reduction under hydrogen (H2-TPR), and diffuse reflectance UV-VIS spectroscopy (DR UV-VIS), while thermogravimetric and differential thermal analyses (TG-DTG-DTA) together with XRD were used for the LDH precursors. The catalysts were evaluated in the total oxidation of methane, a test reaction for volatile organic compounds (VOC) abatement. Their catalytic performance was explained in correlation with their physicochemical properties and was compared with that of a reference Pd/Al2O3 catalyst. Among the mixed oxides studied, Co(3)CuCeMgAlO was found to be the most active catalyst, with a temperature corresponding to 50% methane conversion (T50) of 438 °C, which was only 19 °C higher than that of a reference Pd/Al2O3 catalyst. On the other hand, this T50 value was ca. 25 °C lower than that observed for the unpromoted CuCeMgAlO system, accounting for the improved performance of the Co-promoted catalyst, which also showed a good stability on stream.
Hydrazines and Azo-Compounds in the Synthesis of Heterocycles Comprising N-N Bond

Abstract – The synthesis of nitrogen containing heterocycles is of great importance in modern science, owing to their valuable biological properties, and endocyclic hydrazinocycles are no exception. There are methods that enable the transformation of amines to hydrazines, however the use of hydrazine derivatives and azo-compounds as starting materials is both logical and straightforward. In this review we aimed to summarize the methods that use simple hydrazines and azo-compounds for the synthesis of these heterocycles. We begin with simple stoichiometric alkylation of hydrazines and later on move to catalytic systems. Finally, we provide an overview of the advances in the field of azomethine imines chemistry.
Bestimator™: a novel model-based algorithm for robust estimation of battery SoC

Accurately estimating the state of charge of batteries is an essential part of battery management systems. Indeed, it conditions the ability to maintain the battery in a safe region with respect to ageing, and to ensure service availability when needed. This paper presents Bestimator™, CSEM’s novel estimation algorithm. This algorithm builds on a robust, interpretable electrical circuit model of the battery, and uses an extended Kalman filter to estimate the state of charge and correct parameters. Benchmarking against state-of-the-art estimators shows that Bestimator™ outperforms them by immediately reaching and maintaining over time an estimation error below 2%.
Impact of deposition of indium tin oxide double layers on hydrogenated amorphous silicon/crystalline silicon heterojunction

We report on the effect of sputtering deposition of indium tin oxide (ITO) as the transparent conductive oxide layer on the passivation performance of hydrogenated amorphous silicon/crystalline silicon heterojunctions. The influence of sputtering damage on passivation performance is studied by varying the ITO layer thickness from 0 nm to 80 nm. The passivation performance decreases considerably up to 10 nm and increases gradually from 20 nm to 80 nm, indicating that damage and recovery stages are present during the sputtering process. We focus on the injection energy as the cause of the recovery phenomenon. To optimize the passivation performance by intentionally enhancing the effect of the recovery stage while minimizing the initial damage at the heterointerface, we develop a two-step sputtering process in which the radiofrequency power is changed from 50 W to 100 W during deposition to prepare ITO double layers. Two step sputtering gives the lower damage, and the properties of ITO double layers are better than those of ITO single layers. These results show that two-step sputtering can realize greater a-Si:H passivation. Furthermore, better optical properties are obtained in ITO double layers compared with conventional ITO single layers. Therefore, modulating the radiofrequency power during ITO deposition can offer higher conversion efficiency.
Still a family firm after knowledge transformation? Generational change and enterprise development of plastic manufacturing firms in Malaysia

Abstract This article focuses the changes in the family firms following the development of knowledge transformation with innovation across generational changes, with specific attention given top plastic manufacturing. The case study method is used to examine the impact of generational tracing by tracing the changes in objective, 3Ms and innovation when the new generation attempts to transform the tacit knowledge of the founder by developing the quality products. The results provide an insight into key changes of 3Ms, concept developed by Alfred Chandler, which refers to a firm’s capacity to develop its manufacturing, management and marketing by codifying tacit knowledge and adopting professional management. The changes in the knowledge transformation indicate the cooperative ties with government and MNCs could serve to facilitate enterprise development of plastic manufacturing in Malaysia.
Semantic Segmentation of Remote Sensing Images Based on Multi-Model Fusion

Convolutional neural networks have created a new field in the research of semantic segmentation of remote sensing images. However, different network structures have different effects on the semantic segmentation of different land types. In this paper, the original data set is expanded, and an improved U-Net model is used to train a model for each type of feature target. Then combined with conditional random field (CRF) and image overlapping strategy for optimization processing; Finally, the two binary classification models obtained by training are fused to obtain multi-classified semantic segmentation images. Solve the obvious problem of large-scale remote sensing image edge stitching. The experimental results show that this method has higher accuracy in solving the segmentation of large-scale remote sensing images.