Miracle-dz/UniFAR-FTUs huggingface dataset:
Selective direct hydroxylation of benzene to phenol with hydrogen peroxide by iron and vanadyl based homogeneous and heterogeneous catalysts

A series of first row transition metal complexes with Schiff base ligands or with readily available acetylacetonate ligands were screened as homogeneous catalysts in the challenging direct hydroxylation of benzene to phenol under mild conditions. Phenol was the main product of the oxidation of benzene in acetonitrile at 50 °C using hydrogen peroxide as the oxidant. The Fe(II/III) complexes with Schiff base ligands were the best homogeneous catalysts using only 1% mol based on the substrate with very high selectivities. All the Fe(II/III) complexes were more selective towards phenol than the VO(IV) complexes. The Fe(II/III) Schiff base complexes were more active than the readily available Fe(II/III) acetylacetonate complexes, whereas the opposite was observed for the VO(IV) complexes. The room temperature reaction gave a significantly lower phenol yield. Due to their easy anchoring, the readily available Fe(II), Fe(III) and VO(IV) acetylacetonate complexes were immobilized onto economical porous supports, hexagonal mesoporous silica and activated carbon, which were previously functionalized with amine groups. An Fe(III) Schiff base complex was also anchored onto these materials activated with a NaOH solution. The materials were characterized by elemental analysis, ICP-AES, FTIR spectroscopy, adsorption isotherm analysis at 77 K and TG analysis, showing that both porous materials were conveniently functionalized and that the metal complexes could be effectively anchored onto these materials. All the heterogeneous catalysts prepared were active and selective in the direct oxidation of benzene to phenol with higher yield and selectivity than the original metal salts or complex in homogeneous phase. For the immobilized Fe(II/III) acetylacetonate complexes, a significant improvement in the phenol yields was observed in comparison with the corresponding homogeneous phase catalysts, showing that the incorporation of nitrogen atoms on the metal coordination sphere improves the catalytic activity. The heterogeneous catalysts could also be recycled by simple filtration and re-used in at least three more consecutive cycles without significant loss of catalytic activity. Phenol yields comparable to or higher than the best reported in the literature were obtained.
BORLU BİLEŞİKLER VE SU İTİCİ MADDELERİN CENNET AĞACI ODUNUNUN FİZİKSEL ÖZELLİKLERİ ÜZERİNE ETKİLERİ / PHYSICAL PROPERTIES OF HEAVEN WOOD TREATED WITH BORATES AND WATER REPELLENTS

Bu calisma, cesitli borlu bilesikler ve monomer su itici maddeler (SIM)’le muamele edilen cennet agaci odununun yogunluk, yanma ve su alma gibi bazi fiziksel ozelliklerinin belirlenmesi amaclarina yonelik olarak hazirlanmistir. Calismada borlu bilesiklerden , borik asit (BA), boraks(Bx) ve borik ait ve boraks karisimi (7:3; agirlik:agirlik); monomer su itici maddelerden metilmetakrilat (MMA), Stiren (St), stiren + metilmetakrilat (7.3; hacim:hacim) ve izosiyanat (ISO) kullanilmistir. Calismada ayrica ticari emprenye maddelerinden Vacsol (V), immersol WR, polietilen glikol-400 (PEG-400), Tanalith-CBC ve fosforik asit (FA) karsilastirma amaciyla denenmistir. Deney sonuclarina gore; en yuksek ozgul agirlik degeri ISO ile muamele edilen deney orneklerinde elde edilmistir (0.80 gr/cm3). Calismada kullanilan monomer maddeler, orneklerin su alma oraninda onemli derecede azalma saglarken; borlu bilesikler uzerine uygulanan monomer muamelesi de benzer etkiyi gostermistir. Calismada stiren ve metilmetakrilat karisimi su alimini azaltan en etkili uygulama olmustur. Yanma sonucu olusan agirlik kaybi acisindan BA+Bx karisimi % 63 ‘luk agirlik kaybi orani ile en olumlu sonucu vermistir. This study was designed to investigate some physical properties of heaven wood such as specific gravity, water absorbtion levels and combustion properties treated with borates and water repellent monomers. Three different monomers such as styrene (St), methyl metacrylate (MMA) and St-MMA mixture (70:30; v:v) icocyanate (ISO) were used. Also some commercial preservatives Vacsol (V), Immersol WR, Tanalith-CBC polyethylene glycol (PEG-400) and phosphoric acid were used for comparision. Accordingto the results; wood specimens treated with ISO gave the highest specific gravity value. (0.80 gr/cm3 ). All water repellent monomer chemicals significantly reduced water absorption levels of wood specimens. Secondary treatments with monomers on borates showed same effect. Styrene and MMA mixture was the most effective in reducing water absorbtion levels of wood specimens. Borates exhibit their well known fire-retardant effect at some extent. The lowest mass losses were recorded with the specimens treated with boric acid and borax mixture (% 63).
A Scientometric Analysis of Publications Related to Predictive Medicine

Due to the increasing popularity of new research in medicine thisstudy was conducted to determine recent research trends of predictive, preventive and personalized medicine (PPM). We identified the terms relevant to PPM using own search engine based on neural network processing in PubMed database. We extracted initially about 15000 articles. Then we carried out the statistical analysis for identifying research trends. The article presents the results of solving the problem of evaluating research topics at the level of thematic clusters in a separate subject area. An approach based on the analysis of article titles has been implemented. Identification of terms, connections between them and thematic clustering were carried out using the free software VOSViewer, which allows to extract terms in the form of noun phrases, as well as to cluster them.
Impact of Pandemic COVID-19 to the Online Learning: Case of Higher Education Institution in Malaysia

This study aim is to examine and evaluate the impact of COVID-19 on education systems, which is the implementation of online learning (OL) during Movement Control Order (MCO) to higher learning education institution in Malaysia. A questionnaire was developed, and a random sampling of data was performed. Three hundred and fifty-two samples were collected using the Smart PLS-Structural Equation Modeling (SEM) technique to analyze the results. The study shows that acceptance, usability, satisfaction, and technical skills play a pivotal role in inspiring online learning effectiveness for the institution of higher education. Such consideration allows the entire higher education institution in Malaysia to recognize the importance of online learning in education in a consistent way. All the factors influence the sustained positive efficacy except acceptance of online learning. The present study covers only the institutions of higher learning. Entire elementary and secondary school students also participate in online learning, so this group can also be included for further studies. The research would continue to develop the online learning environment, and the study of higher education organizations is gradually embracing learning as an alternative to conventional classroom learning for current students and as a means to extend its scope to new students. Adopting online learning and its technologies requires significant investment in the staff, resources, energy, and space that administrators and those in educational leadership need to be justifiable. Just a few have explored the effect of COVID-19 on the education system and how online learning are conducted during MCO and using Smart PLS is a novel concept and it is a research of its kind from first hand.
Influence Of Fine-Grained Montmorillonite On Microfungal Pellets Growth In Aqueous Suspensions

Abstract The paper presents an inhibition effect of clay mineral – montmorillonite – on the growth of microscopic filamentous fungus Aspergillus niger in the aqueous solution. The significant reduction in growth of the final size of spherical fungal pellets as well as total amount of produced microbial biomass was found out. Within the observed range of additions of clay mineral of 1, 5, 10, 15 and 20 g in the total volume of the 80 ml suspension, this size was in indirect relation to the weight of montmorillonite. However, the most significant inhibition effect was observed at the lowest concentration of the sorbent (1 g). Microscopic analysis of pellets referred to the presence of mineral particles in their pore structure and the distribution of particles in the spatial structure of fungal hyphae was variable. The experiment clearly demonstrated an inhibition effect of montmorillonite. This inhibition could be answered by the experiments focused on the detection of the influence of size and shape of inorganic sorption particles together with the influence of the physicochemical properties of its surface. It could be stated that the simultaneous application of the microscopic fungus Aspergillus niger and the clay mineral montmorillonite for decontamination of waste waters should be disadvantage due to their interaction if compared with the decontamination based on bioaccumulation and sorption separately.
The Effect and Impact of Signals on Investing Decisions in Reward-Based Crowdfunding: A Comparative Study of China and the United Kingdom

When traditional financial institutions faced difficulties in the task of assisting micro, small and medium-sized enterprises (MSMEs) with capital allocations, crowdfunding can upsurge as an innovative and vibrant vehicle that can support and assist the activity of such MSME’s, by financing their activity and instrumenting the process of risk-sharing. Simultaneously with its enormous growth and popularity, crowdfunding is faced by several key challenges, one of biggest such challenges referring to the problem of information asymmetry that can exist between fundraisers and potential backers. Based on the signaling theory, a research taxonomy has been developed for a comparative analysis between China and the UK. This has been accomplished by retrieving secondary data from the following crowdfunding platforms: Dreamore (Chinese platform) and Crowdfunder (UK platform). The objective of the study is to investigate both the effect and the impact that signals (goal setting, project comments and updates) have upon mitigating the problem of information asymmetry, in order to make the project successful. We have thus deployed an Ordinary Least Square (OLS) regression and validated the models through a robustness check. The findings reveal that signals actively mitigate the problem of information asymmetry in both countries, but this varies in the sense that higher goal setting has a more positive/impactful relationship with project success in the UK than it does in China. Project comments are more positively associated with project success in China as compared to the UK, whereas project updates are more negatively related to project success in China as compared to the UK. These findings demonstrate the importance that signals have upon successful crowdfunding activities/campaigns, highlighting the theoretical and practical influence and relevance for potential fundraisers in the two aforementioned economies.
Detection of DDoS Attacks Using Supervised Learning Technique

The development in digital technologies has been amplified by the drastic growth in the field of digital media applications and it changes the entire life style of the people. The electronic devices and digital contents are becoming more notable and popular among the users. As an emerging research area, security has attracted a lot of attention towards security professionals, experts and practitioners. In spite of this increased interest, this field still faces manifold challenges and issues. Such a fast development in digitization contains a block with attacks from an indirect security attack called Distributed Denial of service. An attack that damages the targets, services or network. The main objective of this paper is to improve the detection rate of the DDoS attacks and to overcome these threats in order to provide a safe network. So, a novel method is proposed in this paper to detect the DDoS attacks using support vector machine. A simulation of a network traffic is created to track and capture the patterns from any type of DDoS attacks with the help of rule creation and blacklisting. Further, using rule creation and SVM model, the simulation result based on different instances of time shows the observations of the real time requests that improves the efficiency of detecting the DDoS attacks.
Image Salient Object Detection Based on K-means and Level Set Superpixel Segmentation

In order to detect and segment the salient objects in digital images to solve complex machine visual problems, this paper proposes an image salient object detection algorithm based on K-means and level set superpixel segmentation. The algorithm segments a given target image into multiple superpixel regions with similar features to abstract unnecessary details in the images, and reduce the number of colors in all superpixels by Histogram acceleration to increase computational efficiency. The saliency map obtained by calculating the distance of all superpixel in the Lab color space, and optimizes the detection effect by background prior and multi-scale spatial fusion. A large number of experiments show that the saliency detection method proposed in this paper is superior to algorithms such as SR, AC, FT, MSS, LC, CA, SF, HC and RC in accuracy, recall rate, AUC value and average absolute error.
Joint allies: Benefits and tensions of co-producing a prostate cancer app for, and with, the Black British African-Caribbean community

ABSTRACT In this paper we use a case study, the co-production of a prostate cancer app with, and for, Black British African-Caribbean communities, to discuss benefits and tensions of inclusive practice and allyship. We view our collaborators as joint partners, and joint allies, for the Black British African-Caribbean community. Here, we document the research process and highlight successful aspects of our collaboration such as mentoring, recruitment, ideas on the format and presentation of the app, supportive data collection practices, useful community feedback and promotion of the app. We also highlight points in the research process that in hindsight needed more discussion and careful negotiation. We end with some recommendations based on our experience.
A Unified Model for Bipolar Outflows from Young Stars: The Interplay of Magnetized Wide-angle Winds and Isothermal Toroids

Large-scale morphology and time evolution are investigated for the unified model of bipolar outflows outlined in Shang et al. (2006), where an outflow forms by a radially directed, wide-angle magnetized wind interacting with magnetized isothermal toroids in various quasistatic states. The primary wide-angle wind is toroidally magnetized and maintains a cylindrically stratified density profile, mimicking the asymptotic solution of the cold X-wind model. We explore the interplay between the toroidally magnetized primary wind and the surrounding toroids threaded by poloidal magnetic fields and examine how the jet and shell morphology and fine structures within them vary with the physical parameters. The variation in flatness of the density distribution in the ambient isothermal toroids helps shape the varieties of lobe morphology and collimation. The presence of a stronger ambient poloidal field helps shape the outflow, forming a magnetic cocoon and nested multilayered cavities surrounding the wind-filled lobe, which is most evident in the more open configurations of the ambient toroids. The wind–toroid interface is prone to substantial shear and thus unstable to the Kelvin–Helmholtz instability. Magnetic forces in the compressed toroidally magnetized high-velocity wind can generate vorticity, leading to nonlinear patterns within the extended magnetized mixing layers. Magnetic disturbances generated by the interplay could modulate lobe shapes, density, and velocities, giving rise to visual impressions of thicker and rugged shells and apparent episodic distribution of matter. The system maintains a quasi-self-similar evolution in time, which serves as a proxy for understanding the underlying physical mechanisms driving it.
Multi-scale Correlation Filter Tracking Algorithm Based on Feature Fusion

For the Kernel Correlation Filter (KCF) algorithm using a single feature can not fully describe the tracking target, and is susceptible to the change of the target scale, lacking the estimation of the target scale size, an improved feature fusion and multi-scale correlation filter tracking algorithm based on KCF is proposed. Firstly, in the stage of location prediction, color features and directional gradient histogram hog features are fused by feature series, and feature dimensions are added to realize target location prediction. Then the scale filter is introduced into the predicted target position to estimate the optimal target scale as the tracking result. Experimental results show that the accuracy and success rate of the improved algorithm are significantly improved compared with other classical tracking algorithms, and it can deal with scale change, occlusion, deformation and other complex situations robustly.
Using semantic field model to create information search engines

In the web infrastructure of information search, the use of semantic methods is considered to be a new round of the technology development. With the emergence of big data, a relevant issue is processing large amounts of data to extract valuable knowledge, especially for text files in natural language. Practice shows that traditional natural language search engines cannot always extract the necessary data from such data sets, as they do not take into account several subtle aspects of the language used in human speech. To solve this problem, the possibilities of using semantic search engines for text processing are being explored. This paper discusses the possible use of the semantic field model developed by the authors, to create a semantic search engine. Experiments have shown that using this model can improve the search accuracy. This model can be additionally used in creation of interactive dialogue systems.
Validation of Real Case Solving (RCS) Methodology as an Efficient Engineering Learning Tool

In recent times, new learning methodologies known as student-based methodologies have been introduced to simplify the learning process for the students and facilitate the acquisition of skills for them. Among them, problem based learning (PBL) and project-based learning (PjBL) are widely used methods in the world of education. Real case solving (RCS) is a variant of the PBL where students solve real cases through the application of the PBL methodology. RCS seems to be a relevant approach for educators, but it has an apparently limited implementation degree at the academic level. This article presents the successful implementation of four different RCS approaches in the lecturing process in five different classes in the engineering degree of University of Deusto. The initiative has been analyzed both quantitative and qualitatively; the overall performance and success rate of the students were compared with the ones acquired from conventional teaching methods. The results were found to be promising, demonstrating a significantly better performance than the traditional teaching methodologies. The successful results encouraged the university to continue working further in this direction.
Harmonic Overvoltage Analysis of Electric Railways in a Wide Frequency Range Based on Relative Frequency Relationships of the Vehicle–Grid Coupling System

Harmonic overvoltage in electric railway traction networks can pose a serious threat to the safe and stable operation of the traction power supply system (TPSS). Existing studies aim at improving the control damping of grid-connected converters, neglecting the impedance frequency characteristics (IFCs) of the actual TPSS. The applicable frequency range of these studies is relatively low, usually no more than half of the switching frequency, and there is a large gap with the actual traction network harmonic overvoltage frequency range of 750 Hz–3750 Hz. In this paper, first, the IFCs of the actual TPSS in the wide frequency range of 150 Hz–5000 Hz are obtained through field tests, and the resonant frequency distribution characteristics of TPSS are analyzed. After that, the aliasing effect of the sampling process and the sideband effect of the modulation process of the digital control of the grid-connected converter are considered. Based on the relative relationships among the inherent resonant frequency of the TPSS, sampling frequency and switching frequency, an impedance matching analysis method is proposed for the wide frequency range of the vehicle–grid coupling system. By this method, the sampling frequency and switching frequency can be decoupled, and the harmonic overvoltage of traction network in the frequency range of two times switching frequency and above can be directly estimated. Finally, the method proposed in this paper is validated by the comparative simulation analysis of seven different cases.
Análisis de la evolución espacio-temporal del uso de suelo urbano en la metrópolis de Chihuahua

La presente investigación tiene como objetivo la monitorización del cambio en los patrones de distribución espacial del uso del suelo urbano que se ha presentado en la zona de presión intermunicipal de Chihuahua en el periodo 1995-2015. Se utilizó el software FRAGSTATS para el cálculo de las métricas de análisis de la ecología del paisaje. Los resultados indican que el crecimiento del suelo destinado a vivienda que se presentó en el periodo de estudio se encuentra en consonancia con el modelo de ciudad dispersa, caracterizado por la baja densidad edificatoria y la preponderancia del transporte privado por carretera.
Chiral Primary Amine–Squaramide Catalyzed Highly Enantioselective Michael Addition of Isobutyraldehyde to Nitroolefins

Abstract Chiral primary amine–squaramides have not been extensively studied to date in the field of organocatalysis. In this paper, novel chiral squaramides derived from natural product stevioside were developed. Both enantiomers of a series of γ-nitroaldehydes were generated by using these squaramide catalysts for the Michael addition reaction of isobutyraldehyde to nitroolefins. This asymmetric reaction proceeded well to afford the desired products in high yields (up to 98%) with high to excellent enantioselectivities (up to 99% ee).
Estimating Soybean Radiation Use Efficiency Using a UAV in Iowa

Radiation use efficiency (RUE) is difficult to estimate and unreasonable to perform on a small plot scale using traditional techniques. However, the increased availability of Unmanned Aerial Vehicles (UAVs) provides the ability to collect spatial and temporal data at high resolution and frequency, which has made a potential workaround. An experiment was completed in Iowa to (i) demonstrate RUE estimation of soybean [Glycine max (L.) Merr. ] from reflectance data derived from consumer-grade UAV imagery and (ii) investigate the impact of foliar fungicides on RUE in Iowa. Some fungicides are promoted to have plant health benefits beyond disease protection, and changes in RUE may capture their effect. Frogeye leaf spot severity did not exceed 2%. RUE values ranged from 0.98 to 1.07 and 0.96 to 1.12 across the entire season and the period post-fungicide application, respectively, and fell within the range of previously published soybean RUE values. Plots treated with fluxapyroxad + pyraclostrobin had more canopy cover (p = 0.078) compared to the non-treated control 133 days after planting (DAP), but yields did not differ. A “greening effect” was detected at the end of the sample collection. RUE estimation using UAV imagery can be considered a viable option for the evaluation of management techniques on a small plot scale. Since it is directly related to yield, RUE could be an appropriate parameter to elucidate the impact of plant diseases and other stresses on yield.