Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Auto Adhesion of Wood Fibers Using Phenol Oxidases

Enzymatic oxidation of lignin phenolic hydroxyl groups can enhance the level of auto adhesion between wood fibers. Previous investigations within the area have not taken the adhesive effect of proteins and carbohydrates in the enzyme solution into consideration, and part of the claimed enzyme generated adhesion may merely be a result of the adhesive effect of the proteins and carbohydrates in the enzyme solution. In this paper the enzyme laccase is used to oxidize beech (Fagus sylvatica) wood fibers. Laccase catalyzes a one-electron oxidation of phenolic hydroxyl groups while reducing oxygen, yielding phenoxy radicals and water. Wet and dry process fiberboards are made from enzyme treated and untreated beech wood fibers. The enzyme treated fiberboards have significantly higher modulus of rupture and modulus of elasticity as well as better dimensional stability. No effect of the protein and carbohydrate content in the enzyme solution upon the mechanical properties and dimensional stability can be found. The bonding effect is caused by the catalytic effect of the enzyme only. Electron spin resonance spectroscopy of beech wood fibers shows that a considerable amount of the laccase generated radicals is stabilized in the lignin polymer. and the bonding mechanism appears to be associated with reactions of these free radicals. The physico-mechanical parameters of the enzyme treated fiberboards have not been optimized in the present work. Hence, strength improvements may be obtained simply by optimizing the process parameters. The possibility of producing a medium density fiberboard without the use of synthetic adhesives appears to be promising. The use of oxidative enzymes in processing and manufacturing of wood-based materials may yield new and more environmentally safe products.
On the fundamental processes in molecular electrical doping of organic semiconductors

Integer electron transfer between organic semiconductors (OSCs) and strong donor/acceptor molecules has been regarded as the fundamental mechanism of molecular electrical doping. However, this process entails a number of consequences that are in conflict with well-established concepts of organic-semiconductor physics such as the charge-induced appearance of polaronic states within the fundamental gap of the OSC. Here, from the results of (time-dependent) density-functional theory calculations on prototypical OSC/dopant pairs, we derive a new and different picture for the mechanism of molecular electrical doping, which resolves these inconsistencies. Common doping-related observations are rationalized through intermolecular hybridization of OSC and dopant frontier molecular orbitals. Controlling the degree of this hybridization thus naturally emerges as a strategy for the design of improved molecular dopants in future high-performance organic electronic devices.
Does blockchain technology democratize entrepreneurial finance? An empirical comparison of ICOs, venture capital, and REITs

ABSTRACT Initial coin offerings (ICOs) are one of the major innovations that characterize the digital revolution of financial markets. Among the expectations created by the digital revolution is the democratization of entrepreneurial finance, defined in terms of the creation of more equality regarding the access to financial resources by categories known to be underrepresented among potential entrepreneurs. Following this line of research, we investigate, through two complementary empirical studies, whether gender, ethnicity, and geography affect the choice of ICOs vs. traditional financing alternatives. Additionally, we assess whether these characteristics increase the amount of money an entrepreneur can raise. In Study I, we compare 390 ICO ventures to a sample of 1,078 VC-backed blockchain ventures, identifying a negative correlation between the choice of an ICO (vs. VC-backing) and a location in an urban area. In Study II, we compare 160 ICO ventures to 163 real estate investment trusts (REITs), reaffirming the results of Study I. The findings show significant participation and likelihood of successful campaigns for ethnical minorities in ICOs, with the latter also being able to collect, ceteris paribus, larger amounts of funding. In contrast, female entrepreneurs do not have higher chances to participate nor raise funds in ICOs.
Creating an Efficient Point-of-Care Ultrasound Workflow

A point-of-care ultrasound (POCUS) workflow is composed of multiple processes managed by various stakeholders. There are concurrent front and back end steps including: acquiring, archiving and interpreting images; documenting the POCUS study and ultimately coding and billing for the study [1]. An efficient POCUS workflow is important for both patient care and billing [24]. Unfortunately, there is no single standard across POCUS programs [5]. Based on our institutional experience, we suggest that programs engage key groups described in this perspective piece.
Fingertip-Specific Mobile Interaction Through Camera-Based Fingertip Identification

In this paper, we propose to utilize camera-based fingertip identification to enable fingertip-specific mobile interaction without hand occlusion. The core idea of the proposed fingertip identification method is to utilize features, whether innate or got-up, on a fingertip to recognize its identity rather than utilize hand information to infer the fingertip’s identity. A fighter game prototype is presented to demonstrate the interaction idea. Possible ways to realize fingertip identification and how to utilize fingertip identification to enable richer interactions on mobile devices are also discussed.
A novel image matching algorithm based on PCA and SIFT

In order to solve the problem of low matching precision and slow matching speed of image matching algorithm based on classical SIFT, a new image matching algorithm based on PCA, SIFT and improved RANSAC is proposed. Firstly, the SIFT feature was extracted from images; Secondly, principal component analysis is used to reduce the dimension of SIFT feature descriptor, from 128 to 20; then, the EUCLIDEAN distance is used for feature matching; finally, an improved RANSAC algorithm is proposed to eliminate the mismatched feature points. Experimental results show that the proposed algorithm improves the accuracy and speed of image matching.
A SIX PLATE MICROBIOLOGICAL ASSAY FOR SCREENING OF ANTIMICROBIAL RESIDUES IN FOOD OF ANIMAL ORIGIN

Occurrence of antimicrobial residues in livestock and aquatic products is a current public health concern. The monitoring of food commodities for antimicrobial residues will ensure the consumer safety and promote trade. Therefore, the objective of this study was to establish a screening test to detect antimicrobial residues in food of animal origin. A bioassay consists of six plates was established, which enables screening of six groups of antimicrobials, namely; penicillins, sulphonamides, streptomycin, erythromycin, tetracyclines and fluroquinolones. The Six Plate Test (SPT) is a bioassay technique, which is carried out using Bacillus subtilis BGA (Merck), Bacillus cereus (ATCC 11778), Micrococcus luteus (ATCC 9341) and Escherichia coli (ATCC 11303) as indicator organisms. The Mueller Hinton Agar (MHA) was used as the test medium at optimum pH for all indicator organisms except B.cereus, for which the Media No.8 was used. The Minimum Detectable Concentrations (MDC) of SPT were determined using serial dilutions of antibiotics. All the MDC values obtained on SPT for the validated antimicrobials were below the recommended MRL of each antimicrobial. SPT can be developed to a quick, easy to perform, robust and low cost screening test to detect antimicrobial residues in food of animal origin.
An automatic self‐initialized clustering method for brain tissue segmentation and pathology detection from magnetic resonance human head scans with graphics processing unit machine

The proposed work introduces a fully automatic modified fuzzy c‐means (MFCM) algorithm for segmenting brain tissue into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) which identifies the pathological conditions of magnetic resonance human head scans. The present work implements histogram smoothing using Gaussian distribution for finding the number of clusters (K) and cluster centers (C) to initialize modified FCM algorithm (MFCM). The modification includes the local impact of each pixel based on the median of local neighborhoods. This needs more computational power to reduce the processing time and requires a parallel programming environment like the Graphics Processing Unit. The parallel MFCM is performed with the help of compute unified device architecture language and reduced the processing time up to 80 speedup folds than the serial implementation in Matlab and 20 speedup folds than C programming implementation. The method is examined with the Internet Brain Segmentation Repository (IBSR20) T1W dataset. The quantitative and qualitative results of the proposed method are compared with state‐of‐the‐art‐methods using the Dice coefficient (DC). Proposed method yields high DC 0.84 ± 0.03 for GM, 0.83 ± 0.04 for WM, and 0.41 ± 0.12 for CSF segmentation. In post‐processing, 3D volumes of segmented regions have been constructed and compared with the gold standard quantitatively and qualitatively.
Teaching and Testing in Hasidic Schools: Skills, Content, and Knowledge Automaticity as a Model for Other Day School Contexts

ABSTRACT This article uses data from site visits to four Hasidic elementary schools in Brooklyn to examine how specific learning, review, and testing activities used in these schools might be applied in other Jewish education classrooms to build knowledge depth and automaticity. The literature on learning and cognition in secular subjects has identified many classroom techniques that promote deep learning and long-term retention rather than superficial recall, but these techniques have not been applied systematically to Jewish studies classrooms. Hasidic schools, whose overall approach to religious education differs significantly from that of other Jewish day schools, employ distinctive learning activities that incorporate many of these techniques. Some elements of Hasidic learning practices may thus represent a valuable model for other Jewish studies contexts.
A INFÂNCIA EM PROCESSOS JUDICIAIS EM BELÉM DO PARÁ: UM ESTUDO DISCURSIVO SOBRE O CASO DO MENOR MANOEL DOS SANTOS (1905)

Objetiva-se analisar a infância e a criminalidade em Belem do Para a partir dos enunciados discursivos do processo judicial do menor Manoel dos Santos, condenado por desordem/vagabundagem, no ano de 1905. Esta pesquisa surge de construcoes historicas e epistemologicas estabelecidas em âmbito de curso de mestrado, cuja investigacao se ancora no referido processo criminal. Metodologicamente, utiliza a analise do discurso polifonico e dialogico com base teorica em Bakhtin. Trata-se de um estudo documental que esta inserido no contexto das transformacoes socioeconomicas e do projeto de modernizacao da capital paraense em decorrencia da comercializacao da borracha, que fez da cidade um lugar de costumes e habitos ordeiros, segundo o modelo de educacao republicano e a logica positivista vigentes. Este metier demonstra um vies da sistematizacao dos discursos no presente documento, em que foi possivel identificar os significados e sentidos que constituiram os autos do processo baseado no Codigo Penal de 1890. Palavras-chave : Infância. Educacao. Processo judicial. Discurso.
Development of Single Nucleotide Polymorphism (SNP) Markers in Tropical Crops

Understanding genetic diversity, association studies, evolution analysis, quantitative trait loci, marker-assisted selection and genome-wide association in tropical crops are important for improving plant characteristics in order to increase food sustainability in tropical countries. Single nucleotide polymorphism (SNP) marker is becoming the most popular molecular marker for those studies. By using SNP marker, genes associated with important traits can be identified efficiently compared to the other molecular markers. This review describes about how SNP can be discovered in the plant genomes and the application of SNP in plant breeding, especially in tropical crops such as rice, maize, peas, potato, tomato, cassava, taro, etc. Keywords: food sustainability, plant breeding, SNP marker, tropical crops
Fine‐scale variation within urban landscapes affects marking patterns and gastrointestinal parasite diversity in red foxes

Abstract Urban areas are often considered to be a hostile environment for wildlife as they are highly fragmented and frequently disturbed. However, these same habitats can contain abundant resources, while lacking many common competitors and predators. The urban environment can have a direct impact on the species living there but can also have indirect effects on their parasites and pathogens. To date, relatively few studies have measured how fine‐scale spatial heterogeneity within urban landscapes can affect parasite transmission and persistence. Here, we surveyed 237 greenspaces across the urban environment of Edinburgh (UK) to investigate how fine‐scale variation in socio‐economic and ecological variables can affect red fox (Vulpes vulpes) marking behavior, gastrointestinal (GI) parasite prevalence, and parasite community diversity. We found that the presence and abundance of red fox fecal markings were nonuniformly distributed across greenspaces and instead were dependent on the ecological characteristics of a site. Specifically, common foraging areas were left largely unmarked, which indicates that suitable resting and denning sites may be limiting factor in urban environments. In addition, the amount of greenspace around each site was positively correlated with overall GI parasite prevalence, species richness, and diversity, highlighting the importance of greenspace (a commonly used measure of landscape connectivity) in determining the composition of the parasite community in urban areas. Our results suggest that fine‐scale variation within urban environments can be important for understanding the ecology of infectious diseases in urban wildlife and could have wider implication for the management of urban carnivores.
Molecular weight determination of 83% degree of decetylation chitosan with non‐Gaussian and wide range distribution by high‐performance size exclusion chromatography and capillary viscometry

Molecular weight determination of 83% degree of deacetylation (DD) chitosan with non-Gaussian and broad molecular weight distribution by high-performance size exclusion chromatography (HPSEC) and by capillary viscometry were proposed. The relationships between weight average retention volumes (RVw) of HPSEC and intrinsic viscosities ([η]) measured by capillary viscometer and the weight average molecular weight (Mw) measured by static light scattering were established for routine molecular weight determination of chitosans either by HPSEC or by the capillary viscometry method, respectively. These results showed: relationships of RVw and Mw for different Mw of 83.0% DD chitosans can be expressed by the equation Log Mw = −0.433 RVw + 11.66. The RVw of other DD chitosans do not correlate well with this equation. It indicated that DD of chitosan affected the relationship of RVw and Mw of chitosans studied. The Mark–Houwink constant a decreased from 0.715 to 0.521, as the solution ionic strength increased from 0.01M to 0.30M, whereas constant k increased from 5.48 × 10−4 to 2.04 × 10−3 over the same range of ionic strength solutions. The established RVw and Mw equation and [η] and Mw equation (Mark–Houwink equation) can be routinely used to determine the molecular weight from RVw or [η] of chitosan by HPSEC or by capillary viscometer, respectively, without the need of expensive instrumentation. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 71: 1905–1913, 1999
Sentiment Analysis For Product Reviews Based on Deep Learning

With the popularity of the Internet and e-commerce, the sentiment analysis of text can help users to quickly and accurately obtain effective information they are interested in from massive product reviews to purchase satisfactory products. In this paper, a sentiment analysis system for product reviews was designed based on deep learning, and the digital and electronic products on Jingdong Mall with at least 100,000 reviews were crawled as the training data set. After data pre-processing operations such as word segmentation and removal of stop words for product reviews to remove useless features, the feature vectors were constructed based on the bag of words model and word2vec method, and then three classification algorithms, namely LSTM, Naive Bayes and logistic regression were used to model reviews. The LSTM algorithm is significantly superior to Naive Bayes and logistic regression algorithm in the training stage, and provides a reliable reference for the analysis of product reviews.
Oberflächengüte von CAD/CAM-gefrästen Implantatstegen aus Titan und Kobalt-Chrom

Gehrke P Die Fixierung von implantatgetragenem Zahnersatz auf CAD/CAM-gefertigten Stegen findet zunehmend Anwendung in der Implantatprothetik. Sowohl funktionelle als auch biologische Gesichtspunkte entscheiden über den Erfolg einer solchen Versorgung. Aus biologischer Sicht ist, wie bei Abutments und einteiligen Implantaten, der transmukosale Anteil des Stegs von besonderem Interesse, da er idealerweise die Anhaftung von Weichgewebe unterstützt, jedoch die mechanische Plaqueanlagerung minimiert. Funktionelle Stege sollten einen spannungsfreien Sitz und optimale Retentionseigenschaften besitzen. Beide Aspekte korrelieren direkt mit den Materialeigenschaften dieser Suprakonstruktionen. Trotz ihrer vermehrten klinischen Verwendung sind derzeit nur wenige Informationen über ihre Oberflächentopografie verfügbar. Der vorliegende Beitrag erläutert die Möglichkeiten zur Herstellung von CAD/CAM-generierten Implantatstegen und zeigt die aktuellen Ergebnisse zur Oberflächenrauheit und Charakterisierung dieser Suprakonstruktionen.
The Performance of IoT Malware Detection Technique Using Feature Selection and Feature Reduction in Fog Layer

The rapid increase in the number of devices connected to internet (IoT) lead to expansion in the attacks that targeting these devices. One of these dangers attacks is malware which embedded with IoT devices that makes the detection for such malware is extremely challenging. The machine learning is one of the most effective techniques that used to detect different types of attacks in IoT environment. This technique includes three main stages: feature extraction, feature selection, and classification. The feature selection is the most important stage in ML technique because it contributes to minimizing the size of features which significantly accelerate the detection system. In this stage, most researchers trend to use one of three methods; feature selection, feature reduction and hybrid between feature selection and reduction. The present research aims to present a comparative study between the effect of using feature selection method and feature reduction method on the performance of the IoT malware detection system. The results showed that the proposed technique could achieved an accuracy about 97% when using feature selection method only. These results emphasize that feature selection method is more efficient than the feature reduction method in detection IoT malware.
THE COMPARISON OF PIRLS, TIMSS, AND PISA EDUCATIONAL RESULTS IN MEMBER STATES OF THE EUROPEAN UNION

The PIRLS (Progress in International Reading Literacy Study), TIMSS (Trends in International Mathematics and Science Study), and PISA (Programme for International Student Assessment) have become gold standards for the international comparison of children’s performances, when aged 10 and 15 years. This paper focuses on secondary analysis of basic statistical indicators on reading literacy (PIRLS), as well as the mathematics and scientific literacy (TIMSS) of pupils at 10 years of age, followed by their reading, mathematics and scientific literacy at 15 years of age (PISA). It compares the pupils’ main educational results in PIRLS and TIMSS with their PSA results. PIRLS, TIMSS, and PISA help to identify key problems within pupils’ educational levels in these selected literacies and create effective educational policy measures. One aspect of the comparison within the research paper is the aggregate indicator; this is the arithmetic mean of PIRLS and TIMSS results, using pupils’ PIRLS results from 2001, 2006, 2011 and 2016, and TIMSS results from 2007, 2011 and 2015. The other aspect of the comparison is the aggregate indicator; which is the arithmetic mean of pupils’ PISA results for 2006, 2009, 2012 and 2015. A significant relationship was found to exist between the arithmetic mean of pupils’ PIRLS, TIMSS, and PISA results. Political and professional policy decisions within schooling affect the early years of pupils’ school attendance. This has a significant impact on their future education at all levels of schooling. The findings of this paper support a hypothesis regarding the effects of pupils’ educational performance and the need for measures to improve education in schools that should be adopted on an ongoing basis. UDC Classification: 338.2, DOI: https://doi.org/10.12955/pss.v1. 70
Irreversibility, heat and information flows induced by non-reciprocal interactions

We study the thermodynamic properties induced by non-reciprocal interactions between stochastic degrees of freedom in time- and space-continuous systems. We show that, under fairly general conditions, non-reciprocal coupling alone implies a steady energy flow through the system, i.e., non-equilibrium. Projecting out the non-reciprocally coupled degrees of freedom renders non-Markovian, one-variable Langevin descriptions with complex types of memory, for which we find a generalized second law involving information flow. We demonstrate that non-reciprocal linear interactions can be used to engineer non-monotonic memory, which is typical for, e.g., time-delayed feedback control, and is automatically accompanied with a nonzero information flow through the system. Furthermore, already a single non-reciprocally coupled degree of freedom can extract energy from a single heat bath (at isothermal conditions), and can thus be viewed as a minimal version of a time-continuous, autonomous ‘Maxwell demon’. We also show that for appropriate parameter settings, the non-reciprocal system has characteristic features of active matter, such as a positive energy input on the level of the fluctuating trajectories without global particle transport.