Miracle-dz/UniFAR-FTUs huggingface dataset:
A comprehensive comparison on current deep learning approaches for plant image classification

Plant identification and classification play a key role in understanding, protecting and conserving biodiversity. Traditional plant taxonomy needs long time intensive training and experience, which limited others to identify plant categories. With the development of automated image-based classification, machine learning (ML) is becoming a popular tool. Image classification, especially plant images taxonomy, has achieved great improvement in these years by deep learning (DL) methods. In this study, we first reviewed current deep learning applications in the field of plant image classification, and then we tested six deep learning methods in four public plant image datasets. In order to test the classification power of DL methods at cultivar level, we prepared a Camellia sasanqua Thunb. dataset, which is called Camellia@clab, for assessing classification performance of the six DL methods. These DL models’ classification performance all exceeded 70% in the four public plant image datasets, and LeNet and DenseNet had stable good performance, with median prediction accuracy of the LeNet was over 87.29% and that of DenseNet was over 93.8% in the four public datasets at species level. At cultivar level, the lowest median prediction accuracy of those DL methods decreased to 62%, but LeNet and DenseNet still performed very well. The prediction accuracy of LeNet and DenseNet was 82.3% and 100% in the Camellia@clab dataset, respectively. DenseNet model showed a stable best classification performance among the five datasets. To our knowledge, this is the first study that provides a comprehensive review and comparison on applying current DL methods to plant image classification. This study will provide guidance for DL applications in plant image classification, and point out the protentional DL research direction for modeling improvement.
A Deep Learning-Based Hybrid Feature Selection Approach for Cancer Diagnosis

Feature selection plays an important role in machine learning-based classification tasks, especially in high dimensional data, such as biological omics datasets. Recent research has begun to explore the use of deep learning to accomplish this task as a step in feature representation. In this research, we developed a deep learning-based hybrid feature selection approach combing Sparse Autoencoder (SAE) and Logistic Regression-Recursive Features Elimination (LR-RFE) and evaluated our method on TCGA miRNA datasets. The results show that our proposed hybrid method achieves a better performance compared to other comparison methods.
Tuning the Conduction Mechanism in Niobium-Doped Titania Nanoparticle Networks

Networks of niobium-doped TiO2 anatase nanoparticles with variable doping concentrations were investigated by time-domain terahertz spectroscopy and microwave impedance spectroscopy. A detailed description of their electromagnetic response is proposed; the model takes into account the depolarization fields of inhomogeneous samples and allows us to understand the conductive and dielectric response of individual nanoparticles. We find that electron hopping is the dominating contribution to the conductivity at terahertz frequencies and that the dielectric losses of TiO2 nanoparticles are enhanced in comparison with bulk anatase. The conductive properties of nanoparticles can be tuned via synthesis conditions and thermal posttreatment. In particular, annealing at elevated temperatures improves the nanoparticle crystallinity, reduces the density of structural defects, and enhances the conductive percolation of the network. The developed model of the conduction processes can be helpful for interpretation of cha.
Navigation in der dentalen Implantologie

Edelmann C, Schnutenhaus S. Navigation in der. ZWR – Das De timal und vorhersagbar zu erreichen [2]. Bei der Planung der Implantatpositionen müssen verschiedene Gesichtspunkte gleichermaßen beachtet und bewertet werden. So sind in der Planung zum Beispiel die Knochensituation [3], die Weichgewebssituation [4] der interimplantäre Abstand [5] oder die Lage des Zementspalts [6] zu berücksichtigen. Der Langzeiterfolg einer Implantatversorgung wird dementsprechend von multiplen Faktoren bestimmt [7].
Hybrid Simulations of Interstellar Pickup Protons Accelerated at the Solar-wind Termination Shock at Multiple Locations

We estimate the intensity of interstellar pickup protons accelerated to ∼50 keV at various locations along the solar-wind termination shock, using two-dimensional hybrid simulations. Parameters for the solar wind, interstellar pickup ions (PUIs), and magnetic field just upstream of the termination shock at one flank of the heliosphere, and at the location in the downwind (or tail-ward) direction are based on a solar-wind/pickup-ion/turbulence model. The parameters upstream of the shock where Voyager 2 crossed are based on observations. The simulation is limited in size, and therefore cannot accurately model the distribution to energies much beyond ∼50 keV. This is sufficient to study the origin of the high-energy tail of the distribution, which is the low-energy portion of the anomalous cosmic-ray spectrum. We also extrapolate our results to other locations along the termination shock, such as the other flank, and the poles of the heliosphere. We find that the intensity of ∼10–50 keV accelerated pickup protons is remarkably similar at all three locations we simulated, suggesting that particles in this energy range are relatively uniformly distributed along the termination shock, and are likely quite uniform throughout the entire heliosheath. In addition, we find significant differences in the distribution in the 0.5–1 keV energy range for energetic neutral atoms coming from the tail region of the heliosphere compared to that at the nose or flank look directions. This is because the peak in the PUI distribution is at a higher energy there.
Current Terminology of Pelvic Floor Dysfunctions

236 ©Copyright 2021 by the Bezmiâlem Vakıf University Bezmiâlem Science published by Galenos Publishing House. Address for Correspondence: Büşra YILMAZ, İstanbul University-Cerrahpaşa Florence Nightingale Faculty of Nursing, Department of Women’s Health and Gynecologic Nursing, İstanbul, Turkey E-mail: ylmzbsr678@gmail.com ORCID ID: orcid.org/0000-0001-6937-5351 Received: 24.05. 2020 Accepted: 06.01. 2021
Gene Identification from Microarray Data for Diagnosis of Acute Myeloid and Lymphoblastic Leukemia Using a Sparse Gene Selection Method

Background: Microarray experiments can simultaneously determine the expression of thousands of genes. Identification of potential genes from microarray data for diagnosis of cancer is important. This study aimed to identify genes for the diagnosis of acute myeloid and lymphoblastic leukemia using a sparse feature selection method. Materials and Methods: In this descriptive study, the expression of 7129 genes of 25 patients with acute myeloid leukemia (AML), and 47 patients with lymphoblastic leukemia (ALL) achieved by the microarray technology were used in this study. Then, the important genes were identified using a sparse feature selection method to diagnose AML and ALL tissues based on the machine learning methods such as support vector machine (SVM), Gaussian kernel density estimation based classifier (GKDEC), k-nearest neighbor (KNN), and linear discriminant classifier (LDC). Results: Diagnosis of ALL and AML was done with the accuracy of 100% using 8 genes of microarray data selected by the sparse feature selection method, GKDEC, and LDC. Moreover, the KNN classifier using 6 genes and the SVM classifier using 7 genes diagnosed AML and ALL with the accuracy of 91.18% and 94.12%, respectively. The gene with the description “Paired-box protein PAX2 (PAX2) gene, exon 11 and complete CDs” was determined as the most important gene in the diagnosis of ALL and AML. Conclusion: The experimental results of the current study showed that AML and ALL can be diagnosed with high accuracy using sparse feature selection and machine learning methods. It seems that the investigation of the expression of selected genes in this study can be helpful in the diagnosis of ALL and AML.
Environmental and Management Practices Affecting Grape Composition and Wine Quality - A Review

World production of wine has steadily risen over recent years and consumption has not kept pace with this increase, thus many countries have surpluses of wine which pose problems in international trade. Despite these problems, there is not, generally, a surplus of high quality wines. Quality is not easy to define, but ideally, it should be related to intrinsic visual, taste, or aroma characters which are perceived as above average for that type of wine. Usually this is reflected in the price paid for that wine — although price is not necessarily a reliable indicator since it can be influenced also by fashion, tradition, availability and personal preferences. Unfortunately, despite the many references to quality and the amount of work which directly or indirectly refers to it, there is still confusion over what contribution climates, sites, and viticultural practices really make. This paper is a review of the effects of these environmental and management practices which may change grape composition and wine quality. Its scope is limited to table wines rather than fortified wines.
Petrophysical characterisation of volcanic ejecta to constrain subsurface lithological heterogeneities: implications for edifice stability at basaltic volcanoes

Piton de la Fournaise (PdF) is an active and dominantly e ﬀ usive basaltic volcano. The geologic record preserves evidence of rare explosive eruptions, associated with the seaward sliding of the steep east ﬂank and the collapse of large calderas emplacing lithic-rich breccias. Breccias of PdF o ﬀ er the opportunity to sample a wide range of crustal lithologies. Unaltered blocks are representative of plutonic (gabbros), sub-volcanic (dolerites emplaced in sills and dykes), and volcanic (lavas) units. We document a large variability in density, porosity, P-wave velocity (dry and wet), and uniaxial compressive strength (UCS). The large variation in P-wave velocity and UCS results from the wide ranges in texture and lithology. Notably, some of the dense gabbroic units having experienced several cycles of natural reheating are comparatively weak. We infer that volcano instability should not be interpreted solely in terms of altered rock units. Rather, the large petrophysical heterogeneity of crustal rocks at PdF, and likely at many other basaltic volcanoes, must be considered when interpreting monitoring data and assessing volcano stability. Le Piton de la Fournaise (PdF) est un volcan basaltique actif et à dominante e ﬀ usive. Les archives géologiques conservent des preuves d’éruptions explosives rares, associées au glissement vers la mer du ﬂanc est escarpé et à l’e ﬀ ondrement de grandes calderas produisant des brèches riches en lithiques. Les brèches de PdF o ﬀ rent l’oppor-tunité d’échantillonner une large gamme de lithologies crustales. Les blocs non modiﬁés sont représentatifs des unités plutoniques (gabbros), subvolcaniques (dolérites placées dans sills et les dykes) et volcaniques (laves). Nous documentons une grande variabilité de la densité, de la porosité, de la vitesse de l’onde P (sèche et humide) et de la résistance à la compression uniaxiale (UCS). La grande variation de la vitesse de l’onde P et du UCS résulte des larges gammes de texture et de lithologie. Notamment, certaines des unités gabbroïques denses ayant subi plusieurs cycles de réchau ﬀ ement naturel sont relativement faibles. Nous en déduisons que l’instabilité du volcan ne doit pas être interprétée uniquement en termes d’unités de roches altérées. Au contraire, la grande hétérogénéité pétrophy-sique des roches crustales à PdF, et probablement dans de nombreux autres volcans basaltiques, doit être prise en compte lors de l’interprétation des données de surveillance et de l’évaluation de la stabilité du volcan.
Video Game Addiction Among Students During COVID-19 Pandemic Based on Regulatory Focus Theory and Interpersonal Competence

Video game addiction is one of the mental health problems due to the uncontrolled activities in accessing video game platforms. This study aimed to identify the tendencies of video game addiction among Senior High School students based on the aspects of Regulatory Focus Theory and interpersonal competence. It implemented a quantitative descriptive model with a 2×2 factorial design. A total of 1046 students participated in the survey. The findings revealed the increasing video game addiction cases among the students during the COVID-19 pandemic. The students with a high promotion focus and a high interpersonal competence as well as those with a low prevention focus and a low interpersonal competence tended to experience video game addiction.
Monitoring Urban Sprawl Using Time-Series Data: Famagusta Region of Northern Cyprus

Monitoring urban sprawl is a controversial topic among scholars. Many studies have tried to employ various methods for monitoring urban sprawl in cases of North American and Northern and Western European cities. Although numerous methods have been applied with great success in various developed countries, they are predominantly impractical for cases of developing Mediterranean European cities that lack reliable census data. Besides, the complexity of the methods made them difficult to perform in underfunded situations. Therefore, this study aims to develop a new multidimensional method that researchers and planners can apply readily in developing Mediterranean European cities. The new method was tested in the Famagusta region of Northern Cyprus, which has been experiencing unplanned growth for the past half-century. In support of this proposal, a detailed review of the existing literature is presented with an emphasis on urban sprawl characteristics. Four characteristics were chosen to monitor urban sprawl’s development in the Famagusta region. The method was structured based on a time-series (2001, 2006, 2011, and 2016) dataset that used remote sensing data and geographical information systems to monitor the urban sprawl. Based on the findings, the Famagusta region experienced rapid growth during the last 15 years. The lack of a masterplan resulted in the uncontrolled expansion of the city in the exurban areas. The development configuration was polycentric and linear in form with single-use composition. Together, the expansion and configuration manifested as more built-up area, scattered development, and increased automobile dependency.
Characteristics of cellulose fibers from Opuntia ficus indica cladodes and its use as reinforcement for PET based composites

ABSTRACT With the aim of valorizing the unexplored Moroccan resources, Opuntia ficus indica (OFI) cladodes were proposed as a renewable source for the production of cellulose. In this work, cellulose microfibers were extracted from OFI cladodes using one of the most suitable methods for the extraction of cellulose based on the alkaline delignification. The morphological (SEM), thermal (TGA/DTG), and structural (XRD, FTIR, and 13C NMR) analysis of the isolated cellulose has been identified. Afterward, the reinforcing capability of cellulose fibers was examined using polyethylene terephthalate (PET) as a matrix by combining extrusion and compression molding processes. The effects of fibers loading on physical properties of the composites, such as tensile strength and Young’s Modulus before and after water absorption, were studied. The stability of the optimal composite was also examined based on the dependence of rheological parameters (G’ and G”) with strain and time. Composites containing 15 wt% of fibers exhibited the best mechanical properties in dry and wet cases, reaching 88% increase from neat PET in Young’s modulus and 36% increase in the tensile strength. However, excellent structural stability of the optimal composite was found with a predominant elastic behavior resulting from the good interface adhesion between cellulose fibers and PET matrix. The present work showed new routes for the valorization of OFI cladodes in the development of composite materials.
Critical Reflection on the Maltese Legal Framework and the Policy Documents in Relation to the Role of the Educational Leader

In Malta, the core role of the educational leader is to be a curricular leader whilst attending to student matters, teaching personnel, home-school-community links, administration and finance. Research recommends that such expectation can be best fulfilled through the adoption of a distributed leadership style. However, when analyzing the Maltese legal contextual background laid out in the Laws of Malta Education Act, the subsequent Government documents and the job description for the post of Head of School (HOS) to identify whether the theoretical stance and what is requested in practice align, the findings indicate that the suggested styles in the legal framework do not align clearly well with the policy documents and the practice thus possibly creating certain conflicts and confusion. The point being made is that notwithstanding being knowledgeable about what should be the core business of the school leader if the laws state otherwise, then the educational practitioners will end in a dilemma between the theory and the practice. Consequently, here, it will be emphasized that the legal documentation’s expectations of the system guiding the work of the educational leaders should not only be adjourned but more importantly, should promote more the distributed leadership role more clearly and allow the school leaders to fulfill what they are expected to do by reducing, or better still, removing unnecessary administrative work that alienates them from their core business.
Performance of Side-Streams from Eucalyptus Processing as Sources of Polysaccharides and Lignins by Kraft Delignification

The performance of bark, branches, sawdust, forest biomass, and short-rotation eucalyptus in kraft delignification to produce polysaccharides and lignin is reported and discussed. A positive correlation was found between pulping severity required for delignification and lignin reactivity. Among all, branches feedstock is the best source of polysaccharides due to the high pulp yield (48–54%) with a satisfactory delignification degree. Branches lignin was characterized for the first time, evaluating syringyl/guaiacyl/p-hydoxyphenyl (65:22:13), β-O-4 units (71/100C6) and condensed structures (12%). Kraft lignins (KL) were isolated from black liquors, including industrial one, and analyzed by NMR demonstrating remarkable differences. Among all, bark KL reveals the highest depolymerization (lowest β-O-4 content, 18/100 C6) and condensation (50%) as a consequence of higher active alkali required for pulping. Sawdust and branches KLs have similar degree of condensation, but the former revealed slightly less β-O-.
H∞ Constrained Pareto Suboptimal Strategy for Stochastic LPV Time-Delay Systems

Not only in control problems, but also in dynamic games, several sources of performance degradation, such as model variation, deterministic and stochastic uncertainties and state delays, need to be considered. In this paper, we present an [Formula: see text] constrained Pareto suboptimal strategy for stochastic linear parameter-varying (LPV) time-delay systems involving multiple decision makers. The goal of developing the [Formula: see text] constrained Pareto suboptimal strategy set is to construct a memoryless state feedback strategy set, so that the closed-loop stochastic LPV system is stochastically mean-square stable. In the paper, the existence condition of the extended bounded real lemma is first established via linear matrix inequalities (LMIs). Then, a quadratic cost bound for cost performance is derived. Based on these preliminary results, sufficient conditions for the existence of such a strategy set under the [Formula: see text] constraint are derived by using cross-coupled bilinear matrix inequalities (BMIs). To determine the strategy set, a viscosity iterative scheme based on the LMIs is established to avoid the processing of BMIs. Finally, two numerical examples are presented to demonstrate the reliability and usefulness of the proposed method.
On the Supramolecular Packing of High Electron Mobility Naphthalene Diimide Copolymers: The Perfect Registry of Asymmetric Branched Alkyl Side Chains

The supramolecular organization of the n-type P(NDI2OD-T2) polymer (also known as Polyera Activink N2200), featuring two branched octyldodecyl lateral chains, has been investigated by a combination of quantum-chemical and molecular mechanics techniques coupled to two-dimensional X-ray diffraction simulations. The structures exhibit non fully extended alkyl chains due to a compromise between the size of the monomer unit and the nature and length of the alkyl chains. Interestingly, the supramolecular organization of the polymer chains is only weakly affected by the nature of the stereogenic centers of the branched alkyl chains. The size and shape of the monomer unit and the chemical structure of the side chains appear to be the key elements governing the relationship between the supramolecular organization of P(NDI2OD-T2) polymer chains and their charge transport properties and are as important as the fine-tuning of the electronic properties of the molecular subunits in order to guarantee large electron (an.
Negativity and Political Behavior: A Theoretical Framework for the Analysis of Negative Voting in Contemporary Democracies

Recent developments in Western societies have motivated a growing consideration of the role of negativity in public opinion and political behavior research. In this article, we review the scant (and largely disconnected) scientific literature on negativity and political behavior, merging contributions from social psychology, public opinion, and electoral research, with a view on developing an integrated theoretical framework for the study of negative voting in contemporary democracies. We highlight that the tendency toward negative voting is driven by three partly overlapping components, namely, (1) an instrumental–rational component characterized by retrospective performance evaluations and rationalization mechanisms, (2) an ideological component grounded on long-lasting political identities, and (3) an affective component, motivated by (negative) attitudes toward parties and candidates. By blueprinting the systematic relationships between negative voting and each of these components in turn, and suggesting multiple research paths, this article aims to stimulate future studies on negative voting in multi-party parliamentary systems to motivate a better understanding of the implications of negativity in voting behavior in contemporary democracies.