Clematis vitalba Is a Natural Host of the Novel Ilarvirus, Prunus Virus I.

Clematis vitalba L. is a climbing shrub and a pioneer plant in abandoned orchards or vineyards that are widespread in temperate climate zones. In past years, several viruses infecting the Clematis species have been identified, including different ilarviruses. Prunus virus I (PrVI) is a recently described ilarvirus, which has been shown to infect sweet cherries and peaches in Greece. Moreover, its presence has been detected in ornamental Clematis in Russia. In the present work, we analyzed the virome of wildly growing C. vitalba plants from Hungary, Slovakia and Croatia showing different kinds of symptoms using high-throughput sequencing (HTS) of small RNAs or ribodepleted RNAs. Applying HTS enabled us to identify the presence of PrVI in C. vitalba, and the bioinformatic analyses were further validated with RT-PCR using PrVI-specific primers and Sanger dideoxy sequencing. Nearly full genome sequences of all three viral RNAs of one Hungarian, two Slovak and one Croatian isolate were determined. Their phylogenetic analysis showed high similarity to each other and to other PrVI isolates described from Central Europe. As the sampled plants were co-infected with other viruses, it is not possible to determine a direct correlation between the infection with PrVI and the observed symptoms. Analyses of different Prunus species in stock collection showed infection of several peach and sweet cherry varieties in Hungary. Our results expand the knowledge on the natural host range of PrVI and highlight the necessity to evaluate alternative plant hosts (even non-Prunus) of PrVI and the role of the virus in the etiology of the potential diseases.

Retinal Lesion Segmentation Using Transfer Learning with an Encoder-Decoder CNN / Segmentación de Lesiones en la Retina Usando Transferencia de Conocimiento con CNN Encoder-Decoder

ABSTRACT Deep learning (DL) techniques achieve high performance in the detection of illnesses in retina images, but the majority of models are trained with different databases for solving one specific task. Consequently, there are currently no solutions that can be used for the detection/segmentation of a variety of illnesses in the retina in a single model. This research uses Transfer Learning (TL) to take advantage of previous knowledge generated during model training of illness detection to segment lesions with encoder-decoder Convolutional Neural Networks (CNN), where the encoders are classical models like VGG-16 and ResNet50 or variants with attention modules. This shows that it is possible to use a general methodology using a single fundus image database for the detection/segmentation of a variety of retinal diseases achieving state-of-the-art results. This model could be in practice more valuable since it can be trained with a more realistic database containing a broad spectrum of diseases to detect/segment illnesses without sacrificing performance. TL can help achieve fast convergence if the samples in the main task (Classification) and sub-tasks (Segmentation) are similar. If this requirement is not fulfilled, the parameters start from scratch.

RESUMEN Las técnicas de Deep Learning (DL) han demostrado un buen desempeño en la detección de anomalías en imágenes de retina, pero la mayoría de los modelos son entrenados en diferentes bases de datos para resolver una tarea en específico. Como consecuencia, actualmente no se cuenta con modelos que se puedan usar para la detección/segmentación de varias lesiones o anomalías con un solo modelo. En este artículo, se utiliza Transfer Learning (TL) con la cual se aprovecha el conocimiento adquirido para determinar si una imagen de retina tiene o no una lesión. Con este conocimiento se segmenta la imagen utilizando una red neuronal convolucional (CNN), donde los encoders o extractores de características son modelos clásicos como VGG-16 y ResNet50 o variantes con módulos de atención. Se demuestra así, que es posible utilizar una metodología general con bases de datos de retina para la detección/ segmentación de lesiones en la retina alcanzando resultados como los que se muestran en el estado del arte. Este modelo puede ser entrenado con bases de datos más reales que contengan una gama de enfermedades para detectar/ segmentar sin sacrificar rendimiento. TL puede ayudar a conseguir una convergencia rápida del modelo si la base de datos principal (Clasificación) se parece a la base de datos de las tareas secundarias (Segmentación), si esto no se cumple los parámetros básicamente comienzan a ajustarse desde cero.

Golden ratio-based capital structure as a tool for boosting firm's financial performance and market acceptance.

In the 20th century, the golden ratio has been discovered by modern science, including economics, business, and finance. In the field of finance, the ratio is mostly applied for technical analysis, and much less attention is given to its use in solving corporate finance problems, such as capital structure decisions. In this study, 455 US and European manufacturing and service firm's data are examined from the period 2010-2019. The purpose of the investigation was to determine if there are any positive impacts of a golden ratio-based capital structure on financial performance and market acceptance. We find significant positive relationships between the deviation from the golden ratio-based capital structure and the deviations of firms' revenue, income, stock price and market value data from their historical maximum. Thus, indicating the golden ratio-based capital structure may be an efficient tool for firms to boost their performance and market acceptance. Based on our results, this relationship is more obvious in the United States than in Europe, and stronger for service firms than for manufacturing companies.

The effect of fair valuation on banks' earnings quality: empirical evidence from developed and emerging European countries.

This study investigates average earnings quality (AEQ) and its determinants in the European banking sector based on data of 409 European banks from the period 2006-2018. We utilize the intensity of fair valuation, average annual interest change, and firm size as explanatory variables for AEQ, with special attention to differences between developed and emerging countries. We split the total time period into a pre-IFRS 13 and a post-IFRS 13 period to examine how the renewed regulation of fair valuation (IFRS 13) has affected the earnings quality of banks. We find that, while the interest change observed in the total period and the banks' size significantly and negatively affect AEQ, the proportion of fair value assets has a significant positive effect. We show that the latter is only valid for developed countries. We find clear evidence that the introduction of IFRS 13 resulted in a measurable improvement in fair value regulation.

Millet Could Be both a Weed and Serve as a Virus Reservoir in Crop Fields.

Millet is a dangerous weed in crop fields. A lack of seed dormancy helps it to spread easily and be present in maize, wheat, and other crop fields. Our previous report revealed the possibility that millet can also play a role as a virus reservoir. In that study, we focused on visual symptoms and detected the presence of several viruses in millet using serological methods, which can only detect the presence of the investigated pathogen. In this current work, we used small RNA high-throughput sequencing as an unbiased virus diagnostic method to uncover presenting viruses in randomly sampled millet grown as a volunteer weed in two maize fields, showing stunting, chlorosis, and striped leaves. Our results confirmed the widespread presence of wheat streak mosaic virus at both locations. Moreover, barley yellow striate mosaic virus and barley virus G, neither of which had been previously described in Hungary, were also identified. As these viruses can cause severe diseases in wheat and other cereals, their presence in a weed implies a potential infection risk. Our study indicates that the presence of millet in fields requires special control to prevent the emergence of new viral diseases in crop fields.

Blockchain Mechanism and Symmetric Encryption in A Wireless Sensor Network.

The Internet of Things (IoT) paradigm allows the connection and exchange of information between millions of smart devices. This paradigm grows and develops exponentially as do the risks and attacks on IoT infrastructures. Security, privacy, reliability, and autonomy are the most important requirements in IoT Systems. If these issues are not guaranteed, the IoT system could be susceptible to malicious users and malicious use. In centralized IoT systems, attacks and risks are greater, especially when data is transmitted between devices and shared with other organizations. To avoid these types of situations, this work presents a decentralized system that guarantees the autonomy and security of an IoT system. The proposed methodology helps to protect data integrity and availability based on the security advantages provided by blockchain and the use of cryptographic tools. The accuracy of the proposed methodology was measured on a temperature and humidity sensing IoT-based Wireless Sensor Network (WSN). The obtained results prove that the proposal fulfils the main requirements of an IoT system. It is autonomous, secure to share and send information between devices and users, has privacy, it is reliable, and the information is available in the infrastructure. Furthermore, this research demonstrates that the proposal is less susceptible to the most frequent attacks against IoT systems, such as linking attack, man in the middle, and Distributed Denial of Service (DDoS) attack.

Data on the parasitological status of golden jackal (Canis aureus L., 1758) in Hungary.

In Hungary, twenty Canis aureus individuals were submitted to parasitological examinations in 2010-2012. Two Coccidia: Cystoisospora canis (15%) and Toxoplasma-type oocysts (5%), one Trematoda: Alaria alata (10%), six Cestoda: Mesocestoides lineatus (20%), Echinococcus granulosus (10%), Dipylidium caninums (5%), Taenia hydatigena (15%), Taenia pisiformis (20%), Taenia crassiceps (40%), and nine Nematoda: Angiostrongylus vasorum (10%), Crenosoma vulpis (30%), Capillaria aerophila (5%), Toxocara canis (20%), Toxascaris leonina (15%), Trichuris vulpis (10%), Ancylostoma caninum (45%), Uncinaria stenocephala (40%), Capillaria plica (45%) have been identified. Angiostronglyus vasorum has been reported from carnivores in Europe, Africa, South America and North America. The helminth A. vasorum or French heartworm is a metastrongylid nematode, widely distributed in Western Europe, that infects the pulmonary arterial tree of dogs, various species of foxes, wolves, Eurasian badgers, coyotes and stoats. To our knowledge, this is the first report of natural A. vasorum infection in golden jackal.

Herbicide-affected plant metabolism reduces virus propagation.

It has been previously shown that certain herbicides or plant extracts inhibited the viral infection. The goal of this study was to investigate the effect of Obuda pepper virus (ObPV) infection and herbicide or plant extract treatments on the photosynthetic processes of the host plants to get informations about the interactions of these factors. In Capsicum annuum-ObPV host-virus relations the virus infection slightly increased the activity of photosystem II (PSII), as it was supposed from fluorescence induction parameters. Chlorophyll content of leaves was also elevated probably due to virus-induced growth inhibition. The herbicide Stomp (active ingredient: pendimethalin) incorporated into the soil one week before planting (preplant treatment) together with virus infection even strengthened these effects in agreement with previous observations that this herbicide always did not prevent virus infection or reduce virus concentration in hosts. In ObPV-infected Nicotiana tabacum the structural changes showed similar tendency like in ObPV-infected C. annuum, but PSII efficiency did not significantly differ from that of the control. However, non-photochemical quenching (NPQ) increased because of the strongly decreasing CO2 fixation activity. Though simultaneous application of a water extract of Cirsium arvense shoot caused a little stronger inhibition of CO2 fixation, little loss in production was obtained due to significant reduction in virus concentration. In Solanum nigrum-ObPV relation the slightly increasing tendency of the values of actual PSII quantum efficiency could be related to the probably elevated ratio of reaction centre components (increased chlorophyll a/b ratio) in the thylakoids. Application of the herbicide Fusilade S (active ingredient: fluazifop-P-butyl) at 4-6 leaf stage as a post-emergence treatment practically prevented systemic virus infection and the virus-induced changes of photosynthesis are probably due to inhibiting the virus infection/replication process.