First Report of 'Candidatus Phytoplasma phoenicium' on Almond in Southern Italy

In spring 2017, phytoplasma suspected symptoms were reported on 25% of 15-year-old almond plants, cultivars Filippo Ceo and Genco grafted onto GF677, in a commercial orchard (20 ha) located at Grottaglie, Apulia (southeast Italy). Among the symptoms, development of many axillary buds with small and yellowish leaves, and witches' brooms developing from the trunk, were the most frequent, followed by leaf rosetting, proliferation of slender shoots, tree decline, and dieback

Fungal pathogens associated with harvested table grapes in Lebanon, and characterization of the mycotoxigenic genera

Table grapes are exposed to fungal infections before and after harvest. In particular, Aspergillus, Penicillium, and Alternaria can cause decays and contamination by mycotoxins. The main fungi affecting Lebanese table grapes after harvest were assessed as epiphytic populations, latent infections, and rots. Effects of storage with and without SO2 generating pads were also evaluated. Representative isolates of toxigenic genera were characterised, and their genetic potential to produce ochratoxin A, fumonisins, and patulin was established. The epiphytic populations mainly included wound pathogens (Aspergillus spp. and Penicillium spp.), while latent infections and rots were mostly caused by Botrytis spp. The use of SO2 generating pads reduced the epiphytic populations and rots, but was less effective against latent infections. Characterization of Aspergillus, Penicillium, and Alternaria isolates showed that A. tubingensis, P. glabrum, and A. alternata were the most common species. Strains of A. welwitschiae and P. expansum were also found to be genetically able to produce, respectively, ochratoxin A plus fumonisins and patulin. These data demonstrate the need for effective measures to prevent postharvest losses caused by toxigenic fung

Evaluation of the Water Quality and the Eutrophication Risk in Mediterranean Sea Area: A Case Study of the Gulf of Gabès

The Gulf of Gabès, located in southern Tunisia, is a distinct and ecologically significant area in the Mediterranean Sea. Unfortunately, this dynamic marine ecosystem is experiencing cultural eutrophication, a process where water enrichment with nutrients like phosphorus and nitrogen salts leads to excessive algae growth, disrupting the ecological equilibrium and degrading water quality. In the Gulf of Gabès, key sources of nutrient pollution include industrial discharges, urbanization and agriculture. Eutrophication’s effects here include harmful algal blooms, oxygen depletion, and declining water quality, upsetting the marine ecosystem’s balance and impacting both fish and aquatic life. Nutrient enrichment interacts with trace metal pollution, overfishing and climate change. Future research must acknowledge and consider the complex interactions among these variables. Efforts in the Gulf of Gabès to address eutrophication involve tighter industrial regulations, enhanced agriculture and improved wastewater management, all crucial for preserving the marine environment’s integrity and ensuring sustainability for the future

Etude numérique de la structure et la dynamique d'un jet coaxial turbulent

Dans ce travail, on se propose d'étudier numériquement un écoulement de type jet coaxial turbulent de l'air dans l'air pour des rapports des vitesses compris entre 1 et 10. 0n s'intéresse particulièrement à l'effet de ce dernier paramètre sur la structure de l'écoulement. Les équations régissant l'écoulement ont été résolues à l'aide d'un code de calcul numérique personnel basé sur une méthode aux volumes finis. Le modèle de fermeture adopté est le modèle de premier ordre k-epsilon standard. Les résultats obtenus montrent l'apparition d'une zone tourbillonnaire au voisinage de l'axe du jet pour des rapports des vitesses r égal à 3. La structure de l'écoulement dépend étroitement de la présence de ces tourbillons

A Novel Convolutional Neural Network Classification Approach of Motor-Imagery EEG Recording Based on Deep Learning

Abstract: Recently, Electroencephalography (EEG) motor imagery (MI) signals have received increasing attention because it became possible to use these signals to encode a person’s intention to perform an action. Researchers have used MI signals to help people with partial or total paralysis, control devices such as exoskeletons, wheelchairs, prostheses, and even independent driving. Therefore, classifying the motor imagery tasks of these signals is important for a Brain-Computer Interface (BCI) system. Classifying the MI tasks from EEG signals is difficult to offer a good decoder due to the dynamic nature of the signal, its low signal-to-noise ratio, complexity, and dependence on the sensor positions. In this paper, we investigate five multilayer methods for classifying MI tasks: proposed methods based on Artificial Neural Network, Convolutional Neural Network 1 (CNN1), CNN2, CNN1 with CNN2 merged, and the modified CNN1 with CNN2 merged. These proposed methods use different spatial and temporal characteristics extracted from raw EEG data. We demonstrate that our proposed CNN1-based method outperforms state-of-the-art machine/deep learning techniques for EEG classification by an accuracy value of 68.77% and use spatial and frequency characteristics on the BCI Competition IV-2a dataset, which includes nine subjects performing four MI tasks (left/right hand, feet, and tongue). The experimental results demonstrate the feasibility of this proposed method for the classification of MI-EEG signals and can be applied successfully to BCI systems where the amount of data is large due to daily recording

Antioxidant Properties of Metabolites from New Extremophiles Microalgal Strain (Southern, Tunisia)

With the demand for bioproducts that can provide benefits for biotechnology sectors like pharmaceuticals, nutraceuticals, and cosmeceuticals, the exploration of microalgal products has turned toward extremophiles. This chapter is intended to provide an insight to most important molecules from halotolerant species, the cyanobacteria Phormidium versicolor NCC-466 and Dunaliella sp. CTM20028 isolated from Sfax Solar Saltern (Sfax) and Chott El-Djerid (Tozeur), Tunisia. These microalgae have been cultured in standard medium with a salinity of 80 PSU. The in vitro antioxidant activities demonstrated that extremolyte from Dunaliella and Phormidium as, phycocaynin, lipids, and polyphenol compound presents an important antioxidant potential

Review On The Methods To Solve Combinatorial Optimization Problems Particularly:Quadratic Assignment Model

The quadratic assignment problem (QAP) is one of the fundamental combinatorial optimization problem (COPs) in the branch of optimization or operation research in mathematics,from the category of the Facilities Location Problems (FLPs).The quadratic assignment problem (QAP) be appropriate to the group of NP-hard issues and is measured as a challenging problem of the combinatorial optimization.QAP in Location Theory considers one of the problems of facilities tracing which the rate of locating a facility be determined by the spaces between facilities as well as the communication among the further facilities.QAP was presented in 1957 by Beckman and Koopmans as they were attempting to model a problem of facilities location.To survey the researcher’s works for QAP and applied,the mapped research landscape outlines literature into a logical classification and discovers this field basic characteristics represented on the motivation to use the quadratic assignment problem applied in hospital layout and campus planning.This survey achieved a concentrated each QAP article search in three key databases:Web of Science,Science Direct,and IEEE Xplore.Those databases are regarded extensive adequate in covering QAP and the methods utilized in solving QAP

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years—a prospective multicentre cohort study

Funding Information: COVIP study did not have any funding. Publication of this article was funded by the Priority Research Area qLife under the program “Excellence Initiative – Research University” at the Jagiellonian University in Krakow (06/IDUB/2019/94). Publisher Copyright: © 2022, The Author(s).Background: Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV. Methods: This is a substudy of COVIP study—an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality. Results: Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36–5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06–2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI − 2.27 to − 0.46 days) compared to primary IMV group (n = 1876). Conclusions: Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial RegistrationNCT04321265, registered 19 March 2020, https://clinicaltrials.gov.publishersversionpublishe

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020