Bidirectional communication infrastructure of smart systems, such as smart grids, are vulnerable to network attacks like distributed denial of services (DDoS) and can be a major concern in the ...present competitive market. In DDoS attack, multiple compromised nodes in a communication network flood connection requests, bogus data packets or incoming messages to targets like database servers, resulting in denial of services for legitimate users. Recently, machine learning based techniques have been explored by researchers to secure the network from DDoS attacks. Under different attack scenarios on a system, measurements can be observed either in an online manner or batch mode and can be used to build predictive learning systems. In this work, we propose an efficient DDoS attack detection technique based on multilevel auto-encoder based feature learning. We learn multiple levels of shallow and deep auto-encoders in an unsupervised manner which are then used to encode the training and test data for feature generation. A final unified detection model is then learned by combining the multilevel features using and efficient multiple kernel learning (MKL) algorithm. We perform experiments on two benchmark DDoS attack databases and their subsets and compare the results with six recent methods. Results show that the proposed method outperforms the compared methods in terms of prediction accuracy.
Cyber-security challenges are growing globally and are specifically targeting critical infrastructure. Conventional countermeasure practices are insufficient to provide proactive threat hunting. In ...this study, random forest (RF), support vector machine (SVM), multi-layer perceptron (MLP), AdaBoost, and hybrid models were applied for proactive threat hunting. By automating detection, the hybrid machine learning-based method improves threat hunting and frees up time to concentrate on high-risk warnings. These models are implemented on approach devices, access, and principal servers. The efficacy of several models, including hybrid approaches, is assessed. The findings of these studies are that the AdaBoost model provides the highest efficiency, with a 0.98 ROC area and 95.7% accuracy, detecting 146 threats with 29 false positives. Similarly, the random forest model achieved a 0.98 area under the ROC curve and a 95% overall accuracy, accurately identifying 132 threats and reducing false positives to 31. The hybrid model exhibited promise with a 0.89 ROC area and 94.9% accuracy, though it requires further refinement to lower its false positive rate. This research emphasizes the role of machine learning in improving cyber-security, particularly for critical infrastructure. Advanced ML techniques enhance threat detection and response times, and their continuous learning ability ensures adaptability to new threats.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
To meet increasing global food demand, breeders and scientists aim to improve the yield and quality of major food crops. Plant diseases threaten food security and are expected to increase because of ...climate change. CRISPR genome-editing technology opens new opportunities to engineer disease resistance traits. With precise genome engineering and transgene-free applications, CRISPR is expected to resolve the major challenges to crop improvement. Here, we discuss the latest developments in CRISPR technologies for engineering resistance to viruses, bacteria, fungi, and pests. We conclude by highlighting current concerns and gaps in technology, as well as outstanding questions for future research.
Improved crops can contribute to a world without hunger, if properly managed
A world without hunger is possible but only if food production is sustainably increased and distributed and extreme ...poverty is eliminated. Globally, most of the poor and undernourished people live in rural areas of developing countries, where they depend on agriculture as a source of food, income, and employment. International data show a clear association between low agricultural productivity and high rates of undernourishment (
1
). Global studies have also shown that rapid reduction of extreme poverty is only possible when the incomes of smallholder farmers are increased (
2
). Therefore, sustained improvement in agricultural productivity is central to socioeconomic development. Here, we argue that with careful deployment and scientifically informed regulation, new plant breeding technologies (NPBTs) such as genome editing will be able to contribute substantially to global food security.
Summary
Tomato leaf curl New Delhi virus (ToLCNDV) is an exceptional Old World bipartite begomovirus. On the Indian subcontinent, a region in which monopartite DNA satellite‐associated begomoviruses ...with mostly narrow geographical ranges predominate, it is widespread, with a geographical range also including the Far East, Middle East, North Africa and Europe. The success of ToLCNDV probably derives from its broad host range and highly flexible genomic configuration: its DNA‐A component is capable of productively interacting with, and trans‐replicating, diverse DNA‐B components and betasatellites. An understanding of the capacity of ToLCNDV to infect a variety of hosts and spread across a broad and ecologically variable geographical range could illuminate the potential economic threats associated with similar begomoviral invasions. Towards this end, we used available ToLCNDV sequences to reconstruct the history of ToLCNDV spread.
Taxonomy
Family Geminiviridae, Genus Begomovirus. ToLCNDV is a bipartite begomovirus. Following the revised begomovirus taxonomic criteria of 91% and 94% nucleotide identity for species and strain demarcation, respectively, ToLCNDV is a distinct species with two strains: ToLCNDV and ToLCNDV‐Spain.
Host range
The primary cultivated host of ToLCNDV is tomato (Solanum lycopersicum), but the virus is also known to infect 43 other plant species from a range of families, including Cucurbitaceae, Euphorbiaceae, Solanaceae, Malvaceae and Fabaceae.
Disease symptoms
Typical symptoms of ToLCNDV infection in its various hosts include leaf curling, vein thickening, puckering, purpling/darkening of leaf margins, leaf area reduction, internode shortening and severe stunting.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Geminiviruses cause damaging diseases in several important crop species. However, limited progress has been made in developing crop varieties resistant to these highly diverse DNA viruses. Recently, ...the bacterial CRISPR/Cas9 system has been transferred to plants to target and confer immunity to geminiviruses. In this study, we use CRISPR-Cas9 interference in the staple food crop cassava with the aim of engineering resistance to African cassava mosaic virus, a member of a widespread and important family (Geminiviridae) of plant-pathogenic DNA viruses.
Our results show that the CRISPR system fails to confer effective resistance to the virus during glasshouse inoculations. Further, we find that between 33 and 48% of edited virus genomes evolve a conserved single-nucleotide mutation that confers resistance to CRISPR-Cas9 cleavage. We also find that in the model plant Nicotiana benthamiana the replication of the novel, mutant virus is dependent on the presence of the wild-type virus.
Our study highlights the risks associated with CRISPR-Cas9 virus immunity in eukaryotes given that the mutagenic nature of the system generates viral escapes in a short time period. Our in-depth analysis of virus populations also represents a template for future studies analyzing virus escape from anti-viral CRISPR transgenics. This is especially important for informing regulation of such actively mutagenic applications of CRISPR-Cas9 technology in agriculture.
The topic of fluid flow through disks is important due to a broad range of its applications in industries, engineering, and scientific fields. The objective of the current article is to analyze the ...bioconvective micropolar nanofluid flow between the coaxial, parallel, and radially stretching double disks in the occurrence of gyrotactic motile microorganisms with convective thermal boundary conditions. Darcy–Forchheimer medium is considered between the double disks that allow the flow horizontally with additional effects of porosity and friction. The flow is also considered under the impacts of thermal conductivity and thermal radiations. The influence of gyrotactic microorganisms is accommodated through the bioconvection, which increases the strength of thermal transportation. Furthermore, the Cattaneo-Christov heat flux theory is also accounted. The flow model is trans moved into a system of ordinary differential equations (ODEs) utilizing appropriate similarity transformation functions. The bvp4c technique has been used to solve the transformed flow model. The implication of some prominent physical and bioconvection parameters on velocities, microrotation, thermal field, volumetric concentration of nanoparticles, and microorganisms’ fields are presented through graphs and tabular ways. It is observed that the stretching ratio parameter of the disks accelerates the axial and micro rotational velocities of the nanofluid. In contrast, the stretching Reynolds number slows down the radial velocity near the plane’s center. The temperature profile goes high against the Brownian motion, thermal radiation, and thermal conductivity parameters, while an inverse trend has been observed for increasing magnitudes of Prandtl number. The nanoparticles concentration profile is upsurged against the thermophoresis parameter. The density profile of gyrotactic motile microorganisms is de-escalated by the Peclet number and the bioconvection Lewis number. Micropolar parameters cause an increase of couple stresses and a decrement in shear stresses. A comparison with published work is provided under certain limitations to test the validity of numerical scheme accuracy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective
Status epilepticus is a life‐threatening neurological emergency. However, delay in median time to administration of second‐line antiseizure medication exists. The aim of this quality ...improvement initiative was to decrease the average delay before fosphenytoin is administered for pediatric patients with generalized convulsive status epilepticus from 30 min (baseline data collected in 2013) to 15 min (50% reduction) by December 2015 and sustain this for 1 year.
Methods
Our team conducted an analysis of baseline data for patients with continuous generalized convulsive status epilepticus who received fosphenytoin after receiving first‐line benzodiazepine treatment. Using quality improvement methodology, areas for improvement were identified and specific interventions developed and implemented. A timeline of 15 min to initiate fosphenytoin administration after failure of first‐line treatment was considered reasonable and achievable as a project aim.
Results
A total of 199 patients were included in the dataset for the project. The database included patients aged 1 month and older. Ninety‐eight percent of patients were between 1 month and 19 years of age. The gender distribution was even, with 54% of patients being White or Caucasian, 30% African American or Black, and 16% classified as “other.” From January 2014 through December 2019, the average time before initiating fosphenytoin administration after failure of benzodiazepine therapy, for patients with generalized convulsive status epilepticus, decreased from 30 min (SD = 45.7) to 11.4 min (SD = 8.2, p = .043), thus reducing time to administration by 62%.
Significance
Quality improvement methodology can be successfully applied to decrease administration time between first‐ and second‐line antiseizure medications for status epilepticus.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Recent advances in genome engineering (GE) has made it possible to precisely alter DNA sequences in plant cells, providing specifically engineered plants with traits of interest. Gene targeting ...efficiency depends on the delivery-method of both sequence-specific nucleases and repair templates, to plant cells. Typically, this is achieved using
mediated transformation or particle bombardment, both of which transform only a subset of cells in treated tissues. The alternate
approaches, stably integrating nuclease-encoding cassettes and repair templates into the plant genome, are time consuming, expensive and require extra regulations. More efficient GE reagents delivery methods are clearly needed if GE is to become routine, especially in economically important crops that are difficult to transform. Recently, autonomously replicating virus-based vectors have been demonstrated as efficient means of delivering GE reagents in plants. Both DNA viruses (
and
) and RNA virus (
) have demonstrated efficient gene targeting frequencies in model plants (
) and crops (potato, tomato, rice, and wheat). Here we discuss the recent advances using viral vectors for plant genome engineering, the current limitations and future directions.
Plant viruses infect many economically important crops, including wheat, cotton, maize, cassava, and other vegetables. These viruses pose a serious threat to agriculture worldwide, as decreases in ...cropland area
may cause production to fall short of that required to feed the increasing world population. Under these circumstances, conventional strategies can fail to control rapidly evolving and emerging plant viruses. Genome-engineering strategies have recently emerged as promising tools to introduce desirable traits in many eukaryotic species, including plants. Among these genome engineering technologies, the CRISPR (clustered regularly interspaced palindromic repeats)/CRISPR-associated 9 (CRISPR/Cas9) system has received special interest because of its simplicity, efficiency, and reproducibility. Recent studies have used CRISPR/Cas9 to engineer virus resistance in plants, either by directly targeting and cleaving the viral genome, or by modifying the host plant genome to introduce viral immunity. Here, we briefly describe the biology of the CRISPR/Cas9 system and plant viruses, and how different genome engineering technologies have been used to target these viruses. We further describe the main findings from recent studies of CRISPR/Cas9-mediated viral interference and discuss how these findings can be applied to improve global agriculture. We conclude by pinpointing the gaps in our knowledge and the outstanding questions regarding CRISPR/Cas9-mediated viral immunity.
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