Miracle-dz/UniFAR-FTUs huggingface dataset:
ScaDS Dresden/Leipzig – A competence center for collaborative big data research

Abstract The efficient and intelligent handling of large, often distributed and heterogeneous data sets increasingly determines the scientific and economic competitiveness in most application areas. Mobile applications, social networks, multimedia collections, sensor networks, data intense scientific experiments, and complex simulations nowadays generate a huge data deluge. Nonetheless, processing and analyzing these data sets with innovative methods open up new opportunities for its exploitation and new insights. Nevertheless, the resulting resource requirements exceed usually the possibilities of state-of-the-art methods for the acquisition, integration, analysis and visualization of data and are summarized under the term big data. ScaDS Dresden/Leipzig, as one Germany-wide competence center for collaborative big data research, bundles efforts to realize data-intensive applications for a wide range of applications in science and industry. In this article, we present the basic concept of the competence center and give insights in some of its research topics.
Do adjuvants reduce the antagonism of quizalofop-p-ethyl when mixed with bispyribac-Na?

Abstract Acetyl co-enzyme A carboxylase (ACCase)-resistant rice allows quizlaofop-p-ethyl to be applied as a POST control of troublesome grass weeds. A field study was conducted in 2017 and 2018 at the H. Rouse Caffey Rice Research Station near Crowley, LA, to evaluate the influence of a crop oil concentrate (COC), a silicon-based surfactant plus a nitrogen source (SNS), or a high-concentrate COC (HCOC) in overcoming the grass weed control antagonism of quizalofop-p-ethyl when mixed with bispyribac-Na. Quizalofop-p-ethyl was applied at 120 g ai ha–1, bispyribac-Na was applied at 34 g ai ha–1, and all adjuvants were applied at 1% vol/vol. Antagonistic interactions were observed at 14 d after treatment (DAT) when quizalofop-p-ethyl was mixed with bispyribac-Na with no adjuvant for control of barnyardgrass, the non–ACCase-tolerant rice cultivars ‘CL-111’ and ‘CLXL-745’, and red rice. At 14 DAT, antagonism of quizalofop-p-ethyl for control of barnyardgrass was observed when mixed with bispyribac-Na plus COC, SNS, or HCOC, with an observed control of 43%, 63%, and 86%, respectively, compared with an expected control of 95% for quizalofop-p-ethyl alone. However, the antagonism of quizalofop-p-ethyl when mixed with bispyribac-Na plus HCOC for barnyardgrass control at 14 DAT was overcome by 28 DAT, with an observed control of 91%, compared with an expected control of 97%. Synergistic or neutral interactions were observed at 14 and 28 DAT when COC, SNS, or HCOC was added to a mixture of quizalofop-p-ethyl plus bispyribac-Na for CL-111, CLXL-745, and red rice control. According to the results of this study, HCOC is the most effective adjuvant for quizalofop-p-ethyl and bispyribac-Na mixtures for control of weedy rice and barnyardgrass. Nomenclature: Bispyribac-Na; quizalofop-p-ethyl; barnyardgrass, Echinochloa crus-galli (L.) P. Beauv. ; red rice, Oryza sativa L. ; rice, Oryza sativa L.
Enhanced Wheat Competition Effects on the Growth, Seed Production, and Seed Retention of Major Weeds of Australian Cropping Systems

Abstract The loss of herbicide options due to resistance and lack of new chemistries have delivered the realization that herbicides are a finite resource and weed control alternatives are desperately needed. In Australian conservation cropping, the only available alternatives suited to routine use are the recently introduced harvest weed seed control (HWSC) and the ever-present but undervalued crop competition. Target-neighbor design pot studies examined wheat (Triticum aestivum L.) competition effects on biomass and seed production of rigid ryegrass (Lolium rigidum Gaudin), wild radish (Raphanus raphanistrum L.), ripgut brome (Bromus diandrus Roth), and wild oat (Avena fatua L.). The influence of wheat competition on crop canopy distribution of weed biomass and seed production was also examined. At the current commercially targeted wheat density (120 plants m–2) weed biomass was reduced by 69%, 73%, 72%, and 49% and seed production by 78%, 78%, 77%, and 50% for L. rigidum, R. raphanistrum, B. diandrus, and A. fatua, respectively, when compared with no competition. These results highlighted the importance of uniform wheat crop establishment in minimizing the ongoing impact of weeds. Enhanced what competition (from 120 to 400 plants m–2) resulted in further smaller, but substantial, reductions in biomass (19%, 13%, 20%, and 39%) and seed production (12%, 13%, 17%, and 45%) for L. rigidum, R. raphanistrum, B. diandrus, and A. fatua, respectively. This enhanced competition also increased weed seed retention in the upper crop canopy (>40 cm) by 35% and 31% for L. rigidum and B. diandrus, respectively, but not for A. fatua and R. raphanistrum, for which weed seed retention was already >80% at the wheat density of 120 plants m–2. Enhanced wheat crop competition, then, has the dual effect of restricting the growth and development of L. rigidum, R. raphanistrum, B. diandrus, and A. fatua as well increasing the susceptibility of these weed species to HWSC.
Safeguarding the genetic integrity of native pollinators requires stronger regulations on commercial lines

Every year more than one million commercial bumblebee colonies are deployed in greenhouses worldwide for its pollination services to several commercially important crops such as tomato and different species of berries. While commercial pollinators have been an enormous benefit for the production of essential food crops and for achieving higher yields and better fruit quality at a low cost, their use is emerging also as an important threat to wild pollinators. Commercial pollinators have been linked to pathogen spillover to wild species, and its introduction outside its native area have had devastating effects on native pollinator populations. However, a more pervasive, but underappreciated threat is their potential impact on the genetic integrity of native pollinators. Here, we show clear evidence of generalized hybridization between native and introduced commercial bumblebee lineages in southern Spain. The signal of genetic introgression is widespread and already expands up to 60 km from main commercial bumblebee release areas. As pollination services demand is predicted to increase in the coming years, only a more restrictive regulation of commercial lines could mitigate their negative impacts on the genetic integrity of native pollinators and prevent the disruption of local adaptations.
Fungal community composition in sodic soils subjected to long-term rice cultivation

ABSTRACT Rice cultivation is widely used to improve saline-sodic soils in Northeast China. However, the chronological effect of rice cultivation on soil fungal communities has not been studied. Therefore, this study investigated the variation of soil fungal communities in different rice cultivation years. Compared with the blank area, the rice cultivation for 20 years significantly decreased the pH and electrical conductivity by 16.6% and 70.1%, while significantly increased the soil organic carbon and available phosphorus by 90.6% and 17.4 times, respectively. Meanwhile, the relative abundance of Ascomycota and Basidiomycota significantly decreased and increased after rice cultivation, respectively. Moreover, some genera of arbuscular mycorrhizal fungi (AMF), e.g. Corymbiglomus, Glomus, and Rhizophagus, and pathogenic fungi (Thanatephorus cucumeris) disappeared, while Dentiscutata (one genus of AMF) appeared after rice cultivation. In addition, the fungal richness significantly increased when the rice cultivation less than 15 years and the fungal communities were similar between 15 and 20 years. Our findings showed that rice cultivation improved the nutrient availability and reduced salinity-alkalinity stress of sodic soils. After the rice cultivation for 15 years, the soil fungal community tended to be stable.
Investigation of phenotypic and molecular diversity of Descurainia sophia (L.) Webb ex Prantl and Sisymbrium irio (L.)

Descurainia sophia and Sisymbrium irio , both from Brassicaceae family have potential medicinal effects. Seeds are consumed widely across Iran in sweet drinks. To determine the morphological and molecular diversity, 55 genotypes from these two genera were studied. All 11 ISSR primers detected polymorphism and generated 274 polymorphic loci. The average values of Polymorphism Information Content (PIC), Marker Index (MI) and Resolving Power (Rp) for ISSR primers were 0.278, 6.899 and 11.57, respectively. The AMOVA analysis revealed a high genetic variation (58%) within each genus. The UPGMA clustering based on molecular analysis separated all 55 genotypes into two main groups, correlating with division of plants into two genera. Moreover, seven morphological traits were evaluated to distinguish all 55 genotypes. Among them, rosette figure showed the most significant differentiation between two genera. The highest correlation was observed between two traits of seed color and seed weight at 0.758. The dendrogram obtained from the morphological traits corresponded with the UPGMA clustering. The chemical composition of essential oils of D. sophia and S. irio were identified via gas chromatography mass spectrum (GC-MS). Although GC-MS analysis detected β-pinene as the dominant component in both plants but different compounds were also detected. The present investigation clearly indicates that these morphological traits alone or combined with molecular analysis using 11 ISSR markers is considered as the true reflection of two genera partitioning, and hence the eligibility of both molecular and morphological criterion are proved. These findings could be used for future breeding programs in fields of seed production and medicinal extracts. Normal 0 21 false false false HR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Obicna tablica"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}
The Human Microbiome: Composition and Change Reflecting Health and Disease

In humans, microbial organisms known as the microbiota, normally colonize airway passages, skin, the oral cavity, the gastrointestinal tract, and the vagina. There is a growing body of evidence linking the gut microbiota with the overall health of its host. Normally, the microbes that make up the microbiota coexist with a human or animal host without any noticeable difficulty. However, if the symbiotic balance is altered as a result of illness, stress, dietary changes, antibiotic treatment, or other disturbances, the result may be a disruption of normal interactions known as dysbiosis. As a result, the body may become more susceptible to disease. This article examines the most common means by which the microbiota are identified, the process by which the microbiome is acquired, fecal microbial transplantation, and the association of the gut microbiome with specific illnesses such as diabetes and autism. The utility of these applications in developing a teaching module that incorporates the microbiome into courses in physiology or pathophysiology is also reviewed. https://doi.org/10.21692/haps.2019. 020
Vertical stratification and stability of biogeochemical processes in the deep saline waters of Lake Vanda, Antarctica

Lake Vanda is a permanently ice‐covered lake in the McMurdo Dry Valleys of Antarctica. Its bottom waters remain stratified year‐round because of a strong salinity‐driven density gradient. We have assessed spatial patterns in and relationships between major biogeochemical processes in the water column of Lake Vanda. Samples were collected in the austral summers of 2008 and 2011 to measure concentrations of metabolites associated with a suite of biogeochemical processes across the deep salinity gradient. The shapes of the resulting geochemical profiles were consistent between 2008 and 2011. Metabolite production and consumption rates were estimated using a reactive transport model based on the assumption that vertical diffusion was the only active physical transport process. We validated this model for nitrification by using stable isotope incubations to show that this process was only active at depths predicted by the model. No nitrification activity was observed at 68 m depth in spite of overlapping oxygen and ammonium gradients. We attribute this lack of activity to the competitive inhibition of ammonia monooxygenase by methane. Net nitrous oxide and nitrate consumption were observed in the oxic water column, providing evidence of aerobic denitrification. The depth of maximum net oxygen production did not coincide with the deep chlorophyll maxima (at 59.3, 63, and 68.2 m) measured in the same profile. Finally, the integrated sulfide oxidation rate was high compared with other oxidation processes, indicating that sulfide was an important electron donor for the water column microbial community.
A Disturbance Rejection-Based Control Strategy for Five-Level T-Type Hybrid Power Converters With Ripple Voltage Estimation Capability

This article proposes a robust control strategy for five-level T-type (5L-T) hybrid power converters to achieve superior dynamic performance for effectively regulating the dc-bus voltage under external disturbances and generating high-quality grid current at the same time. A new filter-less dc-bus ripple voltage estimation method and a simple technique to remove this ripple component from the measured dc-bus voltage of a single-phase converter are developed. A sliding-mode control (SMC) incorporated with an extended-state observer (ESO) is employed for the outer voltage control loop, and to dynamically calculate the input (i.e., the active power reference) for the inner current-tracking controller. The proposed SMC-ESO approach presents a high disturbance rejection capability and robustness against the dc-bus load variation, and thus, significantly improves the dynamic and steady-state performance during system uncertainties. Moreover, a finite control set-model predictive control algorithm is derived as the inner current controller to track their references while balancing the dc-bus capacitor voltages. The effectiveness of the proposed controller is demonstrated and verified through measurement results.
The Interplay of Transistors and Accelerators

The slowdown and the nearing end of transistor scaling play a vital role in the rise of domain-specific architectures. Domain-specific architectures rely on “accelerators” that are specialized chips designed to efficiently execute dominating computation patterns and improve performance under a given transistor budget. Unfortunately, accelerators like FPGAs and ASIC chips are also implemented using transistors, and therefore abide by the same transistor limitations that motivated their deployment. The wide-spread of accelerators necessitates new ways to evaluate the impact of specialization in modern chips. We present a methodology that decouples specialization-driven benefits from transistor-driven benefits, and show that in popular accelerator applications specialization gains are less significant than transistor-driven gains.
Synthesis and Characterization of CoSBA-1 Cubic Mesoporous Molecular Sieves

Vanadosilicate V-SBA-1, which incorporated more than 4 wt % vanadium (Si/V < 20) in cubic mesoporous molecular sieves, was directly synthesized under strongly acidic conditions and characterized by various techniques. Powder X-ray diffraction (XRD) showed that the resultant samples had a well-ordered cubic SBA-1 structure. The structural regularity of V-SBA-1 was improved by preparation under highly acidic conditions. N2 adsorption/desorption measurements confirmed that an additional large mesopore (≈40 A) was simultaneously produced with the main one (≈20 A) in SBA-1 after the incorporation of vanadium into the SBA-1 framework. UV−vis and laser Raman results revealed that the incorporated vanadium species existed in a highly dispersed state and had tetrahedral coordination.
Dual-valve parallel prediction control for an electro-hydraulic servo system

To improve the dynamic response performance of a high-flow electro-hydraulic servo system, scholars have conducted considerable research on the synchronous and time-sharing controls of multiple valves. However, most scholars have used offline optimization to improve control performance. Thus, control performance cannot be dynamically adjusted or optimized. To repeatedly optimize the performance of multiple valves online, this study proposes a method for connecting a high-flow proportional valve in parallel with a low-flow servo valve. Moreover, this study proposes an algorithm in which a proportional–integral–derivative system and multivariable predictive control system are used as an inner loop and outer loop, respectively. The simulation and experimental results revealed that dual-valve parallel control could effectively improve the control accuracy and dynamic response performance of an electro-hydraulic servo system and that the proportional-integral-derivative–multivariable predictive control controller could further dynamically improve the control accuracy.
Leveraging Image Representation of Network Traffic Data and Transfer Learning in Botnet Detection

The advancements in the Internet has enabled connecting more devices into this technology every day. The emergence of the Internet of Things has aggregated this growth. Lack of security in an IoT world makes these devices hot targets for cyber criminals to perform their malicious actions. One of these actions is the Botnet attack, which is one of the main destructive threats that has been evolving since 2003 into different forms. This attack is a serious threat to the security and privacy of information. Its scalability, structure, strength, and strategy are also under successive development, and that it has survived for decades. A bot is defined as a software application that executes a number of automated tasks (simple but structurally repetitive) over the Internet. Several bots make a botnet that infects a number of devices and communicates with their controller called the botmaster to get their instructions. A botnet executes tasks with a rate that would be impossible to be done by a human being. Nowadays, the activities of bots are concealed in between the normal web flows and occupy more than half of all web traffic. The largest use of bots is in web spidering (web crawler), in which an automated script fetches, analyzes, and files information from web servers. They also contribute to other attacks, such as distributed denial of service (DDoS), SPAM, identity theft, phishing, and espionage. A number of botnet detection techniques have been proposed, such as honeynet-based and Intrusion Detection System (IDS)-based. These techniques are not effective anymore due to the constant update of the bots and their evasion mechanisms. Recently, botnet detection techniques based upon machine/deep learning have been proposed that are more capable in comparison to their previously mentioned counterparts. In this work, we propose a deep learning-based engine for botnet detection to be utilized in the IoT and the wearable devices. In this system, the normal and botnet network traffic data are transformed into image before being given into a deep convolutional neural network, named DenseNet with and without considering transfer learning. The system is implemented using Python programming language and the CTU-13 Dataset is used for evaluation in one study. According to our simulation results, using transfer learning can improve the accuracy from 33.41% up to 99.98%. In addition, two other classifiers of Support Vector Machine (SVM) and logistic regression have been used. They showed an accuracy of 83.15% and 78.56%, respectively. In another study, we evaluate our system by an in-house live normal dataset and a solely botnet dataset. Similarly, the system performed very well in data classification in these studies. To examine the capability of our system for real-time applications, we measure the system training and testing times. According to our examination, it takes 0.004868 milliseconds to process each packet from the network traffic data during testing.
The transfer of a mitochondrial selfish element to the nuclear genome and its consequences

Homing endonucleases (HE) are enzymes capable of excising their encoding gene and inserting it in a highly specific target sequence. As such, they act both as intronic sequences (type-I introns) and selfish invasive elements. HEs are present in all three kingdoms of life and viruses; in eukaryotes, they are mostly found in the genomes of mitochondria and chloroplasts, as well as nuclear ribosomal RNAs. We here report the case of a HE that integrated into a telomeric region of the fungal maize pathogen Ustilago maydis. We show that the gene has a mitochondrial origin, but its original copy is absent from the U. maydis mitochondrial genome, suggesting a subsequent loss or a horizontal transfer. The telomeric HE underwent mutations in its active site and acquired a new start codon, but we did not detect significant transcription of the newly created open reading frame. The insertion site is located in a putative RecQ helicase gene, truncating the C-terminal domain of the protein. The truncated helicase is expressed during infection of the host, together with other homologous telomeric helicases. This unusual homing event represents a singular evolutionary time point: the creation of two new genes whose fate is not yet written. The HE gene lost its homing activity and can potentially acquire a new function, while its insertion created a truncated version of an existing gene, possibly altering its original function.
Understanding the Relationship Between the Tonsil Microbiota and Clinical Streptococcus suis Infection in Nursery Pigs

UNDERSTANDING THE RELATIONSHIP BETWEEN THE TONSIL MICROBIOTA AND CLINICAL STREPTOCOCCUS SUIS INFECTION IN NURSERY PIGS Sarah Hill University of Guelph, 2019 Advisor(s): Dr. Nicole Ricker Dr. Vahab Farzan The objective of this study was to determine if the tonsillar microbiota is different in nursery pigs with Streptococcus suis disease compared with that of healthy pigs. Fiftysix pigs from 9 farms were classified as confirmed cases, probable cases and healthy controls. Illumina MiSeq-sequencing of the 16S V3-V4 hypervariable region was done to assess the microbiota composition and the mothur pipeline was used for clustering and taxonomical assignment. Overall, 453, 600 and 334 different taxa were identified in confirmed cases, probable cases and controls, respectively. The beta diversity differed significantly between the farms (p=0.035). Alpha diversity differed between probable cases and control (p<0.001) and tended to be different between confirmed and probable cases (p=0.088). The inverse Simpson tended to be different between confirmed cases and controls (p=0.083). Phylogenetic analysis demonstrated no differences between the microbiota of nursery pigs with clinical S. suis infection and that of heathy animals.