Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Heat Stress on Expression of Wheat Genes Responsive to Hessian Fly Infestation

Heat stress compromises wheat (Triticum aestivium) resistance to Hessian fly (HF, Mayetiola destructor (Say)). This study aimed to investigate the impact of heat stress on transcript expression of wheat genes associated with resistance to HF infestation under normal and heat-stressed conditions. To this end, ‘Molly’, a wheat cultivar containing the resistance gene H13, was subjected to HF infestation, heat stress, and the combination of HF infestation and heat stress. Our RNA-Seq approach identified 21 wheat genes regulated by HF infestation under normal temperatures (18 °C) and 155 genes regulated by HF infestation when plants were exposed to 35 °C for 6 h. Three differentially expressed genes (DEGs) from the RNA-Seq analysis were selected to validate the gene function of these DEGs using the RT-qPCR approach, indicating that these DEGs may differentially contribute to the expression of wheat resistance during the early stage of wheat–HF interaction under various stresses. Moreover, the jasmonate ZIM domain (JAZ) gene was also significantly upregulated under these treatments. Our results suggest that the genes in heat-stressed wheat plants are more responsive to HF infestation than those in plants growing under normal temperature conditions, and these genes in HF-infested wheat plants are more responsive to heat stress than those in plants without infestation.
Low-Temperature Effects on the Growth and Phytochemical Properties of Wheat Sprouts

Sprouting is associated with nutritional value, as microgreens stimulate the accumulation of health-promoting phytochemicals. The purpose of this study was to examine the growth rates and cell protection activity against oxidative stress in sprouts of seven wheat varieties, and to investigate the influence of low temperatures on their phytochemical characteristics. Among the seven wheat varieties (five Korean varieties, Australian standard white, and Chinese wild-type wheat germplasm), purple wheat (Ariheuk) had the fastest growth pattern for 8 days and provided the most protection to skin cells and hepatocytes against oxidative stress. Following low-temperature treatment (<4 °C) for 1–4 days, cold exposure had a similar effect on the growth of purple wheat sprouts during an 8-day period. However, growth was negatively affected by exposure to low temperatures for more than 5 days. Purple wheat sprouts treated with low temperatures for 4 days had considerably higher total polyphenol and total flavonoid contents, as well as a higher antioxidant capacity than untreated wheat sprouts. These findings suggest that low-temperature treatment promotes the expression of phytochemicals in purple wheat sprouts. Thus, purple wheat sprouts are considered a high-value crop that could be used as a functional food material.
Artificial Intelligence and Terrain Handling of a Hexapod Robot

The focus of this master’s thesis has been getting a six-legged robot to autonomously navigate around a room with obstacles. To make this possible a time-of-flight camera has been implemented in order to map the environment. Two force sensing resistors were also mounted on the front legs to sense if the legs are in contact with the ground. The information from the sensors together with a path planning algorithm and new leg trajectory calculations have resulted in new abilities for the robot. During the project comparisons between different hardware, tools and algorithms have been made in order to choose the ones fitting the requirements best. Tests have also been made, both on the robot and in simulations to investigate how well the models work. The results are path planning algorithms and a terrain handling feature that works very well in simulations and satisfyingly in the real world. One of the main bottlenecks during the project has been the lack of computational power of the hardware. With a stronger processor, the algorithms would work more efficiently and could be developed further to increase the precision of the environment map and the path planning algorithms. (Less)
A Fuzzy Bayesian approach for ‘Appraisal’ of ship voyage plans

ABSTRACT The voyage plans are vital for safe navigation. Organisations such as the International Maritime Organization (IMO) and International Chamber of Shipping (ICS) have established guidelines for voyage planning to decrease risks. Inaccuracies performed during the preparation of voyage plans are among the causes of high rates of detention, according to port state inspection reports. In addition, these inaccuracies are frequently encountered in marine accident investigation reports. Many critical factors should be evaluated by masters in conjunction with their officers in the ‘Appraisal’ section of the voyage plans . This research aims to offer a novel model that may identify the weights of importance for each contributing factor involved in the process of voyage plan appraisal. Fuzzy Bayesian Networks (FBN) were used to determine the weightings of the elements underlying the appraisal section. The findings offer valuable data for developing new strategies to reduce the risk of maritime accidents and ship detentions.
A Unified Approach for Controller Reduction in Delta Domain

A Unified framework for controller reduction in the complex delta domain is presented. The frequency domain method computes the parameters of a low order; easily implementable controller in an approximate Pade’ sense by matching the frequency response of the plant cascaded with high order controller. The reduction algorithm is applicable to single-input-single-output (SISO) systems. It further produces a low order discrete-time controller at course sampling frequency and a low order analog controller at high sampling frequency. Example is included to illustrate the usefulness of the method.
Subretinal drusenoid deposits: An update

A wide spectrum of phenotypic manifestations characterizes age-related macular degeneration (AMD). Drusen is considered the hallmark of AMD and is located underneath the retinal pigment epithelium (RPE). In contrast, subretinal drusenoid deposits (SDDs), also known as reticular pseudodrusens, are located in the subretinal space, on top of the RPE. SDDs are poorly detected by clinical examination and color fundus photography. Multimodal imaging is required for their proper diagnosis. SDDs are topographically and functionally related to rods. SDDs cause a deep impairment in retinal sensitivity and dark adaptation. SDDs are dynamic structures that may grow, fuse with each other, or regress over time. An intermediate step in some eyes is the development of an acquired vitelliform lesion. The presence of SDD confers an eye a high risk for the development of late AMD. SDD leads to macular neovascularization, particularly type 3, geographic atrophy, and outer retinal atrophy.
Development of KNN-EIM based hybrid model for brain MRI density range determination

Data mining techniques are used in the medical data analysis to predict the hidden knowledge from the existing data. This work attempted to apply the data mining techniques to analysis the medical image focus to brain tumor evaluation. The affected tumor region range values. The work focused to evaluate the performance of clustering algorithms for medical image analysis via predicting the tumor affected area. It is achieved through analysing Brain MRI to identify the high-density neuron using the integrated approach of K-Means and Equal Interval clustering. The tumour affected area and its range values are identified using a clustering algorithm such as Equal Interval Method and K-Means approach. To enhance the accuracy of the affected region, the common affected high-density pixels are identified using a hybrid model through the Integration of K-Means and Equal Interval Method. It is evaluated according to time complexity and accuracy.
Depth estimation using an improved stereo network

Self-supervised depth estimation approaches present excellent results that are comparable to those of the fully supervised approaches, by employing view synthesis between the target and reference images in the training data. ResNet, which serves as a backbone network, has some structural deficiencies when applied to downstream fields, because its original purpose was to cope with classification problems. The low-texture area also deteriorates the performance. To address these problems, we propose a set of improvements that lead to superior predictions. First, we boost the information flow in the network and improve the ability to learn spatial structures by improving the network structures. Second, we use a binary mask to remove the pixels in low-texture areas between the target and reference images to more accurately reconstruct the image. Finally, we input the target and reference images randomly to expand the dataset and pre-train it on ImageNet, so that the model obtains a favorable general feature representation. We demonstrate state-of-the-art performance on an Eigen split of the KITTI driving dataset using stereo pairs.
EPISTEMOLOGIA DA PRÁTICA: ANÁLISE DA PRODUÇÃO ACADÊMICA EM TESES E DISSERTAÇÕES BRASILEIRAS

Atualmente, há muitas conceituações concernentes ao conceito de epistemologia, à exemplo do constructo denominado “Epistemologia da Prática”. Embora em muitos contextos haver maior utilização de tal conceito, poucos estudos demonstram como tem sido sua utilização no campo científico, isto é, qual tem sido o estado da arte na análise dessa conceituação. Assim, objetivamos analisar o estado da arte das produções acadêmicas que abordam o conceito de Epistemologia da Prática em teses e dissertações publicadas no Brasil, buscando compreender os aspectos quantitativos e qualitativos a esse respeito, no decorrer do recorte temporal de 1999 até 2018, baseado no Catálogo de Teses e Dissertações da CAPES. Os resultados da análise de um total de 98 trabalhos encontrados permitem concluir que a perspectiva da Epistemologia da Prática tem apresentado certa inserção no âmbito das pesquisas na pós-graduação brasileira, especialmente na última década, o que ilustra a proeminência da abordagem desse conceito atualmente. Apesar disso, é fundamental que haja análises criteriosas acerca de suas potencialidades e limitações, bem como considera-se importante haver investimento maior na fundamentação teórica que subsidie os trabalhos de modo mais apropriado.
Development of a dynamic multi-bed Pressure Swing Adsorption process for high purity hydrogen production from Coke Oven Gas: A mathematical modeling approach

Coal is certain to play a major role in the world’s energy future due to its low cost and widespread distribution around the world. At the same time, being the largest contributor to global CO2 emissions from energy use, coal faces significant environmental challenges in terms of air pollution and global warming. The study focuses on developing a pressure swing adsorption (PSA) technology that will allow for continued operation of coal, while improving its energy-efficiency by better utilisation of its by-product coke oven gas from steel industries. A generic, fast and robust simulation tool for simulating a variety of pressure swing adsorption processes considering both equilibrium and kinetic effects using a detailed non-isothermal and non-isobaric model is developed using MATLAB in the study. The adsorption equilibrium data required for the model are first calculated from experimental results using the non-linear regression data fitting method. Activated carbon and zeolite LiX adsorbents are modelled using Spartan molecular modeling software and simulated for estimation of the adsorption equilibrium data. The isosteric heat of adsorption values estimated from the simulation of molecular models matched well with the values calculated from experimental results showing the potential of molecular modeling tool in estimating the adsorption equilibrium data in a simple, fast and cost-effective way. A series of rigorous parametric studies and breakthrough tests are performed using the developed mathematical model for better understanding of the effects of different factors on the PSA process performance. With the better understanding obtained from the above-mentioned parametric studies, the model is optimised by performing several simulation tests to achieve the best possible process performance in terms of purity and recovery of the H2 product, productivity of the adsorbents and energy consumption for compression of gases. The optimised 14-step multi-bed PSA cycle developed in this study allows for an improved energy efficiency of coal usage by better utilisation of its by-product coke oven gas by converting it into valuable high purity (>99.999%) hydrogen fuel for mobility applications with a recovery of over 75%.
High-performance software control platform designed for the autonomous navigation of quad-rotor helicopter

In recent years, unmanned aerial vehicles have gained increasing popularity. They are employed in many applications due to its features in terms of flexibility, low cost, and small size. Due to special structure of mechanical system for the quad-rotor helicopter (typical small-sized unmanned aerial vehicle), one of the main research fields for quad-rotor helicopter is to improve its stability flight control so as to well implement its autonomous navigation. However, for the quad-rotor helicopter whose power is supplied by battery, the embedded operating system directly affects its flight performance; thus, it is of very importance to implement this goal. This article aims to put forward a high-performance software platform consisted of embedded operating system and JAVA virtual machine in the quad-rotor helicopter. Then, this article also proposes an autonomous control algorithm written by real-time JAVA application, which uses image entropy to avoid obstacles and optical flow to discover the most appropriate area to fly in while avoiding obstacles; besides, image identification with image contour detection is used for the cases of junction turn and landing. The practical experimental results show that the implemented software control platform and proposed autonomous flight application are component for indoor autonomous flight of quad-rotor helicopter.
RISK: A PEDAGOGIC NOTE

away. It appears to us that the decomposition of risk into its components is in some cases vague and in most cases imprecise. We define the diversifiable and nondiversifiable risk measures as two complementary components of the stand? ard deviation of a security's rate of return. Furthermore, we require that the nondiversifiable risk measure will completely determine its equilibrium market price. We shall see that the definition presented is appealing for all securi? ties and particularly for those with negative Beta. To be more specific, recall that a security's 3 is given by the slope of the following time series regres? sion:
Upwind, No More: Flexible Traveltime Solutions Using Physics-Informed Neural Networks

The eikonal equation plays an important role across multidisciplinary branches of science and engineering. In geophysics, the eikonal equation and its characteristics are used in addressing two fundamental questions pertaining to seismic waves: what paths do the seismic waves take (its spreading)? and how long do they take? There have been numerous attempts to solve the eikonal equation, which can be broadly categorized as finite-difference (FD)- and physics-informed neural network (PINN)-based approaches. While the former has been developed and optimized over the years, it still inherits some numerical inaccuracies and also the cost scales exponentially with the velocity model size. More importantly, it requires upwind calculations to satisfy the viscosity solution. PINNs, on the other hand, have shown great promise due to several features allowing for higher accuracy and scalability than conventional approaches. In this article, we demonstrate another unique feature of PINN solutions, specifically its flexibility resulting from the global nature of its NN functional optimization, allowing for functional gradients referred to as automatic differentiation. This feature allows us to overcome the inability of conventional methods to handle large areas of missing information (gap) in the velocity model. We find empirically that the PINNs interpolation–extrapolation inherent capability enables us to circumvent a scenario when traveltime modeling is performed on velocity models containing gaps. Such a capability is crucial when performing traveltime modeling using the global tomographic Earth velocity model.
Simulator Sickness and the Oculus Rift

The use of a commercial-off-the-shelf (COTS) head-mounted display (HMD) and its effects on simulator sickness (SS) was investigated in this preliminary study. Participants performed a navigation task and an observational task. Both of the tasks allowed participants to freely view the 360 degree dynamic three-dimensional (3D) virtual reality environment (VRE). We hypothesized that SS would increase over time participating in the VRE and that SS would be greater in the observational task as compared to the navigation task. SS ratings did increase over time; however, SS did not differ between the observational and navigation task. These findings suggested that SS is still a relevant factor to consider with COTS 3D HMD use.
Substituted Syndecan-2-Derived Mimetic Peptides Show Improved Antitumor Activity over the Parent Syndecan-2-Derived Peptide

We previously showed that a synthetic peptide (S2-P) corresponding to a portion of the human syndecan-2 (SDC2) sequence can bind to the pro-domain of matrix metalloproteinase-7 (MMP-7) to inhibit colon cancer activities. Since S2-P had a relatively weak binding affinity for the MMP-7 pro-domain, we herein modified the amino acid sequence of S2-P to improve the anticancer potential. On the basis of the interaction structure of S2-P and MMP-7, four peptides were generated by replacing amino acids near Tyr 51, which is critical for the interaction. The SDC2-mimetic peptides harboring an Ala-to-Asp substitution at the C-terminal side of Tyr 51 (S2-D) or with an Ala-to-Phe substitution at the N-terminal side of Tyr 51 and an Ala-to-Asp substitution at the C-terminal side of Tyr 51 (S2-FE) showed improved interaction affinities for the MMP-7 pro-domain. Compared to S2-P, S2-FE was better able to inhibit the SDC2–MMP-7 interaction, the cell surface localization of MMP-7, the gelatin degradation activity of MMP-7, and the cancer activities (cell migration, invasion, and colony-forming activity) of human HCT116 colon cancer cells in vitro. In vivo, S2-FE inhibited the primary tumor growth and lung metastasis of CT26 mouse colon cancer cells in a xenograft mouse model. Together, these data suggest that S2-FE could be useful therapeutic anticancer peptides for colon cancer.
Power Factor Improvement in Modified Bridgeless Landsman Converter Fed EV Battery Charger

– This work deals with the design and implementation of a new charger for battery operated electric vehicle (BEV) with power factor improvement at the front- end. In the proposed configuration, the conventional diode converter at the source end of existing electric vehicle (EV) battery charger, is eliminated with modified Landsman power factor correction (PFC) converter. The PFC converter is cascaded to a fly back isolated converter, which yields the EV battery control to charge it, first in constant current mode then switching to constant voltage mode. The proposed PFC converter is controlled using single sensed entity to achieve the robust regulation of DC-link voltage as well as to ensure the unity power factor operation. The proposed topology offers improved power quality, low device stress, low input and output current ripple with low input current harmonics when compared to the conventional one. Moreover, to demonstrate the conformity of proposed charger to an IEC 61000-3-2 standard, a prototype is built and tested to charge a 48V EV battery of 100Ah capacity, under transients in input voltage. The performance of the charger is found satisfactory for all the cases.
Multifunction LED Lighting System Combining Tunable Spectrum and Data Communication

A comparison of two different lighting systems combining tunable illumination, visible light communications (VLC) and sensing capabilities. The first method is based on light emitting diodes (LED) as light source and multifunction smart sensors and the second one with LEDs and micro-spectrometer to be included in the transceiver and/or receiver. Both systems are intended for future lighting sensor networks that combine standardized optical communications according the standard IEEE802.15. 7 and sensing (illuminance, proximity, colour, and spectrum detection) for indoor envir
Sphk1 and Sphk2 Differentially Regulate Erythropoietin Synthesis in Mouse Renal Interstitial Fibroblast-like Cells

Erythropoietin (Epo) is a crucial hormone regulating red blood cell number and consequently the hematocrit. Epo is mainly produced in the kidney by interstitial fibroblast-like cells. Previously, we have shown that in cultures of the immortalized mouse renal fibroblast-like cell line FAIK F3-5, sphingosine 1-phosphate (S1P), by activating S1P1 and S1P3 receptors, can stabilize hypoxia-inducible factor (HIF)-2α and upregulate Epo mRNA and protein synthesis. In this study, we have addressed the role of intracellular iS1P derived from sphingosine kinases (Sphk) 1 and 2 on Epo synthesis in F3-5 cells and in mouse primary cultures of renal fibroblasts. We show that stable knockdown of Sphk2 in F3-5 cells increases HIF-2α protein and Epo mRNA and protein levels, while Sphk1 knockdown leads to a reduction of hypoxia-stimulated HIF-2α and Epo protein. A similar effect was obtained using primary cultures of renal fibroblasts isolated from wildtype mice, Sphk1−/−, or Sphk2−/− mice. Furthermore, selective Sphk2 inhibitors mimicked the effect of genetic Sphk2 depletion and also upregulated HIF-2α and Epo protein levels. The combined blockade of Sphk1 and Sphk2, using Sphk2−/− renal fibroblasts treated with the Sphk1 inhibitor PF543, resulted in reduced HIF-2α and Epo compared to the untreated Sphk2−/− cells. Exogenous sphingosine (Sph) enhanced HIF-2α and Epo, and this was abolished by the combined treatment with the selective S1P1 and S1P3 antagonists NIBR-0213 and TY52156, suggesting that Sph was taken up by cells and converted to iS1P and exported to then act in an autocrine manner through S1P1 and S1P3. The upregulation of HIF-2α and Epo synthesis by Sphk2 knockdown was confirmed in the human hepatoma cell line Hep3B, which is well-established to upregulate Epo production under hypoxia. In summary, these data show that sphingolipids have diverse effects on Epo synthesis. While accumulation of intracellular Sph reduces Epo synthesis, iS1P will be exported to act through S1P1+3 to enhance Epo synthesis. Furthermore, these data suggest that selective inhibition of Sphk2 is an attractive new option to enhance Epo synthesis and thereby to reduce anemia development in chronic kidney disease.