Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Cloning and Characterization of Five Glutathione S-Transferase Genes and Promoters from Micromelalopha troglodyta (Graeser) (Lepidoptera: Notodontidae) and Their Response to Tannic Acid Stress

Plants accumulate phenolic compounds such as tannic acid to resist insect herbivores. The survival of insects exposed to toxic secondary metabolites depends on the detoxification metabolism mediated by limited groups of glutathione S-transferases (GSTs). Micromelalopha troglodyta (Graeser) (Lepidoptera: Notodontidae) is an important foliar pest of poplar trees. GSTs play an important role in xenobiotic detoxification in M. troglodyta. Five GST genes were identified in M. troglodyta and were classified into five different cytosolic GST classes, delta, omega, sigma, theta, and zeta. Real-time fluorescent quantitative polymerase chain reaction (qPCR) was used to determine the mRNA expression of the five cloned GSTs in the midguts and fat bodies of M. troglodyta. The mRNA expression of the five GSTs was significantly induced when M. troglodyta was exposed to tannic acid. To further understand the tannic acid regulatory cascade, the 5′-flanking promoter sequences of the five MtGSTs were isolated by genome walking methods, and the promoters were very active and induced by tannic acid. In summary, the induction of GST mRNA expression was due to the response of five MtGST promoters to tannic acid. Therefore, MtGST promoters play an important role in the regulation of GST transcription.
Integrating Multiscale Deformable Part Models and Convolutional Networks for Pedestrian Detection

Pedestrian detection has many real-world applications, such as advanced driver assistance systems, security surveillance, and traffic control, etc. One of the pedestrian detection challenges is the presence of occlusion. In this study, a jointly learned approach using multiscale deformable part models (DPM) and convolutional neural networks (CNN) is presented to improve the detection accuracy of partially occluded pedestrians. Deep convolutional networks provide a framework that allows hierarchical feature extraction. The DPM is used to characterize non-rigid objects on the histogram of oriented gradients (HoG) feature maps. Scores of the root and parts filters derived from the DPM are used as deformable information to help improve the detection performance. Experimental results show that the proposed jointly learned model can effectively reduce the miss rate of CNN-based object detection models tested on the Caltech pedestrian dataset.
The dependence of maize (Zea mays) hybrids yielding potential on the water amounts reaching the soil surface

The aim of the present study was to observe the response of maize hybrids under rainfed and irrigation conditions of the soil in order to establish the dependence of yielding potential on the water amounts reaching the soil surface during the growing season. The four-replicate trail was set up according to the randomised complete-block design on chernozem. Pre-watering soil moisture was approximately 70% of field water capacity, and soil moisture was established thermogravimetrically. During the five-year studies, the following differences in yields could be as follows: 12.68 t ha-1 (ZP 341); 12.76 t ha-1 (ZP 434); 13.17 t ha-1 (ZP 578); 14.03 t ha-1 (ZP 684) and 13.75 t ha-1 (ZP 704) under conditions of 440 mm, 440 mm, 424 mm, 457 mm and 466 mm of water, respectively. The hybrid ZP 341, i.e. ZP 578 expressed the highest, i.e. the lowest tolerance in dry relative seasons, respectively. The reduction of the water amount for every 10 mm decreased the yield by 119.4 kg ha-1 (ZP 341), 156.7 kg ha-1 (ZP 434), 172.3 kg ha-1 (ZP 578), 148.9 kg ha-1 (ZP 684) and 151.1 kg ha-1 (ZP 704). [Projekat Ministarstva nauke Republike Srbije, br. TR 31037]
Effects of a directional abiotic gradient on plant community dynamics and invasion in a coastal dune system

1 Local abiotic factors are likely to play a crucial role in modifying the relative abundance of native and exotic species in plant communities. Natural gradients provide an ideal opportunity to test this hypothesis. 2 In a coastal dune system in northern California, we used comparative and experimental studies to evaluate how a wind and soil texture gradient influences the relative abundance of native and exotic plant species in this community. 3 We detected small‐scale spatial variation in soil texture along a 200‐m gradient from relatively sheltered to more exposed. Sand coarseness significantly increased with exposure while soil nitrate levels significantly decreased. The more extreme end of the gradient was also subject to greater wind speeds and less soil moisture. 4 The plant community consistently responded to this gradient in the 7 years censused. Species richness decreased with exposure, cover of natives decreased and cover of exotics increased at the more extreme end of the gradient. 5 A single‐season wind‐shelter experiment similarly shifted the balance between native and exotic species. Shelters decreased the relative density of exotic species and increased the relative density of natives regardless of position on the gradient. 6 These comparative and manipulative findings both suggest that a single factor, wind, at least partially explains the success of exotic species in a coastal dune plant community. This supports the hypothesis that local abiotic conditions can explain differences in invasibility within a plant community.
Recruitment and Growth of Old World Climbing Fern in Hurricane-Caused Canopy Gaps

Abstract Following 2 y of severe hurricanes in 2004 and 2005, we examined the role of canopy gaps in promoting recruitment and growth of the exotic fern, Old World climbing fern Lygodium microphyllum (hereafter Lygodium), on tree islands of the Arthur R. Marshall Loxahatchee National Wildlife Refuge, Florida. We selected 12 sample tree islands, on which we placed three 1-m2 plots in a hurricane-caused canopy gap and three plots in an adjacent closed canopy area. Spore traps were placed in canopy gaps and closed canopy areas to quantify the number of spores reaching the forest floor on each island. In addition, in each plot occurrence and growth of Lygodium was measured across four height classes (recruitment class, understory, midstory, and canopy). We predicted that recruitment and growth of Lygodium would be higher in canopy gaps than in closed canopy areas. After 3 y of biannual monitoring, a significantly greater number of spores were foundin canopy gaps (4,804 spores·m2·d) than in closed canopy areas.
Investigations of body scales in twelve Heterocapsa species (Peridiniales, Dinophyceae), including a new species H. pseudotriquetra sp. nov.

Abstract The body scales of 12 Heterocapsa species including a new species, H. pseudotriquetra Iwataki, Gert Hansen & Fukuyo, sp. nov. were investigated by transmission electron microscopy to clarify ultrastructural differences. All species had scales with a body-scale structure consisting of a triradiate basal plate and a three-dimensional construction composed of vertically standing uprights or spines and horizontal bars. This basic scale structure is considered to be a generic characteristic. Finer scale details such as the shape and presence of a central hole in the basal plate, the numbers of uprights, bars and spines are considered to be species-specific. Two types of scales were found within clonal cultures of H. arctica and H. circularisquama and it is suggested that these represent ‘mature’ and ‘immature’ body scales. Intraspecific variation of the basal plate ‘reticulation’ was also observed. This variation was particularly evident in prolonged cultures of H. horiguchii and H. rotundata. The body-scale structure of 11 described species can be distinguished. However, two species, namely H. triquetra and H. pseudotriquetra, have the same scale morphology and are distinguished by differences in cell shape and LSU rDNA (25S rDNA) sequences.
A Novel Parametrized Fused Division and Square-Root POSIT Arithmetic Architecture

In modern computing systems and devices, Floating-Point Unit (FPU) plays a significant role on performance-oriented, compute-intensive, Machine Learning/AI related applications. Currently two types of representations for floating-point numbers have been followed, viz. conventional IEEE-754-2008 and recently proposed Type-III Unum POSIT number which has wider dynamic range. Most of the modern processors have FPU as co-processor in order to improve the floating-point performance. Among various FP computations, division and square-root are generally the least-likely performed operations. These hardware operations are typically expensive in-terms of area, speed and power. The overall performance of floating-point division and square-root unit can be significantly affected by the chosen algorithm and the architecture of the implementation. A novel, modified, non-restoring algorithm and a POSIT iterative/pipelined architecture which performs fused division and square-root operation in a single unit, is proposed in this research work. For parameterized POSIT, a one-bit, modified, non-restoring fused division and square-root unit is the core component and can be reused/configured for different exponent and mantissa sizes. We have developed an iterative/pipelined parameterized POSIT fused division and square-root module using Verilog HDL and implemented, validated on Xilinx Virtex UltraScale VCU108 FPGA board (544 LUTs and achieved a throughput of 400 Mega POSIT operations per second). The results have been analyzed and compared in-terms of area-utilization and throughput with known published equivalent IEEE-754-2008 implementations and other POSIT divider units. The proposed design has less data-path delay, uses less hardware and achieves better throughput as compared to published results. The design has also been synthesized targeting SCL 180nm ASIC and achieved a throughput of 250 Mega POSIT operations per second.
N2A Titin: Signaling Hub and Mechanical Switch in Skeletal Muscle

Since its belated discovery, our understanding of the giant protein titin has grown exponentially from its humble beginning as a sarcomeric scaffold to recent recognition of its critical mechanical and signaling functions in active muscle. One uniquely useful model to unravel titin’s functions, muscular dystrophy with myositis (mdm), arose spontaneously in mice as a transposon-like LINE repeat insertion that results in a small deletion in the N2A region of titin. This small deletion profoundly affects hypertrophic signaling and muscle mechanics, thereby providing insights into the function of this specific region and the consequences of its dysfunction. The impact of this mutation is profound, affecting diverse aspects of the phenotype including muscle mechanics, developmental hypertrophy, and thermoregulation. In this review, we explore accumulating evidence that points to the N2A region of titin as a dynamic “switch” that is critical for both mechanical and signaling functions in skeletal muscle. Calcium-dependent binding of N2A titin to actin filaments triggers a cascade of changes in titin that affect mechanical properties such as elastic energy storage and return, as well as hypertrophic signaling. The mdm phenotype also points to the existence of as yet unidentified signaling pathways for muscle hypertrophy and thermoregulation, likely involving titin’s PEVK region as well as the N2A signalosome.
Regulatory Effect of Sishen Pill on Tfh Cells in Mice With Experimental Colitis

The T follicular helper T (Tfh) cells play a significant role in the pathogenesis of inflammatory bowel disease (IBD), which is regulated by the Bcl-6/Blimp-1 pathway. Some studies have suggested that regulating activation of the Bcl-6/Blimp-1 pathway should be an effective method to treat IBD. Sishen Pill (SSP) has been used frequently to treat chronic colitis. Its mechanism is related to the downstream proteins in the Bcl-6/Blimp-1 pathway. However, it is unknown whether SSP regulates the function and differentiation of Tfh cells to treat IBD. In the present study, chronic colitis was induced by dextran sodium sulfate and treated with SSP for 7 days. SSP effectively treated chronic colitis, regulated the balance between Tfh10, Tfh17 and T follicular regulatory cells, while SSP increased the Blimp-1 level, inhibited expressions of Bcl-6, T-cell costimulator, programmed death (PD)-1 and PD-ligand 1 on the surface of Tfh cells. SSP inhibited activation of BcL-6, phosphorylated signal transducer and activator of transcription (p-STAT)3, signal lymphocyte activation molecule (SLAM)-associated protein but improved Blimp-1 and STAT3 expression in colonic tissues. The results indicated that SSP regulated the differentiation and function of Tfh cells to treat IBD, which was potentially related with inhibiting the Bcl-6/Blimp-1 pathway.
Automated classification of childhood brain tumours based on texture feature

We propose a framework for automated classification between normal and abnormal biopsy samples of childhood brain tumour with emphasis on childhood medulloblastoma, a most common childhood brain tumour, using texture features. Texture is a measure to analyze the variation of intensity of surface of an image and the connection of pixels satisfying a repeated grey level property. The feature set consisted of a total of 172 features belonging to five texture features, GLCM, GRLN, HOG, Tamura and LBP. The performance of each feature set was evaluated both individually and in group, using six different classifiers, Linear Discriminant, Quadratic Discriminant, Logistic Regression, Support Vector Machine and K-Nearest Neighbour algorithms. Here, feature of tamura, global low order histogram and local second order GLCM outperforms the local texture measure of LBP and GRLN. Using 80 normal and malignant images of 10x magnification we obtained an optimal accuracy of 100% by combining all five textural features.
Deep learning methods for Fake News detection

Spreading of misinformation on the web nowadays represents a serious issue, as their influence on peoples opinions may be significant. Fake news represents a specific type of misinformation. While its detection was mostly being performed manually in the past, automated methods using machine learning and related fields became more critical. On the other hand, deep learning methods became very popular and frequently used methods in the field of data analysis in recent years. The study presented in this paper deals with the detection of fake news from the textual data using deep learning techniques. Our main idea was to train different types of neural network models using both entire texts from the articles and to use just the title text. The models were trained and evaluated on the Fake News dataset obtained from the Kaggle competition.
Long noncoding RNA LINC00460 conduces to tumor growth and metastasis of hepatocellular carcinoma through miR-342-3p-dependent AGR2 up-regulation

Hepatocellular carcinoma (HCC) is the fifth most common malignant tumor in the world. It ranks third among cancer-induced deaths worldwide and has the characteristics of high metastasis and high recurrence rate. Long non-coding RNA (LncRNA) LINC00460 is significantly up-regulated in multiple types of cancers and is closely related to the progression of tumors. However, effects of LINC00460 and corresponding regulatory path in HCC are still poorly investigated. In our study, we found that expression of LINC00460 was up-regulated in HCC tissues and cell lines compared with the control. Then we revealed that knockdown of LINC00460 suppressed cell proliferation and cell mobility and induced cell apoptosis in HCC cells. Further study demonstrated that knockdown of LINC00460 suppressed the progression of HCC by elevating the expression of microRNA (miRNA, miR)-342-3p. Besides that, metastasis marker, Anterior gradient homolog 2 (AGR2) was found to be a target of miR-342-3p and overexpression of AGR2 promoted the progression of HCC. Finally, the in vivo experiments further verified the anti-tumor effects of LINC00460 / miR-342-3p / AGR2 axis in HCC. The LINC00460 / miR-342-3p / AGR2 axis exerts anti-tumor effect in HCC in vitro and in vivo, consolidating and expanding the research about targeted gene therapy for early diagnosis and treatment of HCC.
Comparative study of cost-effective coherent and direct detection schemes for 100  Gb/s/λ PON

As the capacity of the next-generation passive optical network (PON) is reaching 100 Gb/s and beyond, cost-effective transceivers have been widely discussed. In this work, we provide a comprehensive comparison of various simplified coherent and direct detection (DD) schemes operating at a ${100\; {\rm Gb/s/}}\lambda$100Gb/s/λ 4-ary pulse amplitude modulation signal through numerical simulation. According to the cost, the coherent receivers can be divided into three levels: intensity-only coherent receivers and phase-insensitive and phase-sensitive complex-value coherent receivers. The received power sensitivity at back-to-back, influence of laser frequency offset, local oscillator power, laser linewidth, analog-to-digital convertor resolution, fiber dispersion, and hardware complexity are investigated and analyzed for each transceiver structure. The results show the following: (1) Transmitter-side optical amplification is suggested for DD and intensity-only coherent receivers to meet the 29 dB power budget requirement, and these schemes have a large dispersion penalty. (2) Compared with ${3} \times {3}$3×3 coupler and ${2} \times {4}$2×4 hybrid-based coherent receivers, ${2} \times {2}$2×2 coupler and balanced-photodiode-based heterodyne detection exhibit similar performance with a simpler structure. (3) Both phase-insensitive and phase-sensitive complex-value coherent receivers have superior power budget and dispersion tolerance, and their application in PON would depend on the cost.
A Reference Process Model for Machine Learning Aided Production Quality Management

: The importance of machine learning (ML) methods has been increasing in recent years. This is also the reason why ML processes in production are becoming more and more widespread. Our objective is to develop a ML aided approach supporting production quality. To get an overview, we describe the manufacturing domain and use a visualization to explain the typical structure of a production line. Within this section we illustrate and explain the as-is process to eliminate an error in the production line. Afterwards, we describe a careful analysis of requirements and challenges for a ML system in this context. A basic idea of the system is the definition of product testing meta data and the exploitation of this knowledge inside the ML system. Also, we define a to-be process with ML system assistance for checking production errors. For this purpose, we describe the associated actors and tasks as well.
Nitrogen-fertilised grass in a subtropical dairy system 2. Effect of level of nitrogen fertiliser on animal production

The response in yield of milk and milk components to level of nitrogen (N) fertiliser applied to a tropical grass pasture was measured over 6 years. Pasture (Chloris gayana cv. Callide) was stocked at 2 Holstein-Friesian cows/ha and received annual basal dressings of phosphorus (250 kg superphosphate/ha) and potassium (63 kg KCl/ha), and treatments of urea at 0, 150, 300, 450, and 600 kg N/ha. year. Fertiliser was applied in 3 equal applications in September, December, and February. Cows were maintained on the pasture throughout the year, and 0.4 ha grazing oats/cow (100 kg N/ha. year) and 0.8 t cracked grain/cow were given as supplements. Hay or silage supplements were given when green grass yield was <0.5 t dry matter (DM)/ha. The amount of hay and silage given annually averaged 755, 437, and 529 kg DM/cow at 0, 300, and 600 kg N/ha. Mean milk response over the 6 years was high (8 kg milk/kg N) for 0-150 kg applied N/ha. year. The difference between fertilised and unfertilised pastures increased with time, and this was associated with degradation of pasture, excessive liveweight loss during lactation, and premature drying off of cows at nil applied N. At 150-600 kg N/ha. year, response was consistent across years (4.5 kg milk/kg N. year). Yields of milkfat and lactose reflected changes in milk yield, although milk protein percentage decreased significantly (P<0.05) with increased level of applied N. Conception rate increased with rate of applied N, from 58 to 92% at 0 and 600 kg N/ha. year (P<0.01). The results suggest a maximum margin over feed costs at 334 kg applied N/ha over the total grazed area. We conclude that there will be a large milk response to applying about 150 kg N/ha.year; beyond that, the milk response would be consistently about 4.5 kg/kg N to at least 600 kg N/ha.year.
Influence of isolation by environment and landscape heterogeneity on genetic structure of wild rice Zizania latifolia along a latitudinal gradient

Global aquatic habitats are undergoing rapid degradation and fragmentation as a result of land-use change and climate change. Understanding the genetic variability and adaptive potential of aquatic plant species is thus important for conservation purposes. In this study, we investigated the role of environment, landscape heterogeneity and geographical distance in shaping the genetic structure of 28 natural populations of Zizania latifolia (Griseb.) Turcz. Ex Stapf in China based on 25 microsatellite markers. Genetic structure was investigated by analysis of molecular variance (AMOVA), estimation of FST, Bayesian clustering and Thermodynamic Integration (TI) methods. Isolation by environment (IBE), isolation by resistance (IBR) and isolation by distance (IBD) hypotheses were compared using a reciprocal causal model (RCM). Further, generalized linear models and spatially explicit mixed models, by using geographic, landscape and genetic variables, were developed to elucidate the role of environment in driving Z. latifolia genetic diversity. The genetic differentiation across all populations was high: FST = 0.579; Øpt = 0.578. RCM exclusively supported IBE in shaping genetic structuring, only partial support for IBR, but not for IBD. Maximum temperature of the warmest month and precipitation seasonality were the plausible parameters responsible for genetic diversity. After controlling for spatial effect and landscape complexity, precipitation seasonality was significantly associated with genetic diversity. Based on these findings, genetic structure of Z. latifolia across China seem to be as a result of local adaptation. Environmental gradient and topographical barriers, rather than geographical isolation, influence genetic differentiation of aquatic species across China resulting in instances of local adaptation.