Miracle-dz/UniFAR-FTUs huggingface dataset:
Among- and within-species variation in plant litter decomposition in contrasting long-term chronosequences

1. Following major disturbances ecosystem development occurs but in the prolonged absence of disturbance a decline (retrogressive) phase follows in which productivity and nutrient availability diminishes. Although it is recognized that litter quality and decomposition rates decrease as retrogression proceeds, little is known about the extent to which this is driven among- vs. within-species variation across these sequences. 2. We selected six long-term chronosequences that each included retrogressive stages, in New Zealand, Hawaii, Sweden, Alaska and Australia. Two involve significant species turnover across the sequence so that different species dominate at different stages, two involve low species turnover so that the same dominant species occur at all stages, and two involve some turnover of species but with certain species persisting throughout most of the sequence. 3. For each chronosequence, we collected litter from each dominant plant species at each stage of that sequence. For each litter collection we measured concentrations of N and P, and performed laboratory decomposition bioassays to measure mass loss, N and P loss, and the response of mass loss to mixture with litters of coexisting species. 4. We found that litter N and P concentrations often declined with increasing ecosystem age, both among- and within-species. However, the relative importance of among- and within-species effects varied across the six chronosequences. Rates of litter mass, N, and P loss during decomposition sometimes decreased with increasing ecosystem age, but most often at the among-species rather than the within-species level. 5. Litter mixing effects often varied across chronosequence stages, but the magnitude and direction of these effects was inconsistent among sequences. Variation in litter mixing effects across chronosequence stages was driven mainly by among- rather than within-species variation. 6. Although several recent studies have emphasized the role of within-species variation on ecosystem properties, our results point to among-species variation as a consistently important ecological driver, with within-species variation being important only for some variables and in some instances. As such they highlight that decomposition processes are most likely to be highly responsive to gradients of soil fertility (such as across chronosequences) when significant species turnover occurs across the gradient.
Ca2+ entry through NaV channels generates submillisecond axonal Ca2+ signaling

Calcium ions (Ca2+) are essential for many cellular signaling mechanisms and enter the cytosol mostly through voltage-gated calcium channels. Here, using high-speed Ca2+ imaging up to 20 kHz in the rat layer five pyramidal neuron axon we found that activity-dependent intracellular calcium concentration ([Ca2+]i) in the axonal initial segment was only partially dependent on voltage-gated calcium channels. Instead, [Ca2+]i changes were sensitive to the specific voltage-gated sodium (NaV) channel blocker tetrodotoxin. Consistent with the conjecture that Ca2+ enters through the NaV channel pore, the optically resolved ICa in the axon initial segment overlapped with the activation kinetics of NaV channels and heterologous expression of NaV1.2 in HEK-293 cells revealed a tetrodotoxin-sensitive [Ca2+]i rise. Finally, computational simulations predicted that axonal [Ca2+]i transients reflect a 0.4% Ca2+ conductivity of NaV channels. The findings indicate that Ca2+ permeation through NaV channels provides a submillisecond rapid entry route in NaV-enriched domains of mammalian axons.
Petrophysical properties prediction from prestack seismic data using convolutional neural networks

We have built convolutional neural networks (CNNs) to obtain petrophysical properties in the depth domain from prestack seismic data in the time domain. We compare two workflows — end-to-end and cascaded CNNs. An end-to-end CNN, referred to as PetroNet, directly predicts petrophysical properties from prestack seismic data. Cascaded CNNs consist of two CNN architectures. The first network, referred to as ElasticNet, predicts elastic properties from prestack seismic data followed by a second network, referred to as ElasticPetroNet, that predicts petrophysical properties from elastic properties. Cascaded CNNs with more than twice the number of trainable parameters as compared to end-to-end CNN demonstrate similar prediction performance for a synthetic data set. The average correlation coefficient for test data between the true and predicted clay volume (approximately 0.7) is higher than the average correlation coefficient between the true and predicted porosity (approximately 0.6) for both networks. The cascaded workflow depends on the availability of elastic properties and is three times more computationally expensive than the end-to-end workflow for training. Coherence plots between the true and predicted values for both cases show that maximum coherence occurs for values of the inverse wavenumber greater than 15 m, which is approximately equal to 1/4 the source wavelength or λ/4. The network predictions have some coherence with the true values even at a resolution of 10 m, which is half of the variogram range used in simulating the spatial correlation of the petrophysical properties. The Monte Carlo dropout technique is used for approximate quantification of the uncertainty of the network predictions. An application of the end-to-end network for prediction of petrophysical properties is made with the Stybarrow field located in offshore Western Australia. The network makes good predictions of petrophysical properties at the well locations. The network is particularly successful in identifying the reservoir facies of interest with high porosity and low clay volume.
Teaching irregular words: What we know, what we don-t know, and where we can go from here

Abstract Instruction in regular letter-sound relationships is a key element of teaching children to read. However, in the English language, many words have irregular spellings (e.g. said, are, yacht). What is the best way to help children learn to read these words? To date, a number of different viewpoints have been put forward, but these viewpoints are seldom directly compared, and there is very little empirical evidence to adjudicate between them. Therefore, in this review, we outline the theoretical arguments for and against different methods of instruction, and synthesise the empirical research that does exist. We make recommendations for practice, and outline key areas where further evidence is required.
Silencing of long non-coding antisense RNA brain-derived neurotrophic factor attenuates hypoxia/ischemia-induced neonatal brain injury

Hypoxic/ischemic (HI) brain damage (HIBD) is a major cause of acute neonatal brain injury, leading to high mortality and serious neurological deficits. The antisense RNA of brain-derived neurotrophic factor (BDNF-AS) is transcribed from the opposite strand of the BDNF gene. The aim of the present study was to investigate the role of BDNF-AS in HI-induced neuronal cell injury in vivo and in vitro. Reverse transcription-quantitative PCR (RT-qPCR) assays indicated that BDNF-AS expression was significantly upregulated in HI-injured neonatal brains and hippocampal neurons. However, BDNF expression was downregulated in HI-injured neonatal brains and hippocampal neurons. Cell Counting Kit-8 assays, Hoechst staining, calcein-AM/PI staining, immunostaining, water maze tests and rotarod tests demonstrated that BDNF-AS silencing protected against hypoxia-induced primary hippocampal neuron injury in vitro and HI-induced brain injury in vivo. Mechanistically, RT-qPCR assays and western blotting indicated that BDNF-AS silencing led to increased expression of BDNF and activated the BDNF-mediated signaling pathway, as demonstrated by increased expression levels of BDNF, phosphorylated-Akt and phosphorylated-tropomyosin receptor kinase B. Collectively, the present study provides important insights into the pathogenesis of HIBD, and it was indicated that BDNF-AS silencing may be a promising approach for the treatment of neonatal HIBD.
Preparation and characterization of highly radioactive in vitro labeled adenovirus DNA and DNA restriction fragments. [. cap alpha. -(/sup 32/P) deoxyribonucleoside 5/sup 1/-triphosphates]

A simple microscale procedure is described for the synthesis and purification of high specific activity . cap alpha. -(/sup 32/P)deoxyribonucleoside 5'-triphosphates (300-1300 Ci/mmol) and their utilization in labeling as little as 56 ng of adenovirus DNA or DNA restriction fragments to specific activities up to 4 x 10/sup 8/ cpm/. mu.g by in vitro repair synthesis (''nick translation''). (/sup 3/H)DNA of specific activity 1.5 x 10/sup 7/ cpm/. mu.g has also been prepared by nick translation using commercial (/sup 3/H)thymidine 5'-triphosphate (50 Ci/mmol). These products have been extensively characterized as to reassociation properties. Adenovirus 12 DNA and the EcoRI restriction fragments labeled by this procedure were shown to be identical with in vivo labeled viral DNA by three types of molecular hybridization measurements including copy number determination by reassociation kinetics, of viral DNA in viral transformed cells, renaturation rate of viral DNA and restriction fragments and agreement with genetic complexity, and saturation-hybridization of labeled viral DNA with unlabeled restriction fragments. Finally, the distribution of radioactivity in restriction fragments prepared from in vitro labeled DNA showed that viral DNA is uniformly labeled in vitro.
A serialized classification method for pulmonary nodules based on lightweight cascaded convolutional neural network‐long short‐term memory

Computer Assisted Diagnosis (CAD) is an effective method to detect lung cancer from computed tomography (CT) scans. The development of artificial neural network makes CAD more accurate in detecting pathological changes. Due to the complexity of the lung environment, the existing neural network training still requires large datasets, excessive time, and memory space. To meet the challenge, we analysis 3D volumes as serialized 2D slices and present a new neural network structure lightweight convolutional neural network (CNN)‐long short‐term memory (LSTM) for lung nodule classification. Our network contains two main components: (a) optimized lightweight CNN layers with tiny parameter space for extracting visual features of serialized 2D images, and (b) LSTM network for learning relevant information among 2D images. In all experiments, we compared the training results of several models and our model achieved an accuracy of 91.78% for lung nodule classification with an AUC of 93%. We used fewer samples and memory space to train the model, and we achieved faster convergence. Finally, we analyzed and discussed the feasibility of migrating this framework to mobile devices. The framework can also be applied to cope with the small amount of training data and the development of mobile health device in future.
Analysis of Overtaking Maneuvers to Cycling Groups on Two-Lane Rural Roads using Objective and Subjective Risk

In Spain, the presence of cyclists’ groups riding on two-lane rural roads in a single file or in parallel line is growing. The number of overtaking maneuvers to them is also increasing. This is one of the most dangerous interactions between motor vehicles and bicycles. However, the risk of these maneuvers has not been analyzed in depth. This research analyzes the objective and subjective risk of overtaking maneuvers to cyclists’ groups. During this maneuver, the motorized vehicle overtakes the bicycles with a certain speed and lateral distance. These are the surrogate measures used to analyze the objective risk, whereas the subjective risk was analyzed based on the subjective risk perception that 10 cyclists riding instrumented bicycles (in different group configurations) indicated when every motor vehicle overtook them. Results show that the cyclists most exposed to the overtaking maneuver are those at the front and at the rear of the group. In relation to the configuration, the risk is higher in parallel lines, as the lateral clearance is lower compared with a single line. It is even higher when the overtaking maneuver is flying, which is usually performed at higher speeds and lower lateral clearance. The subjective risk perception increases with higher speed and lower lateral clearance, and is higher at the rear positions. Overtaking in which lateral distance is less than 1.5 m is perceived as the riskiest. These results provide scientific recommendations to enhance safety for cyclists’ groups, and to integrate cycling with vehicular traffic on two-lane rural roads.
Tree growth response to fuel reduction treatments along a topographic moisture gradient in mixed-oak forests of Ohio, U.S.A.

This study examined the effect of the soil moisture gradient on tree growth response to prescribed fire and thinning in oak-dominated forests of Ohio. Six hundred and ninety-six increment cores (348 trees, five species) were collected from eighty 0.1 ha plots distributed across four treatments (control, thin, burn, thin + burn) in two sites. Ring widths were converted to basal area increments (BAIs). A water balance approach based on geographic information systems (GIS) was used to assess the potential evapotranspiration (PET) and moisture deficit for each tree, along with a long-term integrated moisture index, also based on GIS. The moisture gradients varied considerably across the landscape, with the highest PET and moisture deficit on ridges and south-facing slopes. This variation influenced the BAI of the studied species, but more strongly in the control stands than in the managed stands, where treatment effects became the main drivers of growth. Oaks exhibited greater BAI on sites with intermediate m.
Wet extraction—a method for estimating populations of Bembidion lampros (Herbst) (Col., Carabidae)

A new method for density estimation of small carabids is described. After application of water onto the soil in the field, beetles appeared on the soil surface where they could be collected. The dosages used were 20, 40 and 60 l/m2. The catches did not differ significantly between dosages. The method proved effective since the extracted soil, when controlled by flotation, did not contain any beetles.
SMARCB1 loss induces druggable cyclin D1 deficiency via upregulation of MIR17HG in atypical teratoid rhabdoid tumors

Atypical teratoid rhabdoid tumor (ATRT) is a fatal pediatric malignancy of the central neural system lacking effective treatment options. It belongs to the rhabdoid tumor family and is usually caused by biallelic inactivation of SMARCB1, encoding a key subunit of SWI/SNF chromatin remodeling complexes. Previous studies proposed that SMARCB1 loss drives rhabdoid tumor by promoting cell cycle through activating transcription of cyclin D1 while suppressing p16. However, low cyclin D1 protein expression is observed in most ATRT patient tumors. The underlying mechanism and therapeutic implication of this molecular trait remain unknown. Here, we show that SMARCB1 loss in ATRT leads to the reduction of cyclin D1 expression by upregulating MIR17HG, a microRNA (miRNA) cluster known to generate multiple miRNAs targeting CCND1. Furthermore, we find that this cyclin D1 deficiency in ATRT results in marked in vitro and in vivo sensitivity to the CDK4/6 inhibitor palbociclib as a single agent. Our study identifies a novel genetic interaction between SMARCB1 and MIR17HG in regulating cyclin D1 in ATRT and suggests a rationale to treat ATRT patients with FDA‐approved CDK4/6 inhibitors. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Fitness Distance Correlation Strategy for Solving the RGV Dynamic Scheduling Problem

Rail guide vehicle (RGV) problems have the characteristics of fast running, stable performance, and high automation. RGV dynamic scheduling has a great impact on the working efficiency of an entire automated warehouse. However, the relative intelligent optimization research of different workshop components for RGV dynamic scheduling problems are insufficient scheduling in the previous works. They appear idle when waiting, resulting in reduced operating efficiency during operation. This article proposes a new distance landscape strategy for the RGV dynamic scheduling problems. In order to solve the RGV dynamic scheduling problem more effectively, experiments are conducted based on the type of computer numerical controller (CNC) with two different procedures programming model in solving the RGV dynamic scheduling problems. The experiment results reveal that this new distance landscape strategy can provide promising results and solves the considered RGV dynamic scheduling problem effectively.
Towards the development of rapid biofilm antibiotic sensitivity testing (BAST)

This study presents a modification of the antibiotic susceptibility testing (AST), which is a rapid means of determining the response of planktonic bacteria to different antimicrobial agents, for application to biofilms. Colony biofilm was first developed on a cellulose filter/membrane disc, over which an antibiotic disc was imposed. Zone of inhibition was measured after incubation on nutrient agar. Biofilms were not as susceptible to the test antibiotics as compared to the planktonic cultures. The results point to the possibility of this method as a rapid means for antibiotics for treating biofilm infections. Limitations and potential application for biofilm AST are discussed. Key words: Biofilm, antibiotic susceptibility testing
Structural definition of polyspecific compensatory ligand recognition by P-glycoprotein

Polyspecific ligand recognition by P-glycoprotein includes compensatory mechanisms in the form of ligand-binding shifts when ligand-interacting residues are challenged by mutagenesis. Point mutations of ligand-interacting phenylalanine residues to alanines resulted in binding shifts of an environmental pollutant, yet its inhibitory function on ATPase activity was preserved.
Pollinator Activity and the Fecundity of a Rare and Highly Threatened Honeybush Species along a Highway in the Cape Floristic Region

Premise of research. Road verges are important refugia for plants, particularly rare or threatened species, in transformed landscapes. However, traffic disturbance could disrupt plant-pollinator interactions and so undermine the conservation value of road verges. Here we investigate the indirect road impact on the pollination and fecundity of a highly threatened shrub, Cyclopia pubescens, through changes in insect pollinator behavior. Methodology. We compared pollinator activity (visitor frequency and number of flowers visited per pollinator) and plant reproductive output (fruit set and seed set) at three distances from a highway while considering the effects of C. pubescens plant density and floral display size (number of synflorescences per plant and number of flowers per synflorescence) on pollinator activity. Pivotal results. The pollinator, Xylocopa flavorufa, and other floral visitors (Xylocopa caffra and Apis mellifera) were most abundant next to the road, while individual pollinators visited more flowers next to the road compared with farther away. Pollinator activity was highest near the road in response to larger C. pubescens floral displays in this zone compared with farther away, yet pollinator visitation rate, fruit set, and seed set were comparable at all distances from the road. Conclusions. While we found no evidence of a road effect on the reproductive output of C. pubescens, the larger floral displays of plants occurring near the road appear to be attractive enough to pollinators to counteract traffic disturbance—this bodes well for the viability of road verges as habitats for entomophilous plants.
The quiet Portuguese: Are Portuguese taxpayers victims of fiscal illusion?

This article discusses the four dimensions generating fiscal illusion through a survey answered by a sample of the population of the northern region of Portugal. The surveyed dimensions were (1) bias in the taxpayers' perception of the costs and benefits of public programs; (2) ignorance or inattention about the fiscal reality (like about tax structure or associated collection); (3) taking advantage of the taxpayer's timing and expectations for an optimized tax collection; and (4) association of the surrounding socioeconomic reality with the tax structure. The results show that the most serious dimension present among the analyzed Portuguese taxpayers is the relative lack of attention to fiscal reality. Through an analysis using appropriate tests, it was observed that some dimensions, such as education and taxpayer income, significantly influence the individual risk of fiscal illusion.
Modelling and PID control system integration for quadcopter DJI F450 attitude stabilization

In this paper we focus on the overall overview of the mathematical modelling of the DJI F450 UAV quadcopter, the hardware and software system integration based on PID control system for the attitude feedback. The parameter specification of the DJI F450 is fed into the mathematical model and implement a basic PID for the system. Future research using the DJI F450 model can benefit from this observation by implementing the modelling and tune in their own variable that varies, such as the overall of their weight. The data of PID control system simulation using the quadcopter frame model type DJI F450 parameter. The mathematical model for the quadcopter modelled DJI F450 is developed using Newton-Euler method. Altitude data for the control system is obtain from the analysis data of the Simulink simulation. The simulation is done using the Simulink toolbox inside the MATLAB software. From this paper, we can more understand the step involves in making a full control system of a quadcopter. The mathematical model for other type of quadcopter model can be implemented using the steps with their own parameter and achieve fast development.
Quality improvement of liquid smoke from oil palm frond pyrolysis through the adsorption-distillation process using activated carbon as adsorbent

This study aims to produce and analyze the quality of purified liquid smoke through the adsorption process with activated carbon and distillation. In this study, liquid smoke was produced from the pyrolysis of oil palm fronds with operating conditions of temperatures of 400°C, 500°C, and 600°C for 40 minutes, 90 minutes, and 120 minutes. Liquid smoke was adsorbed using activated carbon and distilled at 150°C for 45 minutes. The characteristics of liquid smoke were analyzed using GC-MS instrument. The parameters observed were phenolic, acids, and carbonyl compounds. The results showed that acid compounds were the most dominant component in liquid smoke obtained. After purification, the color of liquid smoke turned bright yellow and the pungent smell of smoke from liquid smoke decreased.