Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Biases in Global Tree Cover Products: A Case Study in Costa Rica

Global tree cover products are widely used in analyses of deforestation, fragmentation, and connectivity, but are rarely critically assessed. Inaccuracies in these products could have consequences for future decision making, especially in data-poor regions like the tropics. In this study, potential biases in global and regional tree cover products were assessed across a diverse tropical country, Costa Rica. Two global tree cover products and one regional national forest cover map were evaluated along biophysical gradients in elevation, precipitation, and agricultural land cover. To quantify product accuracy and bias, freely available high-resolution imagery was used to validate tree and land cover across these gradients. Although the regional forest cover map was comparable in accuracy to a widely-used global forest map (the Global Forest Change of Hansen et al., also known as the GFC), another global forest map (derived from a cropland dataset) had the highest accuracy. Both global and regional forest cover products showed small to severe biases along biophysical gradients. Unlike the regional map, the global GFC map strongly underestimated tree cover (>10% difference) below 189 mm of precipitation and at elevations above 2000 m, with a larger bias for precipitation. All map products misclassified agricultural fields as forest, but the GFC product particularly misclassified row crops and perennial erect crops (banana, oil palm, and coffee), with maximum tree cover in agricultural fields of 89%–100% across all crops. Our analysis calls into further question the utility of the GFC product for global forest monitoring outside humid regions, indicating that, in tropical regions, the GFC product is most accurate in areas with high, aseasonal rainfall, low relief, and low cropland area. Given that forest product errors are spatially distributed along biophysical gradients, researchers should account for these spatial biases when attempting to analyze or generate forest map products.
The self-driving photomask

Machine learning (ML) has become increasingly powerful and several recent works have demonstrated the capa- bility of neural networks to achieve performance gains for lithography applications. Much of the general literature on neural networks involves image classification. Application of neural networks to lithography requires increased scrutiny. How far can such a system be trusted, and how should we respond if the system fails? Neural net- works can appear inscrutable and we lack understanding of why these systems generalize so well. On the other hand, the benefits neural networks appear to offer, in terms of reduced runtime or more accurate models, are compelling. This work will illustrate how two techniques, the Information Bottleneck (IB) and t-Distributed Stochastic Nearest Neighbors (t-SNE), that can improve our understanding of how neural networks work. We will use a multilayer perceptron for a simple resist model implemented with neural networks. We will then discuss how visualiztion methods can help assess the readiness of a neural network for a task, or help diagnose potential causes of failure.
Sensorless SynRG Based Variable Speed Wind Generator and Single-Stage Solar PV Array Integrated Grid System With Maximum Power Extraction Capability

This article presents a grid-integrated hybrid renewable energy sources based system comprising a solar photovoltaic (PV) array and a wind energy conversion system (WECS). The WECS uses a position-sensorless synchronous reluctance generator (SynRG) for the electric power generation from the wind turbine (WT), wherein, a sensorless field-oriented control (FOC) is made use of for the maximum power extraction (MPE). A second-order flux estimation (SFE) method along with frequency-locked loop (FLL) is utilized for the accurate flux estimation from the SynRG stator voltages and currents. A set of back-to-back connected three-phase two leg voltage source converter (VSC) topology is selected for the grid integration of WECS. This system has a common dc link where the solar PV array and the machine-side VSC (MSC) of the wind generator, are directly connected. The power output from the solar PV array and WECS, is shared between the grid and the local loads. The maximum power generation from SynRG in the WECS, is achieved by operating the SynRG at the speed estimated by the MPE algorithm. The maximum power is drawn from the solar PV array by adjusting the dc-link voltage, which is decided by the algorithm. For the proper power control and power quality improvement, the grid-side converter (GSC) is adequately controlled by implementing an observer-based control technique. The real-time validation of the system, is carried out using a developed laboratory prototype.
ATF4 regulates neuronal death in models of Parkinson’s Disease

Parkinson’s Disease (PD) is characterized by the loss of dopaminergic neurons in the substantia nigra resulting in severe motor impairments. However, the mechanisms underlying this neuronal loss remain largely unknown. Activating Transcription Factor 4 (ATF4), a key mediator of the Integrated Stress Response (ISR), is a transcription factor that during prolonged activation can induce the expression of pro-apoptotic target genes. Oxidative stress and ER stress have been implicated in PD and these factors are known to activate the ISR. In this study, we have determined, that both PD neurotoxins (MPP+ and 6-OHDA) and α-synuclein aggregation induced by pre-formed human alpha-synuclein fibrils (PFFs) cause sustained upregulation of ATF4 expression in mouse primary cortical and mesencephalic neurons. Furthermore, we demonstrate that PD neurotoxins induce the expression of the pro-apoptotic factors Chop, Trb3 and Puma in an ATF4-dependent manner. Importantly, using neurons derived from ATF4 +/+ and ATF4 -/- mice, we demonstrate that ATF4 promotes neuronal apoptosis and dopaminergic cell loss in cellular models of PD. Finally, we demonstrate that the eIF2α kinase inhibitor C16 suppresses MPP+ and 6-OHDA induced ATF4 activation and protects against PD neurotoxin induced neuronal death. Taken together these results indicate that ATF4 is a key regulator of dopaminergic cell death induced by PD neurotoxins and pathogenic α-synuclein aggregates and highlight the ISR as a potential therapeutic target in PD.
The Brazilian Amazon Protected Area Network Was Largely Unaffected By Recent Fires

August 2019 saw dramatic increases in wildfires in the Brazilian Amazon, leading to arguments between Brazil and G7 leaders and widespread concern among conservationists. Popular media reports suggested that ‘swathes of the Amazon rainforest in Brazil are on fire’. Here we investigate the spatial distribution of fires through August 2019, showing that fires were largely restricted to deforested regions and areas with low canopy cover, particularly in unprotected areas. In contrast, Brazil’s protected areas had one third as many fires, and forest in protected areas with high canopy cover was almost entirely unaffected by fire. Protected areas reduce deforestation and carbon emissions, and have proved largely untouched by recent fires.
The first complete chloroplast genome sequence from Polemonium chinense (Polemoniaceae)

Abstract In this study, the complete chloroplast genome of Polemonium chinense was determined by next-generation sequencing technology. The plastome is 155,578 bp in length, with a large single-copy region (LSC) of 85,864 bp and a small single-copy region (SSC) of 18,246 bp, separated by a pair of inverted repeat regions (IRs) of 25,734 bp. It contains 135 genes, including 89 protein-coding genes, 37 tRNA genes, 8 rRNA genes, and 1 pseudogene. The overall GC content is 37.1%, while the corresponding values in the LSC, SSC and IR region are 35.1, 30.3, and 42.9%, respectively. The phylogenetic tree shows that Polemoniaceae is sister to Fouquieriaceae.
Neuroscience and digital learning environment in universities: What do current research tell us?

The purpose of this article is to offer insights into current understanding of digital learning environments (DLEs) from a neuroscientific perspective. Cognitive neuroscience methods are increasingly applied in educational research to examine the neural underpinnings of learning. As such, neuroscientific evidence can play an important role in advancing current knowledge base from the existing self-reported data and behavioural measures in the field of educational technology. In this paper, we focus our review of neuroscience research on DLEs that can potentially transform the way we view learning and instruction. We discuss recent empirical studies done on DLEs using common cognitive neuroscience methods which included eye tracking, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). We offer recommendations for future applications of neuroscience methods in behavioural research within DLEs.
Chiseling and gypsum application affecting soil physical attributes, root growth and soybean yield

This study aimed to evaluate the effect of chiseling and gypsum application on soil physical properties, soybean root growth and grain yield. An experiment was carried out in Londrina, Parana state, Brazil, under a randomized complete block design, with six replications. The soil in the experimental area is classified as a dystroferric Red Latosol (Oxisol), containing 720 g kg-1 of clay. The experiment comprised four treatments: (1) continuous no-tillage (CNT) system without gypsum application, (2) CNT with gypsum application at 3.5 Mg ha-1, (3) chiseled soil without gypsum, and (4) chiseled soil with gypsum application. Regardless of gypsum application, chiseling increased water infiltration rate in soil and reduced penetration resistance. Gypsum application affected neither water infiltration nor soil penetration resistance in both no-tillage (NT) and chiseled soil systems. Moreover, gypsum application improved soybean root development at a depth range of 0.20-0.40 m in NT system. Chiseling increased root growth in the surface layer (0-0.20 m depth). Either isolated or combined, chiseling and gypsum application had no impact on soybean grain yield throughout one cropping season.
Effects of Hydroalcoholic Extract of Hogweed and Anise on Broiler Meat Quality, Immune Responses, and Intestinal Microflora and Morphology

BackgroundPoultry meat has high contents of polyunsaturated fatty acids that can cause off-flavors, off-odors, and reduce meat quality and shelf life. Replacement of phytogenic feed additives (PFAs) with chemical additives are highly considered, which reduces the potential risk of using poultry meat.ObjectivesThe current study aimed at determining the effects of hydroalcoholic extract of hogweed (Heracleum persicum) and anise (Pimpinella anisum L.) on broiler meat quality, immune responses, and intestinal microflora and morphology.MethodsThe current study was conducted on 400 male Ross 308 chickens divided into five treatment groups, based on a completely randomized design with four replicates of 20 broilers. The control group was not fed any feed additives, whereas the other groups received 100 mg/kg of probiotics (Primalac®), 200 mg/kg of hogweed extract, 200 mg/kg of anise extract, and 200 mg/kg of oxytetracycline, respectively. On day 35 of chicken breeding, the immune responses were investigated. At the end of chicken breeding, meat quality was analyzed. Also, the jejunal and ileal contents were investigated in terms of intestinal morphology and microflora.ResultsThe findings indicated that the highest immune response belonged to the anise extract treatment. The best meat quality belonged to treatments with hogweed and anise extracts (P < 0.05). Also, the lowest number of harmful intestinal bacteria belonged to hogweed extract treatment (P < 0.05). Morphological characteristics of the intestine improved under the effects of hogweed and anise extract treatments (P < 0.05). ConclusionsTherefore, inclusion of 200 mg/kg of hogweed and anise extracts in broiler diet is suggested to improve meat quality, immune responses, and intestinal morphology as well as reduce the number of harmful bacteria in the ileum.
Conjunction or co-activation? A multi-level MVPA approach to task set representations

While representing and maintaining rules in order to govern behavior is a critical function of the brain, it remains an open question as to how collections of rules - task sets - are represented in cortex. One possibility is that task sets are represented as the co-activation of representations of the simple rules from which a task set is composed. Alternatively, task sets could be encoded in a conjunctive manner as the unique combination of rules that belong to a task set. Using a novel multi-level MVPA approach in combination with fMRI, we attempted to answer both “where” and “how” task sets are represented in the brain. Subjects performed a delayed match-to-sample task using task sets composed of multiple, partially overlapping rules that governed which feature dimensions subjects should attend to, and MVPA was used to identify regions that encoded task set information. We identified voxels most relevant for classifying task sets, and, using these voxels as input to a second MVPA analysis, were able to identify regions in prefrontal cortex with activity consistent with co-active representation, while activity in visual cortex was consistent with conjunctive representation. These results highlight the utility of feature selection methods in neuroimaging analyses.
Robust verification of quantum computation

Quantum computers promise to offer a considerable speed-up in solving certain problems, compared to the best classical algorithms. In many instances, the gap between quantum and classical running times is conjectured to be exponential. While this is great news for those applications where quantum computers would provide such an advantage, it also raises a significant challenge: how can classical computers verify the correctness of quantum computations? In attempting to answer this question, a number of protocols have been developed in which a classical client (referred to as verifier) can interact with one or more quantum servers (referred to as provers) in order to certify the correctness of a quantum computation performed by the server(s). These protocols are of one of two types: either there are multiple non-communicating provers, sharing entanglement, and the verifier is completely classical; or, there is a single prover and the classical verifier has a device for preparing or measuring quantum states. The latter type of protocols are, arguably, more relevant to near term quantum computers, since having multiple quantum computers that share a large amount of entanglement is, from a technological standpoint, extremely challenging. Before the realisation of practical single-prover protocols, a number of challenges need to be addressed: how robust are these protocols to noise on the verifier’s device? Can the protocols be made fault-tolerant without significantly increasing the requirements of the verifier? How do we know that the verifier’s device is operating correctly? Could this device be eliminated completely, thus having a protocol with a fully classical verifier and a single quantum prover? Our work attempts to provide answers to these questions. First, we consider a single-prover verification protocol developed by Fitzsimons and Kashefi and show that this protocol is indeed robust with respect to deviations on the quantum state prepared by the verifier. We show that this is true even if those deviations are the result of a correlation with the prover’s system. We then use this result to give a verification protocol which is deviceindependent. The protocol consists of a verifier with a measurement device and a single prover. Device-independence means that the verifier need not trust the measurement device (nor the prover) which can be assumed to be fully malicious (though not communicating with the prover). A key element in realising this protocol is a robust technique of Reichardt, Unger and Vazirani for testing, using non-local correlations, that two untrusted devices share a large number of entangled states. This technique is referred to as rigidity of non-local correlations. Our second result is to prove a rigidity result for a type of quantum correlations known as steering correlations. To do this, we first show that steering correlations
A Silicon-Compatible Synaptic Transistor Capable of Multiple Synaptic Weights toward Energy-Efficient Neuromorphic Systems

In order to resolve the issue of tremendous energy consumption in conventional artificial intelligence, hardware-based neuromorphic system is being actively studied. Although various synaptic devices for the system have been proposed, they have shown limits in terms of endurance, reliability, energy efficiency, and Si processing compatibility. In this work, we design a synaptic transistor with short-term and long-term plasticity, high density, high reliability and energy efficiency, and Si processing compatibility. The synaptic characteristics of the device are closely examined and validated through technology computer-aided design (TCAD) device simulation. Consequently, full synaptic functions with high energy efficiency have been realized.
Uma Abordagem Holística para a Definição de Service Chains Utilizando Click-on-OSv sobre Diferentes Plataformas NFV

A implantacao de servicos em redes virtualizadas pode ser feita atraves da composicao de varias funcoes implementadas como VNFs (Virtual Network Functions). A instanciacao de VNFs e o encaminhamento do trafego em uma ordem definida atraves das mesmas forma uma SFC (Service Function Chain). Este trabalho propoe um framework para a composicao e o gerenciamento do ciclo de vida de SFCs formadas por VNFs programadas sobre o Click-on-OSv. Alem disso, a proposta deste artigo amplia este contexto, possibilitando a execucao de SFCs em diferentes orquestradores NFV. A abordagem proposta define uma APIunica para a composicao de SFCs que permite abstrair as especificidades dos orquestradores NFV. Um prototipo do framework foi implementado para realizar a composicao e o gerenciamento de SFCs formadas por VNFs programadas com Click-on-OSv sobre o orquestrador NFV OpenStack Tacker.
Using Semantic Context to Rank the Results of Keyword Search

ABSTRACT In an empirical user study, we assessed two approaches to ranking the results from a keyword search using semantic contextual match based on Latent Semantic Analysis. These techniques involved searches initiated from words found in a seed document within a corpus. The first approach used the sentence around the search query in the document as context while the second used the entire document. With a corpus of 20,000 documents and a small proportion of relevant documents (<0.1%), both techniques outperformed a conventional keyword search on a recall-based information retrieval (IR) task. These context-based techniques were associated with a reduction in the number of searches conducted, an increase in users’ precision and, to a lesser extent, an increase in recall. This improvement was strongest when the ranking was based on document, rather than sentence, context. Individuals were more effective on the IR task when the lists returned by the techniques were ranked better. User performance on the task also correlated with achievement on a generalized IQ test but not on a linguistic ability test.
Comparative evaluation of lignocaine and lignocainebupivacaine for lumbo-sacral epidural block in diazepam sedated West African dwarf goats

This study compared the onset of neural blockade, onset and duration of analgesia and duration of recumbency produced in five healthy West African Dwarf (WAD) goats by the lumbo-sacral epidural injections of a mixture of 2mg/kg lignocaine 2% solution and 0.95mg/kg bupivacaine 0.5% solution (LBM) and 4mg/kg lignocaine 2% solution. Associated changes in heart rate (HR), respiratory rate (RR) and rectal temperature (RT) were recorded at 10-min intervals in the initial 1 hour. The onset of neural blockade with LBM (9.6±2.7 min) was significantly (p 0.05) in the physiological parameters between the two groups. It was concluded that epidurally administered LBM had a slower onset of neural blockade but longer onset of analgesia, duration of analgesia and duration of recumbency than with LIG in diazepam-sedated goats. The epidural blockade also produced insignificant changes in the mean HR, RR, and RT responses of the experiment to both drug protocols. Keywords : Bupivacaine, Epidural, Goats, Lignocaine; Loco-regional, Sedation
Investigation of DNA Sequences Related to Latency-Associated Transcripts in the Genome of Canine Herpesvirus Type 1 (CHV-1) by Means of Bioinformatics Tools

A characteristic common to herpesviruses is the ability to establish a latent infection in the hosts, a transcriptionally active region has detected during latency as well as a set of RNA that are known as Latency Associated Transcripts (LATs), their functions have been clarified in recent work. The present work was carried using different bioinformatics method in order to determine if Herpesvirus Canine 1 (CHV-1) has a region associated with latency. Our result was the selection of nine sequences candidate of micro RNA (miRNA) (MIREval 2.0 software), and 26 miRNA (miRNAFold v.1.0 software), of them, were selected 14 with real precursors of miRNA, two were found between the RL2 and RS1 genes, one in the RL2 gene and 11 in the RS1 gene. The results showed that the similarities of these regions are very low among the herpesviruses analyzed, so it was not possible to deduce the presence of the LAT gene in canine herpesvirus type 1 with bioinformatics. On the other hand, the comparison showed that the miRNA predicted: chv1-mir-mirnafold-8 has similarity with the ebv-mir-BART7-3p of Epstein-Barr Virus (EBV), in this way, the microRNAs predicted by means of bioinformatic programs met the theoretical requirements of these molecules, however at not having a degree of preservation in other herpesviruses, the expression by CHV-1 in latency cannot be confirmed and it is necessary to identify through experimental tests.