Miracle-dz/UniFAR-FTUs huggingface dataset:
Representing and Reconstructing PhySH: Which Embedding Competent?

Recent advances in natural language processing make embedding representations dominate the computing language world. Though it is taken for granted, we actually have limited knowledge of how these embeddings perform in representing the complex hierarchy of domain scientific knowledge. In this paper, we conduct a comprehensive comparison of well-known embeddings’ capability in capturing the hierarchical Physics knowledge. Several key findings are: i, Poincaré embeddings do outperform if trained on PhySH taxonomy, but it fails if trained on co-occurrence pairs which are extracted from raw text. ii, No algorithm can properly learn hierarchies from the more realistic case of co-occurrence pairs, which contains more noisy relations other than hierarchical relations. iii, Our statistic analysis of Poincaré embedding’s representation of PhySH shows successful hierarchical representation share two characteristics: firstly, upper-level terms have a smaller semantic distance to root; secondly, upper-level hypernym-hyponym pairs should be further apart than lower-level hypernym-hyponym pairs.
On the use of C# Unsafe Code Context: An Empirical Study of Stack Overflow

Background. C# maintains type safety and security by not allowing direct dangerous pointer arithmetic. To improve performance for special cases, pointer arithmetic is provided via an unsafe context. Programmers can use the C# unsafe keyword to encapsulate a code block, which can use pointer arithmetic. In the Common Language Runtime (CLR), unsafe code is referred to as unverifiable code. It then becomes the responsibility of the programmer to ensure the encapsulated code snippet is not dangerous. Naturally, this raises concern on whether such trust is misused by programmers when they promote the use of C# unsafe context. Aim. We aim to analyze the prevalence and vulnerabilities of share code examples using C# unsafe keyword in Stack Overflow (SO) code sharing platform. Method. By using some regular expressions and manual checks, we extracted C# unsafe code relevant posts from SO and categorized them into some software development scenarios. Results. In the entire SO data dump of September 2018, we find 2,283 C# snippets with the unsafe keyword. Among those posts, 27% of posts are about Image processing, where unsafe codes are mainly used for performance reasons. The second most popular category by 21% of the codes in the posts is used for 'Interoperability' reasons. That is 'unsafe' is used to enable 'Interoperability' between C# managed codes and unmanaged codes. The 'stackalloc' operator is the third category with 9% of unsafe code posts. The stackalloc operator allocates a block of memory on the stack. Since C# 7.2, Microsoft recommends against using 'stackalloc' in unsafe context whenever possible. Manual inspection shows 67 code snippets with dangerous functions that can introduce vulnerability if not used with caution (e.g., buffer overflow). Finally, 35% of 'Interoperability' posts have 'P/Invoke' tag were used outside NativeMethods class, which is in contrast to Microsoft design suggestion. Conclusion. Our study leads to 7 main findings, and these findings show the importance of cautiously using this feature.
Lithology Identification Based on Multi-scale Residual One-dimensional Convolutional Neural Network

In order to make better use of the correlation between few lithological features and reduce the model complexity of convolutional neural network, this paper proposes a lithology recognition method based on a multi-scale residual one-dimensional convolutional neural network. Firstly, according to the logging data, acoustic, density, gamma ray, deep lateral resistivity, shallow lateral resistivity, photoelectric absorption cross-sectional index, p-wave velocity and shear wave velocity are selected as lithological characteristics. Due to the large difference between features and the existence of abnormal data, the Laida criterion, least squares moving average filtering and z-score standardization are used for preprocessing. Then, borrowing from the multi-scale idea of inception structure in GoogLeNet and the residual idea of ResNet, a multi-scale residual structure (MsR) is constructed, and further a multi-scale residual one-dimensional convolutional neural network (MsRNet) is constructed with MsR. Finally, lithology identification is performed by MsRNet. Through experiments with a block in Henan Oilfield, it is proved that this method has a higher lithology recognition rate than the lithology recognition methods including the k-nearest neighbor model, the product-based neural network and direct one-dimensional convolutional neural network.
A numerical study of the aerosol behavior in intra-acinar region of a human lung

The determination of the particle dynamics in the human acinar airways having millions of alveoli is critical in preventing potential health problems and delivering therapeutic particles effectively to target locations. Despite its complex geometrical structure and complicate wall movements, the advanced calculation simulations can provide valuable results to accurately predict the aerosol deposition in this region. The objective of this study was to numerically investigate the aerosol particle transport and deposition in the intra-acinar region of a human lung for different breathing scenarios (i.e., light, normal, and heavy activities) during multiple breaths. Idealized intra-acinar models utilized in this study consisted of a respiratory bronchial model, an alveolar duct model, and an alveolar sac model. The particles with 5 μm in diameter released from the inlet of the model were tracked until they deposited or escaped from the computational domain. The results showed that due to the rhythmic alveolar wall movement, the flow field was divided into two regions: one is the low-speed alveolar flow and the other is the channel flow. It was found that the chaotic acinar flow irreversibility played a significant role in the aerosol transport in higher generations. During the succeeding breaths, more particles deposited or escaped to the relating acinar generation and reached the more distal regions of the lung. The number of particles remaining in the suspension at the end of the third cycle ranged from 0.016% to 3%. When the mouth flow rate increased, the number of particles remaining in the suspension reduced, resulting in higher deposition efficiency. The total deposition efficiencies for each flow rate were 24%, 47%, and 77%, respectively. The particle simulation results also showed that more breathing cycle was required for full aerosol particle deposition or escape from the model. In addition to the alveolar wall motion, the type of breathing condition and breathing cycle had a significant effect on the accurate prediction of the aerosol deposition in the intra-acinar region of the human lung.
Role of Arabidopsis RAB5 GEF vps9a in maintaining potassium levels under sodium chloride stress

Abstract Salt stress is one of the major factors impacting crop productivity worldwide. Through a variety of effector and signaling pathways, plants achieve survival under salinity stress by maintaining high cytosolic potassium/sodium ion (K+/Na+) ratios, preventing Na+ cytotoxicity, and retaining osmotic balance. Ras‐related protein 5 (Rab5) members are involved in the trafficking of endosomes to the vacuole or plasma membrane (PM). The vacuolar protein sorting‐ associated protein 9 (vps9a) encodes the single guanine nucleotide exchange factor (GEF) that activates all three known Rab5 proteins in Arabidopsis thaliana. Previous work from our group has reported the critical function of vps9a for the operation of salt‐induced endocytic pathway, as well as the expansion of endomembrane compartments under saline stress conditions. Here we show an additional role of vps9a in plant response to salt stress via maintenance of K+ status of the cell rather than Na+ homeostasis. Our results show that roots from vps9a‐2 mutant, subjected to 100 mM NaCl, display alterations in transcript levels of genes involved in the K+ homeostasis pathway. Concurrent with the observed sensitivity of vps9a‐2 mutant under NaCl stress, exposure to low K+ environments resulted in growth retardation, and reduced rate of endocytosis. Furthermore, vps9a‐2 mutant displays reduced expression of auxin reporter, Direct Repeat‐5 (DR5), and alterations in polarity and abundance of auxin efflux carrier PIN‐ FORMED2 (PIN2). Imposition of NaCl stress was found to be restrictive to the elongation capacity of cells in the root elongation zone of vps9a‐2 mutant. Together our results indicate that alterations in K+ homeostasis and associated cellular changes causing increased cell wall pH, contribute to diminished root growth and compromised survival of vps9a‐2 mutant under salt stress conditions.
Abundance and Habitat Preferences of Introduced Muscovy Ducks (Cairina moschata)

Muscovy ducks are native only to Central and South America, Mexico, and parts of southern Texas and are considered invasive in some areas outside of their native range. Although they have been introduced worldwide, they remain largely unstudied. The primary focus of this study was to relate Muscovy duck abundance to habitat characteristics of wetlands in Tampa, Florida. Muscovy abundance was measured using point count methods at 21 wetland sites that occur within an eight km radius of the University of South Florida’s main campus. Habitat features at these sites were assessed using field methods and Geographic Information Systems (GIS) (Arc 10.1v). Mann-Whitney U tests and Chi-squared tests were performed to identify significant differences between quantitative data groups. A Chi-squared test determined that there was not a positive correlation between Muscovy abundance and fountains or water regime, yet identified a significant relationship between Muscovy abundance and fencing, in which Muscovies did not frequently occupy ponds with fencing. Mann-Whitney U tests did not identify significances between Muscovy abundance and other habitat groups. Since Muscovy ducks are listed as an invasive species, identifying habitat preferences and deterrents will assist land managers and property owners with habitat modifications in preventing or controlling nuisance Muscovy populations.
Wildfires managed for restoration enhance ecological resilience

Expanding the footprint of natural fire has been proposed as one potential solution to increase the pace of forest restoration programs in fire-adapted landscapes of the western USA. However, studies that examine the long-term socio-ecological trade-offs of expanding natural fire to reduce wildfire risk and create fire resilient landscapes are lacking. We used the model Envision to examine the outcomes that might result from increased area burned by what we call “restoration” wildfire in a landscape where the ecological benefits of wildfire are known, but the need to suppress high-risk fires that threaten human values is also evident. Our study area, in the eastern Cascades of Oregon, USA, includes the Deschutes National Forest where large tracts of mixed conifer forest structure are outside the historical range of variation and characterized by multi-layer, closed-canopy stands. We found that simulation of one restoration wildfire per year in addition to high-risk wildfires in the regular fire season and over the course of 50 yr resulted in a 23% increase in total area burned, but the same probability of fire-on-fire interactions. This translated into 0.3% of the national forest burned by restoration wildfire per year and had a small impact in area burned by high-risk fires albeit more likely in extreme fire years. Smoke production doubled in the restoration scenario relative to the scenario without restoration wildfire, but still resulted in minimal smoke production in most years. Restoration fires burned with lowto mixed-severity and led to a steady reduction in canopy cover and increase in resilient forest structure in dry-forest types. Habitat for the federally protected northern spotted owl declined with the inclusion of restoration fire, while habitat for species that use recently burned forest stands (e.g., black-backed woodpecker) increased. Our results suggest that restoration wildfire can improve forest resilience and contribute to restoration efforts in fire-adapted forests, but there are trade-offs (wildlife habitat, smoke, area burned in fire-sensitive forest types), and the level of restoration fire use we simulated is unlikely to have a significant impact on the occurrence of high-
Adaptive modulation allocation algorithm in elastic optical networks

This paper introduces a new way to allocate the modulation format and improves the energy efficiency in elastic optical networks. For every connection request, both the quality of transmission and quality of service requirements are investigated. The allocation of modulation formats is based on both the physical distance and the required number of frequency slots. To improve the energy efficiency, Yen's algorithm is executed for every connection requested, and the lightpath with the lowest power consumption is selected. Numerical results were compared with adaptive modulation algorithms presented in the existing literature. The energy efficiency was improved by up to 27%, the used bandwidth available was reduced by up to 60%, and the blocking probability was decreased by 30% using our proposed adaptive algorithm.
Systematic Review: Anaesthetic Protocols and Management as Confounders in Rodent Blood Oxygen Level Dependent Functional Magnetic Resonance Imaging (BOLD fMRI)–Part A: Effects of Changes in Physiological Parameters

Background: To understand brain function in health and disease, functional magnetic resonance imaging (fMRI) is widely used in rodent models. Because animals need to be immobilised for image acquisition, fMRI is commonly performed under anaesthesia. The choice of anaesthetic protocols and may affect fMRI readouts, either directly or via changing physiological balance, and thereby threaten the scientific validity of fMRI in rodents. Methods: The present study systematically reviewed the literature investigating the influence of different anaesthesia regimes and changes in physiological parameters as confounders of blood oxygen level dependent (BOLD) fMRI in rats and mice. Four databases were searched, studies selected according to pre-defined criteria, and risk of bias assessed for each study. Results are reported in two separate articles; this part of the review focuses on effects of changes in physiological parameters. Results: A total of 121 publications was included, of which 49 addressed effects of changes in physiological parameters. Risk of bias was high in all included studies. Blood oxygenation [arterial partial pressure of oxygen (paO2)], ventilation [arterial partial pressure of carbon dioxide (paCO2)] and arterial blood pressure affected BOLD fMRI readouts across various experimental paradigms. Conclusions: Blood oxygenation, ventilation and arterial blood pressure should be monitored and maintained at stable physiological levels throughout experiments. Appropriate anaesthetic management and monitoring are crucial to obtain scientifically valid, reproducible results from fMRI studies in rodent models.
Indirect Immunofluorescence and Tumorspheres Enrichment Technique for Identifying Cancer Stem Cell Markers in Cancer Cell Lines From Primary Oral Cancer Tissues: An In Vitro Study

Aim: The cancer stem cells (CSCs) are known to be responsible for drug resistance and cancer relapse in the treatment of cancer. Identification and isolation of CSCs and study of their properties will play a crucial role in developing an effective drug against these targets. The aim of the study was to isolate CSCs from primary cancer by the tumorspheres enrichment method, to confirm by indirect immunofluorescence and gene expression of stem cell markers by using real-time polymerase chain reaction (RT-PCR) technique. Materials and Methods: In this in vitro study, we enriched oral CSCs through tumorsphere formation assay from seven primary cultures of OSCC patients with defined serum media. The expression and localization of the cell surface markers of CD133 and CD44 were tested by indirect immunofluorescence. Gene expression of stem cell markers such as CD44, CD133, Oct4, Sox2, and Nanog were quantified by RT-PCR technique. One-way analysis of variance was applied to analyze gene expression. Results: Tumorsphere formation has been used to isolate the CSCs from the OSCC tissue culture. Both CD133 and CD44 antibody confirmed the presence of CSCs through indirect immunofluorescence. In comparison to parental cell lines, the expression levels of CD133, CD44, Oct4, Sox2, and Nanog stem cell were significantly higher in CSC-enriched subpopulations. Conclusions: The cost-effective spheroid enrichment and the indirect immunofluorescence methods are useful for the isolation of CSCs from the primary tumor.
Task scheduling approaches in fog computing: A systematic review

The Internet of Things (IoT) interconnects billions of physical objects to collect and exchange information and makes available various applications. Despite all the advantages of the IoT, some of its applications are not feasible because of the existing restrictions in the IoT sensors. To overcome these restrictions, cloud computing has been developed in recent years. Although cloud computing has removed some of these restrictions, the cloud itself has faced some other challenges. One of these challenges is the distance between the cloud and the end‐devices, which is not ideal for delay‐sensitive applications and also leads to high communication costs and security problems. To handle these challenges, the fog computing has been introduced in literature, which places the resources and services at the edge of the network, close to the end‐devices. On the other hand, fog nodes suffer from heterogeneity, uncertainty, and dispersion of resources, and also processing, storage, and memory limitations. Thus, there is need for a proper task scheduling approach to use these resources optimally. In this study, the task scheduling algorithms proposed by different researchers for the cloud‐fog environment, their advantages and disadvantages, and also various tools and issues regarding the scheduling methods and their restrictions were discussed. The results indicated that about 58% of the scheduling algorithms use static scheduling and that the other 42% use dynamic scheduling, and the delay metric is the most noteworthy parameter considered in most studies with a share of nearly 17%. Finally, we identified the open issues related to the task scheduling based on cloud‐fog computing and provided some directions for future works.
The Impact of A Collection of Tasks And Activities On Accounting Information Quality: Survey in Indonesia

An organization in general, of course, has a goal of being able to survive in the long term. To achieve this goal, an organization needs a good business process to support the running of the organization. Business Process can be considered as a collection of tasks and activities that exist in a structured and orderly manner to provide results in the form of goods or services for internal and external users. Organizational managers are responsible for managing business processes. Business processes are needed to see how the company runs its daily business, business processes also have an important role in structuring and implementing flexible information systems. Information systems are built and operated to provide information for managers. This research intends to understand effect of business processes quality (BPQ) to accounting information systems quality (AISQ) and its impact on accounting information quality (AIQ).
Beam‐aware energy harvesting discontinuous reception in machine‐to‐machine millimeter‐wave 5G communications

Machine‐to‐machine (M2M) communication interconnects a large number of machines to exchange information in a network. These battery operated devices exhaust their energy after continuous usage for a long period of time. Discontinuous reception (DRX) standardized by the third generation partnership project (3GPP) is an efficient power saving protocol used in wireless networks. The power saving achieved by the DRX mechanism is often compromised with the ensuing buffering delay suffered by the packets. DRX mechanism with energy harvesting improves the performance of the M2M devices by exploiting the extra sleep cycles yielded by the harvested energy. However, the operation of the energy harvesting‐DRX (EH‐DRX) in the fifth generation (5G) millimeter‐wave (mm‐wave) systems with beamforming results in poor performance metrics. Beamforming is used in 5G mm‐wave networks for a base station to communicate with a group of devices situated in a particular direction. In this paper, an analytical model is devised by merging a beam‐aware mechanism with the EH‐DRX in the M2M mm‐wave 5G networks to improve the energy efficiency. As a result, the power saving at the user equipment (UE)/M2M device is enhanced by 16% by the proposed method compared with the original EH‐DRX mechanism.
The Effects of Rating and Sentiment on Online Review Helpfulness: A Dynamic Perspective

Too many reviews lead to information overload, which makes it vital for an effective review system to identify helpful ones. Extensive empirical studies have shown that review helpfulness is affected by many factors, two of which are review sentiment and rating. However, almost all the existing studies assumed that the effects of these factors are time-invariant, and the review system is static. This study challenges such unrealistic yet prevalent assumption. Using 82, 703 phone review data from Amazon.com, we examine how review rating and sentiment impact review helpfulness and how such impact varies with time. Echoing the mixed results on the effects of rating or sentiment on perceived review helpfulness, our results suggest that in a decade before, rating and sentiment were positively associated with review helpfulness, while in recent years the relationship became negative instead. Our findings offer theoretical and managerial insights for both researchers and practitioners.
CNN-Based Fault Phase Identification Method of Double Circuit Transmission Lines

Abstract—In order to address the problems that model-based distance protection cannot correctly identify the fault phases in the DCTL (Double Circuit Transmission Lines on the same tower), a CNN-based (Convolutional Neural Network) fault phase identification method is proposed. The proposed method only uses the current and voltage waveforms of single-ended and single-circuit of DCTL to identify the fault phases. The CNN includes two convolution layers and two pooling layers, which are used to automatically extract the features of the waveforms. Furthermore, the CNN realizes the phase identification function by the extracted features. A training set is constructed by the simulation result of PSCAD, which is used for training the CNN to fit the mapping relationship between the waveforms and the fault types. Then, a validation set is used to optimize the hyper-parameters of CNN. Finally, several test sets are used to test the performance of CNN for phase identification. Compared with the traditional model-driven methods, the CNN-based method avoids manually analyzing the fault characteristics under different fault types and constructing identification criteria. The test results show that the proposed method can greatly improve the fault phase identification accuracy of DCTL.