Miracle-dz/UniFAR-FTUs huggingface dataset:
The Function Of Emoji In Digital Communication In Indonesia

This article aimed at elaborating the functions of emojis used in communication engaged in digital media, especially WhatsApp Group (WAG) and Instagram (IG). This topic was noteworthy due to the empirical facts showing that in communication digital in Indonesia emojis were used as expressions supporting communication nevertheless people often utilized them by breaking the communication logics. In undertaking the research, netnosemiotics, an approach integrating digital ethnography (netnography) and semiotics was applied. Through this study it was revealed that emojis did not only function as visual texts conveying particular messages, but also as the contexts representing the cultural relationship of various types of communication relations. Emojis were signs above signs. At this point, emojis built a communication we called metasemiotics. This finding significantly contributed to the development of digital communication model related to the digital culture as a whole, both at the local and global levels.
A Review on Mechanism of Flood Disaster Management in Asia

This paper attempts to analyze the review on mechanism of flood disaster management in Asia. Flood is amongst the most common of natural disasters and its impact is one of the most significant disasters in the world. In this paper, we have discussed the flood disaster management some selected countries in Asia such as Malaysia, Indonesia, Thailand, Bangladesh, India, Pakistan, Japan and China. For these countries, we tried to explore the flood disaster risk, pre- and post-disaster program and participants, emergency response and recovery, flood mitigation and management, relief and preparedness machinery, flood forecasting and warning system, policy, planning as well as strategic etc. This paper can make for the above countries disaster management system better respond and handle to disasters risk, and reduce the social and economic losses of disasters caused. It also required to improve data availability and evaluation, and possibly to combine with other types of information in view of increasing usefulness for policy making
Review of Researches on Biomass Carbon Stock in Grassland Ecosystem of Qinghai-Tibetan Plateau

It is critical to know Qinghai-Tibetan Plateau’s grassland biomass carbon(C) stock and its dynamics in order to study the regional C cycle and sustainable use of grassland resources.After reviewing the publications,the authors present a summary of methods and results in the studies of biomass C stock in grassland ecosystem of Qinghai-Tibetan Plateau. (1) Four methods are mainly used in this field: searching in literature and documents,field measurement,remote sensing of vegetation/vegetation indices,and process modeling.In the practice,methods of estimation,quality standards for sample collection,and underground biomass estimation are the most important factors impacting the results. (2) According to the published literature,biomass C density of Qinghai-Tibetan Plateau’s grasslands is approximately 223g/m2,and can be translated to a total grassland biomass C stock of 277 Tg C(1Tg=1012g). (3) The estimation results based on remote sensing indicate that the biomass C stock of Qinghai-Tibetan Plateau’s grasslands increased over the past 20 years,suggesting that alpine grasslands might have functioned as a biomass C sink. (4) The above ground biomass C stock of Qinghai-Tibetan Plateau’s grasslands is strongly affected by precipitations,while the role of temperature is unclear.In addition,human activities are considered to be a crucial factor affecting grassland biomass C stock as well.Problems remain in the studies of biomass C stock in grassland ecosystem of Qinghai-Tibetan Plateau;more thorough investigations are needed in the fields such as data acquirement in the basic field measurements,optimization of algorithms for remotely-sensed vegetation indices,and process modeling of carbon-nitrogen-water coupling cycle in the alpine ecosystem.
Identifying the Affecting Factors on Consumer`s Online Shopping Behavior Based on TAM, DTPB Model

─ In the present study the factors affecting the behavior of online shoppers in using the internet as a shopping channel was investigated to determine the effective factors on customer's orientation for buying via internet. This was done because of the many benefits of e-commerce for customers, enterprise, and society, including speed and ease of doing business. These factors with the use of compiled model combining of two theories of Decomposed Theory of Planned Behavior and Technology Acceptance Model were inspected to access a union prospect for the reception of technology by users. The findings of the study, which was conducted on a sample of 360 Internet customers of Saipa revealed that three variables of perceived risk, subjective norms, and marketing mix are influencing factors on the online shoppers` behavior.
The Ascent of Geared Turbofan Engines

The two-day virtual event attracts the industry’s leading professionals and key decision makers, whose innovation and expertise are shaping the future of turbomachinery. Authors and presenters are invited to participate in this event to exchange ideas on research, development and best practices on Gas Turbines and allied areas. Participating in the conference and exhibition is an excellent opportunity to initiate and expand international co-operation.
Postpartum Reclassi ﬁ cation of Glycemic Status in Women with Gestational Diabetes Mellitus and Associated Risk Factors Reclassi ﬁ cação pós-parto do estado glicêmico em mulheres com diabetes mellitus gestacional e fatores de risco associados

Objective The aims of the study were to evaluate, after pregnancy, the glycemic status of women with history of gestational diabetes mellitus (GDM) and to identify clinical variables associated with the development of type 2 diabetes mellitus (T2DM), impaired fasting glucose (IFG), and impaired glucose tolerance (IGT). Methods Retrospective cohort of 279 women with GDM who were reevaluated with an oral glucose tolerance test (OGTT) after pregnancy. Characteristics of the index pregnancy were analyzed as risk factors for the future development of prediabetes (IFG or IGT), and T2DM. Results: T2DM was diagnosed in 34 (12.2%) patients, IFG in 58 (20.8%), and IGT in 35 (12.5%). Women with postpartum T2DM showed more
Auditory Temporal Processing in Older Listeners: A Brief Review

: Researchers propose that auditory temporal processing declines with age, which further contributes to speech perception deficits in older listeners. Temporal cues relevant to speech perception occur at three levels: prosodic temporal cues, gap and duration cues and periodicity cues. Psychoacoustic and evoked potential studies suggest that auditory temporal processing declines with age, which might be caused by loss of neural synchrony. This reduced neural synchrony can be modeled by simulating neural jitter. Studies of temporal jitter model support the age-related decline of auditory temporal processing, which could account for speech perception deficits experienced by some older adults in challenging listening condition.
Climate Change and Individual Behavior: Considerations for Policy

Climate change is anthropogenic - the product of billions of acts of daily consumption. That solutions need to be anthropogenic too is well accepted. Yet, suggested solutions are normally cast in the realms of finance and technology, often neglecting the primal root of the problem: individual behavior. An emerging body of social-psychology scholarship has examined the barriers and drivers of individual behavior in relation to both adaptation and mitigation. This paper reviews some of its conclusions, and suggests policy areas that should be considered in devising appropriate interventions.
Gender differences in IT entrepreneurship: comparing the entrepreneurial intention/behavior in the pre and post-implementation phases

: Currently, the number of women entrepreneurs starting businesses is increasing. Women manage between a quarter and a third of the companies in the formal economy in the world. In Morocco, women entrepreneurs represent 10 to 12% of the total number of entrepreneurs with a low representation in the information technology (IT) sector 2 . The purpose of this paper is to compare the entrepreneurial intention and behavior of female and male entrepreneurs in the pre-and post-implementation phase, particularly in the IT sector. The content analysis of the interviews conducted allowed us to observe that in the pre-implementation phase, the gender variable only moderates the relationship between individual determinants and entrepreneurial intention. However, in the post-implementation phase, we found that the gender variable moderates both the relationship between individual and contextual determinants and entrepreneurial behavior. Ultimately, differences in terms of social ties, desirability and feasibility were revealed.
Assessment of time implicit discretizations for the computation of turbulent compressible (cid:13)ows

Restrictions on the maximum allowable time step of explicit time integration methods can be very severe for direct and large eddy simulations of compressible turbulent (cid:13)ows at high Reynolds numbers, for which extremely small space steps have to be used close to solid walls in order to capture tiny and elongated boundary layer structures. A way of increasing stability limits is to use implicit time integration schemes. However, the price to pay is a higher computational cost per time step, higher discretization errors and lower parallel scalability. A successful implicit time scheme should provide the best possible compromise between these opposite requirements. In this paper, several implicit schemes assessed against two explicit time integration techniques, namely a standard four-stage and a six-stage optimized Runge{Kutta methods, in terms of computational cost required to achieve a threshold accuracy level for the simulation of compressible turbulent (cid:13)ows. Pre-cisely, a second-order backward scheme solved by means of matrix-free quasi-exact Newton subiterations is compared to time-accurate Runge{Kutta implicit residual smoothing (IRS) schemes. A new IRS scheme of fourth-order accuracy, based on a bilaplacian operator, is developed to improve the accuracy of the classical second-order approach. Numerical re-sults show that the proposed IRS scheme leads to reductions in computational time by about a factor 5 for an accuracy comparable to that of the corresponding explicit Runge-Kutta scheme.
Commentary Complex Regulation of Telomerase Activity Implications for Cancer Therapy

Telomerase activity is a marker of malignancy. The observation that its activity is present in 85 to 90% of all human tumors but not in normal nonneoplastic cells 1 has made telomerase a superb target not only for the diagnosis of malignancy, but also for the development of novel therapeutic agents. For neoplastic cells to maintain sustained proliferation beyond the cellular senescent phase, cells must either reactivate telomerase or inhibit repressors of telomerase activity. Thus, the mechanisms regulating telomerase activity are of great interest and are the focus of the work by Lin and colleagues, 2 in this issue of The American Journal of Pathology .
The Ravel data set

In this paper, we introduce the publicly available data set Ravel. All scenarios were recorded using the AV robot head POPEYE, equipped with two cameras and four microphones. The recording environment was a regular meeting room enclosing all the challenges of a natural indoor scene. The acquisition setup is fully detailed as well as the design of the scenarios. Two examples of use of the data set are provided, proving the usability of the Ravel data set. Since the current trend is to design robots able to interact with unconstrained environments, this data set provides several scenarios to test algorithms and methods aiming to satisfy this design constraints. The data set is publicly available at the following URL: http://ravel.humavips. eu/
Data-driven Reaction Template Fingerprints

Chemical reactions can be classiﬁed into distinct categories that encapsulate concepts for how one molecule is transformed into another. One can encode these concepts in rules specifying the set of atoms and bonds that change during a transformation, which is commonly known as a reaction template. While there exist multiple possibilities to represent a chemical reaction in a vector representation, or ﬁngerprint, this is not the case for reaction templates. As a consequence, methods to navigate the space of reaction templates are limited. In this work, we introduce the ﬁrst reaction template ﬁngerprint. To this end, we follow a data-driven approach relying on a masked language modelling task on SMIRKS strings. We combine unsupervised pre-training with ﬁne-tuning on the classiﬁcation of templates according to the RXNO ontology, for which we achieve up to 98.4% classiﬁcation accuracy. We highlight how the learned embeddings can be extracted and used in downstream applications.
Some reﬁnements of formulae involving ﬂoor and ceiling functions

The ﬂoor and ceiling functions appear often in mathematics and manipulating sums involving ﬂoors and ceilings is a subtle game. Fortunately, the well-known textbook Concrete Mathematics provides a nice introduction with a number of techniques explained and a number of single or double sums treated as exercises. For two such double sums we provide their single-sum analogues. These closed-form identities are given in terms of a dual partition of the multiset (regarded as a partition) of all b-ary digits of a nonnegative integer. We also present the double-and single-sum analogues involving the fractional part function and the shifted fractional part function
Dangerous Driving Behavior Recognition Based on Improved YoloV5 and Openpose

—This paper focuses on the automatic detection of two dangerous driving behaviors, smoking and talking on the phone. First, our own datasets are constructed for the two anomalous behaviors of smoking and making phone calls. Furthermore, a two-stage behavioral anomaly detection method is proposed. The object detection network model improves the prediction head of YoloV5, making it more effective in detecting small target objects, and optimizes the loss function for the categorically mutually exclusive datasets. The pose estimation network structure is improved, and the attention mechanism of the Coordinate Attention (CA) structure is introduced to improve the efficiency and accuracy of information processing. Finally, the end result is evaluated through Euclidean distance calculation, and the elbow joint angle is used as an auxiliary judgment condition. The proposed dangerous driving behavior recognition model achieves a mean average precision of 93.4% under the condition of about 61FPS and improves the detection accuracy by 8.2%. It meets real-time requirements and increases accuracy while maintaining speed.
Fungal Pretreatment and Hydrolysis of Sawdust Wastes from Ethiopian Sawmills for Sugar Production

: Pretreatment with wood rot fungi has been reported for improving the enzymatic hydrolysis of lignocelluloses into usable sugars. In this research sawdust samples of Eucalyptus globulus and Cupressus lusitanica were pretreated with three white rot fungi and then hydrolyzed with enzyme extracts from three cellulolytic wood rot fungi. Results indicated that the amounts of lignin, cellulose and hemicellulose losses of the two sawdust types were significantly increased with the increasing incubation days. Pretreating with the white rot fungi resulted in more selective modifications in the lignin content of the sawdust samples. Sugar yield from the hydrolysis of the white rot fungi pretreated sawdust in all cases was significantly higher than that has been obtained from the control indicating the efficiency of the white rot fungi. The effects of the white rot fungi vary with biomass species on delignification efficiency. Results also indicated that with increasing hydrolysis period, sugar yields were found increased. By improving their culture conditions, these wood rot fungi could be used to efficiently reduce recalcitrance of raw sawdust wastes and then efficiently hydrolyze the pretreated lignocellulosic resources into usable sugars. This finding appears to be the first for Ethiopian wood rot fungal isolates in this regard.
Atmospheric circulation and storm events in the Black Sea and Caspian Sea

Extreme sea storms are dangerous and a potential source of damage. In this study, we examine storm events in the Black Sea and Caspian Sea, the atmosphere circulation patterns associated with the sea storm events, and their changes in the present (1961–2000) and future (2046–2065) climates. A calendar of storms for the present climate is derived from results of wave model SWAN (Simulating WAves Nearshore) experiments. On the basis of this calendar, a catalog of atmospheric sea level pressure (SLP) fields was prepared from the NCEP/NCAR reanalysis dataset for 1961–2000. The SLP fields were subjected to a pattern recognition algorithm which employed empirical orthogonal decomposition followed by cluster analysis. The NCEP/NCAR reanalysis data is used to evaluate the occurring circulation types (CTs) within the ECHAM5-MPI/OM Atmosphere and Ocean Global Circulation Model (AOGCM) for the period 1961–2000. Our analysis shows that the ECHAM5-MPI/OM model is capable of reproducing circulation patterns for the storm events. The occurrence of present and future ECHAM5-MPI/OM CTs is investigated. It is shown that storm CTs are expected to occur noticeably less frequently in the middle of the 21st century.
Low-Complexity, Efﬁcient 9/7 Wavelet Filters VLSI implementation

—This paper proposes a novel low-complexity, efﬁ-cient 9/7 wavelet ﬁlters VLSI architecture for image compression applications. The 9/7 wavelet ﬁlters are widely used in different image compression schemes, such as the JPEG2000 image coding standard. Thus the implementation of efﬁcient codecs is of great concern. The performance of a hardware implementation of the 9/7 ﬁlter bank depends on the accuracy of coefﬁcients representation. However the greatest part of current implementations does not consider 9/7 wavelet ﬁlters starting from their original derivation, but as taps to be implemented. The aim of this work is to show that great complexity reduction with excellent performance can be achieved going through the derivation of the 9/7 taps values.
Ciencias Pecuarias

Background: the use of semi-purified glycerin in pig diets has been studied as an alternative energy source. Objective: to evaluate growth performance and serum levels of glucose, triglycerides, cholesterol, and urea in pigs fed diets containing semi-purified glycerin during the growth phase. Methods: forty barrows with an initial weight of 27.30 ± 1.74 Kg, distributed in a randomized complete block design with four treatments and five replicates were used. The dietary treatments were a combination of corn and soybean meal diets with the addition of 0, 5, 10 or 15% semi-purified glycerin. The experimental period lasted 27 days and was divided into two periods. Results: during Period 1, pig performance did not differ with the inclusion of semi-purified glycerin in the diet. In Period 2, an improvement in average daily weight gain was observed. In the total period, an improvement was observed in the average daily weight gain, feed/gain ratio and final weight of the animals. However, serum parameters were not affected by the inclusion of semi-purified glycerin in the diets. Conclusion: the addition of up to 15% semi-purified glycerin to the diet of growing pigs improves growth performance without affecting serum parameters.
Effect of Integrated Some Amendments and Bio-Fertilizers with Mineral-N Fertilization on Soil Fertility and Peanut Crop Productivity

: Two field experiments were conducted during the two successive summer seasons of 2019 and 2020, on a loamy sand soil at El-Qantra Shark, Ismailia Governorate, Egypt. The aim was to study the effect of nitrogen fertilizer as Urea (46% N) at different rates (15, 20 and 30) kg N fed either alone or in a combination 1 with compost at a rate of 5Mg fed , bio-fertilizer, ( Rhizobium radiobacter sp.) as salt tolerant PGPR strain as 1 well as humate substances at a rate of 10 kg fed on soil fertility and peanut ( Arachis hypogaea ) crop 1 productivity. The results could be summarized as follow: The soil pH and EC were decreased due to application of compost with 20kg N fed compared with the values of such values before planting. Also, in most cases, 1 results reveal that the available content of NPK, after peanut harvest, were significantly influenced due to compost, bio-fertilization and K-humate applied with 20 kg fed of mineral N fertilizer compared to mineral 1 fertilizer alone. In most cases, the peanut yield and its components as well as N, P, K, Fe, Mn and Zn uptake of peanut seed were significantly increased due to compost, bio-fertilization and K-humate applied with 20 kg fed of mineral N fertilizer compared to other treatments. The highest values of chlorophyll in peanut leaves 1 at 70 days from planting and seed protein content were obtained when applying the 20 kg N fed with compost 1 or bio-fertilizer. Also, the proline content was increased with decreasing the rates of mineral N fertilizer in combination with all amendment treatments and the highest content of proline was obtained by application of 15 kg N/ fed alone. So, it is worth mentioning the effective role of applied compost at the rate of 5Mg fed 1
Observation data processing methods in SINS/multi-GNSS integrated navigation simulation

In this paper, two methods are proposed, namely the unified processing method and the distributed processing method, to process the global navigation satellite system observation data in integrated navigation simulation which uses the strapdown inertial navigation system as the reference system and the multi-global navigation satellite systems as the sub-systems. The unified processing method takes all the global navigation satellite systems as a whole as one sub-system while the distributed processing method takes each global navigation satellite system as one sub-system. The centralized filter and federated filter are utilized respectively to process the global navigation satellite system observation data in the unified processing method and the distributed processing method. The mathematical models of the unified processing method and the distributed processing method are given in detail. Through theoretical derivation and mathematical simulations, the performances of the unified processing method and the distributed processing method are investigated and compared, showing that while they have the same position (velocity) accuracy, the distributed processing method offers better efficiency than the unified processing method especially when the number of global navigation satellite systems is large (>3).
Learning Analytics and Scholar Dropout: A Predictive Model

: The identification of potential students candidates to desert is one of the main utilities of the learning analytics. Thanks to this, teachers and students can take preventive measures to combat this problem that affects the majority of latin american universities. The objective of this paper is to present a predictive model to identify potential students to abandon their studies, which was built using multivariate statistical techniques. This paper concludes that the aspects relating to the interaction between teachers and students have a greater importance, including above personal and institutional factors