Miracle-dz/UniFAR-FTUs huggingface dataset:
ORCHILEAK (revision 3875): a new model branch to simulate carbon transfers along the terrestrial–aquatic continuum of the Amazon basin

Lateral transfer of carbon (C) from terrestrial ecosystems into the inland water network is an important component of the global C cycle, which sustains a large aquatic CO2 evasion flux fuelled by the decomposition of allochthonous C inputs. Globally, estimates of the total C exports through the terrestrial–aquatic interface range from 1.5 to 2.7 Pg C yr−1 (Cole et al., 2007; Battin et al., 2009; Tranvik et al., 2009), i.e. of the order of 2–5 % of the terrestrial NPP. Earth system models (ESMs) of the climate system ignore these lateral transfers of C, and thus likely overestimate the terrestrial C sink. In this study, we present the implementation of fluvial transport of dissolved organic carbon (DOC) and CO2 into ORCHIDEE (Organising Carbon and Hydrology in Dynamic Ecosystems), the land surface scheme of the Institut Pierre-Simon Laplace ESM. This new model branch, called ORCHILEAK, represents DOC production from canopy and soils, DOC and CO2 leaching from soils to streams, DOC decomposition, and CO2 evasion to the atmosphere during its lateral transport in rivers, as well as exchange with the soil carbon and litter stocks on floodplains and in swamps. We parameterized and validated ORCHILEAK for the Amazon basin, the world's largest river system with regard to discharge and one of the most productive ecosystems in the world. With ORCHILEAK, we are able to reproduce observed terrestrial and aquatic fluxes of DOC and CO2 in the Amazon basin, both in terms of mean values and seasonality. In addition, we are able to resolve the spatio-temporal variability in C fluxes along the canopy–soil–water continuum at high resolution (1°, daily) and to quantify the different terrestrial contributions to the aquatic C fluxes. We simulate that more than two-thirds of the Amazon's fluvial DOC export are contributed by the decomposition of submerged litter. Throughfall DOC fluxes from canopy to ground are about as high as the total DOC inputs to inland waters. The latter, however, are mainly sustained by litter decomposition. Decomposition of DOC and submerged plant litter contributes slightly more than half of the CO2 evasion from the water surface, while the remainder is contributed by soil respiration. Total CO2 evasion from the water surface equals about 5 % of the terrestrial NPP. Our results highlight that ORCHILEAK is well suited to simulate carbon transfers along the terrestrial–aquatic continuum of tropical forests. It also opens the perspective that provided parameterization, calibration and validation is performed for other biomes, the new model branch could improve the quantification of the global terrestrial C sink and help better constrain carbon cycle–climate feedbacks in future projections.
N49: THE FIRST ROBUST DISCOVERY OF RECOMBINING PLASMA IN AN EXTRA GALACTIC SUPERNOVA REMNANT

Recent discoveries of recombining plasmas (RPs) in supernova remnants (SNRs) have dramatically changed our understanding of SNR evolution. To date, a dozen RP SNRs have been identified in the Galaxy. Here, we present Suzaku deep observations of four SNRs in the LMC, namely, N49, N49B, N23, and DEM L71, for accurate determination of their plasma states. Our uniform analysis reveals that of these SNRs, only N49 is in the recombining state, which is the first robust discovery of an RP from an extra-galactic SNR. Given that RPs have only been identified in core-collapse SNRs, our results strongly suggest a massive star origin for this SNR. On the other hand, no clear evidence of an RP is confirmed in N23, for which detection of recombination lines and continua was previously claimed. Comparing the physical properties of the RP SNRs identified so far, we find that all of them can be categorized into the “mixed-morphology” class, interacting with surrounding molecular clouds. This might be a key to determining the formation mechanisms of RPs.
COLON TARGETED DRUG DELIVERY SYSTEM-AN APPROACH FOR TREATING COLONIC AILMENTS

The colon is a site where both local and systemic delivery of drugs can take place. Local delivery could, for instance, allow topical treatment of inflammatory bowel disease. Treatment could be made more efficient if it was possible for drugs to be targeted like a shot to the colon. Systemic side effects could also be reduced. Colon specific systems might also allow oral administration of peptide and protein drugs, which are normally inactivated in the upper portions of the gastrointestinal tract. Primary approaches for CDDS (Colon Specific Drug Delivery), which includes prodrugs, pH and time dependent systems and microbial triggered drug delivery system achieved limited success and accepting limitations. Newly developed CDDS, which includes pressure controlled colonic delivery capsules (PCDCS), CODESTM and osmotic controlled drug delivery are unparalleled in terms of achieving in vivo site specificity and feasibility of fabrication operation. This review also focuses on evaluations of CDDS in general. Keywords: Colon specific drug delivery, Prodrugs, CODESTM, PCDCS.
A STRATEGY FOR FORECASTING OPTION PRICES USING FUZZY TIME SERIES AND LEAST SQUARE SUPPORT VECTOR REGRESSION WITH A BOOTSTRAP MODEL

Recently, the strategy for forecasting option price has become a popular financial topic because options are important tools on risk management in financial investments. The well-known Black-Scholes model (B-S model) is widely used for option pricing. In B-S model, the normal distribution assumption is important. However, the financial data in real life may not follow the normal distribution assumption. For this reason, this paper proposes a novel hybrid model, which is a nonlinear prediction model without normal distribution assumptions to forecast the option prices. The proposed model is composed of a fuzzy time series (FTS) model, a least square support vector regression (LSSVR), and a bootstrap method. In the proposed model, FTS model is firstly used to fuzzify dataset and to build historical database. Subsequently, the proposed method uses the remainder contractual time to search similar historical trends as training samples. Finally, we use the bootstrap method on LSSVR to enhance the prediction accuracy. The experiment results show that the proposed model outperforms traditional time series models and several hybrid models in terms of the root mean square error (RMSE), the mean absolute error (MAE) and the correlation coefficient (r) of actual and forecasted option price.
Environmentally conscious behavior among Malaysians consumers: an empirical analysis

This paper aims to investigate the influence of demographic and psychographicv variables on environmentally conscious cosumer behavior (ECCB)v in the context of Malaysian consumers. A survey was developed and administered. generating a total sample of 319 respondents across the country. The preliminary results indicated that all of the variables examin ed were significantly correlated to ECCB, expert for income. Later the analysis from the regression highlighted that only age, gender and perceived consumer effectiveness (PCE)were significant predictors to ECCB. The findings confirmed that, in terms of psychographic variables, PCE has been proven to be more accurate and significant determinant than environmental concern (EC) for segmenting and explaining different segments and characteristics of pro-environmental behavior . These findings may assist Malaysian policy makers in formulating actionable decisions related to environmental education and protection.The finding also allows marketers to use marketing and awareness-raising campaigns to encourage consumers to choose environmental friendly products.
TRUST IN DIGITAL SUPPLY CHAIN MANAGEMENT

Companies managing supply chains are increasingly facing a decision to migrate or start operating in the digital world. Gaining competitive advantage by supply chain management means sharing the information as the evidence of trust between partners. Digital Supply Chains are based on technologies that enable increasing competitiveness mainly by delivering information in real time simultaneously to many supply chain partners. However the type and range of the information shared indicates the level of trust. Research results show that partners in supply chain were sharing information about inventory and transport activities. These are the main areas of competing by logistics and supply chain management. The aspect of partnership and cooperation was also raised in the research. Cloud computing had been willingly used in Supplier Relationship Management, Customer Relationship Management and Customer Service Management processes by the respondents.
Gas and Dust Condensations and a Peculiar Class 0 Object in the Lupus 3 Star-Forming Cloud

The Lupus 3 molecular cloud has been surveyed for dense gas and dust cores and embedded objects in radio [H13CO+ J = 1-0 line and 1.2 mm continuum] and infrared [JHKsL′MN1 bands and H2 v = 1-0 S(1) line] wavelengths. These observations unveil a filamentary cloud, three dense cores, an embedded millimeter-wave source (MMS), and an associated elongated object in the K band. The properties of the three dense cores are M = 3.5-5.6 M☉, R = 0.04-0.06 pc, and n(H2) = (1.0-3.9) × 105 cm-3, properties similar to those in Taurus. Two of these three objects are likely to be prestellar cores, while the other one exhibits ongoing star formation. The spectral energy distribution (SED) analysis of the MMS shows that it is a remarkably cold Class 0 object with molecular outflow detected in the CO(J = 3-2) line and peculiar near-IR detections. From the estimated low bolometric temperature (39.5 K), faint bolometric luminosity (0.16 L☉), and sufficiently large envelope mass (0.52 M☉), the MMS is expected to be in a very early phase (~104 yr) of mass accretion. The K-band elongated feature appears to be scattered light originating from the embedded central object of the MMS seen through the outflow cavity opening toward HH 78 on the near side as shown by the blueshifted CO wings. The MMS has also been detected by the Spitzer Space Telescope, and its near-IR images exhibit butterfly-shaped nebulosity emission as scattered light through the bipolar cavities in contrast to that in the K band. Together with the Spitzer and NTT JHK photometric data, the observed SED has a short-wavelength cutoff suggesting a low effective temperature (<1400 K) of the central object.
Chloroplast DNA: A Promising Source of Information for Plant Phylogeny and Traceability

Chloroplasts are organelles with a specific DNA (cpDNA), which are responsible by the energetic metabolism in eukaryotic cells from plants and algae. Their key role is to perform the photosynthesis, when the cell converts sunlight and carbon dioxide into glucoses (=energy) and oxygen. Studies aiming to understand how chloroplast works are important to highlight details about plant evolution. The new approaches in molecular biology have raised the knowledge about the chloroplast genome characteristics and opened a wide range of possible applications for the increased background. In this review, we discuss the use of chloroplast DNA for plant phylogeny and traceability. Considering the increasing need for food safety, identification of gene flow from genetically modified plants and for better tools to police investigation, many works have demonstrated the viability of using cpDNA for this purposes, either for phylogeny of land plants or traceability of food, genetically modified plants and illicit drugs.
Statistical and dynamical downscaling of precipitation over Spain from DEMETER seasonal forecasts

Statistical and dynamical downscaling methods are tested and compared for downscaling seasonal precipitation forecasts over Spain from two DEMETER models: the European Centre for Medium-Range Weather Forecasts (ECMWF) and theUKMeteorological Office (UKMO). The statistical method considered is a particular implementation of the standard analogue technique, based on close neighbours of the predicted atmospheric geopotential and humidity fields. Dynamical downscaling is performed using the Rossby Centre Climate Atmospheric model, which has been nested to the ECMWF model output, and run in climate mode for six months. We first check the performance of the direct output models in the period 1986–1997 and compare it with the results obtained applying the analogue method. We have found that the direct outputs underestimate the precipitation amount and that the statistical downscaling method improves the results as the skill of the direct forecast increases. The highest skills — relative operating characteristic skill areas (RSAs) above 0.6 — are associated with early and late spring, summer and autumn seasons at zero- and one-month lead times. On the other hand, models have poor skill during winter with the exception of the El Niño period (1986–1988), especially in the south of Spain. In this case, high RSAs and economic values have been found. We also compare statistical and dynamical downscaling during four seasons, obtaining no concluding result. Both methods outperform direct output from DEMETER models, but depending on the season and on the region of Spain one method is better than the other. Moreover, we have seen that dynamical and statistical methods can be used in combination, yielding the best skill scores in some cases of the study.
Combination of Thresholding and Log Edge Detection Technique in Thermal Image Analysis

: Accuracy itself a complete statement to describe a final destination. Now days, we have so many image processing tools available. By using that, it is very easy to extract the information or details of background of an Image taken from thermal imaging camera. Without any special function or a tool it is a very cumbersome task to be carried out for any researcher. Normally, thresholding technique is applied to separate out different objects from the background present in an image. To get an accurate result and enhancement in analysis and measurement of any object of thermal image, it is required to apply essential steps in an algorithm used in addition with thresholding. In this paper, thermal image of an electrical system is used. To protect the circuit, it is necessary to distinguish area of an acquired thermal image by high heated area and normally heated area. Now to protect circuit, it is necessary to measure high heated area accurately where normally heated area is ignored. In this paper I have used LoG (Laplacian of Gaussian), an optimal edge detection technique in addition with thresholding, and achieved high accuracy in a result identified. The result or measured area is in terms of pixel for simplicity.
Cultural Influences on IT Usage Amongst Industrial Workers in Malaysia

This paper examines the cultural influences on IT usage amongst industrial workers in Malaysia. It explores the relationship between the workers’ cultural attributes and IT usage. It also examines the factors that influence IT usage, their innovativeness and barriers that hinder IT application. This study reveals that the workers’ capability in IT is partly nurtured by cultural attributes such as their love for knowledge, perception towards IT and their willingness to take risks; and external factors such as management’s support and government’s encouragement. Competition is one factor which is found to influence workers’ innovativeness. The inability to own a computer, low English proficiency and the difficulty in understanding knowledge in IT are the major barriers in IT usage. Finally, we observe that a large majority of industrial workers use low capacity network services, mainly the e-mail, electronic newspaper and electronic classified advertisements
Speech prosody and developmental dyslexia: Reduced phonological awareness in the context of intact phonological representations

Recent research indicates that awareness of the rhythmic patterns present in spoken language (i.e., prosody) may be an important and relatively overlooked predictor of reading ability. Two studies investigated the prosodic processing abilities of skilled adult readers and adults with developmental dyslexia. Participants with dyslexia showed reduced awareness of lexical and metrical stress and these skills were found to be significantly associated with, and predictive of, phonological decoding ability. In contrast, the same individuals showed normal patterns of stress based priming at magnitudes similar to controls. These results—suggesting reduced phonological awareness in the context of intact phonological representations—are consistent with recent findings reported in the domain of phonemic processing. Implications for the phonological deficit theory of dyslexia are discussed.
Computing Evaporanspiraton from Weather Data Obtained from Distant, Non-Reference Weather Stations in a Hyper-Arid Region

Problem statement: Reference agro-climatic Weather Stations (WS) are rarely found in newly reclaimed areas. The usage of weather data from non-reference WS may lead to inaccurate estimations of Evapo Transpiration (ET), especially if the non-reference stations are distant from the reclaimed location. Approach: Weather data from four WS located at Riyadh were used to calculate ET by using Penman Monteith (PM) and Hargreaves equations. PM equation was applied with both alfalfa and grass reference crops. Calculations were done with and without temperature correction for non-reference weather stations. All calculations were compared with measured lysimeter data and corrections in Hargreaves formula were suggested. Results: (1): Weather data from non-reference WS can be used safely to calculate ET only when temperature corrections are applied. (2) Hargreaves formula underestimates ET at all locations in the study area. By applying the simple linear correction to the data, highly acceptable results are obtainned. (3) The ET ratio between alfalfa and grass in Riyadh is 1.25. Conclusion: The study concluded that temperature correction for non-reference WS is essential to ensure acceptable ET calculations. Usage of Hargreaves formula is recommended with the corrections suggested in the study due to its simplicity.
Evidence Sources, Methods and Use Cases for Learning Lightweight Domain Ontologies

By providing interoperability and shared meaning across actors and domains, lightweight domain ontologies are a cornerstone technology of the Semantic Web. This chapter investigates evidence sources for ontology learning and describes a generic and extensible approach to ontology learning that combines such evidence sources to extract domain concepts, identify relations between the ontology’s concepts, and detect relation labels automatically. An implementation illustrates the presented ontology learning and relation labeling framework and serves as the basis for discussing possible pitfalls in ontology learning. Afterwards, three use cases demonstrate the usefulness of the presented framework and its application to real-world problems.
Use of MM5 model for weather forecasting over Bangladesh region

The severity of weather appears almost every year in Bangladesh. It causes damage of property and takes a very high death toll due to absence of timely and proper forecasting facility. Thus the focus of this paper is to demonstrate the usefulness of weather model for forecasting and estimating convective system. A high resolution mesoscale model MM5 has been used in this regard to observe the accurate rainfall estimation over Bangladesh. The model is run at two nested domains at 45 km and 15 km resolutions for two durations i.e. 31 March to 05 April 2002 and 20 to 25 May 2002. In both the cases, results indicate that the MM5 model has a good capability to estimate rainfall over Bangladesh.
Hybrid poly(lactic acid)/nanocellulose/nanoclay composites with synergistically enhanced barrier properties and improved thermomechanical resistance

: Poly(lactic acid) (PLA)-based hybrid nanocomposites (PLA, nanoclay and nanocellulose) were prepared by reinforcing neat PLA with commercially available nanoclay (Cloisite C30B) and nanocellulose, in the form of either partially acetylated cellulose nanofibres (CNF) or nanocrystalline cellulose (CNC). Composites with 1 or 5 wt% of nanocellulose, in combination with 1, 3 and 5 wt% of nanoclay, were prepared, and their barrier properties were investigated. It was found that the combination of clay and nanocellulose clearly results in synergistic behaviour in terms of the oxygen transmission rate (OTR) through a reduction of up to 90% in OTR and a further reduction in the water vapour transmission rate (WVTR) of up to 76%. In addition, the nanocomposite films showed improved thermomechanical resistance and improved crystallisation kinetics while maintaining high film transparency. This makes hybrid PLA/CNF/C30B nanocomposites a very promising material for food packaging applications. mL µm m -2 day -1 25°C and different relative humidities 420 g µm m -2 day -1 at 23°C and RH , while PLA an OTR from mL 23°C and a WVTR of g µm m -2 day at and RH and until they reached 200°C 10°C/min. Optical properties were measured at at least three different points using a UV-Vis spectrometer (Polar Star Omega) in the range of 200 nm – 1000 nm. The oxygen transmission rate (OTR) was measured in triplicate, using a Lyssy OPT-5000 oxygen permeability tester. OTR measurements were performed at 23°C at 0% and 50% of RH, and the results were expressed in mL