Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain Heuristic Fusion of Multi-Word Embeddings for Nutrient Value Prediction

Being both a poison and a cure for many lifestyle and non-communicable diseases, food is inscribing itself into the prime focus of precise medicine. The monitoring of few groups of nutrients is crucial for some patients, and methods for easing their calculations are emerging. Our proposed machine learning pipeline deals with nutrient prediction based on learned vector representations on short text–recipe names. In this study, we explored how the prediction results change when, instead of using the vector representations of the recipe description, we use the embeddings of the list of ingredients. The nutrient content of one food depends on its ingredients; therefore, the text of the ingredients contains more relevant information. We define a domain-specific heuristic for merging the embeddings of the ingredients, which combines the quantities of each ingredient in order to use them as features in machine learning models for nutrient prediction. The results from the experiments indicate that the prediction results improve when using the domain-specific heuristic. The prediction models for protein prediction were highly effective, with accuracies up to 97.98%. Implementing a domain-specific heuristic for combining multi-word embeddings yields better results than using conventional merging heuristics, with up to 60% more accuracy in some cases.
Climate and Landscape Controls on the Water Balance in Temperate Forest Ecosystems: Testing Large Scale Controls on Undisturbed Catchments in the Central Appalachian Mountains of the US

The long‐term water balance of catchments is given by precipitation partitioned into either runoff or evaporation. Understanding precipitation partitioning controls is a critical focus of hydrology and water resources management. A useful theoretical framework that serves their understanding is the Budyko Framework. Our purpose is to understand how Budyko's n parameter is related to different controls and what is its relevance to precipitation partitioning. We investigated the relative importance of the dryness index and the Budyko parameter for precipitation partitioning, then applied partial correlation analysis and multivariate regressions to find out which were the principal partitioning controls. We focused our research in the central Appalachian mountains located in the eastern United States, considered as water towers to metropolitan areas in the eastern and mid‐western US (e.g., Pittsburgh, Washington DC), and selected a set of catchments characterized by minimal human disturbance and with large proportions of temperate forests. We found that climate controls such as mean annual temperature and fraction of precipitation falling in the form of snow exert a higher influence on partitioning than landscape controls (e.g., forest cover, Normalized Difference Vegetation Index, and slope). Thus, the importance of vegetation as a primary driver of partitioning could not be confirmed based on regional or basin‐wide characteristics. On the other hand, the influence of topography, and elevation in particular, was highly ranked as important. Our study highlights that partitioning controls could differ between basins in the same climate region, especially in a complex, mountainous topography setting.
Manipulation of CNT by using optically-induced dielectrophoresis

This paper reports a technique for manipulation of carbon nanotubes (CNTs). A photoconductive layer capable of generating a non-uniform electric field at illuminated sites was used to optically induce dielectrophoretic forces for manipulating CNTs. The light patterns enabled a variety of flexible modes for CNT manipulation since it was possible to dynamically reconfigure the optical patterns. This approach can achieve a variety of manipulation and patterning of CNTs. The developed method may be promising for patterning of CNTs-based nano-sensors.
A new hierarchical temporal memory based on recurrent learning unit

ABSTRACT Hierarchical temporal memory is an emerging machine learning technology that aims to model the structural and algorithmic properties of the neocortex. It is particularly suitable for learning and predicting sequential data. However, when dealing with long time series or complex sequences, the accuracy is relatively lower than desired. In this paper, a novel hierarchical temporal memory based on recurrent learning unit is proposed, where a feedback mechanism is involved into the model. The original cell is extended with a recurrent unit to capture long temporal dependencies of synaptic connections between neurons. The temporal pooler algorithm is then modified to adapt to the recurrent learning unit, and the supervised gradient information is combined with the Hebbian synaptogenesis learning rule in speeding up the training. The prototype of the proposed hierarchical temporal memory is implemented and extensive experiments are carried out on two public datasets under various settings. Experimental results show that the proposed model obtains an accuracy increase by up to 32% and a perplexity drop by up to 14% on sequence prediction and text generation tasks, respectively, which indicates the hierarchical temporal memory with recurrent feedback outperforms the original model on sequence learning.
Semantic Segmentation With Attention Mechanism for Remote Sensing Images

Semantic segmentation for high-resolution remote sensing images is one of the most significant tasks in the field of remote sensing applications. Remote sensing images contain substantial detailed information of ground objects, such as shape, location, and texture. Therefore, these objects make the images exhibit large intraclass variance and small interclass variance, which makes it very difficult to be recognized. In this study, an end-to-end attention-based semantic segmentation network (SSAtNet) is proposed. A pyramid attention pooling module is proposed to introduce the attention mechanism into the multiscale module for adaptive features refinement. To correct the detailed information, the pooling index correction module integrates pooling index maps from the encoder with high-level feature maps, which can help recover the fine-grained features. In the encoder phase, a more effective ResNet-101 backbone is designed to capture detailed features. What is more, a series of data augmentation methods are proposed to enhance the model’s robustness. The proposed model is compared with several previous advanced networks and achieves the state of the art on the ISPRS Vaihingen dataset. The experiment results prove the effectiveness of the SSAtNet.
Occult hepatitis B virus infection and the risk of hepatocellular carcinoma: a systematic review and meta-analysis

Duke-NUS Medical School, Singapore; Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore; Medicine Academic Clinical Program, Duke-NUS Medical School, Singapore; Center of Quantitative Medicine, Duke-NUS Medical School, Singapore Contributions: (I) Conception and design: C Weng, R Kumar, R Sultana, WC Chow; (II) Administrative support: C Weng; (III) Provision of study materials or patients: C Weng, R Kumar; (IV) Collection and assembly of data: C Weng, R Kumar; (V) Data analysis and interpretation: C Weng, R Sultana; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. Correspondence to: Rajneesh Kumar. Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore 169608, Singapore. Email: Rajneesh.kumar@singhealth.com. sg.
Effect of sodium dodecyl benzene sulfonate (SDBS) on the performance of anaerobic co-digestion with sewage sludge, food waste, and green waste

Abstract The anionic detergent sodium dodecyl benzene sulfonate (SDBS) inhibits anaerobic solid waste fermentation process in mesophilic anaerobic digesters. In this study, the effect SDBS on the performance of anaerobic digestion (AD) of mixture of sewage sludge, food waste, and green waste serving as substrate was investigated. The batch experiments were conducted with five SDBS concentrations namely 0, 0.01, 0.02, 0.05, 0.1, and 0.2 g/g (SDBS/dry sludge) under mesophilic condition (37 ± 1 °C) and lasted for 63 days. The results showed that the presence of SDBS remarkably increased the release of protein and carbohydrate, and resulting in the serious accumulation of volatile fatty acids (VFAs), especially for propionate accumulation. Likewise, the observed variations in enzyme activities associated with different stage of AD revealed that methanogenesis was quite sensitive to SDBS and inhibited by the increase of SDBS addition. Meanwhile, the presence of SDBS decreased the pH value and the concentration of free ammonia, but increased the concentration of NH4+-N. Furthermore, the production of biogas was reduced by SDBS. In conclusion, SDBS addition has a negative impact on anaerobic co-digestion. On the one hand, methanogens were severely inhibited and biogas yield decreased remarkably, on the other hand, the accumulation of VFAs was excessive. Thus, the presence of surfactant (SDBS) in the municipal organic waste should be concerned during the waste disposal via anaerobic digestion process.
Functionalising lignin in crude glycerol to prepare polyols and polyurethane

In this work, crude glycerol liquefaction of lignins produced in the pulp and paper industry, as well as an organosolv lignin (sugarcane bagasse), was studied with the ultimate aim of preparing bio-based polyols for polyurethane (PU) preparation. This is a proposed strategy to valorise the by-products of biodiesel and lignocellulose biorefineries. Size-exclusion chromatography revealed that the lignins behave differently during liquefaction based on a ranging product molecular weight (MW). The MW of the liquefaction products was concluded to be related to the phenolic and aliphatic hydroxyl group content of the respective lignins, as well as the removal of glycerol and monoacylglycerol during liquefaction. Lignin was modified to yield mostly a solid-phase product. Fourier transform infrared spectroscopy suggests that crude glycerol constituents like glycerol and fatty acid esters are bound to lignin during liquefaction through formation of ether and ester bonds. Liquefaction yield further also varied with lignin type. The liquefaction products were effectively employed as bio-based polyols to prepare PU.
Benefits of Legume Species in an Agroforestry Production System of Yellow Pitahaya in the Ecuadorian Amazon

Agroforestry systems have become an alternative that promotes the conservation of natural resources and the sustainable production of fruit crops in the Ecuadorian Amazon. However, it is required to demonstrate the benefit of the companion species that make up these production systems. The objective of this research was to determine how the legume species within an agroforestry system influence the yield of yellow dragon fruit (pitahaya), carbon sequestration and nutritional contribution. The experiment was carried out in Palora (province of Morona Santiago) and organized in a randomized complete block design with three replications. The treatments were two agroforestry arrangements and the monoculture as a control treatment. Erythrina poeppigiana, Gliricidia sepium and Flemingia macrophylla were used in the agroforestry arrangements for the contribution of biomass. Results showed that during the five years of study, pitahaya yield was influenced by the quality of the leaf litter (biomass) incorporated in to the fruit crop. Biomass from E. poeppigiana and F. macrophylla as companion crops contributed a greater amount of Ca and Mg, increased C sequestration and crop yield. The results suggest that the use of legume species in agroforestry systems positively affects pitahaya productivity, enabling sustainable agriculture in the Ecuadorian Amazon.
Rail potential control with train diagram optimization in multitrain DC traction power system

ABSTRACT Currently, abnormally elevated rail potential exists in the DC traction power system, which greatly threatens the safe operation of the line. In order to realize the reflux safety, timetable optimization of multitrain based on improved Seeker Optimization Algorithm (SOA) is proposed to suppress the rail potential of the system. Firstly, the simulation model of the system is built and the calculation process of rail potential is proposed. Secondly, an optimization model based on maximum rail potential is formulated, where the dwell time is the decision variable and is adjusted to change the regenerative power distribution of the system. Finally, the improved SOA is used to handle the optimization model. Compared with the maximum rail potential before optimization, the simulation results demonstrate that the maximum rail potential is reduced by 55.5% with the proposed method, which greatly improves the reflux safety of the multi-train subway system.
Green Synthesis of Metal Nanostructures and Its Nonlinear Optical Properties

Simple green synthesis of metal nanoparticles (Ag NPs) was prepared by using Raphanussativus leaf extract. This extract acts as reduce and stabilizing agent. The formation of silver NPs was confirmed and characterized by XRD, UV–visible absorption spectrum, TEM, and FTIR. The luminescence enhancement and quenching of Eu3+and Sm3+ ions were observed in the presence of silver NPs. The luminescence enhancement is owing to arise in the electric-dipole transition with alteration of the field around Ln3+ ions. Nonlinear studies in femtosecond (fs) and picosecond (ps) time scales have been studied by using the Z-scan technique. Third-order nonlinear optical susceptibility of silver nanoparticles was obtained with Degenerate Four-Wave Mixing (DFWM) in the fs regime. The lifetimes of lanthanum complexes were increased by the concentration of silver NPs and decreased for further silver. The high enhanced luminescence and nonlinear studies of green synthesized silver nanoparticles can be used in optics and bio applications.
Preliminary evidence of an endangered species benefiting from moderate climate warming: A palaeolimnological study of the charophyte
 Lychnothamnus barbatus

1. In a time of rapid environmental changes, identification of the effects of climate warming on charophytes (Characeae, Charophyta) will enable the optimization of conservation measures, especially for extremely rare species. Lychnothamnus barbatus is one of the rarest charophytes worldwide, which has decreased in the number of occupied sites over the last century. However
Optimization of Rutin-Loaded PLGA Nanoparticles Synthesized by Single-Emulsion Solvent Evaporation Method

Bioactive rutin molecule has high-volume applications in food and pharmaceutical products. A considerable problem is its poor water solubility and low bioavailability. In this study, propylene glycol was first used as in the literature to dissolve rutin molecule while entrapping it into poly(d,l-lactide-co-glycolide) nanoparticles by oil-in-water single-emulsion solvent evaporation method. The reason of using propylene glycol is to improve rutins’ low bioavailibility and to determine the optimized nanoparticles. For this reason, various encapsulation parameters were tested and their effects were analyzed. Then, NP4 (hydrodynamic particle size: 252.6 ± 2.854 nm)-optimized nanoparticle with 47% reaction yield and 81% encapsulation efficiency was determined. In vitro % cumulative releases of rutin from optimum NP4 in two different concentrations (0.5 and 1 mg/mL) were examined. NP4 with 0.5 mg/mL concentration reached 100% release on the 5th day (120 h). Optimum rutin-loaded nanoparticles are expected to be .
A parallel hardware hypervisor for hardware‐accelerated cloud computing

Hardware‐accelerated cloud computing systems based on FPGA or ASIC chips have proved useful in providing power‐efficient acceleration for a variety of software applications. However, these computing systems rely on operating systems and hypervisors, which not only are implemented with inefficient software, but which also are incapable of handling massively parallel systems, due to the lack of parallelism and scalability in their algorithmic designs. As a result, power, performance, and scalability problems will emerge in an exascale cloud computing environment. As a solution to these problems, the present study proposes a parallel hardware hypervisor system implemented entirely in special‐purpose hardware without resorting to energy‐inefficient general‐purpose processors. Furthermore, the proposed hypervisor system virtualizes application‐specific multi‐chip supercomputers, in order to enable the virtual supercomputers to share available FPGA and semi‐configurable ASIC resources in a cloud system. Single‐chip verification studies based on Verilog simulation have been done to verify the functional correctness of the proposed hardware hypervisor system, which consumes only a fraction of hardware resources. This article will in particular focus on the virtualization of multi‐chip message‐passing based supercomputers using limited reconfigurable hardware resources.
On the Regionality of Moist Kelvin Waves and the MJO: The Critical Role of the Background Zonal Flow

A global model with superparameterized physics is used to shed light on the observed regionality of convectively coupled Kelvin waves and the Madden‐Julian Oscillation (MJO). A series of aquaplanet simulations over zonally uniform sea‐surface temperatures is performed, in which the axisymmetric structure of the background zonal flow [u¯] is altered through nudging, while maintaining a quasi‐fixed rainfall climatology. Results show that nudging [u¯] at the equator to match profiles typical of the Indo‐Pacific or eastern Pacific sectors yields eastward‐moving tropical rain spectra typical of those sectors. Two different mechanistic pathways are identified as being responsible for this mean‐flow dependence, in addition to Doppler shifting effects. The first is through shifts of the Rossby wave critical line in the subtropical upper troposphere that affect the lateral forcing of Kelvin‐mode circulations at the equator by eastward and equatorward‐propagating eddies impinging on the tropics from higher latitudes. The second is through changes in the strength of the mean cyclonic shear in the lower tropical troposphere that affect the degree to which intraseasonal fluctuations in Kelvin‐mode zonal winds modulate the activity of higher‐frequency equatorial Rossby‐type eddies. In cases where the mean low‐level cyclonic shear is enhanced, the strength of this modulation, referred to as “shear‐induced eddy modulation” or SIEM, is also seen to be enhanced, such that MJO‐like modes of variability are rendered either unstable or near neutral, depending on the strength of the shear.
Proposal and demonstration of controllable Q factor in directly coupled microring resonators for optical buffering applications

Optical resonators with controllable Q factors are key components in many areas of optical physics and engineer-ing. We propose and investigate a Q -factor controllable system composed of two directly coupled microring resonators, one of which is tunable and coupled to dual waveguides. By shifting the resonance of the controllable microring, the Q factor of the system as well as the other microring changes significantly. We have demonstrated wide-range controllable Q factors based on this structure in silicon-on-insulator, for example. The influences of spectral detuning and coupling strength between two resonators on the variation of Q factors are studied in detail experimentally. Then, we explore its applications in optical buffering. Tunable fast-to-slow/slow-to-fast light has been carried out by switching the system between the high- Q state and low- Q state. Moreover, optical pulse capture and release are also achievable using this structure with dynamic tuning, and the photon storage proper-ties are investigated. The proposed Q -factor tunable system is simple, flexible, and realizable in various integrated photonic platforms, allowing for potential applications in on-chip optical communications and quantum information processing.
Maximizing customers' lifetime value using limited marketing resources

PurposeFor any given customer, his/her profitability for a business enterprise can be estimated by the so-called customer lifetime value (CLV). One specific goal for many enterprises consists in maximizing the aggregated CLV associated with its set of customers. To achieve this goal, a company uses marketing resources (e.g. marketing campaigns), which are usually expensive.Design/methodology/approachThis paper proposes a formal model of the Customer Life Value problem inspired by the uncapacitated facility location problem.FindingsThe computational experiments conducted by the authors illustrate the potential of the approach when compared with a standard (non-algorithm-supported) one.Originality/valueThe approach leads up to the economic trade-off between the volume of the employed resources and the aggregated CLV, i.e. the higher the number of resources utilized, but also the higher the cost of achieving this level of lifetime value. Hence, the number of resources to be “activated” has to be decided, and the effect of each of these resources on each CLV will depend upon how “close” the resource is from the corresponding customer (i.e. how large will the impact of the active resource on the customer).
Experiment to determine the specific heat of oils

During machining process cutting fluids are used to minimize the heat that is developed between tool, work piece and the chip. Heat absorption capacity of any cutting fluid used is measured by specific heat. Higher the specific heat better will the heat absorption capacity. This paper discusses the experimental procedure used to measure the specific heat of Neem oil, Honge (Karanja), Sunflower oil and Petroleum based oil (Hydro 68). This experiment is a function of temperature with respect to time. This method is validated by measuring the specific heat of distilled water, since the standard specific heat value of distilled water is known. The results show that Specific Heat of Neem Oil is good compared to Honge and sunflower Oil, but less compared to Petroleum oil (Hydro 68) which is used as cutting fluid for drilling operation in Industries after mixing with water.
EFFCT OF LONG-TERM TREATMENT OF INSULIN ON GROWTH PERFOMANCE, LIPID METABOLISM AND ELECTROLYE IN TILAPIA FIORIDA

Material & methods: Forty Fish, Tilapia florida. were injected with insulin (20 IU/Kg body weight) for different periods. Single dose for 24h and repeated doses (dose every 48 h for 30, 45 and 55 days) were used in this experiment. Body gain, condition factor (CF), hepatosomatic index (HSI) and gut weight were calculated . Levels of total lipids, triglycerides and cholesterol were determined in serum, liver and myotomal muscle. Also, sodium and potassium levels were estimated in both serum and muscle but inorganic phosphorus was determined only in serum. Results: Insulin injection increased significantly body gain (P<0.05) and gut weight (P<0.01). While hepatosomatic index was significantly decreased (P<0.01) in insulin treated group at 30 and 45 days of the experimental periods. The prolonged administration of insulin in Tilapia florida showed a continued effect on the stimulation of lipogenic in the myotomal muscle as well as in the liver triglycerides synthesis. The lowering effect of insulin on liver content of triglycerides but not in the serum. Conclusion: So, it has been suggested that insulin might promote the triglyceride synthesis in liver to be removed as rapidly as synthesized to lipid stores in the body. The increasing effect of insulin on serum and muscle potassium level probably reflect role of such hormone in osmoregulation in this fish.