Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Cassava ( Manihot Esculenta Crantz) variety, drying process and blending ratio on the proximate composition and sensory properties of Cassava- Wheat composite bread

The use of composite cassava-wheat flour for commercial bread making purposes and consumption of composite cassava-wheat bread are relatively new in Ethiopia. This experiment was conducted to explore the effects of cassava variety, drying methods and blending ratio on chemical compositions and sensory properties of cassava-wheat composite bread. Two levels of cassava varieties (Qulle and Kello), two levels of drying methods (sun and oven) and three levels of blending ratio (11.12g, 25.00 g and 42.90 g of cassava in 100 g of control wheat flour) were used and the treatments were factorial arranged in complete randomized design with three replications. Blending with Qulle and Kello varieties had reduced crude protein content to 9.18 and 8.84 %, respectively as compared to the protein content (10.05 %) in the control (100% wheat bread). Similarly, the crude fat dropped to 1.18 -and 1.12 % from 2.33%, the crude fiber increased to 2.05 and 2.03 % from 1.17 %, the carbohydrate (%) increased to 80.13 and 81.10 from 77.33, the ash increased to 2.21 and 2.10 % relative to 1.82 % in wheat bread. No significant (P>0.05) differences were detected in proximate compositions attributed to the two drying methods. With increase in blending ratio the carbohydrate, the crude fiber and the ash contents increased whereas the protein content decreased significantly (P 0.05) differences were observed in overall acceptability of the composite breads due to varieties and drying methods. However, as the blending ratio increased the overall acceptability dropped significantly (P<0.05). It could be concluded that the substitution of cassava flour with wheat flour in bread making with substitution level up to 25 g in 100g wheat flour did not adversely affect the quality properties of the bread and produce bread comparable to that produced from wheat flour in the proximate compositions and sensory acceptability. Further studies are required to investigate the impacts of anti-nutrients and storage period on cassava-wheat composite bread.
Optimal Control Based on Meshfree Approximations

In dieser Arbeit werden Optimalsteuerungsprobleme unter Anwendung von gitterfreien Methoden (Partikelmethoden) untersucht. Nach einer kurzen Einführung in die Funktionalanalysis für die optimale Steuerung und einer Einfühung in Partikelmethoden, wird die Optimierung von 1D hyperbolischen Gleichungen unter Nutzung einer Delta-Approximation untersucht. Es werden die Optimierungsstrategien "erst optimieren, dann diskretisieren" und "erst diskretisieren, dann optimieren" betrachtet. Zusätzlich ist in Hinblick auf Partikelmethoden noch der Fall "erst transformieren, dann optimieren, dann diskretisieren" von Interesse. Die Äquivalenz aller Ansätze, bis auf die Approximationsgenauigkeit, wird sowohl analytisch als auch numerisch gezeigt.
Two-Temperature Green and Naghdi Model on Thermoelastc Interaction in an Infinite Fibre-Reinforced Anisotropic Plate Containing a Circular Hole

Abstract The present work is aimed at the study of thermoelastic interactions in an infinite fibre-reinforced anisotropic plate containing a circular hole in the context of a theory of generalized thermoelasticity in which the theory of heat conduction in deformable bodies depends on two different temperatures - conductive temperature and dynamic temperature. The two-temperature generalized thermoelastic model and one-temperature generalized thermoelastic model are formulated on the basis of Green and Naghdi theory of type II (2TGNII). The circular hole surface is assumed to be stress free and is subjected to a thermal shock. The problem is solved numerically using a finite element method. The effects of the presence and absence of reinforcement on the conductive temperature, the dynamical temperature, the stresses and the displacement distributions are studied. A comparison is made with the results predicted by the two theories. Results carried out in this paper can be used to design various fibre-reinforced anisotropic elements under thermal load to meet special engineering requirements.
Upper ocean vertical supply: A neglected primary factor controlling the distribution of neodymium concentrations of open ocean surface waters?

Neodymium (Nd) isotopes are an important geochemical tool to trace the present and past water mass mixing as well as continental inputs. The distribution of Nd concentrations in open ocean surface waters (0–100 m) is generally assumed to be controlled by lateral mixing of Nd from coastal surface currents and by removal through reversible particle scavenging. However, using 228Ra activity as an indicator of coastal water mass influence, surface water Nd concentration data available on key oceanic transects as a whole do not support the above scenario. From a global compilation of available data, we find that more stratified regions are generally associated with low surface Nd concentrations. This implies that upper ocean vertical supply may be an as yet neglected primary factor in determining the basin-scale variations of surface water Nd concentrations. Similar to the mechanism of nutrients supply, it is likely that stratification inhibits vertical supply of Nd from the subsurface thermocline waters and thus the magnitude of Nd flux to the surface layer. Consistently, the estimated required input flux of Nd to the surface layer to maintain the observed concentrations could be nearly two orders of magnitudes larger than riverine/dust flux, and also larger than the model-based estimation on shelf-derived coastal flux. In addition, preliminary results from modeling experiments reveal that the input from shallow boundary sources, riverine input, and release from dust are actually not the primary factors controlling Nd concentrations most notably in the Pacific and Southern Ocean surface waters.
The Challenge of Global Selective Outsourcing Environment: Implementing Customer-Centric IT Service Operations and ITIL Processes

Presently, internal Information Technology (IT) organizations make strategic level decisions to explore new capabilities and solutions from outsourcing markets to fulfill various business and customer expectations. However, far too little is known about the operational level challenges that emerge between IT service purchasing companies and suppliers in a global selective outsourcing environment. In this research, we focus on analyzing the operational level challenges and nonconformances from the IT service purchasing company’s point-of-view. Nokia’s IT unit selectively outsourced parts of its operational level IT service activities to the supplier. The IT unit and the supplier jointly implemented Information Technology Infrastructure Library (ITIL) processes, globally. The cooperation was not completely trouble-free. It was identified that ITIL processes can provide standardized structures for executing the IT service activities, but quality and customer-centric operation will also require active and participative management and leadership, efficient communication and information sharing, globally implemented quality management practices, and clear responsibility and ownership structures between the parties. These findings improve operational level selective outsourcing knowledge, and the findings can be exploited by other global IT service transition projects.
Compound Glass Microsphere Resonator Devices

In recent years, compound glass microsphere resonator devices have attracted increasing interest and have been widely used in sensing, microsphere lasers, and nonlinear optics. Compared with traditional silica resonators, compound glass microsphere resonators have many significant and attractive properties, such as high-Q factor, an ability to achieve high rare earth ion, wide infrared transmittance, and low phonon energy. This review provides a summary and a critical assessment of the fabrication and the optical characterization of compound glasses and the related fabrication and applications of compound glass microsphere resonators.
SGR: Self-Supervised Spectral Graph Representation Learning

Representing a graph as a vector is a challenging task; ideally, the representation should be easily computable and conducive to efficient comparisons among graphs, tailored to the particular data and analytical task at hand. Unfortunately, a "one-size-fits-all" solution is unattainable, as different analytical tasks may require different attention to global or local graph features. We develop SGR, the first, to our knowledge, method for learning graph representations in a self-supervised manner. Grounded on spectral graph analysis, SGR seamlessly combines all aforementioned desirable properties. In extensive experiments, we show how our approach works on large graph collections, facilitates self-supervised representation learning across a variety of application domains, and performs competitively to state-of-the-art methods without re-training.
Heat transfer in an oscillatory gas flow inside a parallel-plate channel with imposed axial temperature gradient

Understanding of heat transfer process es between a solid boundary and an oscillatory gas flow is important for the design of internal components such as heat exchangers, regenerators and thermal buffer tubes in thermoacoustic and Stirling thermodynamic machines where the flow oscillations are part of the power production or transfer processes. The heat transfer between the flow and an arrangement of hot and cold plates forming a parallel-plate channel is studied experimentally an d numerically. Here, the particular focus is on the processes occurring within the thermal and viscous boundary layers. The measured phase-dependent temperature fields combined with the velocity fields are studied in detail. Near wall temperature minima and maxima of the cross sectional temperature profiles are observed when the gas moves from cold to hot or from hot to cold parts of the channel. They are referred to as "temperature undershoot" and "overshoot", respectively. The existence of these temperature minima and maxim causes large local temperature gradients in the direction normal to the wall, which result in large heat diffusion between gas layers in the direction normal to the wall. It is observed that the flow history has a strong impact on the temperature fields. This invalidates the so-called "Iguchi hypothesis", based on which the heat transfer data for steady flows is being applied to oscillatory flow conditions. General guidelines for the design of heat exchangers used in thermoacoustic devices are discussed.
Multimodel Ensemble Forecasts for Weather and Seasonal Climate

Abstract In this paper the performance of a multimodel ensemble forecast analysis that shows superior forecast skills is illustrated and compared to all individual models used. The model comparisons include global weather, hurricane track and intensity forecasts, and seasonal climate simulations. The performance improvements are completely attributed to the collective information of all models used in the statistical algorithm. The proposed concept is first illustrated for a low-order spectral model from which the multimodels and a “nature run” were constructed. Two hundred time units are divided into a training period (70 time units) and a forecast period (130 time units). The multimodel forecasts and the observed fields (the nature run) during the training period are subjected to a simple linear multiple regression to derive the statistical weights for the member models. The multimodel forecasts, generated for the next 130 forecast units, outperform all the individual models. This procedure was deployed.
General high-order rogue wave to NLS-Boussinesq equation with the dynamical analysis

General high-order rogue waves of the NLS-Boussinesq equation are obtained by the KP-hierarchy reduction theory. These rogue waves are expressed with the determinants, whose entries are all algebraic forms. It is found that the fundamental rogue waves can be classified three patterns: four-petals state, dark state, bright state by choosing different parameter $\alpha$ values. As the evolution of the parameter $\alpha$. An interesting phenomena is discovered: the rogue wave changes from four-petals state to dark state, whereafter to the bright state, which are consistent with the change of the corresponding critical points to the function of two variables. Furthermore, the dynamics of second-order and third-order rogue waves are presented in detail, which can be regarded as the nonlinear superposition of the fundamental rogue waves.
Particle modeling of semiconductor quantum devices

With the scaling down of semiconductor device deeply into the sub-0.lpm region, it is increasingly important to take quantum mechanical effects of carrier transport into account in device simulation. However, it is difficult to simulate practical devices where clear semi-classical and quantum features coexist, as is the case for nanoscale devices at normal temperatures. In this paper, we present a particle description of quantum phenomena based upon a quantum force derived from the Wigner's transport formalism. The quantum force can be incorporated into the driving force term of the Boltzmann transport equation, which enables us to utilize the well-developed particle Monte Carlo computational techniques. We demonstrate that the quantum transport effects such as quantum tunneling and energy quantization are incorporated in the standard Monte Carlo technique.
Precise Temporal Disaggregation Preserving Marginals and Correlations (DiPMaC) for Stationary and Nonstationary Processes

Hydroclimatic variables such as precipitation and temperature are often measured or simulated by climate models at coarser spatiotemporal scales than those needed for operational purposes. This has motivated more than half a century of research in developing disaggregation methods that break down coarse‐scale time series into finer scales, with two primary objectives: (a) reproducing the statistical properties of the fine‐scale process and (b) preserving the original coarse‐scale data. Existing methods either preserve a limited number of statistical moments at the fine scale, which is often insufficient and can lead to an unrepresentative approximation of the actual marginal distribution, or are based on a limited number of a priori distributional assumptions, for example, lognormal. Additionally, they are not able to account for potential nonstationarity in the underlying fine‐scale process. Here we introduce a novel disaggregation method, named Disaggregation Preserving Marginals and Correlations (DiPMaC), that is able to disaggregate a coarse‐scale time series to any finer scale, while reproducing the probability distribution and the linear correlation structure of the fine‐scale process. DiPMaC is also generalized for arbitrary nonstationary scenarios to reproduce time varying marginals. Additionally, we introduce a computationally efficient algorithm, based on Bernoulli trials, to optimize the disaggregation procedure and guarantee preservation of the coarse‐scale values. We focus on temporal disaggregation and demonstrate the method by disaggregating monthly precipitation to hourly, and time series with trends (e.g., climate model projections), while we show its potential to disaggregate based on general nonstationary scenarios. The example applications demonstrate the performance and robustness of DiPMaC.
Improved Albedo Estimates Implemented in the METRIC Model for Modeling Energy Balance Fluxes and Evapotranspiration over Agricultural and Natural Areas in the Brazilian Cerrado

In this study we assessed METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model performance to estimate energy balance fluxes and evapotranspiration (ET) in two heterogeneous landscapes in the Brazilian Cerrado, including fluxes and ET in both agricultural and natural vegetation. The estimates were evaluated by comparing them to flux tower data collected over sugarcane (USR site), woody savanna (PDG site) and stricto-sensu savanna (RECOR site) areas. The selection of the study years (2005–2007 for USR/PDG sites and 2011–2015 for RECOR site) was based on the availability of meteorological data (to be used as inputs in METRIC) and of flux tower data for energy balance fluxes and ET comparisons. The broadband albedo submodel was adjusted in order to improve Net Radiation estimates. For this adjustment, we applied at-surface solar radiation simulations obtained from the SMARTS2 model under different conditions of land elevation, precipitable water content and solar angles. We also tested the equivalence between the measured crop coefficient (Kc_ec) and the reference evapotranspiration fraction (ETrF or F), seeking to extrapolate from instantaneous to daily values of actual evapotranspiration (ETa). Surface albedo was underestimated by 10% at the USR site (showing a better performance for full crop coverage), by 15% at the PDG site (following the woody savanna dynamics pattern through dry and wet seasons) and was overestimated by 21% at the RECOR site. METRIC was effective in simulating the spatial and temporal variability of energy balance fluxes and ET over agricultural and natural vegetation in the Brazilian Cerrado, with errors within those reported in the literature. Net radiation (Rn) presented consistent results (coefficient of determination (R2) > 0.94) but it was overestimated by 8% and 9% in sugarcane and woody savanna, respectively. METRIC-derived ET estimates showed an agreement with ground data at USR and PDG sites (R2 > 0.88, root mean square error (RMSE) up to 0.87 mm day−1), but at the RECOR site, ET was overestimated by 14% (R2 = 0.96, mean absolute error (MAE) = 0.62 mm.day−1 and RMSE = 0.75 mm day−1). Surface energy balance fluxes and ET were marked by seasonality, with direct dependence on available energy, rainfall distribution, soil moisture and other parameters like albedo and NDVI.
INTERACTIVE TRAINING SOFTWARE FOR OPTIMUM TRAVEL ROUTE ANALYSIS APPLICATIONS IN RAILWAY NETWORKS

Optimum travel route analysis applications are so important in railway networks. Especially, itinerary for the passangers and route and duration planning for the trainload. On the other hand, process of route optimization is one of the basic applications of Network Analyses in Geographic Information Systems too. In mathematical background of network analysis applications are graph theory and graph algorithms. Primary graph algorithm employed in process of route optimization is Dijkstra’s Algorithm. Dijkstra’s Algorithm is placed on the top of linear methods which yield exact solutions. Geographic Information Systems analyses such as the shortest route, the shortest duration and route with the least waiting period etc are solved through Dijkstra’s Algorithm. In this study, an interactive training software program, developed for educational use in Railway applications within GIS and Graph Theory is introduced. This software provides the opportunity to use Dijkstra’s Algorithm on graphs which they have designed by the user and teaches details of algorithm, its working principles and structure of data to them, step by step, through interactive messages and graphics.
Results of Laboratory Tests not Accessed in Brazilian Private Laboratories.

BACKGROUND Laboratory medicine is an important part of the healthcare system and directly contributes to preventive actions, diagnostics, treatment, and management of diseases. The level and quality of the utilization of laboratory resources have been frequently questioned. A dissemination of conflicting data regarding the quantity of laboratory tests not accessed by the requesting doctors or by the patients themselves is observed, although very often the sources and methodologies used to raise those numbers are not properly clarified. The objective of this study was to obtain data about access to results of tests taken in Brazilian private clinical analysis laboratories which use the laboratory information system developed by SHIFT Consultoria e Sistemas. METHODS Information was extracted from 81 laboratories, which were responsible for the performance of 93,240,651 tests, collected from 7,067,087 patients. RESULTS The total number of tests not accessed, considering all the regions, was 5,071,454, corresponding to a proportion of 5.4%. In the face of the potential risks of adverse events or impacts in the management of diagnostics and treatments, including economic impacts due to prolonged hospitalization time, the proportion of 17.9% which was found corresponding to tests "not accessed" showing "abnormal" results, is worrisome, mainly if we observe that of those, 2.5% were related to "abnormal" test results processed by laboratories which work in hospital care. CONCLUSIONS SBPC/ML, in face of the relevance of the theme, will keep stimulating the monitoring and utilization of adequate laboratory resources, in order to allow sustainable healthcare systems.
Strategic planning of electric logistics eet networks : A robust location routing approach Working

We present a robust location routing approach that considers simultaneous decisions on routing vehicles and locating charging stations for strategic network design of electric logistics eets. In this approach, we consider uncertain customer patterns with respect to the spatial customer distribution, demand, and service time windows. To solve large sized instances as well as instances considering a high number of scenarios, a (parallelized) adaptive large neighbourhood search is presented. We derive new benchmark instances for the proposed problem class with di erent degrees of uncertainty and evaluate the performance of our algorithm. Results are presented for a real-world application case and are compared to results of di erent deterministic modeling approaches. Based on these results, the bene t of a robust planning approach with regard to operational feasibility and savings in overall costs is analyzed for the underlying planning problem, and managerial insights are derived.
A reliable decision support system for fresh food supply chain management

The paper proposes a decision support system (DSS) for the supply chain of packaged fresh and highly perishable products. The DSS combines a unique tool for sales forecasting with order planning which includes an individual model selection system equipped with ARIMA, ARIMAX and transfer function forecasting model families, the latter two accounting for the impact of prices. Forecasting model parameters are chosen via two alternative tuning algorithms: a two-step statistical analysis, and a sequential parameter optimisation framework for automatic parameter tuning. The DSS selects the model to apply according to user-defined performance criteria. Then, it considers sales forecasting as a proxy of expected demand and uses it as input for a multi-objective optimisation algorithm that defines a set of non-dominated order proposals with respect to outdating, shortage, freshness of products and residual stock. A set of real data and a benchmark – based on the methods already in use – are employed to evaluate the performance of the proposed DSS. The analysis of different configurations shows that the DSS is suitable for the problem under investigation; in particular, the DSS ensures acceptable forecasting errors and proper computational effort, providing order plans with associated satisfactory performances.
End-to-End Network Topology Generation

Motivated by the desire to generate topologies which take into account the dynamic failure and growth of the Internet nodes and links, we identify the need for high quality, multi-scale, end-to-end network topology generators. After examining a number of commonly used generators and comparing their output with data sources available at wide area (AS level), ISP (IP routing level) and enterprise networks, we are developing a mechanism for synthetically generating topologies which are able to represent networks across multiple scales. We are extending this work to include the dynamic evolution of networks.