Miracle-dz/UniFAR-FTUs huggingface dataset:
Duration-differentiated energy services

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Growth and Yield Response of Maize (Zea mays L.) to a Wide Range of Nutrients on Ferralsols of Western Kenya

Declining soil fertility is one of the main causes of low yields of maize. Farmers apply low rates of unbalanced nutrients leading to further nutrient mining. A randomized complete block nutrient omission trial with six replications was therefore set to determine maize response to the application of a wide range of nutrients from inorganic fertilizers on Ferralsols. The treatments were NK, NP, PK, NPK, and NPK + CaMgZnBS. The results showed that application of PK fertilizer resulted in low crop growth rate (CGR), and relative growth rate (RGR), and biomass compared to other treatments. Application of a wider range of nutrients (NPK + CaMgZnBS treatment) improved maize growth and yield compared to other treatments. In terms of grain response, Urea application recorded the highest yield (1800 kg/ha) followed by Triple Superphosphate (1300 kg/ha) then Muriate of potash (1100 kg/ha) and least by a combined application of secondary nutrients and micronutrients (ZnBMgCaS = 400 kg/ha). Highest agronomic efficiency of 32.5 kg grain /kg P applied was recorded due to P followed by K (27.5 kg grain /kg K) and least by N (15 kg grain /kg N). Based on the combined effect, application of N-P-K based fertilizers could give better yields. Use of micronutrients should be assessed further for conclusive recommendations.
Refinement types in Futhark

Among programming languages supporting arrays, there are those that raise runtime errors when an array is indexed out of bounds and those that omit these checks for the sake of performance as dynamic array bound check takes time during execution. Futhark is a programming language designed to target general purpose computing on graphics processing units (GPUs). We propose that extending the Futhark type system with refinement types will allow the programmer to refine a program using types in such a way that array bounds checking can be avoided at runtime. In this thesis we present a small subset of the Futhark language with additional refinement type annotations and a transformation function that transforms programs to an internal language representation. The internal language features explicit polymorphism, dependent quantifiers and refinement types. We also present a set of bidirectional type rules for the internal language and a type checker implemented in Haskell based on the type rules. We have shown that we can refine the types of a small program in such a way that array bounds checks can be safely omitted.
Retrospective Study of the Adverse Drug Reaction/Event Induced by Danshen Injection

Objective To investigate the use of Danshen injection and its adverse drug reation/event(ADR/ADE),and discuss the related factors of ADR/ADE.Methods 322 Danshen injection cases collected by a hospital in Hunan Province have been studied retrospectively.Results have been analyzed by SPSS(version 11.5). Results The majority of Danshen injection ADRs are skin and appendixes damage which account for 46.67%. The nervous system damage accounts for 20.00%. The digestive and skeletal musculature system damage account for 13.33% respectively.The urinary system damage accounts for 6.67%. Conclusion The incidence rate of Danshen injection ADRs/ADEs is high.Clinicians should use reasonably Danshen injection.
Wild mammal dung abundance in Lake Mburo National Park is lower than in adjacent ranchlands

The establishment of livestock ranchlands adjacent to protected areas in savanna ecosystems is believed to threaten wild animals. Intensive competition for vegetative resources, water and poaching are considered to be immediate factors that reduce the capacity of protected areas to sustain wild mammals. The coexistence of wild mammals and ranchlands is common in Southern Africa but has rarely been suggested as a viable conservation option in East Africa. To assess the importance of ranchlands in conserving wild mammals, 36 plots of 20 × 20 m dimension were positioned along a 7240 m stretch from the boundary in Lake Mburo National Park (LMNP) and 36 plots of similar dimension were set within the ranchlands adjacent to the Park. The dung counts of different species recorded in the plots were used as a relative index of mammal abundance in the ranchlands and in LMNP. The results reveal 18 wild mammal species recorded in both sampled areas, 12 within LMNP and 17 in the adjacent ranchlands. The topi Damaliscus lunatus was only found in the park. Total dung count estimated in both ranchlands and LMNP was 2,586 with LMNP accounting for 29% and ranchlands 71%. In terms of wild mammal dung, ranchlands had a higher wild mammal dung count than LMNP (30% higher). The study points to the compatibility of the two land uses in conserving wild mammals and biodiversity in general, negating the common belief of competition and exclusion. Future research is needed on the compatibility of ranchlands with protected areas on biodiversity status of other species.
Human-Centric Data Science for Urban Studies

Due to the wide-spread use of disruptive digital technologies like mobile phones, cities have transitioned from data-scarce to data-rich environments. As a result, the field of geoinformatics is being reshaped and challenged to develop adequate data-driven methods. At the same time, the term "smart city" is increasingly being applied in urban planning, reflecting the aims of different stakeholders to create value out of the new data sets. However, many smart city research initiatives are promoting techno-positivistic approaches which do not account enough for the citizens’ needs. In this paper, we review the state of quantitative urban studies under this new perspective, and critically discuss the development of smart city programs. We conclude with a call for a new anti-disciplinary, human-centric urban data science, and a well-reflected use of technology and data collection in smart city planning. Finally, we introduce the papers of this special issue which focus on providing a more human-centric view on data-driven urban studies, spanning topics from cycling and wellbeing, to mobility and land use.
Determinants of Parental Leave Uptake among Fathers

Fathers in the Nordic countries were among the first in the world to gain the right to paid parental leave. The overall uptake has however been low, despite various attempts to increase it. This paper compares characteristics of fathers in four Nordic countries, to identify important determinants of parental leave uptake. The relationships were tested using logistic regression models. Support for theories regarding household division of labor and household bargaining was found: the socioeconomic position of the father, but also the spouse was positively correlated with the probability of parental leave uptake of the father.
Deep Learning of Inverse Dynamic Models

In the last few years, deep learning has alleviated most fields of machine learning to new levels. However, deep learning has yet to prove its value in the field of model learning in robotics. Currently, dynamics models have to be derived analytically in a tedious process of measuring the mechanical system part by part. In applications like automated industrial production where high precision and reliability are required, robot movements are engineered precisely costing money and time. The reason why the models are not learned may be the fact that data-based approaches lack the physical plausibility of analytical models. In this thesis I propose Deep Lagrangian Network (DeLaN) a deep learning approach to inverse dynamics models. The novelty of DeLaN is the incorporation of a physics prior, the Lagrange-Euler partial differential equation. Thus, DeLaN encodes physical knowledge while facilitating standard model learning advantages, like end-to-end training using data samples. I compare my proposed approach to a standard feed-forward neural network (FF-NN) in various experiments to showcase the usefulness of DeLaN in learning inverse dynamics models online. I am also highlighting advantages and limitations of my approach based on the characteristics inherited from the physics prior. In a nutshell, DeLaN is able to learn and control a real robot and provides capabilities to extrapolate to unseen tasks. Zusammenfassung In den letzten Jahren hat Deep Learning viele Bereiche des Machine Learnings auf neue Ebenen gehoben. Deep Learning muss seinen Wert für Model Learning in der Robotik allerdings noch beweisen. Dynamische Modelle werden aktuell noch in einem aufwendigen Prozess analytisch hergeleitet, wobei das mechanische System Stück für Stück ausgemessen werden muss. In Anwendungen, wie der automatisierten industriellen Produktion, die hohe Präzision und Zuverlässigkeit benötigen, werden Roboterbewegungen präzise von Ingenieuren modelliert, was Zeit und Geld kostet. Der Grund, warum die Modelle aktuell nicht gelernt werden, könnte der Fakt sein, dass datenbasierte Ansätze nicht die physikalische Plausibilität analytischer Modelle bieten. In dieser Arbeit stelle ich Deep Lagrangian Network (DeLaN) vor, einen Deep Learning Ansatz für inverse Dynamik Modelle. Die Neuheit an DeLaN ist die Einbindung einer physikalischen Voraussetzung, der partiellen Lagrange-Euler Differentialgleichung. Damit enkodiert DeLaN physikalisches Wissen und erlaubt gleichzeitig die Nutzung von Vorteilen des klassischen Machine Learnings, wie Ende-zu-Ende Training basierend auf einzelnen Messwerten. Ich vergleiche meinen Ansatz in verschiedenen Experimenten zu einem klassischen Feed-Forward Neural Network, um die Anwendbarkeit DeLaNs auf Online Learning von inversen Dynamik Modellen zu zeigen. Außerdem stelle ich die Vorteile und Einschränkungen meines Ansatzes dar, die sich aus den Eigenschaften der eingebundenen physikalischen Voraussetzung ergeben. Kurz gesagt, DeLaN ist in der Lage in Echtzeit zu lernen und einen echten Roboter zu steuern und es bietet dabei die Fähigkeit zu neuen, unbekannten Aufgaben zu extrapolieren.
Lattice Boltzmann Simulation on Droplet Flow through 3D Metal Foam

The hydrodynamics of droplets passing through metal foam is investigated using the lattice Boltzmann method (LBM). The accurate 3D porous structure for the simulation is generated by X-ray micro-computed tomography. The simulated results are in good agreement with the experimental ones using high-speed video. The simulated results show that for droplets passing metal foam, there is a critical capillary number, Cac (around 0.061), above which the droplet continues to deform until it breaks up. The simulated results show that the capillary number, droplet size, pores diameter, and thickness of metal foam have the significant effect of droplets deforming and breaking up when the droplets pass through the metal foam. To avoid the calescence of two droplets at the inlet zone of the metal foam, the distance between droplets should be larger than three times the diameter of the droplet.
Early Fault Detect ion Tools

The traditional software development cycle relies mostly on informal methods to capture design errors in its initial phases, and on more rigorous testing methods during the later phases. It is well understood, though, that those bugs that slip through the early design phases tend to cause the most damage to a design. The anomaly of traditional design is therefore that it excels at catching bugs at the worst possible point in a design cycle: at the end. In this paper we consider what it would take to develop a suite of tools that has the opposite characteristic: excelling at catching bugs at the start, rather than the end of the design cycle. Such early fault detection tools differ from standard formal verification techniques in the sense that they must be able to deal with incomplete, informal design specifications, with possibly ill-defined requirements. They do not aim to replace either testing or formal verification techniques, but to complement their strengths.
Morphogenetic signaling in growing tissues

During the development of multicellular organisms, organs grow to well-defined shapes and sizes. The proper size and patterning of tissues are ensured by signaling molecules as e.g. morphogens. Secreted from a restricted source, morphogens spread into the adjacent target tissue where they form a graded concentration profile. Upon binding of the morphogens to receptors on the cell surfaces, the morphogenetic signal is transduced inside the cell via the phosphorylation of transcription factors, which subsequently regulate the expression of different target genes. Thus, cell fates are determined by the local concentration of such morphogens. In this work, we investigate three key aspects of morphogenetic signaling processes in growing tissues. First, we study the mechanics of tissue growth via cell division and cell death. We examine the rearrangements of cells on large scales and times by developing a continuum theory which describes the growing tissue as an active complex fluid. In our description we include anisotropic stresses generated by oriented cell division, and we show that average cellular trajectories exhibit anisotropic scaling behaviors. Our description is used to study experimentally measured shape changes of the developing wing disk of the fruit fly Drosophila melanogaster. Second, we focus on the spreading of morphogens in growing tissues. We show that the flow field of cell movements due to oriented cell division and cell death causes a drift term in the morphogen transport equation, which captures the stretching and dilution of the concentration profile. Comparing our theoretical results to recent experiments in the Drosophila wing disk, we find that the transport of the morphogen Dpp is mainly intracellular. We moreover show that the decay length of the Dpp gradient increases during development as a result of changing degradation rate and diffusion coefficient, whereas the drift of molecules due to growth is negligible. Thus growth does not affect the decay length of the gradient, but the decay length of the gradient might affect the tissue growth rate as discussed in this work. Finally, we develop a microscopic theoretical description of the intracellular transduction machinery of morphogenetic signals within an individual cell. Our description captures the kinetics of the trafficking of proteins between different cellular compartments in response to receptor-bound signaling molecules. Analyzing experimental data at the Drosophila neuromuscular junction, we show that the morphogenetic signaling is modulated by synaptic signaling via neuronal action potentials.
Effect of Service Quality, Trust and Price On Online Shop Customer Satisfaction in Kendari City

This study aims to determine and analyze the influence of service quality, trust and price on online shop customer satisfaction in the city of Kendari. This research was conducted by survey method using a questionnaire and distributed randomly to all internet users in the city of Kendari who had already shop online. The analytical tool used in this study is multiple linear regression analysis. The results showed that service quality, trust and price significantly increased customer satisfaction both simultaneously and partially.
Comparison of Load Balance Processes for Multiple Distributed Indices on a Common Framework

A number of distributed index methods to manage data among multiple machines have been proposed. Since implementing distributed index methods is a difficult task for developers, comparison of distributed index methods in a common environment has not been sufficiently investigated. Therefore, we have been developing a framework capable of making easy to implement distributed index methods. In distributed environment, load balancing is important to avoid forcing a specific machine to become a bottleneck. Our research goal is to reduce implementation cost for load balancing by extracting common portions which are independent of data structures of distributed index methods. In this paper,we add the feature of balancing load among machines to the framework and compare performance of multiple distributed index methods in load balance processes by the developed framework.
Are Consumers’ Egg Preferences Influenced by Animal-Welfare Conditions and Environmental Impacts?

We conducted a labelled discrete choice experiment (DCE) to assess consumers’ preferences and willingness to pay (WTP) for fresh hens’ eggs produced via different production systems (caged, barn, free range, or organic). We estimated purchase intentions and WTP for different possible reductions (0%, 10%, 20%, and 30%) of greenhouse gas (GHG) emissions and water use in the egg production systems. Data were collected using an online open-ended questionnaire completed by a representative sample of 1045 Spanish egg consumers. The results of a random parameter logit (RPL) model showed heterogeneous preferences for different types of eggs with higher marginal utility and WTP for a production system ensuring higher animal welfare level, such as free-range eggs. However, consumers showed a lower preference for organic eggs at the actual market prices since they were unwilling to pay for this category of eggs. Moreover, there were positive marginal WTPs for reductions in GHG emissions and water use, but only for significant reductions (20% or 30%) with respect to the current situation. Potential buyers for free-range eggs were identified to be persons under 40 years old, persons with a monthly income of more than €1500, and persons who were pro-environment. Our findings provide producers, sellers and policy makers with useful information that may guide them in the development of successful communication and pricing strategies.
Femtocell-to-Femtocell Handoff Management in Dense Femtocellular Networks

Femtocells are small consumer-installed base stations that enhance indoor cellular services coverage. Deploying a large number of such femtocells in a small area results in “Dense Femtocellular Networks. ” These networks face a number of problems, including handoff. Different scholars have put forward various prescriptions for resolving the handoff problem. In this paper, we propose a model to enhance and minimize the neighbor femtocell list for femtocell-to-femtocell handoff in a dense femtocellular network by adapting a user movement prediction technique based on femtocell location.
An Evaluation and Comparison of Four Dense Time Series Change Detection Methods Using Simulated Data

Access to temporally dense time series such as data from the Landsat and Sentinel-2 missions has lead to an increase in methods which aim to monitor land cover change on a per-acquisition rather than a yearly basis. Evaluating the accuracy and limitations of these methods can be difficult because validation data are limited and often rely on human interpretation. Simulated time series offer an objective method for evaluating and comparing between change detection algorithms. A set of simulated time series was used to evaluate four change detection methods: (1) Breaks for Additive and Seasonal Trend (BFAST); (2) BFAST Monitor; (3) Continuous Change Detection and Classification (CCDC); and (4) Exponentially Weighted Moving Average Change Detection (EWMACD). In total, 151,200 simulations were generated to represent a range of abrupt, gradual, and seasonal changes. EWMACD was found to give the best performance overall, correctly identifying the true date of change in 76.6% of cases. CCDC performed worst (51.8%). BFAST performed well overall but correctly identified less than 10% of seasonal changes (changes in amplitude, length of season, or number of seasons). All methods showed some decrease in performance with increased noise and missing data, apart from BFAST Monitor which improved when data were removed. The following recommendations are made as a starting point for future studies: EWMACD should be used for detection of lower magnitude changes and changes in seasonality; CCDC should be used for robust detection of complete land cover class changes; EWMACD and BFAST are suitable for noisy datasets, depending on the application; and CCDC should be used where there are high quantities of missing data. The simulated datasets have been made freely available online as a foundation for future work.
Characterization of Carotenoid Biosynthesis in Newly Isolated Deinococcus sp. AJ005 and Investigation of the Effects of Environmental Conditions on Cell Growth and Carotenoid Biosynthesis

Our purpose was to characterize the structures of deinoxanthin from Deinococcus sp. AJ005. The latter is a novel reddish strain and was found to synthesize two main acyclic carotenoids: deinoxanthin and its derivative. The derivative (2-keto-deinoxanthin) contains a 2-keto functional group instead of a 2-hydroxyl group on a β-ionone ring. A deinoxanthin biosynthesis pathway of Deinococcus sp. AJ005 involving eight putative enzymes was proposed according to genome annotation analysis and chemical identification of deinoxanthin. Optimal culture pH and temperature for Deinococcus sp. AJ005 growth were pH 7.4 and 20 °C. Sucrose as a carbon source significantly enhanced the cell growth in comparison with glucose, glycerol, maltose, lactose, and galactose. When batch fermentation was performed in a bioreactor containing 40g/L sucrose, total carotenoid production was 650% higher than that in a medium without sucrose supplementation. The culture conditions found in this study should provide the basis for the development of fermentation strategies for the production of deinoxanthin and of its derivative by means of Deinococcus sp. AJ005.
Mitochondrial oxidative phosphorylation and mitophagy in myocardial ischaemia/reperfusion: effects of chloroquine.

AIM The aim of this study was to evaluate the temporal relationship between mitochondrial oxidative phosphorylation and mitophagy in rat hearts subjected to ischaemia/reperfusion. Measurements were made at specific points during the experimental protocol (snapshot approach) and by assessments of mitophagic flux, using chloroquine pre-treatment. METHODS Isolated working rat hearts were subjected to 25 or 30 minutes of global ischaemia/10 minutes of reperfusion. Half of each group received chloroquine (10 mg/kg, intraperitoneally) one hour before experimentation. Mitochondria were isolated after stabilisation, ischaemia and reperfusion, and oxidative phosphorylation was measured polarographically. Mitochondrial mitophagy markers were detected by Western blot analysis. RESULTS Mitochondrial oxygen uptake (state 3) and oxidative phosphorylation rate were reduced by ischaemia and increased by reperfusion. Chloroquine pre-treatment increased both parameters. Using a snapshot approach, exposure to ischaemia ± reperfusion had little effect on mitochondrial PINK1, Parkin and p62/SQSTM1 expression. Ischaemia reduced Rab9 expression, and reperfusion upregulated the phosphor DRP1, phosphor/total DRP1 ratio and Rab9 levels. Chloroquine significantly reduced PINK1, p62/SQSTM1, Rab9 and particularly Parkin expression during reperfusion, without an effect on mitochondrial total and phospho DRP1 levels. CONCLUSIONS Ischaemia/reperfusion-induced changes in mitochondrial oxidative phosphorylation function occurred concomitantly with changes in mitophagic flux. Pre-treatment with chloroquine profoundly affected mitochondrial function as well as the pattern of mitophagy during ischaemia/reperfusion.