Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Dual-Scale Deep Belief Network Method for Daily Urban Water Demand Forecasting

Water demand forecasting applies data supports for the scheduling and decision-making of urban water supply systems. In this study, a new dual-scale deep belief network (DSDBN) approach for daily urban water demand forecasting was proposed. Original daily water demand time series was decomposed into several intrinsic mode functions (IMFs) and one residue component with ensemble empirical mode decomposition (EEMD) technique. Stochastic and deterministic terms were reconstructed through analyzing the frequency characteristics of IMFs and residue using generalized Fourier transform. The deep belief network (DBN) model was used for prediction using the two feature terms. The outputs of the double DBNs are summed as the final forecasting results. Historical daily water demand datasets from an urban waterworks in Zhuzhou, China, were investigated by the proposed DSDBN model. The mean absolute percentage error (MAPE), normalized root-mean-square error (NRMSE), correlation coefficient (CC) and determination coefficient (DC) were used as evaluation criteria. The results were compared with the autoregressive integrated moving average (ARIMA) model, feed forward neural network (FFNN) model, support vector regression (SVR) model, EEMD and their combinations, and single DBN model. The results obtained in the test period indicate that the proposed model has the smallest MAPE and NRMSE values of 1.291099 and 0.016625, respectively, and the largest CC and DC values of 0.976528 and 0.953512, respectively. Therefore, the proposed DSDBN method is a useful tool for daily urban water demand forecasting and outperforms other models in common use.
In Situ Genomics and Transcriptomics of SAR202 Subclusters Revealed Subtle Distinct Activities in Deep-Sea Water

Deep-sea water columns are enriched with SAR202 that may conduct detrital matter degradation. There are several subclusters in SAR202, but their subtle differences in geochemical cycles are largely unknown, particularly for their in situ activities in the marine deep zone. Deep-sea DNA/RNA samples obtained from 12 continuous time periods over two days by in situ nucleic acid collection apparatus were used to re-evaluate the ecological functions of each SAR202 subcluster at a depth of ~1000 m in the South China Sea (SCS). Phylogenomics of 32 new SAR202 genomes from the SCS and western Pacific revealed their distribution in five subclusters. Metatranscriptomics analysis showed that the subclusters II and III were the dominant SAR202 groups with higher transcriptional activities in the SCS deep-sea zone than other subclusters. The analyses of functional gene expression further indicated that SAR202 subclusters II and III might be involved in different metabolic pathways in the deep-sea environment. The SAR202 subcluster III might take part in the degradation of deep-sea aromatic compounds. Time-course metagenomics and metatranscriptomics data did not show metabolic correlation of subclusters II and III over two days, suggesting diversified ecological functions of SAR202 subclusters under different organic inputs from the overlying water column. Collectively, our results indicate that the SAR202 subclusters play different roles in organic degradation and have probably undergone subtle and gradual adaptive evolution in the dynamic environment of the deep ocean.
Selecting a series of storm events for a model-based assessment of combined sewer overflows

ABSTRACT The hydraulic verification of combined sewer systems as well as the assessment of combined sewer overflows (CSOs) can be conducted using a hydrodynamic model. Unfortunately, long-term simulations with hydrodynamic models for the assessment of CSOs can cause unacceptably long computation times. Using only a series of storm events instead of a precipitation continuum can reduce this time and enables parallel simulation of single storm events. We introduce a method to select this series of storm events. The method’s parameters have been optimized to replicate the overflow volume of the continuous simulation and to minimize the overall computation time. This optimization revealed a generally applicable parameter set that results in series of storm events that are shorter than the precipitation continuum by 86.2–95.2% for the investigated cases. Additionally, the deviation of overflow volume between continuous simulation and series simulation ranges between only 0.1% and 4.1%.
Extension and Evaluation of University of Washington Moist Turbulence Scheme to Gray‐Zone Scales

With the rapid improvement in computational resources, it has become possible to structure numerical weather model simulations to use sub‐kilometer grid spacing. Traditional turbulence‐mixing closures have become obsolete within the context of the gray zone of turbulence. Here, a new scale‐aware algorithm (SA‐UW) is developed based on the UW (University of Washington Moist Turbulence) scheme. By dividing both the local and nonlocal vertical turbulence flux into sub‐grid and resolved parts, the partition of sub‐grid turbulence is tuned by a set of well‐acknowledged scale‐dependent relationships. Idealized simulations confirm that the newly developed scheme can adequately reproduce sub‐grid turbulence transport at gray‐zone scales. The inclusion of a nonlocal transport term in the SA‐UW scheme is essential, as it vastly improves the distribution and intensity of coherent structures. The SA‐UW scheme recovers the conventional UW scheme when grid spacing is larger than the turbulence length scale, thereby evincing the sale‐aware capability of the new method. For real‐case simulations, the SA‐UW scheme can capture the diurnal cycle and provide a more accurate vertical structure of temperature and humidity.
Detecting gravitomagnetism with space-based gravitational wave observatories

We discuss the idea of a measurement that, making use of data from space interferometers, could detect the gravito-magnetic field generated by the rotation of the Milky Way, including the possible contribution of the dark matter halo. The galactic signal would be superposed to the gravito-magnetic field of the Sun. The proposed technique is based on the asymmetric propagation of light along the closed contour of the space interferometer, in a Sagnac-like approach. We discuss the principles of detection as well as some practical aspects of the proposed experiment using, as a case study, LISA, the most mature project to date. Both gravito-magnetic signals will be modulated thanks to the annual oscillation of the plane of the interferometer with respect to the galactic plane and to the spin axis of the Sun. Although larger than the detector intrinsic noise, these signals will be superposed to a much larger kinematic modulation due to orbital motion, making them very hard to be observed. We also mention a second phenomenon, where the gravito-magnetic field rotates the polarization of the propagating electromagnetic beams: the effect will be present in LISA, although exceedingly small and out of reach of present technology.
Recent advances in the chromatin-based mechanism of FLOWERING LOCUS C repression through autonomous pathway genes

Proper timing of flowering, a phase transition from vegetative to reproductive development, is crucial for plant fitness. The floral repressor FLOWERING LOCUS C (FLC) is the major determinant of flowering in Arabidopsis thaliana. In rapid-cycling A. thaliana accessions, which bloom rapidly, FLC is constitutively repressed by autonomous pathway (AP) genes, regardless of photoperiod. Diverse AP genes have been identified over the past two decades, and most of them repress FLC through histone modifications. However, the detailed mechanism underlying such modifications remains unclear. Several recent studies have revealed novel mechanisms to control FLC repression in concert with histone modifications. This review summarizes the latest advances in understanding the novel mechanisms by which AP proteins regulate FLC repression, including changes in chromatin architecture, RNA polymerase pausing, and liquid–liquid phase separation- and ncRNA-mediated gene silencing. Furthermore, we discuss how each mechanism is coupled with histone modifications in FLC chromatin.
The partner link worker: A vital but undervalued service for women who have been subjected to or at risk of domestic abuse

This study aims to explore the partner link worker (PLW) role in supporting women who have been subjected to or at risk of domestic abuse. Prior research in a probation setting tends to focus solely on the person on probation, failing to examine the experiences of people subjected to crime and support services on offer. The PLW role provides an essential service that has been undervalued and overlooked. The study begins to provide some evidence to counter the broader political rhetoric that people subjected to crime are central to probation practice within the criminal justice system. It draws on the findings from thirteen semi-structured interviews conducted across five Community Rehabilitation Companies (CRCs). The findings suggest that PLWs demonstrate a professional commitment to protecting and safeguarding vulnerable women and addressing domestic abuse. However, PLWs face many challenges and obvious gaps in provisions to provide a fully inclusive and accessible service to meet the individual needs of women and their children. The recently reunified probation service offers an optimum opportunity to review, resource and regenerate the PLW service to protect and safeguard people who have been subjected to or at risk of domestic abuse.
Spacetimes with a transitive similarity group

Spacetimes admitting a four-dimensional transitive similarity group are studied. It is shown that when the homogeneous hypersurfaces (which necessarily exist) are spacelike (spatially homogeneous case) then the connection components in a Lorentz frame adapted to the spatially homogeneous slicing are proportional to t-1 where t is the proper time of the homogeneous slices. An analogous statement holds when those slices are timelike except that t is a spacelike coordinate in that case. The transitively self-similar universes correspond exactly to the exact power law solutions in Wainwright's terminology, (1984). They are also closely connected to the regularised form of the Einstein field equations used in the qualitative approach to spatially homogeneous cosmology. In fact the transitively self-similar models are in one-one correspondence and those critical points of the regularised system which lie in the physical region of that system.
Towards Green Shipping with Integrated Fleet Deployment and Bunker Management

The vast majority of world trade is carried by the sea shipping industry and petroleum is still the major energy source. To reduce greenhouse gas emissions, it is an urgent need for both industry and government to promote green shipping. To move shipping towards a more environmentally and financially sustainable future, we consider to develop an integrated fleet deployment and bunker management model in this paper. The fleet deployment refers to the decisions on which ships to operate on which route, at what speed and what cargos to be transported. The bunker management refers to the decision on which ships to bunker on which port and at what volume. A more realistic fuel consumption function with considering not only cruise speed but also freight tonnage on board is adopted in the proposed optimization model, which can further improve its effectiveness in practice. An efficient algorithm termed "Most Promising Area Search" (MPAS) is developed afterwards to solve the corresponding mixed integer programming problem, which can guarantee to converge to a local optimal solution. The benefits of the integrated model and the computational performance of the MPAS are illustrated by numerical examples and a case study.
MFOC-CliqueNet: A CliqueNet-Based Optimal Combination of Multidimensional Features Classification Method for Large-Scale Laser Point Clouds

As large-scale laser 3D point clouds data contains massive and complex data, it faces great challenges in the automatic intelligent processing and classification of large-scale 3D point clouds. Aiming at the problem that 3D point clouds in complex scenes are self-occluded or occluded, which could reduce the object classification accuracy, we propose a multidimension feature optimal combination classification method named MFOC-CliqueNet based on CliqueNet for large-scale laser point clouds. The optimal combination matrix of multidimension features is constructed by extracting the three-dimensional features and multidirectional two-dimension features of 3D point cloud. This is the first time that multidimensional optimal combination features are introduced into cyclic convolutional networks CliqueNet. It is important for large-scale 3D point cloud classification. The experimental results show that the MFOC-CliqueNet framework can realize the latest level with fewer parameters. The experiments on the Large-Scale Scene Point Cloud Oakland dataset show that the classification accuracy of our method is 98.9%, which is better than other classification algorithms mentioned in this paper.
Effects of Obesity and Diabesity on Ventricular Muscle Structure and Function in the Zucker Rat

(1) Background: Cardiovascular complications are a leading cause of morbidity and mortality in diabetic patients. The effects of obesity and diabesity on the function and structure of ventricular myocytes in the Zucker fatty (ZF) rat and the Zucker diabetic fatty (ZDF) rat compared to Zucker lean (ZL) control rats have been investigated. (2) Methods: Shortening and intracellular Ca2+ were simultaneously measured with cell imaging and fluorescence photometry, respectively. Ventricular muscle protein expression and structure were investigated with Western blot and electron microscopy, respectively. (3) Results: The amplitude of shortening was increased in ZF compared to ZL but not compared to ZDF myocytes. Resting Ca2+ was increased in ZDF compared to ZL myocytes. Time to half decay of the Ca2+ transient was prolonged in ZDF compared to ZL and was reduced in ZF compared to ZL myocytes. Changes in expression of proteins associated with cardiac muscle contraction are presented. Structurally, there were reductions in sarcomere length in ZDF and ZF compared to ZL and reductions in mitochondria count in ZF compared to ZDF and ZL myocytes. (4) Conclusions: Alterations in ventricular muscle proteins and structure may partly underlie the defects observed in Ca2+ signaling in ZDF and ZF compared to ZL rat hearts.
Changes in Blood Metabolic Profiles Reveal the Dietary Deficiencies of Specific Nutrients and Physiological Status of Grazing Yaks during the Cold Season in Qinghai Province of China

This study aimed to investigate the changes in the blood metabolic profiles of grazing yaks during the cold season to reveal their physiological status and seek the nutrients needed to be supplemented. Six castrated yaks (3 years old) with 166.8 kg (standard deviation = 5.3) of liveweight grazed in the Qinghai-Tibetan Plateau were used as experimental animals without supplementary feeding. Blood samples of each animal were collected in October and December 2015, and March 2016 for the analysis of serum biochemicals and metabolome. Results showed serum indices involved in protein metabolism in grazing yaks showed greater differences during the cold season than the metabolisms of energy or minerals. Cold stress in December had minor effects on the serum metabolic profiles of yaks compared with those in October. Yaks in October and December shared seven differential serum metabolites and enrichments of the “arachidonic acid metabolism” and “glycine, serine, and threonine metabolism” pathways compared with those in March caused by the shortage of feeds. Summarily, the nutrient deficiency would be influential on the physiological status of grazing yaks during the cold season, especially on the protein metabolism, which could be improved by supplementary feeds.
Xenocentrism, Ethnocentrism, and Global Culture Influence on Consumer Preference for Global and Local Brands

Abstract This study examines the effect of ethnocentrism and xenocentric consumer dispositions, and global culture on the purchase intention of national and global brands, in a developing country, conditioned on the individual’s social capital and identity. Through structural equation modeling, and a field experiment, we provide evidence that global preference bias, the cognitive duality of consumers in developing countries in choosing local or global brands, may be due to xenocentrism and global culture, and its interaction with consumer’s network and self-extension. It advances the understanding of global preference bias by bringing the perspective of micro and macro levels of group influence.
Uniqueness theorems for inverse obstacle scattering in Lipschitz domains

An inverse problem of finding an obstacle and the boundary condition on its surface from the fixed-energy scattering data is studied. A new method is developed for a proof of the uniqueness results. The method does not use the discreteness of the spectrum of the corresponding Laplacian in a bounded domain. Proof of the uniqueness results is based on the fact that the Hilbert space of square integrable functions is separable.
A COMPREHENSIVE REVIEW OF ENERGY OPTIMIZATION TECHNIQUES IN CLOUD COMPUTING

: The most concerning problem on a global scale is the rise in energy usage. Massive data centers have been built as a result of the expansion and development of sophisticated data-intensive applications, which has raised the demand for energy. As a result, concerns related to energy efficiency are receiving more and more attention in corporate practice, theory development, and research related to cloud computing. The survey shows the research trends based on regions, journals, conferences, etc., in the domain of energy efficiency in cloud computing. The study includes Challenges or Issues, Existing Methods, Decisive Review Findings and Future Aspects/ Limitations. It is concluded with some of the critical findings that could be potential future directions.
Checking Bounded-Memory Execution for Delayed Sampling on Probabilistic Streams

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Checking Bounded-Memory Execution for Delayed Sampling on Probabilistic Streams Eric Atkinson, Guillaume Baudart, Louis Mandel, Charles Yuan, Michael Carbin
Tolerability of an Amino Acid-based Oral Rehydration Solution in Children with Short Bowel Syndrome

1. Background Intestinal failure (IF) is defined as a critical reduction of the gut mass/function below the minimum needed to absorb nutrients and fluids required for adequate homeostasis, growth and development. It is a condition in which severe malabsorption results in the need for lifesaving parenteral nutrition (PN) or enteral nutrition (EN) (1). In neonates, the most common cause of IF is surgical short bowel syndrome (SBS), which is defined as the need for prolonged parenteral nutrition following surgery for congenital or acquired gastrointestinal disorders. SBS is characterized by a compromised bowel absorptive capacity because of a reduced mucosal surface, which if left untreated can result in diarrhea, fluid and electrolyte imbalance, and malnutrition. Limiting the duration of PN by promoting enteral autonomy has been shown to decrease complications and improve survival for pediatric patients with IF (2).
Comparison of experimental and theoretical spiral MR trajectories

In this project, a spiral fast imaging sequence was implemented on a Bruker Avance MR system. Acquisition and processing schemes were developed to measure the experimental k-space trajectories. Since errors in k-space are reflected as errors in the corresponding image, we used different strategies to measure and calculate corrections for deviation of the experimental k-space trajectory from the theoretical one. Even if the k-space trajectories deviate from the theoretical ones, an experimentally measured trajectory can be incorporated in the spiral reconstruction and a reduction of image artifacts can be obtained. Trajectories were measured according a method using self-encoding gradients (Takahashi et al., 1995). Necessary corrections were deduced from a quantitative comparison of theoretical and experimental data, which can be used to adjust specific parameters in the MR imaging sequence before spiral image acquisition. The corrections included the assessment of baseline, gradient delay, amplitude and timing mismatch. The influence and extent of different corrections pre-and post-acquistion on the final spiral image quality still remains to be evaluated.
Asymptotics of the Yang-Mills flow for holomorphic vector bundles over Kahler manifolds

In the following article we study the limiting properties of the Yang-Mills flow associated to a holomorphic vector bundle E over an arbitrary compact K\"ahler manifold (X,{\omega}). In particular we show that the flow is determined at infinity by the holomorphic structure of E. Namely, if we fix an integrable unitary reference connection A_0 defining the holomorphic structure, then the Yang-Mills flow with initial condition A_0, converges (away from an appropriately defined singular set) in the sense of the Uhlenbeck compactness theorem to a holomorphic vector bundle E_{\infty}, which is isomorphic to the associated graded object of the Harder-Narasimhan-Seshadri filtration of (E,A_0). Moreover, E_{\infty} extends as a reflexive sheaf over the singular set as the double dual of the associated graded object. This is an extension of previous work in the cases of 1 and 2 complex dimensions and proves the general case of a conjecture of Bando and Siu.
Adaptive Sampling of Latent Phenomena using Heterogeneous Robot Teams (ASLaP-HR)

In this paper, we present an online adaptive planning strategy for a team of robots with heterogeneous sensors to sample from a latent spatial field using a learned model for decision making. Current robotic sampling methods seek to gather information about an observable spatial field. However, many applications, such as environmental monitoring and precision agriculture, involve phenomena that are not directly observable or are costly to measure, called latent phenomena. In our approach, we seek to reason about the latent phenomenon in real-time by effectively sampling the observable spatial fields using a team of robots with heterogeneous sensors, where each robot has a distinct sensor to measure a different observable field. The information gain is estimated using a learned model that maps from the observable spatial fields to the latent phenomenon. This model captures aleatoric uncertainty in the relationship to allow for information theoretic measures. Additionally, we explicitly consider the correlations among the observable spatial fields, capturing the relationship between sensor types whose observations are not independent. We show it is possible to learn these correlations, and investigate the impact of the learned correlation models on the performance of our sampling approach. Through our qualitative and quantitative results, we illustrate that empirically learned correlations improve the overall sampling efficiency of the team. We simulate our approach using a data set of sensor measurements collected on Lac Hertel, in Quebec, which we make publicly available.