Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of dense nonaqueous phase liquid pool morphology on the performance of partitioning tracer tests: Evaluation of the equilibrium assumption

Partitioning tracer techniques, initially developed in the petroleum industry, are promoted as a way to determine entrapped dense nonaqueous phase liquid (DNAPL) mass in source zones. A suite of chemical tracers, some of which partition into the DNAPL phase, is injected into the source zone to estimate the entrapped saturation of contaminant. Current application of the technique can determine DNAPL at residual saturation but does not provide reliable mass estimates of DNAPL in high‐saturation areas (e.g., pools) that may occur in some source zones. To evaluate this technique's limitations in characterizing source zones with complex entrapment architectures that may contain pools, we investigated estimation errors associated with well‐characterized single‐isolated DNAPL pools. X‐ray attenuation was used to determine the spatial distribution of saturation within the pool under different total DNAPL mass entrapment while the DNAPL was subjected to tracer tests. Model analysis used showed that the partitioning tracer breakthrough simulations based on equilibrium partition coefficient (Kp, from equilibrium batch tests) fit the experimental data poorly, suggesting nonequilibrium partitioning that is controlled by the water flow velocity through the NAPL entrapment zone. In order to relax the requirement of partitioning to be at equilibrium, we investigated the use of “effective partition coefficients” (Kpe). A comparison of the saturation estimates using method of moments and inverse modeling with both equilibrium and effective partition coefficients was conducted. Results demonstrated that the incorporation of nonequilibrium behavior in the analysis can improve DNAPL mass estimation by tracers in high‐saturation zones.
An integrated model for soil organic carbon and CO2: Implications for paleosol carbonate pCO2 paleobarometry

The geologic history of atmospheric CO2 concentration (CAtm) is relevant to studies of paleoclimate, paleobiology, and elemental cycling at the Earth's surface. Here we present a model that represents processes controlling the concentration, stable carbon isotope composition, and vertical distribution of organic matter and CO2 within soils. In the model we include a volumetric scaling term necessary to calculate the soil pore CO2 concentration and δ13CO2 from soil respiration rate per unit area, which has been omitted in previous work. Our model provides several new insights into the commonly used method for estimating paleo‐CAtm based on the δ13C of paleosol carbonates. We show that because refractory, microbially processed organic matter is increasingly abundant toward the base of the soil, isotope effects associated with organic matter decay can potentially lead to significant offset between the δ13C of soil‐respired CO2 (δφ) and that of soil organic matter at depth. The magnitude of this effect depends on the production and decay characteristics of the individual soil, and can lead to substantial underestimation of paleo‐CAtm if organic matter preserved in subsurface paleosol horizons is used to approximate δφ. Paleo‐CAtm reconstruction will be more accurate if surface‐layer fossil organic matter is used as a proxy for δφ. In this case, however, there is a small (200–300 ppm), consistent, positive bias in CAtm estimates resulting from the decay of 13C‐enriched organic matter deep within the soil. Re‐examination of earlier studies using the soil carbonate approach to estimate CAtm identifies examples where each bias may be present.
Gaussian mixture probability hypothesis density smoothing with multistatic sonar

Passive sonar is widely used in practice to covertly detect maritime vessels. However, the detection of stealthy vessels often requires active sonar. The risk of the overt nature of active sonar operation can be reduced by using multistatic sonar techniques. Cheap sonar sensors that do not require any beamforming technique can be exploited in a multistatic system for spacial diversity. In this paper, Gaussian mixture probability hypothesis density (GMPHD) filter, which is a computationally cheap multitarget tracking algorithm, is used to track multiple targets using the multistatic sonar system that provides only bistatic range and Doppler measurements. The filtering results are further improved by extending the recently developed PHD smoothing algorithm for GMPHD. This new backward smoothing algorithm provides delayed, but better, estimates for the target state. Simulations are performed with the proposed method on a 2-D scenario. Simulation results present the benefits of the proposed algorithm.
Multiple Human Activities Classification Based on Dynamic On-Body Propagation Characteristics Using Transfer Learning

Human activity recognition and classification have been widely used in various fields. To make full use of wireless body area networks (WBANs), multiple human activities classification based on dynamic on-body propagation characteristics is presented in this article. Four on-body links are established to collect propagation data set for four groups of activities, which include hand activities, arm activities, leg activities and head activities. A total of 30 human activities are considered. The line-of-sight (LOS) and non-LOS (NLOS) on-body propagation characteristics are analyzed in detail by comparing measurement with full-wave simulation. Multiple human activities, including some fine-grained motions, can be accurately classified using the propagation data collected by the on-body antennas. Based on the similar propagation mechanism among different links, an interlink transfer learning framework is proposed by pretraining the deep convolutional neural network (DCNN) on one link before training it on other links. The results show that after pretrained in source domain, the interlink transfer learning can improve classification accuracy and accelerate model convergence in target domain with a small amount of training data, which alleviates the complex and time-consuming data collection. The results of this article are particularly useful for the deployment of WBAN integrated communication and sensing.
Calcareous pine forests on Gotland, their typology and main soil properties/ Gotlandi kaltsifi ilsed männikud; nende tüpoloogia ja muldade peamised omadused

Abstract The calcareous pine forests have one of the highest species diversity among the forest communities in northern Europe. We analysed their classification structure and the relationship with principal environmental variables on Gotland Island, South East Sweden. There were 14 species recorded in the tree layer, 60 species in the shrub layer, including 18 species of tree saplings, 273 species in the field layer and 80 species in the moss layer. The former classifications of the Gotland’s calcareous pine forests are conducted too coarsely or without statistical justification of established community types. In the current study the stands were classified into four community types, 1) Arctostaphylos uva-ursi-Tortella tortuosa type, 2) Brachypodium sylvaticum-Rhytidiadelphus triquetrus type, 3) Carex montana-Scleropodium purum type and, 4) Geranium sanguineum-Scleropodium purum type. All these community types have significantly different species content and they are mutually distinct also by numerous considered environmental variables. The species variation in the shrub, field and moss layers was related primarily with three rather strongly correlated variables: tree layer height, abundance of Picea abies (L.) H.Karst. and soil humus horizon depth. Soils were mainly the Sceletic Regosols or Calcaric Gleyic Regosols, but also Rendzic Leptosols.
The role of Indonesian throughflow in a global ocean GCM

Abstract The effect of the Indonesian Throughflow on the World Ocean circulation is examined by a series of experiments with a global ocean GCM. The principal objective is to gain an understanding of how ocean flows respond to the throughflow, and how these changes result in changes in the pattern of surface heat flux and sea surface temperature. Four model runs are conducted. The first run features an open Indonesian passage through which a nonzero net throughflow is permitted. The second run features a complete blockage of the Indonesian passage. The third run is designed to isolate the effects of purely buoyancy-driven throughfiow: the Indonesian passage is open but the net volume transport is required to be zero. The fourth run is designed to isolate the effects of nonzero net throughflow on the Indian Ocean, independent of interocean buoyancy differences: the Indonesian passage is open but the throughflow water is cooled and salted toward profiles characteristic of the east Indian Ocean in the absenc.
ACADEMIC RESILIENCE AND SELF-ESTEEM AS DETERMINANT OF STUDENTS’ ACADEMIC PERFORMANCE IN ZAMFARA STATE

The academic performance of students in the nations tertiary institutions has been on the decline. The study explored self-esteem and academic resilience as determinants of students’ academic performance in Federal Polytechnic Kaura-Namoda, Zamfara state. The study employed survey and cross-sectional research design. The study employed purposive sampling technique as 800 pieces of questionnaire were administered students in the institution out of which 682 were valid and used for the analyses. The study used statistical package for social sciences (SPSS) to run the preliminary analyses such as detection of missing value, outliers, multicollinearity and test of normality. Structural equation model (SmartPLS) was used to run the measurement and structural models. The findings revealed that self-esteem and academic resilience have positive and significant effect on students’ academic performance in Federal Polytechnic Kaura-Namoda, Gusau, Zamfara state. The study recommended that educational stakeholders (the government, school management, lecturers and school peers) should encourage students to bounce-back from seemly difficult situation to stimulate their performance.
Mobile Edge Computing Enabler Layer: Edge-native APPLICATION Architecture For Mobile Networks

Despite the incredible advances in mobile communications technology over multiple generations of wireless networks, service quality remains inherently limited by the physical distance between end service consumers and their network service providers, coupled with constrained resources (e.g., computation power and storage) of end user devices. To tackle these intrinsic challenges, mobile edge computing, which aims to provide a service environment and computing capabilities in close proximity to the user devices, has received increasing attention within the industry. Specifically, the ability to provision and access mobile applications from the edge of the network enables ultra-reliable and low latency applications such as immersive AR/VR content, multi-player gaming, and vehicle-to-everything (V2X) applications. We provide an overview of the 3GPP efforts and related standard-based solutions addressing these industry requirements. In particular, we will review the 3GPP service and system aspect working group 6 (SA WG6) developed application architecture for enabling edge applications, referred to as the edge enabler layer (EEL). This article elaborates the motivation and detailed design principles behind the EEL architecture, and provides an insight into the overall procedures that are critical to enabling a UE with access to edge computing service information. In addition, EEL deployment scenarios over 5G core network are discussed, as well as potential open issues and challenges that remain to be addressed in upcoming 3GPP releases.
A Transfer-Based Convolutional Neural Network Model with Multi-Signal Fusion and Hyperparameter Optimization for Pump Fault Diagnosis

Pumps are one of the core components of drilling equipment, and their fault diagnosis is of great significance. The data-driven approach has made remarkable achievements in the field of pump fault diagnosis; however, most of them are easily affected by complex background conditions and usually suffer from data scarcity problems in real-industrial scenarios, which limit their application in practical engineering. To overcome the above shortcoming, a novel framework for a model named Hyperparameter Optimization Multiple-Signal Fusion Transfer Convolution Neural Network is proposed in this paper. A convolutional neural network model based on transfer learning is built to promote well-learned knowledge transfer over different background conditions, improve robustness, and generalize the model to cross-domain diagnosis tasks. The multi-signal fusion strategy is involved in capturing system state information for establishing the mapping relationship between the raw signal and fault pattern by integrating the multi-physical signal with the weight allocation protocol. The hyperparameter optimization method is explored in conjunction with the transfer-based model by integrating Grid Search with the Gradient Descent algorithm for further improvement of diagnosis performance. Results show that the proposed model can effectively realize the fault diagnosis of pumps under different background conditions, achieving 95% accuracy.
Energy-Efficient Network Architecture for Smart City Development

The growing number of objects connected to the Internet due to the evolution of smart cities development and the tremendous data in the future 6G networks with extensive processing has produced massive amounts of data that need to be processed. This will burden the conventional clouds to process the data besides reducing the Quality of Services due to high latency. Also, the increase in data volumes increased the energy consumed by transport networks and the cloud. Therefore, fog computing has been introduced to overcome the limitation of the cloud. This study proposed a new fog computing architecture for Internet-of-Things (IoT) applications based on wireless access networks using WiFi technology. A new mathematical model has been developed to optimize the number and locations of the fog servers at the access network to minimize the energy consumption of the networking and processing equipment at the access layer. This is beneficial for smart city development which contributes to the 2030 Agenda for Sustainable Development Goals (SDG) under Goal 7. The Mixed Integer Linear Programming (MILP) model using AMPL software with CPLEX solver is used to model the energy-efficient fog computing architecture considering twelve tourist locations in Melaka as the case study. The results show that the proposed optimized approach (OA) has 52.6% energy saving as the low number of fog servers and networking devices are utilized in the network compared to the non-optimized approach (NOA). Besides, the energy saving increased up to 81.1% when high processing server capacity is considered in the network. In addition to that, the results also show that increasing the traffic demands by each user does not give a significant energy increment when considering a fog server with high processing capacity in the network
A stochastic process for the interannual snow storage and melting dynamics

A continuous time process of alternating stochastic growths and deterministic decays is proposed as a simple model for the interannual dynamics of snow water equivalent (SWE) storage and melting. The related stationary properties are studied, and an integral difference equation for the probability density function of the state variable is derived. The corresponding solution is obtained by both solving the master equation numerically and simulating the process with a Monte Carlo scheme. An analytical solution is also obtained for the inverse problem, i.e., when the pdf of growths that lead to accumulation is reconstructed from that of the process. The model's statistical properties help explain the probabilistic character of the end of summer snowlines and their intrinsic variability with the geographic location and climatic factors. Possible applications to model the interannual SWE cover evolution or to reconstruct the past precipitation characteristics are also discussed.
The Role of Mesoscale Eddies in the General Circulation of the Ocean—Numerical Experiments Using a Wind-Driven Quasi-Geostrophic Model

Abstract Results from a two-layer, quasi-geostrophic, general circulation model of the ocean with fine horizontal resolution are presented. As in Holland and Lin (1975a.b), mesoscale eddies spontaneously arise due to instabilities in the oceanic currents, giving rise to transient oceanic circulations that reach a statistical equilibrium. In these final equilibrium states, the interaction of the eddy field with the mean state is examined, and it is shown that the eddies determine the character of the large-scale mean flow. In particular, the eddies act to limit the amplitude of the mean flow in the upper ocean, are responsible for a downward energy propagation that fills the deep sea with eddy energy, and create a downward momentum flux which is responsible for the creation of deep, time-mean, abyssal gyres that are an important component of the vertically averaged mass transport in the ocean. Three new aspects of the mesoscale eddy problem are discussed. First, the Holland and Lin (1975a,b) results are ex.
Synergistic Responses of Tibetan Sheep Rumen Microbiota, Metabolites, and the Host to the Plateau Environment

Plateau adaptation in animals involves genetic mechanisms as well as coevolutionary mechanisms of the microbiota and metabolome of the animal. Therefore, the characteristics of the rumen microbiome and metabolome, transcriptome, and serum metabolome of Tibetan sheep at different altitudes (4500 m, 3500 m, and 2500 m) were analyzed. The results showed that the rumen differential metabolites at 3500 m and 4500 m were mainly enriched in amino acid metabolism, lipid metabolism, and carbohydrate metabolism, and there was a significant correlation with microbiota. The differentially expressed genes and metabolites at middle and high altitudes were coenriched in asthma, arachidonic acid metabolism, and butanoate and propanoate metabolism. In addition, the serum differential metabolites at 3500 m and 4500 m were mainly enriched in amino acid metabolism, lipid metabolism, and metabolism of xenobiotics by cytochrome P450, and they were also related to microbiota. Further analysis revealed that rumen metabolites accounted for 7.65% of serum metabolites. These common metabolites were mainly enriched in metabolic pathways and were significantly correlated with host genes (p < 0.05). This study found that microbiota, metabolites, and epithelial genes were coenriched in pathways related to lipid metabolism, energy metabolism, and immune metabolism, which may be involved in the regulation of Tibetan sheep adaptation to plateau environmental changes.
Coupling Cancellation Using Coupling Stubs for MIMO Array Applications

A novel decoupling method using coupling stubs is presented to design a wideband 8 × 8 multiple-input–multiple-output (MIMO) array. The array element consists of two tightly coupled printed inverted-F antennas (PIFAs), which are directly contacted and back-to-back for a compact structure. To decouple this PIFA pair, coupling stubs are elaborately utilized to cancel the different couplings. Detailed equivalent circuit and coupling parameter analyses show that the introduced capacitive coupling from the coupled stubs can well cancel the original inductive coupling in the PIFA pair in the lower frequency band, and the introduced inductive coupling can cancel the original capacitive coupling in the upper-frequency band. Thus, because of the complementary cancellation, the coupling in the original antenna pair is successfully reduced with a wide isolation bandwidth. The 8 × 8 MIMO PIFA pair array was fabricated and measured for the performance investigation. A wide impedance bandwidth of 3.3–4.88 GHz (38.6%) is achieved with the isolation higher than 10.2 dB. In addition, the envelope correlation coefficient of less than 0.092 is obtained for MIMO applications.
Five year (2004–2009) observations of upper tropospheric water vapor and cloud ice from MLS and comparisons with GEOS-5 analyses

[1] This paper gives an overview of August 2004 through February 2010 upper tropospheric (UT) water vapor (H2O) and ice water content (IWC) from the Aura Microwave Limb Sounder (MLS) and comparisons with outputs from the NASA Goddard Earth Observing System Version 5 (GEOS-5) data assimilation system. Both MLS and GEOS-5 show that high values of H2O and IWC at 215 to 147 hPa are associated with areas of deep convection. They exhibit good (within ∼15%) agreement in IWC at these altitudes, but GEOS-5 H2O is ∼50% (215 hPa) to ∼30% (147 hPa) larger than MLS values, possibly due to higher temperatures in the data assimilation system at these altitudes. A seasonally migrating band of tropical deep convection is clearly evident in both the MLS and GEOS-5 UT H2O and IWC, but GEOS-5 produces a weaker intertropical convergence zone than MLS. MLS and GEOS-5 both show spatial anticorrelation between IWC and H2O at 100 hPa, where low H2O is associated with low temperatures in regions of tropical convection. At 100 hPa, GEOS-5 produces 50% less IWC and 15% less H2O in the tropics, and ∼20% more H2O in the extratropics, than does MLS. Behavior of the 100 hPa H2O is consistent with it being controlled by temperature. The seasonal cycle in the vertical transport of tropical mean H2O from ∼147 hPa to ∼10 hPa appears much stronger in MLS than in GEOS-5. The UT IWC and H2O interannual variations, from both MLS and GEOS-5, show clear imprints of the El Nino–Southern Oscillation.