Miracle-dz/UniFAR-FTUs huggingface dataset:
Weakly compact operators into sequence spaces: A counterexample

In a recent paper Gutierrez and Villanueva have used, without giving a detailed proof, an analogue of a well-known result of Ryan characterizing the weakly compact operators from a Banach space E into the space c 0 (X) of null sequences in a Banach space X. In this note a counterexample is given showing that in the statement of Gutierrez and Villanueva an additional condition is needed.
A new astronomical method for determining the brightness of the night sky and its application to study long-term changes in the level of light pollution

In this paper, I present a new method that has been developed for determining the brightness of a cloudless night sky, on the basis of widely available amateur observations of comets. The tests show the correctness of the method, which makes it possible to determine the level of light pollution, deﬁned as the brightness of the artiﬁcial sky glow, through the use of the archival observations of comets. The use of data bases of comet observations in Poland in the period 1994–2009 has led to a positive veriﬁcation of the known model map of the brightness of the night sky. Also, it has been possible to ﬁnd changes in the level of light pollution in this period, at the selected observation sites.
A Review on Direct Digital Conversion Techniques for Biomedical Signal Acquisition

Biomedical signals such as Electrocardiogram (ECG), Electroencephalogram (EEG) and photoplethysmography (PPG) are recorded routinely to provide helpful information for early diagnosis of disease. Low power consumption is very important to allow long-term ambulatory monitoring with battery-powered systems. A direct digital conversion (DDC) technique has been proposed in recent years, which employs preamplifier and data converters, reducing the complexity of the readout chain and thus its power consumption. This paper provides a review on DDC for biopotential signals and bio-optical signal acquisition. The state-of-the-art DDC-based readout architectures together with circuit implementations are provided.
GDF15 Promotes the Osteogenic Cell Fate of Periodontal Ligament Fibroblasts, thus Affecting Their Mechanobiological Response

Periodontal ligament fibroblasts (PdLFs) exert important functions in oral tissue and bone remodeling following mechanical forces, which are specifically applied during orthodontic tooth movement (OTM). Located between the teeth and the alveolar bone, mechanical stress activates the mechanomodulatory functions of PdLFs including regulating local inflammation and activating further bone-remodeling cells. Previous studies suggested growth differentiation factor 15 (GDF15) as an important pro-inflammatory regulator during the PdLF mechanoresponse. GDF15 exerts its effects through both intracrine signaling and receptor binding, possibly even in an autocrine manner. The extent to which PdLFs are susceptible to extracellular GDF15 has not yet been investigated. Thus, our study aims to examine the influence of GDF15 exposure on the cellular properties of PdLFs and their mechanoresponse, which seems particularly relevant regarding disease- and aging-associated elevated GDF15 serum levels. Therefore, in addition to investigating potential GDF15 receptors, we analyzed its impact on the proliferation, survival, senescence, and differentiation of human PdLFs, demonstrating a pro-osteogenic effect upon long-term stimulation. Furthermore, we observed altered force-related inflammation and impaired osteoclast differentiation. Overall, our data suggest a major impact of extracellular GDF15 on PdLF differentiation and their mechanoresponse.
Preamp Decoupling - Eigenvalue Solution Approach

Introduction Over the last 30 years of MRI clinical usage, almost all subparts of the system have been redesigned or improved. In the early days of the MRI transmission and receiving have been performed with the same volume body coil. Starting with the late eighties several groups proposed taking advantage of multiple coils during receive cycle of the MR sequence [1,2]. Utilization of the multiple channel coils allows improved SNR, which can be fructified into increased resolution or reduced scan time. One of the major problems an RF engineer encounters when designing a multi-channel RF coil is the element-from-element decoupling. There are three techniques, with some sub-varieties, habituated in achieving acceptable decoupling: inductive decoupling, capacitive decoupling and so called “preamp decoupling”. Inductive decoupling, consisting in partial overlap of the coils so that cancellation of magnetic fluxes between neighboring coils occurs, is the most often been used because it is geometrically fixed, does not need tuning and permits decoupling of the coils in a large broadband. Capacitive decoupling is used when topology and position of the element cannot be changed [3]. It consists in an introduction of a decoupling capacitor in series with the mutual inductance of the two elements, allowing narrow band decoupling of the two imaging channels centered at system frequency. The most modern decoupling method is the so-called “preamp decoupling”[2], which consists in bringing a low impedance preamp as close as possible to the coil element and inserting it into a parallel resonance trap which itself is in series with the coils element. This method allows decoupling of the coil elements placed far from each other (next nearest of more distant neighbors), which exhibits week coupling and cannot be decoupled by other means. Although there are many interpretation of this techniques based on transmission line theory [1,4], we consider that an eigenvalue interpretation [5] is closer to the multiple-degree-of-freedom electrical oscillator, which the MR phased array RF coil represents par excellence. Theory The mathematical model used to demonstrate our point is applied to the system of the two neighboring elements with inserted preamps (Figure 1). The inductances of the coil elements are denoted by Ls1 and Ls2, resistances including the load effect of the lossy phantom Rs1 and Rs2, mutual inductance by M, series capacitance of the coil elements by Cs1 and Cs2, parallel capacitances by Cp1 and Cp2 and preamp impedance by Rp1 and Rp2. Lagrangean of the system is derived and Euler-Lagrange equations are written for the unknown currents through the elements Is1 and Is2 and the currents trough the preamps Ip1 and Ip2 with source voltages Vs1 and Vs2 (1). This system of equations can be generalized for any number of elements in a multi channel array coil (2N equations for N channels).
CAFE: A Cross-Attention Based Adaptive Weighting Fusion Network for MODIS and Landsat Spatiotemporal Fusion

Dense medium-resolution images play an important role in time-series geoscience applications. However, due to technical limitations, remote sensing imaging systems inevitably trade off temporal frequency and spatial swaths, resulting in difficulties to acquire images simultaneously with high spatial and temporal resolution. To overcome this limitation, under the framework of residual learning, we propose a cross-attention-based adaptive weighting fusion network (CAFE) for MODIS-Landsat spatiotemporal fusion to generate dense medium-resolution images. Based on the cross-attention mechanism, we propose multichannel separated cross-attention (MSCA) and full-feature joint cross-attention (FJCA) blocks to enhance spatial resolution and retain spectral signatures from the perspectives of band-wise processing and full-feature joint processing, respectively. The adaptive temporal difference weighting mechanism (ATDWM) is proposed to improve the ability to capture dynamic land surface changes. Besides, we employ an adaptive fusion loss function to constrain the network training. Experimental results indicate that the developed method is superior to several existing algorithms in terms of visual evaluation and quantitative evaluation and it can generate high-quality fusion results in scenarios of both subtle and dramatic temporal changes. Codes are available at https://github.com/LiupengLin/CAFE.
A Critical Evaluation of Central Bank of Nigeria (CBN) Cash-less Policy, Currency Redesign, Financial Performance and Macroeconomy: The Socio- Economic Ramifications perspectives

The reform of the financial sector is a critical component for the process of economic growth and development. These views are abundantly emphasised in empirical literatures that relate financial sector expansion to economic growth. Recognising this fact, Nigerian economic managers have focussed on the banking sector as a route to impact economic policy changes and policy shifts. The most recent of these financial sectors economic policy was the formal introduction of cashless financial policy in January 2012. The advantages and disadvantages of the cashless policy with the Naira redesign strategy on financial performance and the Nigerian macroeconomy were analysed in this research. This research study employed a systematic literature review (SLR) to examine this. A SLR was performed using a sample of 100 research articles chosen from a pool of 400 papers obtained from Scopus, Web of Science, Google Scholar, ABS journals and, among other sources. As a result, the cashless policy provides enormous advantages to the financial industry. It was suggested that sufficient infrastructural and legal framework should be enhanced to assist in facilitating the effective implementation of the policy.
Forming the Character of Discipline and Responsibility Through Character Education

A nation with strong character can become a nation with dignity and respect by other nations in the world. There is a discipline which is a very important character to be applied in the previous educational environment and in tertiary institutions besides the responsibility discipline character education which is very important to be applied in the everyday environment. Seeing the current condition of students, students have experienced a decline in terms of applying the character of discipline and character of responsibility in carrying out lecture assignments. This study aims to analyze the character of discipline and responsibility through character education, describing the views of lecturers in shaping the character of discipline and responsibility in tertiary institutions. The research method used is qualitative research where the data collection technique is to review literature books, journal entries that have something to do with the problem being discussed. The results of the study can be concluded that in the implementation of discipline and responsibility character education for students there are internal and external factors that affect the decline in discipline and loss of student responsibility. One way to remove these obstacles is through habituation which can change the character of student discipline and responsibility. Character education in tertiary institutions is needed to form and develop students to become individuals with character and strengthen the character acquired by students at the previous level.
Issues Regarding the Measurement of Turbulence Properties in Bubble Plumes

This paper discusses different issues that appear when characterizing turbulence in two-phase, air-water flows, in relatively deep containers. The flows correspond to bubble plumes with relatively large bubble diameters. Results of velocity time series obtained with the help of Acoustic Doppler Velocimeters (ADVs) are presented and analyzed. The post-processing of those signals is discussed in detail, presenting a methodology to separate air velocity from water velocity using ADV. Turbulence statistics, obtained from the time series, are also presented. Specifically, spatial distributions for the turbulent kinetic energy are analyzed. An interpretation of the behavior of the plume in the tank is also provided.
Tracing tourism with Bruno Latour: actor-network theory, critical proximity and down to earth

Bruno Latour passed away on October 9, 2022. At the age of 75, he was still actively querying pertinent questions of human existence on Earth through relational thought and tools he had developed since the 1970s. Latour’s intellectual work is difficult to classify into disciplinary categories; it traverses the boundaries of philosophy, anthropology and sociology, as well as geography, among others, and has also been translated for tourism studies. The question is how to account for the merits of someone, whose academic career has been focused on de-centering agency, merely as human capacity, and on understanding how power is distributed and networked? How does one sum up the work of a scholar whose work has impacted the social and human sciences in such profound ways? One way could be to do as Latour himself has done, and decenter human agency. Rather than approaching Latour as the actor and attempting to do justice to his legacy in a all-encompassing way (as if this is ever possible), we take Latour’s idea that every actor is a network, as a starting point. Thus, to pay tribute to his influence and inspiration, we re-trace the trajectory of his (net)work, and its journey into the field of tourism studies. As scholars who have learnt, enjoyed and benefited from Latours’ productive, generous, radical and wide ranging work, we follow trajectories, through which Latour’s work has inspired, informed and provoked us in order to demonstrate how his ways of thinking has moved into and affected tourism research. Three themes from Latours’ work that have been most valuable in our research are homed in on: actor-network theory, critical proximity and earthly relations. We conclude by highlighting future opportunities to engage, describe and compose tourism research with Latour in mind.
Arsenic in groundwater in the Grand Canyon region and an evaluation of potential pathways for arsenic contamination of groundwater from breccia pipe uranium mining

The Grand Canyon in northern Arizona is an international tourist destination, a home or sacred place to many Native Americans, and hosts some of the highest-grade uranium deposits in the United States. Although potential contamination of water resources by uranium from mining activities is a concern, other elements commonly associated with these uranium deposits may pose a greater risk to human populations in the area. This study presents an assessment of arsenic in groundwater in the Grand Canyon area. First, sampling results for arsenic are presented and areas with elevated arsenic concentrations are discussed. Potential pathways of groundwater contamination by arsenic from uranium mines are then discussed to elucidate situations and conditions under which elevated concentrations of arsenic might be expected to become mobilized from breccia-pipe uranium mining activities. Results for arsenic in groundwater in the study area were available for 652 samples collected from 230 sites. Arsenic concentrations in groundwater ranged from less than reporting limits in 60 samples to a maximum concentration of 875 μg/L at Pumpkin Spring. About 88% (202) of the sites sampled had a maximum arsenic concentration below the drinking water standard of 10 μg/L. Available data from near former or current breccia-pipe uranium mines in the area indicate limited evidence to-date of mining effects on elevated arsenic in groundwater, although slow groundwater flow paths in the region may result in extended times of decades or more for groundwater to reach discharge locations. Post-mining entry of groundwater into the shaft and underground mine workings, with subsequent transport of metal-enriched groundwater offsite, may be a potential pathway of groundwater arsenic contamination from mining, although concentrations would likely be attenuated by contact with sedimentary rock units and dilution with native groundwater along flow paths. Monitoring of perched groundwater at reclaimed mine sites post-reclamation could provide data on the effectiveness of clean-closure practices on protecting groundwater quality in the area.
A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond

State estimation (SE) is indispensable for the situational awareness of power systems. Conventional SE is fed by measurements collected from the supervisory control and data acquisition (SCADA) system. In recent years, available data sources have been greatly enriched with the deployment of phasor measurement units (PMUs), advanced metering infrastructure (AMI), intelligent electronic devices (IEDs), etc. The integration of multiple data sources provides unprecedented opportunities for enhancing the performance of SE, but also presents major challenges to resolve, including optimal multi-type-sensor co-placement, multiple reporting rates and asynchronization, diverse types of measured quantities, correlations between measurements, integration of online and historical data sources, and system and measurement uncertainties. This paper outlines the state of the art and research opportunities in this area by providing a comprehensive literature review and extensive discussions. It starts by presenting the motivations and challenges, followed by a summary of existing data sources for SE in power systems. Subsequently, for both transmission system (static and dynamic) and distribution system SE, existing methods are systematically reviewed and categorized based on the addressed challenges. Interesting attempts of using novel measurements in SE are also studied. Finally, the paper concludes by providing a detailed discussion on the remaining research gaps and future research directions to be explored.
The response of phytoplankton nutrient uptake kinetics to a wastewater treatment plant 
upgrade

Low phytoplankton biomass and depressed primary productivity in the northern San Francisco Estuary (nSFE) has been attributed to light availability, clam grazing and anthropogenic ammonium loading. Ammonium loading in the Sacramento River, primarily from wastewater effluent, has raised ambient ammonium concentrations in the nSFE to levels that are repressive to phytoplankton nitrate-N uptake and bloom formation. This study used a time series of nutrient, chlorophyll-a, primary productivity and nutrient uptake data to examine the response of phytoplankton and nutrient dynamics at Rio Vista, CA to a reduction in ammonium loading from an upgrade of the Regional San Wastewater Treatment Plant located upstream in Freeport, CA. Nutrient uptake kinetics experiments were also conducted to determine how phytoplankton nitrogen uptake rate changes across a range of substrate concentrations in a low ammonium system. A significant decline in ammonium-N concentration at Rio Vista was observed following the upgrade, along with a significant increase in nitrate-N uptake and chlorophyll-a concentration. Phytoplankton uptake versus substrate kinetics showed Michaelis Menten kinetics for both nitrate and ammonium. These data will inform modelers and stakeholders to interpret the broader ecological impacts of management actions like the upgrade.
A new model-based approach for recognizing occluded curved objects in dense-range images

Although the use of range imaging has been gaining popularity in 3D object recognition, it is still widely accepted that recognition of real world scenes, with possible occlusion, and based on a single view, is a difficult task. In this paper, some of these recognition problems are investigated. In particular, a new model-based matching technique is applied to recognize a scene with many occluded curved objects using a single range image viewed from any direction. The proposed method is capable of recognizing single objects as well as configurations of objects. The segmentation process is based on two newly developed directional curvature operators. The resulting data, expressed in terms of linear segments, cylindrical arcs and spherical arcs, is then transformed into a surface-based representation that is enforced by a boundary representation scheme. Objects in the scene are recognized using a matching strategy based on the generation of relative bases to models (RBM). If a match is found, the model appearance with reference to the RBM will be similar to that of the object in the absolute base. Once all objects have been recognized, the system attempts to match configurations, if there are any. By configuration here we mean, a set of primitive-objects related to each other by spatial relationships. The system has been tested on a large number of real range images and synthetic data. The experimental results have shown that the system can successfully recognize complex scene with an acceptable reliability and accuracy.
Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach

The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time processing at edge servers, existing message queue systems face challenges in adapting to changing system conditions, such as fluctuations in the number of devices, message size, and frequency. This necessitates the development of an approach that can effectively decouple message processing and handle workload variations in the AIoT computing environment. This study presents a distributed message system for AIoT edge computing, specifically designed to address the challenges associated with message ordering in such environments. The system incorporates a novel partition selection algorithm (PSA) to ensure message order, balance the load among broker clusters, and enhance the availability of subscribable messages from AIoT edge devices. Furthermore, this study proposes the distributed message system configuration optimization algorithm (DMSCO), based on DDPG, to optimize the performance of the distributed message system. Experimental evaluations demonstrate that, compared to the genetic algorithm and random searching, the DMSCO algorithm can provide a significant improvement in system throughput to meet the specific demands of high-concurrency AIoT edge computing applications.
Colored Local Type Inference (colored version) (black and white version)

We present a type system for a language based on F-sub, which allows certain type annotations to be elided in actual programs. Local type inference determines types by a combination of type propagation and local constraint solving, rather than by global constraint solving. We refine the previously existing local type inference system of Pierce and Turner [ Local Type Inference, POPL 98] by allowing partial type information to be propagated. This is expressed by coloring types to indicate propagation directions. Propagating partial type information allows us to omit type annotations for the visitor pattern, the analogue of pattern matching in languages without sum types.
Resilient and Robust QoS-Preserving Post-Fault VNF Placement

In the realm of network management and orchestration, such as Virtual Network Function (VNF) lifecycle management, the dynamicity of 5G networks raises the importance of reliability and robustness when determining optimal VNF placement. Specifically, after a fault has occurred, the set of services that must maintain a certain level of performance and quality depends on the interaction between VNFs. This letter proposes a novel robust optimization model for VNF placement during post-fault status, while addressing the resilience and reliability of the 5G network in testing. The model results are compared with a deterministic placement solution with varying demand uncertainties.