Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel Nonstationarity and Consistency for Beyond 5G and 6G: A Survey

As the fifth-generation (5G) wireless communication networks are at the stage of commercial deployment, beyond 5G (B5G)/sixth-generation (6G) wireless communication networks have also been under extensive research. In the B5G/6G era, the vision of the wireless communication network is the so-termed space-air-ground-sea integrated network (SAGSIN), which will focus on more various and dynamic communication scenarios, including vehicle-to-vehicle (V2V), high-speed train (HST), unmanned aerial vehicle (UAV), satellite, and maritime communications. Meanwhile, B5G/6G communication systems will also employ two potential technologies, i.e., millimeter wave (mmWave)-terahertz (THz) and ultra-massive multiple-input multiple-output (MIMO), and have a new development trend, i.e., integrated sensing and communication (ISAC) systems. For the successful design of B5G/6G communication systems, accurate and easy-to-use channel models, which can fully mimic the underlying characteristics and features of B5G/6G channels, are indispensable. However, more diverse communication scenarios, higher frequency band, larger-scale antenna array, and the emergence of ISAC systems in B5G/6G will bring two significant points of concern for wireless channels, i.e., channel non-stationarity and channel consistency. Channel non-stationarity is a typical channel characteristic, whereas channel consistency is an inherent channel physical feature. To capture those, extensive works have been carried out, but have not yet been adequately summarized, compared, and analyzed. This paper first provides the definitions of channel non-stationarity and channel consistency from mathematical and physical perspectives, and then discusses the necessity of capturing them for various wireless applications. Recent advances in the topic of capturing channel non-stationarity and channel consistency are further elaborated and investigated. Additionally, simulation results concerning them are provided and analyzed. Finally, promising and meaningful future research directions for this topic are outlined.
Traffic-Prediction-Based Optimal Control of Electric and Autonomous Buses

This letter considers electric and autonomous buses which have to follow a given route, including fixed stops, in extra-urban roads with a given timetable. A charging infrastructure is present in each stop, allowing to charge the bus batteries. An optimal control scheme is proposed in this letter in order to regulate the optimal speed of buses along the route and the stopping/charging times at stops. The proposed control scheme, acting in real time according to a receding-horizon logic, consists of two modules: a traffic prediction model and an optimal control problem solver. The traffic model measures the traffic state in real time, provides the traffic state prediction in the considered road stretch and, in particular, communicates the predicted average speed in each road section to the second module. This latter computes the optimal behavior of buses by optimizing their expected final energy level, by maximizing their compliance with the timetable and by reducing oscillations in the speed profile. Simulation results based on a real case study show the effectiveness of the proposed control scheme.
Chronic Toxicity of Primary Metabolites of Chloroacetamide and Glyphosate to Early Life Stages of Marbled Crayfish Procambarus virginalis

Simple Summary Due to the rising population, it is necessary to ensure sustainable agricultural management, especially in agricultural production. Therefore, using pesticides is the only way to reach a sufficient number of crops for the human population. However, using these agrochemicals has one big disadvantage—harmful effects on non-target species. Since aquatic ecosystems are essential for biota, fauna, flora, and humans, this study provides information about the toxicity of primary metabolites of commonly used glyphosate and acetochlor herbicides. Generally, it is known that pesticide degradation products may have lower, the same, or even higher toxicity than their parental compounds. Moreover, the developmental stages are more predisposed to be affected by pollution than adults, and consequently, in the worst case, it may affect the whole species population. Due to this reason, we studied the toxicity of these metabolites on embryolarval marbled crayfish—how they can affect their growth, ontogenetic development, behaviour, and gill morphology. Our study revealed that these two metabolites alone induce changes in behaviour, antioxidant enzymes, and gill morphology, even in combination. Nevertheless, there is a gap in the knowledge about pesticides’ metabolite toxicities, a small fraction of the hundreds with potential for entering the aquatic ecosystem. Therefore, chronic toxicity tests are suitable for evaluating the toxicity of aquatic pollution. Abstract Degradation products of herbicides, alone and in combination, may affect non-target aquatic organisms via leaching or runoff from the soil. The effects of 50-day exposure of primary metabolites of chloroacetamide herbicide, acetochlor ESA (AE; 4 µg/L), and glyphosate, aminomethylphosphonic acid (AMPA; 4 µg/L), and their combination (AMPA + AE; 4 + 4 µg/L) on mortality, growth, oxidative stress, antioxidant response, behaviour, and gill histology of early life stages of marbled crayfish (Procambarus virginalis) were investigated. While no treatment effects were observed on cumulative mortality or early ontogeny, growth was significantly lower in all exposed groups compared with the control group. Significant superoxide dismutase activity was observed in exposure groups, and significantly higher glutathione S-transferase activity only in the AMPA + AE group. The gill epithelium in AMPA + AE-exposed crayfish showed swelling as well as numerous unidentified fragments in interlamellar space. Velocity and distance moved in crayfish exposed to metabolites did not differ from controls, but increased activity was observed in the AMPA and AE groups. The study reveals the potential risks of glyphosate and acetochlor herbicide usage through their primary metabolites in the early life stages of marbled crayfish.
A comparison of design‐based and model‐based approaches for finite population spatial sampling and inference

The design‐based and model‐based approaches to frequentist statistical inference rest on fundamentally different foundations. In the design‐based approach, inference relies on random sampling. In the model‐based approach, inference relies on distributional assumptions. We compare the approaches in a finite population spatial context. We provide relevant background for the design‐based and model‐based approaches and then study their performance using simulated data and real data. The real data are from the United States Environmental Protection Agency's 2012 National Lakes Assessment. A variety of sample sizes, location layouts, dependence structures, and response types are considered. The population mean is the parameter of interest, and performance is measured using statistics like bias, squared error and interval coverage. When studying the simulated and real data, we found that regardless of the strength of spatial dependence in the data, the generalized random tessellation stratified (GRTS) algorithm, which explicitly incorporates spatial locations into sampling, tends to outperform the simple random sampling (SRS) algorithm, which does not explicitly incorporate spatial locations into sampling. We also found that model‐based inference tends to outperform design‐based inference, even for skewed data where the model‐based distributional assumptions are violated. The performance gap between design‐based inference and model‐based inference is small when GRTS samples are used but large when SRS samples are used, suggesting that the sampling choice (whether to use GRTS or SRS) is most important when performing design‐based inference. There are many benefits and drawbacks to the design‐based and model‐based approaches for finite population spatial sampling and inference that practitioners must consider when choosing between them. We provide relevant background contextualizing each approach and study their properties in a variety of scenarios, making recommendations for use based on the practitioner's goals.
An autonomous method for diagnosing raceway defects and misalignment in a self-aligning rolling-element bearing

This paper presents an autonomous method to diagnose a double-row self-aligning ball bearing for any dynamic misalignment or localized defects, using vibration signals. The frequency spectra from the experimental investigation revealed that irrespective of the health condition of the bearing i.e. either healthy or defective, the frequency spectrum had a clear cage frequency peak whenever the system was under dynamic-misalignment. An improved version of Harmonic Product Spectrum (HPS) called sideband product spectrum (SPS) was used to identify the cage frequency peaks which was preprocessed using kurtosis-based band-pass filter and parameter-optimized variational mode decomposition (VMD) algorithm. A mathematical model is also presented to analyze the dynamic behavior of double-row self-aligning ball bearing under such conditions. From the model, it was realized that during misalignment, the contact load shared by the rolling elements, generates some moment which has a tendency to rotate the bearing’s inner-race about the radial axis and thus resulting in a wobbly rotary motion. This wobbly motion of the inner race in fact characterizes the bearing for dynamic misalignment. The simulated results were in accordance with the experimentally obtained results.
Impact of a Carboxymethyl Cellulose Coating Incorporated with an Ethanolic Propolis Extract on the Quality Criteria of Chicken Breast Meat

Recently, the demand for composite edible coatings has increased significantly as a new trend to confront the serious processing and storage problems that always arise regarding chicken meat. We aim to develop a carboxymethyl cellulose (CMC) coating containing various concentrations (0, 1, 2, 3, and 4%) of an ethanolic propolis extract (EPE) to maintain the quality and extend the shelf life of chicken breast meat stored at 2 °C for 16 days. The influence of the CMC and EPE coating on the physicochemical and microbiological quality parameters of chicken breast meat, e.g., pH, color, metmyoglobin (MetMb), lipid oxidation (thiobarbituric acid reactive substance, TBARS), and microbiological and sensory analyses, was studied. Significantly lower weight loss and pH (p ≤ 0.05) were noted in the coated samples compared with the uncoated samples (control) over the storage period. MetMb content was significantly reduced (p ≤ 0.05) in the coated samples compared to the control. Additionally, the addition of EPE to CMC was more effective in inhibiting microbial growth, preventing lipid oxidation, and keeping the overall acceptability of coated chicken breast meat compared to the control. This work presents CMC and EPE as alternative preservatives to produce active packaging coatings.
Land‐use change shifts and magnifies seasonal variations of the decomposer system in lowland tropical landscapes

Abstract Deforestation and agricultural expansion in the tropics affect local and regional climatic conditions, leading to synergistic negative impacts on land ecosystems. Climatic changes manifest in increased inter‐ and intraseasonal variations and frequency of extreme climatic events (i.e., droughts and floods), which have evident consequences for aboveground biodiversity. However, until today, there have been no studies on how land use affects seasonal variations below ground in tropical ecosystems, which may be more buffered against climatic variation. Here, we analyzed seasonal variations in soil parameters, basal respiration, microbial communities, and abundances of soil invertebrates along with microclimatic conditions in rainforest and monocultures of oil palm and rubber in Sumatra, Indonesia. About 75% (20 out of 26) of the measured litter and soil, microbial, and animal parameters varied with season, with seasonal changes in 50% of the parameters depending on land use. Land use affected seasonal variations in microbial indicators associated with carbon availability and cycling rate. The magnitude of seasonal variations in microbial parameters in the soil of monocultures was almost 40% higher than in the soil of rainforest. Measured parameters were associated with short‐term climatic conditions (3‐day period air humidity) in plantations, but not in rainforest, confirming a reduced soil buffering ability in plantations. Overall, our findings suggest that land use temporally shifts and increases the magnitude of seasonal variations of the belowground ecosystem compartment, with microbial communities responding most strongly. The increased seasonal variations in soil biota in plantations likely translate into more pronounced fluctuations in essential ecosystem functions such as nutrient cycling and carbon sequestration, and these ramifications ultimately may compromise the stability of tropical ecosystems in the long term. As the observed seasonal dynamics is likely to increase with both local and global climate change, these shifts need closer attention for the long‐term sustainable management of plantation systems in the tropics.
Assessing Wave Attenuation With Rising Sea Levels for Sustainable Oyster Reef-Based Living Shorelines

In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.
Detection of Weeds Growing in Alfalfa Using Convolutional Neural Networks

Alfalfa (Medicago sativa L.) is used as a high-nutrient feed for animals. Weeds are a significant challenge that affects alfalfa production. Although weeds are unevenly distributed, herbicides are broadcast-applied in alfalfa fields. In this research, object detection convolutional neural networks, including Faster R-CNN, VarifocalNet (VFNet), and You Only Look Once Version 3 (YOLOv3), were used to indiscriminately detect all weed species (1-class) and discriminately detect between broadleaves and grasses (2-class). YOLOv3 outperformed other object detection networks in detecting grass weeds. The performances of using image classification networks (GoogLeNet and VGGNet) and object detection networks (Faster R-CNN and YOLOv3) for detecting broadleaves and grasses were compared. GoogLeNet and VGGNet (F1 scores ≥ 0.98) outperformed Faster R-CNN and YOLOv3 (F1 scores ≤ 0.92). Classifying and training various broadleaf and grass weeds did not improve the performance of the neural networks for weed detection. VGGNet was the most effective neural network (F1 scores ≥ 0.99) tested to detect broadleaf and grass weeds growing in alfalfa. Future research will integrate the VGGNet into the machine vision subsystem of smart sprayers for site-specific herbicide applications.
Interest rate options close to expiry

We use an asymptotic expansion to study the behavior of American- style interest rate caplets and floorlets close to expiry, under the assumption that interest rates obey a mean-reverting random walk as given by the Vasicek model. Series solutions are obtained for the location of the free boundary and the price of the option for both the caplet and floorlet. AMS 2000 Mathematics Subject Classification. 91B28.
Biofilm Formation and Antimicrobial Susceptibility of E. coli Associated With Colibacillosis Outbreaks in Broiler Chickens From Saskatchewan

The global poultry industry has grown to the extent that the number of chickens now well exceeds the number of humans on Earth. Escherichia coli infections in poultry cause significant morbidity and economic losses for producers each year. We obtained 94 E. coli isolates from 12 colibacillosis outbreaks on Saskatchewan farms and screened them for antimicrobial resistance and biofilm formation. Fifty-six isolates were from broilers with confirmed colibacillosis, and 38 isolates were from healthy broilers in the same flocks (cecal E. coli). Resistance to penicillins, tetracyclines, and aminoglycosides was common in isolates from all 12 outbreaks, while cephalosporin resistance varied by outbreak. Most E. coli were able to form biofilms in at least one of three growth media (1/2 TSB, M63, and BHI broth). There was an overall trend that disease-causing E. coli had more antibiotic resistance and were more likely to form biofilms in nutrient-rich media (BHI) as compared to cecal strains. However, on an individual strain basis, there was no correlation between antimicrobial resistance and biofilm formation. The 21 strongest biofilm forming strains consisted of both disease-causing and cecal isolates that were either drug resistant or susceptible. Draft whole genome sequencing indicated that many known antimicrobial resistance genes were present on plasmids, with disease-causing E. coli having more plasmids on average than their cecal counterparts. We tested four common disinfectants for their ability to kill 12 of the best biofilm forming strains. All disinfectants killed single cells effectively, but biofilm cells were more resistant, although the difference was less pronounced for the disinfectants that have multiple modes of action. Our results indicate that there is significant diversity and complexity in E. coli poultry isolates, with different lifestyle pressures affecting disease-causing and cecal isolates.
Collective induced phenomena in systems of coupled oscillators

This thesis will explore the deterministic dynamics of systems of coupled oscillators. In particular, the focus of the thesis will be concerned with the transport properties of these systems. Of interest is how particles work together, cooperatively, to achieve directed transport. For this reason, the strength of the coupling between the particles will serve as the main control parameter. Further, ensemble dynamics will serve to highlight some of the collective effects of these systems. The thesis will be split into two parts. The first part will look at a class of autonomous Hamiltonian systems, while the second part will consider a class of driven and damped systems. A common feature of these systems is that they contain a spatially open component that will facilitate long range transport. More precisely, transport proceeds in a spatially symmetric and periodic multiple well potential. Thus transport will be characterised by particles overcoming successive energetic barriers created by the potential landscape. The cooperative effects between the particles will become apparent in Part I when autonomous Hamiltonian systems are considered. In the uncoupled limit the full systems decompose into two integrable subsystems and the dynamics are fully understood. However, the dynamics become more complicated when the particles are coupled. As these systems are conservative a coordinated energy exchange between the particles is often required for directed transport to ensue. Interestingly, these systems contrast well with the nonautonomous one and a half degree-of-freedom Hamiltonian systems, where transport occurs through intermittent periods of directed motion in so-called ballistic channels. The autonomous two degree-of-freedom counterpart considered here relies on a rather different mechanism for directed transport that will be provided solely by regular structures in phase-space. With the inclusion of external driving and damping (Part II) the transport dynamics are controlled by various coexisting attractors in phase-space. The nature and stability of these attractors is determined by the system parameters. As before, cooperative e�ects will play a key role when it comes to particle transport. Notably, it will be seen that coupling between the particles can result in a suppression of chaos that will allow for, for example, collective periodic motion of rotational type. Particular attention will be paid to the phase-space structures and how they change as the coupling parameter is varied. Throughout the thesis these nonlinear systems, and their transport features, will be explored using analytical and numerical means. A number of model systems will also be introduced to further illuminate the systems dynamics.
Enzymatic aqueous extraction with ultrasound: a prospective overview on the state of the art

The oil extracted from different oleaginous raw materials is usually obtained through mechanical pressing, associated or not with organic solvents. The objective of this prospection was to evaluate if the aqueous enzymatic extraction (AEE) with ultrasound should be a cleaner and more effective technology for the production of lipids and other products. The state of the art of this issue was observed with a focus on food, and more precisely oleaginous fruits and seeds. The advanced search in the Science Direct, Scopus and Web of Science (WOS) databases was carried out in July 2021. A total of 1,099, 79, and 46 scientific papers were retrieved within the Science Direct, WOS and Scopus databases, respectively. Identifying the experiments made in these studies with EAE and ultrasound, there was a selection of 24, 13 and 4 original articles in the investigated bases. The articles described that ultrasound used as pre-treatment or during AEE increased the yield of food lipid extraction. This prospection described that EAE technology and ultrasound are impactful techniques in obtaining lipids. The advanced research highlighted that there is a gap related to researches with oleaginous matrices and the replacement of conventional techniques with clean techniques can be economically feasible.