Small Systems Research Articles

TomFi: Small Object Tracking Using Commodity WiFi

Rodent infestation has always been one of the most severe threats to humans, which to solve consumes massive manpower and resources. People usually use traps or poisons to treat rat infestation. Such passive countermeasures are inefficient. Damage often occurs when the rats are finally trapped or killed, not to mention the potential risk to injure humans or cause pollution. In this article, we propose a WiFi-based active small object tracking system named TomFi . The core components of TomFi include several deep learning techniques that bridge rat locations/motions and WiFi signal variations (represented by the channel state information). TomFi first employs a detection model to detect the appearance of the rat and then localize it based on a two-branch localization model. Through the design of the two-branch localization model, to our best knowledge, we are the first to solve the information loss and distortion problem. We conducted extensive experiments in both the laboratory environment and real-world kitchen scenarios. The results show that TomFi can achieve a detection success rate of 99%+ and a centimeter-level localization accuracy in real time.

Three-phase equilibria of hydrates from computer simulation. I. Finite-size effects in the methane hydrate.

Clathrate hydrates are vital in energy research and environmental applications. Understanding their stability is crucial for harnessing their potential. In this work, we employ direct coexistence simulations to study finite-size effects in the determination of the three-phase equilibrium temperature (T3) for methane hydrates. Two popular water models, TIP4P/Ice and TIP4P/2005, are employed, exploring various system sizes by varying the number of molecules in the hydrate, liquid, and gas phases. The results reveal that finite-size effects play a crucial role in determining T3. The study includes nine configurations with varying system sizes, demonstrating that smaller systems, particularly those leading to stoichiometric conditions and bubble formation, may yield inaccurate T3 values. The emergence of methane bubbles within the liquid phase, observed in smaller configurations, significantly influences the behavior of the system and can lead to erroneous temperature estimations. Our findings reveal finite-size effects on the calculation of T3 by direct coexistence simulations and clarify the system size convergence for both models, shedding light on discrepancies found in the literature. The results contribute to a deeper understanding of the phase equilibrium of gas hydrates and offer valuable information for future research in this field.

How the blast-wave model describes PID hadron spectra from 5 TeV p-Pb collisions

The blast-wave (BW) spectrum model has been applied extensively to nucleus-nucleus collision data with the intention to demonstrate formation of a quark-gluon plasma (QGP) in more-central A-A collisions. More recently the BW model has been applied to p-p, d-Au and p-Pb collisions. Such results are interpreted to indicate that “collectivity” (flows) and QGP appear in smaller systems. In this talk I review BW analysis of identified-hadron spectra from 5 TeV p-Pb collisions and examine the shape evolution of model spectra with collision centrality. I evaluate data-model fit quality using conventional statistical measures. I conclude that the BW model is not a valid data model.

Comparison of power system flow analysis methods of IEEE 5-bus system

Load flow analysis is a crucial tool used by electrical engineers for simulating the power system. It is aimed at examining the most possible way of operating and controlling a power system and the exchange of power flow within the power system. For the economic and optimal operation of power systems, the most essential task is to find the most feasible solution technique suitable and efficient for the study of power generation, transmission, and distribution. There are various power flow study solution techniques, and for some solution techniques, the simulation of the system can take a long time, which prevents the simulator from attaining a higher accuracy result for the power flow simulation due to the interrupting rise and fall in power demand from the consumer, which also affects the power generation as well. This paper discusses the comparison of various techniques used in load flow studies with the assistance of a small power system with five buses. The numerical solution techniques used are the fast decoupled load flow solution technique, the Gauss-Seidel solution technique, and the Newton-Raphson solution technique for a power flow study solution on an IEEE 5-bus using MATLAB/Simulink.

Development of Hydroelectric Power Generation from Water Pipelines

Abstract: Pico hydroelectricity is a good way to make clean energy. We're talking about making a system that gets water from the tanks in houses. The water moving through household pipes can make electricity that we can store. To make this system work even better, we've thought of some new ideas: an air bladder to keep the water pressure steady, U-tube piping, and a big nozzle pipe at the end. This system doesn't need any fuel and doesn't need much fixing to keep working. Our plan is to make a small hydro system that can use the energy stored in a water tank to make power. This power can then be used in homes for different things

Economic impact of peste des petits ruminants on small ruminant production in Senegal: Gender considerations within a system dynamics modelling approach

CONTEXTPeste des petits ruminants (PPR) remains a persistent challenge for small ruminant production in Senegal, leading to economic losses for livestock keepers. Gender dynamics and socio-cultural factors influence production decisions at the household level. Despite its relevance, economic impact models of PPR have not incorporated gender dynamics. OBJECTIVEThis paper seeks to redress this gap by disaggregating the farm-level impacts of PPR based on the gender of the household head and implementers of routine and management activities in small ruminant production at the household level. METHODSTo quantify the gendered economic impacts of PPR, a system dynamics model was developed with four modules: integrated production-epidemiology, economics and profitability, disease control, and marketing. The model was parameterised based on survey data from 747 households in 49 agro-pastoral and pastoral villages in Senegal and augmented by secondary data. The model was validated (structurally and behaviourally) and simulated for 30 years with a weekly timestep. A set of disease scenarios were run for ten different farm household typologies based on the gender of the household head and household members who perform production management activities (like purchasing, selling, gifting, and vaccinating animals) and routine activities (like feeding, cleaning pens, and caring for sick animals). RESULTS AND CONCLUSIONSModel results estimated annual reductions in farm profitability of 51% to 61% with a hypothetical 25% incidence rate of PPR, corresponding to an average of $1051 to $1246 USD lost per household per year. In the two most impacted household typologies, management activities were performed by either men only or women only, and in the three least impacted household typologies, management activities were shared by men and women. The least impacted household typology with the highest gross margins without PPR ($2429 USD per year) and the lowest percentage of loss (51%) was female-headed households with men and women doing management tasks and primarily women or girls doing routine activities. SIGNIFICANCESHouseholds with both women and men engaged in management activities were less impacted by PPR, highlighting the crucial role of women's agency in management decisions taken in small ruminant production at the farm level. The findings further provide the empirical grounding for considering gender dynamics in interventions to control PPR and other livestock diseases in small ruminant production systems.

A Cyber-Physical Testbed for IoT Microgrid Design and Validation

Microgrids are small power systems, often equipped with renewable energy sources, that are alternatives or supplementary to utility grids. Many studies have been conducted on the design and implementation of microgrids and their interconnects to utility grids, and investigations have been extended to the use of Internet of Things technology (IoT) to monitor and operate such power grids. However, the broad applications of the IoT technology itself also call for a green energy solution. This paper investigates how to power local IoT applications via an integration of a microgrid and the utility grid. Together, we call such a system an IoT microgrid. The goal of an IoT microgrid is to maintain the availability of IoT applications while saving energy costs, and this is achieved by sustaining IoT applications via local renewable energy from a microgrid and by mitigating the intermittent power supply using the utility grid. This paper characterizes the IoT microgrid and proposes a configurable cyber-physical testbed for its design and validation. The testbed incorporates the hardware-in-the-loop (HIL) approach, where real-time simulation is integrated with physical elements for quick prototyping of those components in an IoT microgrid. The paper concludes with an example implementation of the proposed testbed, which demonstrates its use for validating both an IoT microgrid and the IoT application it sustains.

Large-scale bioreactor production of extracellular vesicles from mesenchymal stromal cells for treatment of acute radiation syndrome

BackgroundHematopoietic acute radiation syndrome (H-ARS) occurring after exposure to ionizing radiation damages bone marrow causing cytopenias, increasing susceptibility to infections and death. We and others have shown that cellular therapies like human mesenchymal stromal cells (MSCs), or monocytes/macrophages educated ex-vivo with extracellular vesicles (EVs) from MSCs were effective in a lethal H-ARS mouse model. However, given the complexity of generating cellular therapies and the potential risks of using allogeneic products, development of an “off-the-shelf” cell-free alternative like EVs may have utility in conditions like H-ARS that require rapid deployment of available therapeutics. The purpose of this study was to determine the feasibility of producing MSC-derived EVs at large scale using a bioreactor and assess critical quality control attributes like identity, sterility, and potency in educating monocytes and promoting survival in a lethal H-ARS mouse model.MethodsEVs were isolated by ultracentrifugation from unprimed and lipopolysaccharide (LPS)-primed MSCs grown at large scale using a hollow fiber bioreactor and compared to a small scale system using flasks. The physical identity of EVs included a time course assessment of particle diameter, yield, protein content and surface marker profile by flow-cytometry. Comparison of the RNA cargo in EVs was determined by RNA-seq. Capacity of EVs to generate exosome educated monocytes (EEMos) was determined by qPCR and flow cytometry, and potency was assessed in vivo using a lethal ARS model with NSG mice.ResultsPhysical identity of EVs at both scales were similar but yields by volume were up to 38-fold more using a large-scale bioreactor system. RNA-seq indicated that flask EVs showed upregulated let-7 family and miR-143 micro-RNAs. EEMos educated with LPS-EVs at each scale were similar, showing increased gene expression of IL-6, IDO, FGF-2, IL-7, IL-10, and IL-15 and immunophenotyping consistent with a PD-L1 high, CD16 low, and CD86 low cell surface expression. Treatment with LPS-EVs manufactured at both scales were effective in the ARS model, improving survival and clinical scores through improved hematopoietic recovery. EVs from unprimed MSCs were less effective than LPS-EVs, with flask EVs providing some improved survival while bioreactor EVs provide no survival benefit.ConclusionsLPS-EVs as an effective treatment for H-ARS can be produced using a scale-up development manufacturing process, representing an attractive off-the-shelf, cell-free therapy.

The functional generalization of the Boltzmann-Vlasov equation and its gauge-like symmetry

We argue that one can model deviations from the ensemble average in non-equilibrium statistical mechanics by promoting the Boltzmann equation to an equation in terms of functionals , representing possible candidates for phase space distributions inferred from a finite observed number of degrees of freedom. We find that, provided the collision term and the Vlasov drift term are both included, a gauge-like redundancy arises which does not go away even if the functional is narrow. We argue that this effect is linked to the gauge-like symmetry found in relativistic hydrodynamics [Ann. Phys. 442, 168902 (2022)] and that it could be part of the explanation for the apparent fluid-like behavior in small systems in hadronic collisions and other strongly-coupled small systems [Annu. Rev. Nucl. Part. Sci. 68, 211 (2018)]. When causality and Lorentz invariance are omitted this problem can be look at via random matrix theory show, and we show that in such a case thermalization happens much more quickly than the Boltzmann equation would infer. We also sketch an algorithm to study this problem numerically.

Research Progress of High-Speed Data Transmission Technology for Lightweight and Small-Sized Unmanned Aerial Vehicle Platforms

With the continuous development of science and technology, UAV technology has been widely used in various fields. As an essential part, light and small UAV platforms have the advantages of being small, lightweight, and easy to operate and thus have been widely used in aerial photography, monitoring, rescue, and other fields. However, the traditional data transmission method can no longer meet the demand for the data transmission speed and stability of small and light UAV platforms. Wireless optical communication has the advantages of being high-speed and license-free, as well as having a large bandwidth strong anti-interference ability, and good confidentiality. Therefore, this paper aims to study high-speed data transmission technology for light and small UAV platforms to improve their transmission speed and stability. In this paper, the characteristics and advantages of UAV airborne laser communication are first elaborated to illustrate the advancements and importance of data transmission technology based on light and small UAV platforms. Then, the composition of a UAV airborne laser communication system is clarified to illustrate the feasibility of conducting airborne laser communication research. Then, the current domestic and international research status of people on light and small UAV airborne laser communication high-speed data transmission systems is reviewed, and its key technical features are analyzed. Finally, the prospects for its application and development trend are investigated.

Rationale for the extrapolation procedure in selected configuration interaction.

Selected configuration interaction (SCI) methods have emerged as state-of-the-art methodologies for achieving high accuracy and generating benchmark reference data for ground and excited states in small molecular systems. However, their precision relies heavily on extrapolation procedures to produce a final estimate of the exact result. Using the structure of the exact electronic energy landscape, we provide a rationale for the common linear extrapolation of the variational energy as a function of the second-order perturbative correction. In particular, we demonstrate that the energy gap and the coupling between the so-called internal and external spaces are the key factors determining the rate at which the linear regime is reached. Starting from the first principles, we also derive a new non-linear extrapolation formula that improves the post-processing of data generated from SCI methods and can be applied to both ground- and excited-state energies.

Temporal changes in habitat use by dugongs in a spatially restricted coral reef environment

Context The dynamic habitat use by dugongs (Dugong dugon) in small coral reef lagoon systems spatially limited by tides is not well understood and has hampered adaptive management. Aims We investigated how dugongs locally used a high conservation value coral-reef lagoon system during different seasons and tides to support local management. Methods We conducted local-scale aerial surveys to document the seasonal and tidal changes in the distribution and number of dugongs over seagrass and non-seagrass coral reef habitats in a small lagoon in New Caledonia. The surveys were conducted fortnightly over 18 months in different seasons and at different tides. Temperature loggers and existing local footage of dugong herding behaviour were used to study the habitat use and behaviour of the animals in the area. Key results More dugongs were sighted in Cap Goulvain during the cool season than during the warm season. As tides restricted access to the intertidal seagrass meadows and during the cool season, more dugongs were sighted outside the lagoon on the fore reef shelf outside the lagoon. Dugongs were resting in large aggregations during their use of this non-seagrass habitat. Conclusions Our study emphasises the importance of non-seagrass habitats for dugongs in spatially restricted coral reef environments as well as the importance of considering outer lagoon habitats as key dugong management areas. This study also adds evidence of behavioural thermoregulation in dugongs. Implications The development of dynamic management strategies is essential, especially where different habitats should be protected at different times of the year.

A stochastic optimization framework to planing for geographically correlated failures in coupled natural gas and electric power systems

We develop a transmission planning framework for coupled natural gas and electric power systems facing geographically correlated failures. The framework uses a stochastic optimization method incorporating uncertainty in the locations of the geographically correlated failures. We compare the proposed planning framework with the traditional N-k method which plans for geographically uncorrelated failures in terms of improving resilience effectively against geographically correlated failures. The proposed planning framework is illustrated using a small test system, but is scalable to larger system sizes and portable to other coupled-infrastructure contexts. We illustrate how planning for geographically correlated failures can enhance system-wide robustness by reinforcing the network connectivity between supply and demand locations instead of addressing local vulnerability at specific locations when planning for geographically uncorrelated failures. Planning for geographically correlated failures improves system resilience to both geographically correlated and uncorrelated failures significantly, but the converse is not true in our case study.

Unconditional error analysis of linearized BDF2 mixed virtual element method for semilinear parabolic problems on polygonal meshes

In this paper, we construct, analyze, and numerically validate a class of H(div)-mixed virtual element method for the semilinear parabolic problem in mixed form, in which the parabolic problem is reformulated in terms of the velocity and the pressure of the time-dependent Darcy flow. The Newton linearized method for the nonlinear term is designed to cooperate with the second-order backward differentiation formula of the temporal discretization scheme. This allows each time step to only require the solution of a small and well-structured linear system rather than the solution of a nonlinear system. The linearization improves computational efficiency without decreasing convergence rates. Moreover, the “Fortin” operator and its approximation properties are applied to derive an optimal error estimates O(hk+1+τ2) for the virtual element solution of the velocity and the pressure. Finally, its remarkable performance is illustrated by several numerical examples that also validate the theoretical rates of convergence.

Dynamic behavior of small system under the influence of parameters and application of image encryption

Dynamic behavior of small system under the influence of parameters and application of image encryption

Implementation of fuzzy logic MPPT based on Arduino in small scale PV pumping system

The performance of photovoltaic (PV) affected directly by climatic changes, The controller maintain maximum potential energy conversation to operate the pimping system at nominal conditions, fuzzy logic intelligent controllers are successfully suitable and applicable in engineering and applied science. The aim of this paper is present an experimental approach in Implementation of fuzzy logic maximum power point tracking (MPPT) with boost converter based on Arduino Mega micro-controller to maximize energy production in different weather condition applied to small scale pumping system for water and chemical fluid analyses in isolated area. The system is supplied by 20 (W) solar photovoltaic (PV) panel. This paper present a real-time MATLAB/Simulink fuzzy logic method controlling and monitoring MPPT application using an low cost Arduino Mega micro-controller combined with (LV25, LP55) sensors controlling boost converter interconnected with solar panel and plastic pump.

Impact of Imperfect Kolsky Bar Experiments Across Different Scales Assessed Using Finite Elements

Abstract Typical Kolsky bars are 10–20 mm in diameter with lengths of each main bar being on the scale of meters. To push 104+ strain rates, smaller systems are needed. As the diameter and mass decrease, the precision of the alignment must increase to maintain the same relative tolerance, and the potential impacts of gravity and friction change. Finite element models are typically generated assuming a perfect experiment with exact alignment and no gravity. Additionally, these simulations tend to take advantage of the radial symmetry of an ideal experiment, which removes any potential for modeling nonsymmetric effects, but has the benefit of reducing computational load. In this work, we discuss results from these fast-running symmetry models to establish a baseline and demonstrate their first-order use case. We then take advantage of high-performance computing techniques to generate half symmetry simulations using Abaqus® to model gravity and misalignment. The imperfection is initially modeled using a static general step followed by a dynamic explicit step to simulate the impact events. This multistep simulation structure can properly investigate the impact of these real-world, nonaxis symmetric effects. These simulations explore the impacts of these experimental realities and are described in detail to allow other researchers to implement a similar finite element (FE) modeling structure to aid in experimentation and diagnostic efforts. It is shown that of the two sizes evaluated, the smaller 3.16-mm system is more sensitive than the larger 12.7 mm system to such imperfections.

Taraxasterol enhanced bladder cancer cells radiosensitivity via inhibiting the COX-2/PGE2/JAK2/STAT3/MMP pathway

Purpose Radiotherapy with bladder preservation is highly acceptable among patients bearing bladder cancer (BCa), but the occurrence of secondary tolerance (ARR) during treatment is one of the important reasons for the failure of clinical radiotherapy. COX-2 has been frequently reported to be highly expressed and associated with radio-resistance in various cancers. In this study, the feasibility of Taraxasterol (Tara) as a radiosensitizer was investigated, and the target effect of Tara on COX-2 and its underlying mechanism were explored. Methods and materials The toxicity of Tara toward BCa cells was detected with the MTT method and cells in response to IR or Tara + IR were compared by clone formation assay. Next, a small RNA interference system (siRNA) was employed to decrease endogenous COX-2 expression in BCa cells, and the stem cell-like features and motion abilities of BCa cells under different treatments were investigated using microsphere formation and transwell chamber assay, respectively. Meanwhile, the expression of a series of inflammation-related molecules and stem cell characteristic molecules was determined by qRT-PCR, western blot and ELISA method. In vivo studies, BCa cells were subcutaneously injected into the right flank of each male mouse. Those mice were then grouped and exposed to different treatment: Tara, IR, IR + Tara and untreated control. The volumes of each tumor were measured every two days and target proteins were detected with immunohistochemical (IHC) staining. Results The results show that COX-2 decline, due to COX-2 knocking-down or Tara treatment, could greatly enhance BCa cells’ radiosensitivity and significantly decrease their migration, invasion and microsphere formation abilities, companied with the reduce of JAK2, phos-STAT3, MMP2 and MMP9 expression. However, Tara could not further reduce the expression of an above molecule of cells in COX-2-deficient BCa cells. Correspondingly, Tara treatment could not further enhance those siCOX-2 BCa cells response to IR. Conclusions Our data support that Tara can improve the radiosensitivity of BCa cells by targeting COX-2/PGE2. The mechanism may involve regulating STAT3 phosphorylation, DNA damage response protein activation, and expression of MMP2/MMP9.

Morning Glory Flower Detection in Aerial Images Using Semi-Supervised Segmentation with Gaussian Mixture Models

The invasive morning glory, Ipomoea purpurea (Convolvulaceae), poses a mounting challenge in vineyards by hindering grape harvest and as a secondary host of disease pathogens, necessitating advanced detection and control strategies. This study introduces a novel automated image analysis framework using aerial images obtained from a small fixed-wing unmanned aircraft system (UAS) and an RGB camera for the large-scale detection of I. purpurea flowers. This study aimed to assess the sampling fidelity of aerial detection in comparison with the actual infestation measured by ground validation surveys. The UAS was systematically operated over 16 vineyard plots infested with I. purpurea and another 16 plots without I. purpurea infestation. We used a semi-supervised segmentation model incorporating a Gaussian Mixture Model (GMM) with the Expectation-Maximization algorithm to detect and count I. purpurea flowers. The flower detectability of the GMM was compared with that of conventional K-means methods. The results of this study showed that the GMM detected the presence of I. purpurea flowers in all 16 infested plots with 0% for both type I and type II errors, while the K-means method had 0% and 6.3% for type I and type II errors, respectively. The GMM and K-means methods detected 76% and 65% of the flowers, respectively. These results underscore the effectiveness of the GMM-based segmentation model in accurately detecting and quantifying I. purpurea flowers compared with a conventional approach. This study demonstrated the efficiency of a fixed-wing UAS coupled with automated image analysis for I. purpurea flower detection in vineyards, achieving success without relying on data-driven deep-learning models.

Small UAV Urban Overhead Transmission Line Autonomous Correction Inspection System Based on Radar and RGB Camera

Small UAV Urban Overhead Transmission Line Autonomous Correction Inspection System Based on Radar and RGB Camera