Cost-effective Framework Research Articles

MIDAS: Multi-layered attack detection architecture with decision optimisation

The proliferation of cyber attacks has led to the use of data-driven detection countermeasures, in an effort to mitigate this threat. Machine learning techniques, such as the use of neural networks, have become mainstream and proven effective in attack detection. However, these data-driven solutions are limited by: a) high computational overhead associated with data pre-processing and inference cost, b) inability to scale beyond a centralised deployment to cope with environmental variances, and c) requirement to use multiple bespoke detection models for effective attack detection coverage across the cyber kill chain. In this context, this paper introduces MIDAS, a cost-effective framework for attack detection, which introduces a dynamic decision boundary that is used in a multi-layered detection architecture. This is achieved by modelling the decision confidence of the participating detection models and judging its benefits using a novel reward policy. Specifically, a reward is assigned to a set of available actions, corresponding to a decision boundary, based on its cost-to-performance, where an overall cost-saving is prioritised. We evaluate our approach on two widely used datasets representing two of the most common threats today, i.e., phishing and malware. MIDAS shows that it effectively reduces the expenditure on detection inference and processing costs by controlling the frequency of expensive detection operations. This is achieved without significant sacrifice of attack detection performance.

Local Electronic Structure Regulation Enabling Fluorophosphates Cathode with Improved Redox Potential and Reversible Capacity for Sodium-Ion Batteries.

Mn-based fluorophosphates have attracted much attention as cathodes for sodium-ion batteries owing to their high cost effectiveness, considerable capacity, and stable framework. However, the fascinating Mn3+/2+ redox couple suffers from inadequate activation due to the Mn-O covalent character and poor electronic conductivity, impeding its further applications. Herein, a local electronic structure regulation strategy is proposed to improve the Mn3+/2+ redox potential and reversible capacity simultaneously through introducing elements with low-energy 3d orbitals to expand the energy gap between the eg orbitals and Fermi energy of Na. Moreover, the 3d element substitution serves to narrow the band gap toward the improved intrinsic electronic conductivity. In comparison with pristine Na2Fe0.45Mn0.55PO4F, the as-prepared Na2Fe0.45Mn0.4V0.1PO4F cathode achieves an increase from 3.5 to 3.6 V in the high-voltage platform and an improvement in energy density from 330 to 361 Wh kg-1. This work inspires new ideas in adjusting the redox potential of polyanionic cathodes through deliberate regulation of the local electronic structure.

Biomonitoring emerging hazards of pharmaceuticals in river water using gut microbiome and behavioural Daphnia magna responses

A cost-effective Daphnia magna testing framework was applied to identify emerging hazards such as neurological and cardiovascular defects as well as antibiotic resistant genes (ARGs), related to pharmaceuticals present in waste water treated (WWTP) effluent discharged into rivers. D. magna juveniles were exposed during 48 h to water samples from three rivers in the vicinity of Barcelona (NE Spain), Besós, Llobregat and Onyar, upstream and downstream of WWTP discharging points. The analyses included measuring levels of 80 pharmaceutical residues in water samples by HPLC-MS, determination of the loads of different clinically relevant antibiotic resistant genes (ARGs) in both water samples and exposed animals, and assessment of toxic effects in feeding, heartbeat responses, and behavioural indicators. ARG prevalence in water, but not in gut microbiomes, was associated with the presence of bactericides in water. These results suggest that their levels were high enough to put a selective pressure over river microbial populations, but that Daphnia guts were not easily populated by environmental bacteria. Toxic effects were found in 20 to 43% of water samples, depending on the river, and related to water quality parameters and to pollutant levels. For example, heartbeats were correlated with salinity, whereas feeding impairment did so with high loads of suspended solids. In contrast, behavioural alterations were associated to the concentration of neuroactive chemicals. Accordingly, we hypothesize that measured neuroactive chemicals have caused the observed effects. If this also applies to local invertebrate populations, the environmental consequences may be severe and unpredictable.

A scalable, high-throughput neural development platform identifies shared impact of ASD genes on cell fate and differentiation.

Deleterious mutations in hundreds of genes confer high risk for neurodevelopmental disorders (NDDs), posing significant challenges for therapeutic development. Identifying convergent pathways shared across NDD genes could reveal high-impact therapeutic targets. To identity convergent pathways in NDD genes, we optimized Perturb-seq, a method combining CRISPR perturbation with single-cell RNA sequencing (scRNA-seq), and applied structural topic modeling (STM) to simultaneously assess impact on cell fate and developmental stage. We then studied a subset of autism spectrum disorder (ASD) genes implicated in regulation of gene expression using these improved molecular and analytical approaches. Results from targeting 60 high-confidence ASD risk genes revealed significant effects on neural development. As expected, ASD risk genes impacted both progenitor fate and/or neuronal differentiation. Using STM, we could identify latent topics jointly capturing cell types, cell fate, and differentiation stages. Repression of ASD risk genes led to changes in topic proportions and effects of four genes (DEAF1, KMT2A, MED13L, and MYT1L) were validated in an independent dataset. Our optimized Perturb-seq method, combined with a novel analytical approach, provides a powerful, cost-effective framework for uncovering convergent mechanisms among genes involved in complex neurodevelopmental processes. Application of these methods advanced understanding of the impact of ASD mutations on multiple dimensions of neural development, and provides a framework for a broader examination of the function of NDD risk genes.

Camera-based mapping in search-and-rescue via flying and ground robot teams

Search and rescue (SaR) is challenging, due to the unknown environmental situation after disasters occur. Robotics has become indispensable for precise mapping of the environment and for locating the victims. Combining flying and ground robots more effectively serves this purpose, due to their complementary features in terms of viewpoint and maneuvering. To this end, a novel, cost-effective framework for mapping unknown environments is introduced that leverages You Only Look Once and video streams transmitted by a ground and a flying robot. The integrated mapping approach is for performing three crucial SaR tasks: localizing the victims, i.e., determining their position in the environment and their body pose, tracking the moving victims, and providing a map of the ground elevation that assists both the ground robot and the SaR crew in navigating the SaR environment. In real-life experiments at the CyberZoo of the Delft University of Technology, the framework proved very effective and precise for all these tasks, particularly in occluded and complex environments.

An efficient and cost-effective methods framework for performing biomechanical analysis on cadaveric skeletal muscle

IntroductionThe structure and arrangement of skeletal muscle fibers is the primary determinant of muscle function. While analysis of morphologic parameters to elucidate muscle structure-function relationships dates to the 17th century, considerable variability in methodology and technique to quantify these relationships exists within the literature. Additionally, applications to assess the impact of non-typical musculoskeletal morphologies on structure-function relationships are limited. This study aims to assemble and present a practical, step-by-step framework of combined methods and techniques for efficiently analyzing biomechanical impacts of cadaveric skeletal muscles. MethodsExisting skeletal muscle biomechanical formulas and experimentally determined parameters for typical fast-acting skeletal muscle were identified in the literature. The methods framework was assembled as a stepwise protocol that includes mathematical formulas, referenced accepted values, optional steps, section breaks, suggested techniques, important notes and footnotes, and materials needed for collecting necessary measurements. Proof of concept was achieved with primary histological data and imaging, along with references to examples where the methods have been successfully applied. ResultsThe assembled framework presents an ordered process for measuring skeletal muscle parameters, calculating the maximal isometric force of a skeletal muscle, and applying that data to understand musculoskeletal mechanics. Histology data, imaging, and a summary of studies that have successfully applied the framework methods provide visual aids and validation for the methods. ConclusionsThis study presents an efficient and convenient framework of combined methods and techniques for investigators to evaluate the biomechanical impact of skeletal muscles. The practical use of this framework should optimize project efficiency and spending, increase study rigor, and minimize procedural variation across different studies. This report may serve as a foundational resource for researchers studying cadaveric muscle biomechanics, and its use especially adds translational clinical value to case analyses of non-typical musculoskeletal morphologies.

Cost-effective framework for design optimization using metamodel and evolutionary algorithm: with a case study of bio-filtration system

Cost-effective framework for design optimization using metamodel and evolutionary algorithm: with a case study of bio-filtration system

Vibration-Based Railway Suspension Monitoring Under Varying Operating Conditions via Robust Statistical Time Series Type Methods

The on-board condition monitoring of railway suspension components is important for ensuring passenger comfort, maintaining proper operation, enhancing safety, and reducing operational costs. In this context statistical time series type random-vibration-based methods constitute a potentially efficient and cost-effective framework. Yet a significant challenge emerges from the competing requirements for high sensitivity to suspension component degradation and robustness to varying Operating Conditions (OCs) and uncertainty. Varying Operating Conditions and uncertainty are related to factors such as varying payload, travelling speed, and rail profile. The problem is further aggravated by the complexity of the vehicle dynamics, including the wheelbase filtering effect. Despite the significant progress made so far and the development of various methods, the challenges related to varying OCs and uncertainty largely remain as a technical barrier. The aim of the present study is the introduction of a data-based methodology aspiring to overcome them. The methodology is based on Multiple-Input Single-Output Transmittance Function (MISO-TF) time series models of a special form allowing for eliminating the effects of varying rail profile while properly treating the wheelbase filtering effect. Monitoring is based on a MISO-TF feature space, using either a Random Coefficient Gaussian Mixture or a Multiple Model based scheme. The former, although more elaborate, allows for the introduction of a complete probabilistic framework. An interesting advantage of both versions is that operation can be based on a very limited number of sensors and only a partial data-driven model of the dynamics. The methodology is comprehensively assessed via hundreds of SIMPACK based Monte Carlo runs under variable payload and rail profiles. The achievable performance is shown to be very good for both versions and for 10%, 15%, and 20% of condition degradation in either primary or secondary suspension components.

EE475 The Benefit-Cost Analysis Adjustment Through the Generalized Risk-Adjustment Cost-Effectiveness (GRACE) Framework: An Application on Acute Ischemic Stroke Patients

EE475 The Benefit-Cost Analysis Adjustment Through the Generalized Risk-Adjustment Cost-Effectiveness (GRACE) Framework: An Application on Acute Ischemic Stroke Patients

Robust economic-resilient operational planning of distribution networks considering multi-microgrids black-start service

The increasing growth of natural disasters and cyber-physical attacks has made the development of resilience enhancement strategies for distribution networks a significant challenge for operators. Hence, in this paper, a black-start strategy based on multi-microgrids capability is developed as a two-layer preventive-corrective measure within a cost-effective energy management framework. The preventive layer includes regulating bilateral contracts between the active distribution network operator and the multi-microgrids owner pre-event. The corrective layer includes islanding microgrids during the event, calling the responsive loads, and economic-resilient operational planning of the active distribution network post-event. In this regard, a hybrid robust multi-objective optimization approach is applied to model the proposed black-start strategy as a risk-averse portfolio. The effectiveness of the developed model is tested on the modified IEEE 33-bus distribution network. Results such as an 83.38 % load recovery of the active distribution network, a 65.78 % reduction in distribution system operator costs, and a 131.28 % increase in multi-microgrid owner profit clearly illustrate the enhanced resilience of the active distribution network within an economically robust framework, which indicates the effectiveness of the proposed strategy.

Tau-PET in early cortical Alzheimer brain regions in relation to mild behavioral impairment in older adults with either normal cognition or mild cognitive impairment

Mild Behavioral Impairment (MBI) leverages later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a high-risk group for incident dementia. Phosphorylated tau (p-tau) is a hallmark biological manifestation of Alzheimer disease (AD). We investigated associations between MBI and tau accumulation in early-stage AD cortical regions. In 442 Alzheimer’s Disease Neuroimaging Initiative participants with normal cognition or mild cognitive impairment, MBI status was determined alongside corresponding p-tau and Aβ. Two meta-regions of interest were generated to represent Braak I and III neuropathological stages. Multivariable linear regression modelled the association between MBI as independent variable and tau tracer uptake as dependent variable. Among Aβ positive individuals, MBI was associated with tau uptake in Braak I (β=0.45(0.15), p<.01) and Braak III (β=0.24(0.07), p<.01) regions. In Aβ negative individuals, MBI was not associated with tau in the Braak I region (p=.11) with a negative association in Braak III (p=.01). These findings suggest MBI may be a sequela of neurodegeneration, and can be implemented as a cost-effective framework to help improve screening efficiency for AD.

Proactive framework for obsolescence management of electrical equipment in oil and gas industry

PurposeEnergy consumption has increased significantly since the 1970s, which has increased demand for sufficient infrastructure in the oil and gas industry. Many top-notch oil and gas companies invested in and equipped their facilities with high-capacity electrical equipment to meet high demand and benefit from high revenues. This is becoming a challenge nowadays for old facilities in the oil and gas industry, as most of the electrical equipment installed has reached or even exceeded its lifetime. Moreover, many of the original equipment manufacturers (OEMs) for electrical equipment from the 1980s are no longer in market today. Therefore, the aim of this study is to develop a proactive, cost-effective obsolescence management framework for electrical equipment in the oil and gas industry, considering the aging factor of the equipment.Design/methodology/approachFirstly, the study begins with gathering available information and identifying criteria. Secondly, the data collection is evaluated by subject-matter-experts (SMEs) in asset management field to ensure compliance with updated international standards and relevant regulatory requirements. Thirdly, a multi-criteria decision-making process is used to rank criteria. Finally, a scoring system is developed to measure the electrical equipment obsoleteness.FindingsThe developed framework will assist decision-makers in making informed decisions about maintenance, replacement or upgrades, using knowledge from previous studies and experts’ input. The result finding indicates that considering aging correction factors when measuring equipment obsoleteness leads to accurately and correctly predicting the electrical equipment obsoleteness score.Originality/valuePrevious studies have addressed obsolescence management without taking equipment age into account, regardless of how the equipment is performing. Thus, the lack of a comprehensive obsolescence management framework that accounts for both cost-effectiveness and the aging factor in the oil and gas industry poses a critical challenge.

Cost-effectiveness of sutimlimab in cold agglutinin disease.

Primary cold agglutinin disease (CAD) is a rare autoimmune hemolytic anemia caused by cold-reactive antibodies that bind to red blood cells and lead to complement-mediated hemolysis. Patients with primary CAD experience the burden of increased health resource utilization and reduced quality of life. The standard-of-care (SOC) in patients with primary CAD has included cold avoidance, transfusion support, and chemoimmunotherapy. The use of sutimlimab, a humanized monoclonal antibody that selectively inhibits C1-mediated hemolysis, was shown to reduce transfusion-dependence and improve quality of life across two pivotal phase 3 studies, further supported by 2-year extension data. Using data from the transfusion-dependent patient population that led to sutimlimab's initial FDA approval, we performed the first-ever cost-effectiveness analysis in primary CAD. The projected incremental cost-effectiveness ratio (ICER) in our Markov model was $2 340 000/QALY, significantly above an upper-end conventional US willingness-to-pay threshold of $150 000/QALY. These results are consistent across scenarios of higher body weight and a pan-refractory SOC patient phenotype (i.e., treated sequentially with bendamustine-rituximab, bortezomib, ibrutinib, and eculizumab). No parameter variations in deterministic sensitivity analyses changed our conclusion. In probabilistic sensitivity analysis, SOC was favored over sutimlimab in 100% of 10 000 iterations. Exploratory threshold analyses showed that significant price reduction (>80%) or time-limited treatment (<18 months) followed by lifelong clinical remission off sutimlimab would allow sutimlimab to become cost-effective. The impact of sutimlimab on health system costs with longer term follow-up data merits future study and consideration through a distributional cost-effectiveness framework.

FGO-MFI: factor graph optimization-based multi-sensor fusion and integration for reliable localization

Reliable and precise information pertaining to the position, velocity, and attitude is essential for automated driving. This paper proposes FGO-MFI, a cost-effective and robust multi-sensor fusion and integration localization framework that utilizes factor graph optimization. Firstly, a tightly coupled Global Navigation Satellite Systems (GNSS)/on-board sensor fusion localization framework is established to estimate vehicle states, including position, velocity, and attitude. To address the large drift rate of the Inertial Measurement Unit (IMU), this study introduces a novel IMU/Dynamics pre-integration method based on the vehicle dynamics model. We establish a two-degree-of-freedom vehicle dynamics model utilizing measurements from the wheel speed sensor and steering wheel angle sensor. The IMU/Dynamics factor is devised through a close integration of the model output and IMU pre-integration, enabling the construction of precise odometry with low-cost on-board sensors. Then, to address the issue of the non-Gaussian distribution of GNSS pseudorange error, this paper employs a Gaussian Mixture Model (GMM) to characterize the pseudorange noise, which is then applied to further sensor fusion. Given the time-varying nature of pseudorange noise, the expectation maximization algorithm is utilized to estimate GMM parameters online, leveraging the pseudorange residuals within a sliding window. Comprehensive experiments, inclusive of challenging scenarios such as urban canyons, tunnels, and wooded areas, have been carried out. They affirm the superior performance of the proposed method. Experiments have shown that our method demonstrates reliable localization across different statuses of GNSS signal, exhibiting a 39.4% improvement in the root mean square error of position error when compared to the state-of-the-art. Additionally, this FGO-MFI is a general sensor data fusion framework and is able to incorporate diverse sensor measurements, for example, from cameras and LiDARs to provide more reliable and accurate localization information.

A 30 m annual cropland dataset of China from 1986 to 2021

A 30 m annual cropland dataset of China from 1986 to 2021

Levels and health risk assessment of twenty-one current-use pesticides in urban and riverside waters of the Brazilian Amazon Basin

In Brazil, the favorable weather conditions and abundant land contribute to the thriving agricultural production. Brazilian crops extensively employ pesticides due to their high efficacy, cost-effectiveness, and permissive regulatory framework. However, pesticide use also endangers water resources, animal organisms, and human health. Due to the lack of data on pesticide use in the Amazonas forest-based Brazil, the present study aimed to assess the levels of twenty-one current-use pesticides (CUPs) from five different classes in river waters collected from urban and riverside areas in this region. Moreover, the non-carcinogenic risks associated with water consumption were also characterized. Thirteen CUPs were detected in concentrations above the limit of detection (LOD) in at least one of the water samples, and most pesticides were detected in riverside areas. In contrast, only 18% of the analyzed samples were considered “clean,” with only one compound detected. Fenitrothion showed the highest concentration, with a mean value of 4.86 ng/mL (0.30–14.3 ng/mL). Up to 33% of the samples showed levels of fipronil above the LOD, an issue of environmental and human health concern, mainly because of the adverse effects observed in honeybees. Despite this, the human health risk assessment showed a target hazard quotient below one (HQ < 1) in adults for all substances, suggesting that pesticide exposure through water consumption should not mean risk for the riverside populations. Taking into account the large extension of Brazil, as well as its different agricultural practices throughout the country, it would be of great importance to conduct extensive research in other areas. It would help to gain knowledge in this field and to promote eco-friendly alternatives to mitigate pesticide use and, consequently, to reduce their potential adverse effects on human health and the ecosystems.

Fundamental Frequency Layer-Wise Optimization of Tow-Steered Composites Considering Gaps and Overlaps

AbstractThe advent of Automated Fiber Placement (AFP) in aerospace composites lay-up and manufacturing has allowed orientations to vary along pre-defined curved directions rather than being forced to remain constant within the lamina. These composites are called Variable Angle Tow (VAT) or Variable Stiffness Composites (VSC). Despite the enhancements in mechanical performance offered by VAT, constraints from the manufacturing process hinder their full potential. This paper explores the effect of primary defects, i.e., gaps and overlaps, on optimal design and fundamental frequency optimization. For doing so, the Carrera Unified Formulation (CUF) and the Defect Layer Method (DLM) are integrated directly into the optimization process to provide an efficient and cost-effective framework for modeling the structural behavior and manufacturing process of VSCs. Particular attention is given to manufacturing and tow-steering simulation to quantify and map defects for each laminate layer. This research serves a dual purpose: (i) examining the impact of process-induced defects on achieving an optimal design and (ii) exploring how the choice of structural theory may affect the optimal solution.

Enhancing Wireless Sensor Network in Structural Health Monitoring through TCP/IP Socket Programming-Based Mimic Broadcasting: Experimental Validation

This paper presents the implementation of a synchronous Structural Health Monitoring (SHM) framework utilizing wireless, low-cost, and off-the-shelf components. Vibration-based condition monitoring plays a crucial role in assessing the reliability of structural systems by detecting damage through changes in vibration parameters. The adoption of low-cost Micro-Electro-Mechanical Systems (MEMS) sensors in Wireless Sensor Networks (WSNs) has gained traction, emphasizing the need for precise time synchronization to schedule wake-up times of multiple sensor nodes for data collection. To address this challenge, our proposed method introduces a TCP/IP socket programming-based mimic broadcasting mechanism and a scalable sensing network controlled by a central gateway, leveraging the Raspberry Pi Python platform. The system operates using Internet of Things (IoT) concepts and adopts a star topology, where a packet is transmitted from the gateway to initiate measurements simultaneously on multiple sensor nodes. The sensor node comprises a MEMS accelerometer, a real time clock DS3231 module and Raspberry Pi Zero 2W (RPi0-2W), while the gateway employs a Raspberry Pi 4 (RPi4). To ensure accurate time synchronization, all Pi0-2W nodes were configured as Network Time Protocol (NTP) clients, synchronizing with an RPi4 server using chrony, the reliable implementation of the NTP. Through experimental evaluations, the system demonstrates its effectiveness and reliability in achieving initial time synchronization. This study addresses the challenge of achieving precise time alignment between sensor nodes through the utilization of the Dynamic Time Wrapping (DTW) method for Frequency Domain Decomposition (FDD) applications. The contribution of this research significantly enhances the field by improving the accuracy and reliability of time-aligned measurements, with a specific focus on utilizing low-cost sensors. By developing a practical and cost-effective SHM framework, this work advances the accessibility and scalability of structural health monitoring solutions, facilitating more widespread adoption and implementation in various engineering applications

Portable and highly enhanced surface enhanced Raman scattering and photocatalytic activity of cost-effective hierarchical hollow metal organic frameworks heterostructures induced by etched titanium sheet

In order to effectively detect and remove organic toxics in wastewater, the facile construction of plug and play bifunctional materials is very vital. Herein, a kind of metal-organic frameworks (MIL-53 (Fe) with hollow tubular structure was induced by an etched Ti sheet (ET), and then small sized Ag nanoparticles (Ag NPs) were in-situ anchored evenly on the internal and external surfaces of MIL-53 (Fe). Subsequently, a new type of bifunctional material (ETMA) was assembled. Surface enhanced Raman scattering (SERS) and photocatalytic activity of the material were investigated with crystal violet (CV, a carcinogenic and teratogenic toxic) as an analyte. The results found that trace amount of CV (1 × 10−12 M) can still be sensitively detected by the fabricated ETMA, and analysis enhancement factors as high as 6.9 × 105 even though only 1.39 wt % Ag was contained in the ETMA. Moreover, nearly 100 % of CV can be rapidly degraded by the ETMA after irradiated for 15 min, which was 44.47 times and 7.27 times faster than those of ET-Ag (ETA) and ET-MIL-53 (Fe) (ETM), respectively. Additionally, the removal efficiency of total organic carbon (TOC) was as high as 75.44 %. The remarkable enrichment effect, the strong interaction among components, and the synergistic effect in the target ETMA material were responsible to the dramatically enhanced SERS and photocatalytic performances. In addition, the cost-effective ETMA exhibited excellent uniformity, repeatability, stability, and recyclability towards the detection and removal of CV in actual water samples, showing great potentials in monitoring and removing organic pollutants in practical ecological environment.

Simulation of Human Movement in Zero Gravity.

In the era of expanding manned space missions, understanding the biomechanical impacts of zero gravity on human movement is pivotal. This study introduces a novel and cost-effective framework that demonstrates the application of Microsoft's Azure Kinect body tracking technology as a motion input generator for subsequent OpenSim simulations in weightlessness. Testing rotations, locomotion, coordination, and martial arts movements, we validate the results' realism under the constraints of angular and linear momentum conservation. While complex, full-body coordination tasks face limitations in a zero gravity environment, our findings suggest possible approaches to device-free exercise routines for astronauts and reveal insights into the feasibility of hand-to-hand combat in space. However, some challenges remain in distinguishing zero gravity effects in the simulations from discrepancies in the captured motion input or forward dynamics calculations, making a comprehensive validation difficult. The paper concludes by highlighting the framework's practical potential for the future of space mission planning and related research endeavors, while also providing recommendations for further refinement.