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Development of a Ti3C2 MXene-AgNPs-based SERS platform for ionophore-based ion-selective detection

SENSORS AND ACTUATORS B-CHEMICAL 2025年 433卷

作者： Zhang, Laiqi Zhu, Elena Coronel-Zegarra, Alejandra Somu, Dawn Raja Dhar, Shankar Merk, Vivian Zhang, Xiaolang Wang, Renjie Florida Atlantic Univ Dept Chem & Biochem 777 Glades Rd Boca Raton FL 33431 USA Florida Atlantic Univ Dept Ocean & Mech Engn 777 Glades Rd Boca Raton FL 33431 USA Florida Atlantic Univ Dept Geosci 777 Glades Rd Boca Raton FL 33431 USA Univ Florida Dept Comp & Informat Sci & Engn 432 Newell Dr Gainesville FL 32611 USA

Surface-enhanced Raman spectroscopy (SERS) has advanced as a crucial analytical technology, benefiting numerous fields with its high sensitivity and versatility. However, its application in detecting ions has been underexplored. In this study, we developed a novel SERS sensing platform for ion detection by creating a Ti3C2 Mxene-AgNPs substrate and integrating it with the ionophore-based ion-selective sensing framework. The Ti3C2 Mxene-AgNPs substrate was successfully prepared via electrodeposition on conductive glass, achieving an enhancement factor of 1.86 x 106 and demonstrating good signal repeatability (RSD = 8.17 %). The AgNPs ensure amplified and stable SERS activity, while large surface area of the MXene nanosheets offers a significant advantage for AgNPs and sensing chemical loading. The Ti3C2 Mxene-AgNPs SERS substrate enables ionophorebased ion-selective sensing with exceptional selectivity and high sensitivity for target ion detection, eliminating the need for plasticizers. A selective turn-on SERS response of this platform to various concentrations of K+, Na+, and Ca2+ was exemplified in this study, further revealing its excellent generalizability. Moreover, the applicability of this method was preliminarily demonstrated by its successful application in determining Na+ in human blood serum and environmental water samples (river and estuary). The successful integration of the versatile and rapidly progressing SERS technique, enabled by the Ti3C2 Mxene-AgNPs substrate, for electrolyte cation detection offers a promising avenue for enhancing current ion detection capabilities in biological and environmental samples.

关键词： Surface-enhanced Raman spectroscopy (SERS) Ion detection Ionophore

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A unified analytical framework for distributed variable step size LMS algorithms in sensor networks

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TELECOMMUNICATION systems 2018年第4期69卷 447-459页

作者： Bin Saeed, Muhammad Omer Ejaz, Waleed Rehman, Saad Zerguine, Azzedine Anpalagan, Alagan Song, Houbing Natl Univ Sci & Technol Dept Comp Engn Coll Elect & Mech Engn Rawalpindi Pakistan Ryerson Univ Dept Elect & Comp Engn Toronto ON Canada King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia Embry Riddle Aeronaut Univ Dept Elect Comp Software & Syst Engn Daytona Beach FL 32114 USA

Internet of Things (IoT) is helping to create a smart world by connecting sensors in a seamless fashion. With the forthcoming fifth generation (5G) wireless communication systems, IoT is becoming increasingly important since 5G will be an important enabler for the IoT. Sensor networks for IoT are increasingly used in diverse areas, e.g., in situational and location awareness, leading to proliferation of sensors at the edge of physical world. There exist several variable step-size strategies in literature to improve the performance of diffusion-based Least Mean Square (LMS) algorithm for estimation in wireless sensor networks. However, a major drawback is the complexity in the theoretical analysis of the resultant algorithms. Researchers use several assumptions to find closed-form analytical solutions. This work presents a unified analytical framework for distributed variable step-size LMS algorithms. This analysis is then extended to the case of diffusion based wireless sensor networks for estimating a compressible system and steady state analysis is carried out. The approach is applied to several variable step-size strategies for compressible systems. Theoretical and simulation results are presented and compared with the existing algorithms to show the superiority of proposed work.

关键词： Least-mean-square algorithms Mean-square analysis Steady-state analysis Variable step-size Wireless sensor networks

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Precision-Enhanced Differentially-Private Mining of High-Confidence Association Rules

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2020年第6期17卷 1297-1309页

作者： Maruseac, Mihai Ghinita, Gabriel Univ Massachusetts Boston MA 02125 USA

Association rule mining discovers patterns in large data repositories, and benefits diverse application domains such as healthcare, marketing, etc. However, mining datasets that contain data about individuals may cause significant privacy breaches. Recent research addresses the privacy threats that arise when mining sensitive data, and several techniques allow data mining with differential privacy guarantees. However, existing methods only discover rules that have very large support, i.e., occur in a large fraction of the dataset transactions (typically, more than 50 percent). This is a serious limitation, as numerous high-quality rules do not reach such high frequencies (e.g., rules about rare diseases, or luxury merchandise). We propose a method that focuses on mining high-quality association rules with moderate and low frequencies. We employ a novel technique for rule extraction that combines the exponential mechanism of differential privacy with reservoir sampling. The proposed algorithm allows us to directly mine association rules, without the need to compute noisy supports for large numbers of itemsets. Our experimental evaluation shows that our technique is able to sample low- and moderate-support rules with good precision, clearly outperforming existing solutions.

关键词： Itemsets Reservoirs Sensitivity Security experimentation

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ELIXIR: An Expedient Connection Paradigm for Self-Powered IoT Devices

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IEEE TRANSACTIONS ON computer-AIDED DESIGN OF INTEGRATED CIRCUITS AND systems 2023年第11期42卷 3743-3756页

作者： Pan, Chen Zhang, Wen Wang, Yanzhi Xie, Mimi Texas A&M Univ Dept Comp Sci Corpus Christi TX 78412 USA Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA

IoT devices usually work under power-constrained scenarios like outdoor environmental monitoring. Considering the cost and sustainability, in the long run, energy-harvesting technology is preferable for powering IoT devices. Since harvesting power is intrinsically weak and transient, the connection between IoT devices not only cannot be maintained constantly but is also extremely difficult to be established. In order to communicate, those devices should have a synchronized timeline so that both transmitter and receiver can start connection simultaneously. Yet due to the transient nature of ambient energy, volatile time data can be easily tampered with by the unstable power supply or corrupted completely by frequent power outages. As a result, unsynchronized IoT devices require significant efforts in time and energy to reconnect and communicate, which further escalates the performance degradation of the edge network. To adapt to ubiquitous self-powered scenarios on the IoT edge, we propose ELIXIR, an expedient connection paradigm, to synchronize swiftly and autonomously in a joint effort for self-powered IoT devices. The lightweight and highly efficient natures enable ELIXIR to be integrated into low-power IoT devices easily and efficiently. The experimental results show that the proposed ELIXIR can avoid a connection loop and help speed up the connection 2.83x and 1.84x faster than baseline methods.

关键词： Communication embedded systems energy harvesting IoT transient power

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Interactive Context for Mobile OS Resource Management

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2020年第3期19卷 612-623页

作者： Zhu, Meng Shen, Kai Mesosphere San Francisco CA 94104 USA Google New York NY 10011 USA

This paper presents an application-transparent execution context for mobile operating systems that reflects the criticality of current execution on the user interactivity. We track Android / Linux system-level events including semantic syscalls, UI actions, and standard inter-process and intra-process communication interfaces that signal the initiation and propagation of interactivity-related executions. This interactive context enables new optimizations in CPU scheduling and power state management. We recognize that online resource scheduling is susceptible to inaccurate contexts-e.g., misidentifying an interactive execution as background leads to possible priority inversion by schedulers. In particular, low-level OS events such as kernel block / wake-up carry ambiguous semantics that could induce false context propagations. We selectively expose such uncertainties to the schedulers so that executions with uncertain contexts are prioritized behind interactive executions but otherwise run as fast as possible to minimize the priority inversion. We further recognize the importance of prompt propagation of the interactivity context at the earliest possible moment to facilitate immediate prioritization. We utilize the interactivity context to enable differential per-core frequency control and background workload consolidation. Experiments on a quad-core smartphone with a dozen mobile workload scenarios show that we can, on average, save 13 percent energy with only 1 percent degradation on the interactive performance.

关键词： Context Message systems Program processors Task analysis Multicore processing Power demand Semantics Energy-aware systems mobile computing scheduling

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Collaborative Search Log Sanitization: Toward Differential Privacy and Boosted Utility

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2015年第5期12卷 504-518页

作者： Hong, Yuan Vaidya, Jaideep Lu, Haibing Karras, Panagiotis Goel, Sanjay SUNY Albany Dept Informat Technol Management Albany NY 12222 USA Rutgers State Univ Dept Management Sci & Informat Syst Piscataway NJ 08855 USA Santa Clara Univ Dept Operat Management & Informat Syst Santa Clara CA 95053 USA Skolkovo Inst Sci & Technol Skolkovo Russia

Severe privacy leakage in the AOL search log incident has attracted considerable worldwide attention. However, all the web users' daily search intents and behavior are collected in such data, which can be invaluable for researchers, data analysts and law enforcement personnel to conduct social behavior study [14], criminal investigation [5] and epidemics detection [10]. Thus, an important and challenging research problem is how to sanitize search logs with strong privacy guarantee and sufficiently retained utility. Existing approaches in search log sanitization are capable of only protecting the privacy under a rigorous standard [24] or maintaining good output utility [25]. To the best of our knowledge, there is little work that has perfectly resolved such tradeoff in the context of search logs, meeting a high standard of both requirements. In this paper, we propose a sanitization framework to tackle the above issue in a distributed manner. More specifically, our framework enables different parties to collaboratively generate search logs with boosted utility while satisfying Differential Privacy. In this scenario, two privacy-preserving objectives arise: first, the collaborative sanitization should satisfy differential privacy;second, the collaborative parties cannot learn any private information from each other. We present an efficient protocol - Collaborative sEarch Log Sanitization (CELS) to meet both privacy requirements. Besides security/privacy and cost analysis, we demonstrate the utility and efficiency of our approach with real data sets.

关键词： Search log differential privacy sampling optimization secure multiparty computation

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Wearable Heart Rate Sensor systems for Wireless Canine Health Monitoring

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IEEE SENSORS JOURNAL 2016年第10期16卷 3454-3464页

作者： Brugarolas, Rita Latif, Tahmid Dieffenderfer, James Walker, Katherine Yuschak, Sherrie Sherman, Barbara L. Roberts, David L. Bozkurt, Alper N Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27606 USA N Carolina State Univ Coll Vet Med 4700 Hillsborough St Raleigh NC 27606 USA N Carolina State Univ Dept Comp Sci Raleigh NC 27606 USA

There is an increasing interest from dog handlers and veterinarians in an ability to continuously monitor dogs' vital signs (heart rate, heart rate variability, and respiratory rate) outside laboratory environments, with the aim of identifying physiological correlations to stress, distress, excitement, and other emotional states. We present a non-invasive wearable sensor system combining electrocardiogram (ECG), photoplethysmogram (PPG), and inertial measurement units (IMU) to remotely and continuously monitor the vital signs of dogs. To overcome the limitations imposed by the efficiently insulated skin and dense hair layers of dogs, we investigated the use of various styles of ECG electrodes and the enhancements of these by conductive polymer coatings. We also studied the incorporation of light guides and optical fibers for an efficient optical coupling of PPG sensors to the skin. Combined with our parallel efforts to use IMUs to identify dog behaviors, these physiological sensors will contribute to a canine-body area network to wirelessly and continuously collect data during canine activities with a long-term goal of effectively capturing and interpreting dogs' behavioral responses to environmental stimuli that may yield measurable benefits to handlers' interactions with their dogs.

关键词： computer applications inertial measurement unit animal machine interface physiology

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Ethical Design of computers: From Semiconductors to IoT and Artificial Intelligence

IEEE DESIGN & TEST

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IEEE DESIGN & TEST 2024年第1期41卷 7-16页

作者： Pasricha, Sudeep Wolf, Marilyn Colorado State Univ Elect & Comp Engn Ft Collins CO 80523 USA Univ Nebraska Sch Comp Lincoln NE 68588 USA Colorado State Univ Ft Collins CO 80523 USA

This article proposes a new approach to estimate peak memory usage of software that is synthesized from a dataflow-model-based software development framework.

关键词： Ethics Internet of Things computers Companies Hardware Artificial intelligence Software ethics ethical computing IoT semiconductors artificial intelligence sustainable computing

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Reinforcement Learning Enabled Intelligent Energy Attack in Green IoT networks

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2022年 17卷 644-658页

作者： Li, Long Luo, Yu Yang, Jing Pu, Lina Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA Mississippi State Univ Dept Elect & Commun Engn Starkville MS 39762 USA

In this paper, we study a new security issue brought by the renewable energy feature in green Internet of Things (IoT) network. We define a new attack method, called the malicious energy attack, where the attacker can charge specific nodes to manipulate routing paths. By intelligently selecting the victim nodes, the attacker can "encourage" most of the data traffic into passing through a compromised node and harm the information security. The performance of the energy attack depends on the charging strategies. We develop two reinforcement-learning enabled algorithms, namely, Q- learning enabled intelligent energy attack (Q-IEA) and Policy Gradient enabled intelligent energy attack (PG-IEA). Through interacting with the network environment, the attacker can intelligently take attack actions without knowing the private information of the IoT network. This can greatly enhance the adaptability of the attacker to different network settings. Simulation results verify that the proposed IEA methods can considerably increase the amount of traffic traveling through the compromised node. Compared with the network without attack, an additional 53.3% data traffic is lured to the compromised node, which is more than 4 times higher than the performance of Random Attack.

关键词： Routing Green products Batteries Radio frequency Energy harvesting Security Routing protocols Green IoT networks security malicious energy attack reinforcement learning

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Design and Analysis of a Higher Order Power Filter for Grid-Connected Renewable Energy systems

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2017年第5期53卷 4149-4161页

作者： Anzalchi, Arash Moghaddami, Masood Moghadasi, Amir Pour, Maneli Malek Sarwat, Arif I. Florida Int Univ Dept Elect & Comp Engn Coll Engn & Comp Miami FL 33174 USA Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA Florida Int Univ Dept Elect Engn Miami FL 33174 USA Florida Int Univ Coll Engn & Comp Miami FL 33174 USA

Harmonic compensation is regularly implemented for a grid-tied inverter to reduce the influence of the grid current and voltage harmonics. In this study, the L(LCL)(2) filter, which is a high-order power filter for single-phase grid-tied voltage-source inverters, is designed and analyzed. In order to attenuate the high-frequency harmonics, additional resonant branch at the double of the switching frequency is added to the LLCL filter. The total inductance of this filter is almost less than the LLCL filter with the amount of the grid-side inductor. A comparative study on filter parameter design, size estimation, efficiency, stability, and dc-link dynamics in bidirectional power flow applications between the LLCL filter and the proposed L(LCL)(2) filter has been conducted. The assessment of these studies is presented through both experimental hardware implementation and MATLAB/Simulink-based simulation on a 700 W, 120 V/60 Hz single-phase grid-tied inverter. It is concluded that, compared with the LLCL filter, the L(LCL)(2) filter not only has less voltage drop and total component size, but also has better performance on reducing high-order current harmonics. Additionally, the L(LCL)(2) filter has a smaller size, less losses, stable closed-loop control system, and compared with traditional LLCL filter, it does not add any control difficulty to the system.

关键词： Current harmonics LCL filter LLCL filter L(LCL)(2) filter power quality switching frequency voltage-source inverter (VSI)

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