arXiv subjects

Lars Thomsen

Publications and source records attributed to Lars Thomsen.

10 recordsLinked to original sources

arXiv2026

Combined Radar and Magnetometer Sensor Network with LoRa-Mediated Awareness for Wildlife-Vehicle Collision Prevention: A Monte Carlo Analysis

Wildlife-vehicle collisions (WVCs) cause approximately 570 human fatalities in Canada per 20-year cohort, with Alberta accounting for 22% of these and incurring an estimated CAD $300,000 per day in direct and indirect costs. Wildlife fencing combined with crossing structures reduces collisions by ~86% on well-instrumented sites but remains economically infeasible across the majority of rural road kilometres, leaving a substantial collision residual. We present a combined sensor network integrating alternating-side radar nodes (10-m spacing baseline), three-axis magnetometers, dynamic message signs, and LoRa-mediated awareness propagation between adjacent radars. System performance is evaluated through a discrete-time Monte Carlo simulation on a 1 km test corridor, incorporating a six-state animal behavioural Markov model with vehicle-threat-dependent decision branching, Intelligent Driver Model vehicle dynamics, and a three-mode contrast that isolates the contributions of sensing, driver alerting, and network coordination. Across 60 independent trials, the integrated system reduces the collision rate per road entry by 47.4% relative to an unmitigated control (Welch's t = 2.82, p < 0.01), and simultaneously increases safe road-crossing throughput by 77% by lowering the perceived vehicle threat that otherwise triggers pre-crossing retreats. Sensitivity sweeps establish a statistically significant equivalent-performance band across 5-20 m alternating radar spacing and across small-to-medium animal classes (fox- through deer-class), with operational robustness against tenfold degradation of baseline sensor sensitivity.

cs.NI↗

arXiv2026

Restoring CFAR Validity for Single-Channel IoT Sensor Streams: A Monte Carlo Comparison of Five Detectors under Cortex-M0+ Constraints

Real-time event detection in IoT mesh sensor networks must balance sensitivity against false-positive load on a constrained mesh radio. We present a Monte Carlo comparison of the Temporal Spectral Noise-Floor Adaptation (TSNFA) detector against four classical comparators drawn from the radar Constant False Alarm Rate (CFAR) family and from sequential change detection: the Lipski FFT energy detector, Cell-Averaging CFAR (CA-CFAR), Ordered-Statistic CFAR (OS-CFAR), and state-machine Cumulative Sum (CUSUM). All five detectors are implemented to fit a Cortex-M0+ class envelope, process a 1-D 100 Hz time series in 128-sample frames, and use temporal reference windows in place of the spatial reference cells of conventional radar CFAR. Across a factorial set of four configurations (10 and 50 nodes; 12 dB and 18 dB SNR), each replicated five times over 24 hours, TSNFA achieves 99.97 to 100% event detection rate with 100% event precision and zero false-positive clusters per node. The classical comparators each succeed on one quality dimension and fail on another. Lipski FFT (k = 3), CA-CFAR, and OS-CFAR all maintain near-perfect detection rate but with event precision below 3% and per-node bandwidth between 145 kB/h and 1.2 MB/h. CA-CFAR and OS-CFAR are indistinguishable in false-alarm performance, both saturating the same broadband-statistic failure mode. CUSUM shows an SNR-dependent detection-rate drop from about 70% at 18 dB to 51% at 12 dB. TSNFA is the only algorithm tested that simultaneously achieves high detection rate, high precision, and low per-node bandwidth.

cs.NI↗

arXiv2026

Temporal Spectral Noise-Floor Adaptation for Error-Intolerant Trigger Integrity in IoT Mesh Networks

In this paper, we present a lightweight, embedded algorithm for autonomous edge event triggering in IoT sensor nodes suitable for operating in mesh networks. The device acquires local sensor data, performs deterministic FFT spectral feature extraction in firmware, and maintains a temporal spectral noise-floor baseline that absorbs non-stationary environmental excitations such as rain, wind, and mechanical vibration. While adaptive thresholds in IoT sensor nodes are often applied to manage communication load or stabilize long-term metrics, this work focuses on maintaining a time-evolving spectral noise floor to preserve event trigger reliability in dynamic environments. Our method targets trigger integrity under environmental non-stationary conditions, enabling calibration-free deployment of autonomous nodes; without shared noise models or cloud-side inference. Local decision authority preserves node responsiveness when connectivity is intermittent and mitigates security risks inherent in centralized remote-analysis systems. We validate the algorithm in a single node mesh sensor deployed in a dynamic outdoor environment using a radar-class proximity sensor as one example sensor modality. Results demonstrate substantial suppression of nuisance-induced triggers, reduced false-event traffic amplification in the mesh, bounded embedded execution, and reliable detection sensitivity to true spectral signatures.

cs.NI↗

arXiv2026

Edge Triggering in IoT Mesh Networks: A Comparative Monte Carlo Study of Seven Detection Algorithms

Real-time event detection in Internet of Things (IoT) mesh sensor networks presents significant challenges due to time-varying noise conditions, limited computational resources at edge nodes, and the need for autonomous operation without centralised coordination. This paper presents a comprehensive Monte Carlo simulation study comparing the Temporal Spectral Noise-Floor Adaptation (TSNFA) method against six alternative detection algorithms, evaluated across a 200-node mesh network over 24 hours with realistic noise models including 60 Hz electromagnetic interference (EMI), sinusoidally drifting noise power (+/- 6 dB), and intermittent digital switching bursts. TSNFA achieves 100% detection rate with zero false positives, uniquely combining three interlocking defences: spectral band selection, temporal persistence filtering, and adaptive noise-floor tracking. Every competing algorithm omits at least one of these three defences and fails correspondingly, with false-positive rates ranging from 0 (Send-on-Delta, which also detects nothing) to 13,387,930 (broadband energy ratio). These results identify the three-defence combination as necessary and sufficient for autonomous edge triggering in resource-constrained IoT deployments.

cs.NI↗

arXiv2025

Infrared observations reveal the reprocessing envelope in the tidal disruption event AT 2019azh

Tidal disruption events (TDEs) are expected to release much of their energy in the far-ultraviolet (UV), which we do not observe directly. However, infrared (IR) observations can observe re-radiation of the optical/UV emission from dust, and if this dust is observed in the process of sublimation, we can infer the un-observed UV radiated energy. TDEs have also been predicted to show spectra shallower than a blackbody in the IR, but this has not yet been observed. We present near/mid-IR observations of the TDE AT 2019azh spanning from -3 d before peak until >1750 d after. We evaluate these observations for consistency with dust emission or direct emission from the TDE. We fit the IR data with a modified blackbody associated with dust emission. The UV+optical+IR data are compared with simulated spectra produced from general relativistic radiation magnetohydrodynamics simulations of super-Eddington accretion. We model the data at later times (> 200 d) as an IR echo. The IR data at the maximum light can not be self-consistently fit with dust emission. Instead, the data can be better fit with a reprocessing model, with the IR excess arising due to the absorption opacity being dominated by free-free processes in the dense reprocessing envelope. We infer a large viewing angle of $\sim$60$^{\circ}$, consistent with previously reported X-ray observations, and a tidally disrupted star with mass > 2 M$_{\odot}$. The IR emission at later times is consistent with cool dust emission. We model these data as an IR echo and find that the dust is distant (0.65 pc), and clumpy, with a low covering factor. We show that TDEs can have an IR excess not arising from dust and that IR observations at early times can constrain the viewing angle for the TDE in the unified model. Near-IR observations are therefore essential to distinguish between hot dust and a non-thermal IR excess.

astro-ph.HE↗

arXiv2023

Diamond Surface Functionalization via Visible Light-Driven C-H Activation for Nanoscale Quantum Sensing

Nitrogen-vacancy centers in diamond are a promising platform for nanoscale nuclear magnetic resonance sensing. Despite significant progress towards using NV centers to detect and localize nuclear spins down to the single spin level, NV-based spectroscopy of individual, intact, arbitrary target molecules remains elusive. NV molecular sensing requires that target molecules are immobilized within a few nanometers of NV centers with long spin coherence time. The inert nature of diamond typically requires harsh functionalization techniques such as thermal annealing or plasma processing, limiting the scope of functional groups that can be attached to the surface. Solution-phase chemical methods can be more readily generalized to install diverse functional groups, but they have not been widely explored for single-crystal diamond surfaces. Moreover, realizing shallow NV centers with long spin coherence times requires highly ordered single-crystal surfaces, and solution-phase functionalization has not yet been shown to be compatible with such demanding conditions. In this work, we report a versatile strategy to directly functionalize C-H bonds on single-crystal diamond surfaces under ambient conditions using visible light. This functionalization method is compatible with charge stable NV centers within 10 nm of the surface with spin coherence times comparable to the state of the art. As a proof of principle, we use shallow ensembles of NV centers to detect nuclear spins from functional groups attached to the surface. Our approach to surface functionalization based on visible light-driven C-H bond activation opens the door to deploying NV centers as a broad tool for chemical sensing and single-molecule spectroscopy.

cond-mat.mtrl-sci↗

arXiv2023

One-step Preparation of ZnO Electron Transport Layers Functionalized with Benzoic Acid Derivatives

We present a "one-step" approach to modify ZnO electron transport layers (ETLs) used in organic solar cells. This approach involves adding benzoic acid (BZA) derivatives directly to the ZnO precursor solution, which are then present at the surface of the resulting ZnO film. We demonstrate this approach for three different BZA derivatives, namely benzoic acid, chlorobenzoic acid, and 4-hydrazinobenzoic acid. For all molecules, improved device performance and stability is demonstrated in solar cells using an active layer blend of PTQ10 (donor) and ITIC-Br (non-fullerene acceptor) compared to such cells prepared using untreated ZnO. Furthermore, similar or improved device performance and stability is demonstrated compared to conventional PEIE treatment of ZnO. The presence of the BZA derivatives at the surface after processing is established using X-ray photoelectron spectroscopy and near-edge X-ray absorption fine-structure spectroscopy. From atomic force microscopy analysis and X-ray diffraction studies, the addition of BZA derivatives appears to restrict ZnO grain growth; however, this does not negatively impact device performance. ZnO layers treated with BZA derivatives also exhibit higher water contact angle and lower work function compared to untreated ZnO. This approach enables simplification of device manufacture while still allowing optimization of the surface properties of metal oxide ETLs. Keywords: electron transport layers, zinc oxide, organic solar cells, surface modification

cond-mat.mtrl-sci↗

arXiv2021

Hydrothermal liquefaction of sewage sludge; energy considerations and fate of micropollutants during pilot scale processing

The beneficial use of sewage sludge for valorization of carbon and nutrients is of increasing interest while micropollutants in sludge are of concern to the environment and human health. This study investigates the hydrothermal liquefaction (HTL) of sewage sludge in a continuous flow pilot scale reactor at conditions expected to reflect future industrial installations. The processing is evaluated in terms of energy efficiency, bio-crude yields and quality. The raw sludge and post-HTL process water and solid residues were analyzed extensively for micropollutants via HPLC-MS/MS for target pharmaceuticals including antibiotics, blood pressure medicine, antidepressants, analgesics, x-ray contrast media, angiotensin II receptor blockers, immunosuppressant drugs and biocides including triazines, triazoles, carbamates, a carboxamide, an organophosphate and a cationic surfactant. The results show that a positive energy return on investment was achieved for all three HTL processing temperatures of 300, 325 and 350 °C with the most beneficial temperature identified as 325 °C. The analysis of the HTL by-products, process water and solids, indicates that HTL is indeed a suitable technology for the destruction of micropollutants. However, due to the large matrix effect of the HTL process water it can only be stated with certainty that 9 out of 30 pharmaceuticals and 5 out of 7 biocides products were destroyed successfully (over 98% removal). One compound, the antidepressant citalopram, was shown to be moderately recalcitrant at 300 °C with 87% removal and was only destroyed at temperatures $\geq$325 °C ($>$99% removal). Overall, the results suggest that HTL is a suitable technology for energy efficient and value added sewage sludge treatment enabling destruction of micropollutants.

physics.chem-ph↗

arXiv2015

Extremely high negative electron affinity of diamond via magnesium adsorption

We report large negative electron affinity (NEA) on diamond (100) using magnesium adsorption on a previously oxygen-terminated surface. The measured NEA is up to $(-2.01\pm0.05)$ eV, the largest reported negative electron affinity to date. Despite the expected close relationship between the surface chemistry of Mg and Li species on oxygen-terminated diamond, we observe differences in the adsorption properties between the two. Most importantly, a high-temperature annealing step is not required to activate the Mg-adsorbed surface to a state of negative electron affinity. Diamond surfaces prepared by this procedure continue to possess negative electron affinity after exposure to high temperatures, air and even immersion in water.

cond-mat.mtrl-sci↗

arXiv2014

Manipulating the orientation of an organic adsorbate on silicon: a NEXAFS study of acetophenone on Si(001)

We investigate the chemical and structural configuration of acetophenone on Si(001) using synchrotron radiation core-level spectroscopy techniques and density functional theory calculations. Samples were prepared by vapour phase dosing of clean Si(001) surfaces with acetophenone in ultrahigh vacuum. Near edge X-ray adsorption fine structure spectroscopy and photoelectron spectroscopy measurements were made at room temperature as a function of coverage density and post-deposition anneal temperature. We show that the dominant room temperature adsorption structure lies flat on the substrate, while moderate thermal annealing induces the breaking of Si-C bonds between the phenyl ring and the surface resulting in the reorientation of the adsorbate into an upright configuration.

cond-mat.mtrl-sci↗