A long and winding road: a brief history of the idea of a ‘government of national unity’ in Timor-Leste and its current implications

Abstract In this Discussion Paper, I consider first the academic debate on the establishment of democracy and the role of political competition and cooperation as a background to the current Timorese government formula. This is followed by a brief historical tour of the idea of institutional inclusion in the Timorese recent past (including actual opposition to it) in order to frame the following discussion of some problems that the inauguration of a new form of government may pose in the process of democratic consolidation. I shall then address the rationale for change that may explain the decision to revert to the new formula, whose merits and limitations will also be discussed. Finally, one and a half years after the inauguration of the new government, Timor- Leste has been shaken by political events that call into question whether the scope of ‘inclusion’ of its basis is actually so broad as to embody ‘national unity’, as important players (such as President Taur Matan Ruak) appear to be challenging critical decisions of Rui Maria de Araújo and his government. The end of History is not in sight

Unraveling the paradox of intensity-dependent DVS pixel noise

Dynamic vision sensor (DVS) event camera output is affected by noise, particularly in dim lighting conditions. A theory explaining how photon and electron noise affect DVS output events has so far not been developed. Moreover, there is no clear understanding of how DVS parameters and operating conditions affect noise. There is an apparent paradox between the real noise data observed from the DVS output and the reported noise measurements of the logarithmic photoreceptor. While measurements of the logarithmic photoreceptor predict that the photoreceptor is approximately a first-order system with RMS noise voltage independent of the photocurrent, DVS output shows higher noise event rates at low light intensity. This paper unravels this paradox by showing how the DVS photoreceptor is a second-order system, and the assumption that it is first-order is generally not reasonable. As we show, at higher photocurrents, the photoreceptor amplifier dominates the frequency response, causing a drop in RMS noise voltage and noise event rate. We bring light to the noise performance of the DVS photoreceptor by presenting a theoretical explanation supported by both transistor-level simulation results and chip measurements.Comment: Presented in 2021 International Image Sensor Workshop (IISW

Feedback control of event cameras

Dynamic vision sensor event cameras produce a variable data rate stream of brightness change events. Event production at the pixel level is controlled by threshold, bandwidth, and refractory period bias current parameter settings. Biases must be adjusted to match application requirements and the optimal settings depend on many factors. As a first step towards automatic control of biases, this paper proposes fixed-step feedback controllers that use measurements of event rate and noise. The controllers regulate the event rate within an acceptable range using threshold and refractory period control, and regulate noise using bandwidth control. Experiments demonstrate model validity and feedback control

Shining light on the DVS pixel: A tutorial and discussion about biasing and optimization

The operation of the Dynamic Vision Sensor (DVS) event camera is controlled by the user through adjusting different bias parameters. These biases affect the response of the camera by controlling - among other parameters - the bandwidth, sensitivity, and maximum firing rate of the pixels. Besides determining the response of the camera to input signals, biases significantly impact its noise performance. Bias optimization is a multivariate process depending on the task and the scene, to which the user’s knowledge about pixel design and non-idealities can be of great importance.In this paper, we go step-by-step along the signal pathway of the DVS pixel, shining light on its low-level operation and non-idealities, comparing pixel level measurements with array level measurements, and discussing how biasing and illumination affect the pixel’s behavior. With the results and discussion presented, we aim to help DVS users achieve more hardware-aware camera utilization and modelling

Exploiting Alternating DVS Shot Noise Event Pair Statistics to Reduce Background Activity Rates

Dynamic Vision Sensors (DVS) record ”events” corresponding to pixel-level brightness changes, resulting in dataefficient representation of a dynamic visual scene. As DVS expand into increasingly diverse applications, non-ideal behaviors in their output under extreme sensing conditions are important to consider. Under low illumination (below ≈10 lux) their output begins to be dominated by shot noise events (SNEs) which increase the data output and obscure true signal. SNE rates can be controlled to some degree by tuning circuit parameters to reduce sensitivity or temporal response bandwidth at the cost of signal loss. Alternatively, an improved understanding of SNE statistics can be leveraged to develop novel techniques for minimizing uninformative sensor output. We first explain a fundamental observation about sequential pairing of opposite polarity SNEs based on pixel circuit logic and validate our theory using DVS recordings and simulations. Finally, we derive a practical result from this new understanding and demonstrate two novel biasing techniques shown to reduce SNEs by 50% and 80% respectively while still retaining sensitivity and/or temporal resolution

Optimal biasing and physical limits of DVS event noise

Under dim lighting conditions, the output of Dynamic Vision Sensor (DVS) event cameras is strongly affected by noise. Photon and electron shot-noise cause a high rate of non-informative events that reduce Signal to Noise ratio. DVS noise performance depends not only on the scene illumination, but also on the user-controllable biasing of the camera. In this paper, we explore the physical limits of DVS noise, showing that the DVS photoreceptor is limited to a theoretical minimum of 2x photon shot noise, and we discuss how biasing the DVS with high photoreceptor bias and adequate source-follower bias approaches optimal noise performance. We support our conclusions with pixel-level measurements of a DAVIS346 and analysis of a theoretical pixel model

Demystifying Event-based Sensor Biasing to Optimize Signal to Noise for Space Domain Awareness

Neuromorphic dynamic vision sensors (DVS), often called event-based sensors (EBS), are a novel class of cameras that have recently shown potential to make a significant impact in the SDA community. Their biologically-inspired design simultaneously achieves high temporal resolution, wide dynamic range, low power consumption and sparse data output, making them an ideal fit for space applications. Although initial results for SDA are promising, they typically exhibit elevated noise rates in dim conditions and have thus far failed to outperform conventional cameras in terms of limiting visual magnitude and sensitivity with high telescope scan rates. A hurdle for widespread adoption is a lack of general guidance regarding optimal camera biases (settings) for SDA. Prior studies either serve as proof of concept or focus on algorithm development; however, to date, none have provided detailed guidance on biasing EBS to optimize signal to noise ratio (SNR) for SDA tasks. The goal of this paper is to narrow the knowledge gap between EBS pixel biasing and resulting performance to optimize their capabilities for SDA. To accomplish this, we adopt a bottom-up approach, revisiting the pixel architecture to consider physics-based performance limitations. In an EBS, each pixel responds autonomously, generating "events" in response to local brightness changes within its field of view (FOV), and outputs a sparse representation of the visual scene where each event is encoded by a pixel address (x,y), a microsecond resolution timestamp (t), and a single bit polarity value (p) indicating either an increase or decrease in brightness by a defined threshold. In most camera models, behavior is fine-tuned by adjusting roughly a half-dozen biases, including threshold levels (sensitivity), bandwidth (speed of the front-end photoreceptor), and refractory period (dead-time between events in a given pixel). These parameters make EBS cameras adaptable for varied applications, but many degrees of freedom presents a challenge for optimization. Researchers unfamiliar with the technology can be overwhelmed by the myriad of biasing options and must either rely on a prescribed set of biases or manually adjust them to achieve desired performance; the latter is not typically recommended for non-experts due to 2nd-order effects such as excessive noise rates. Manufacturer default biases are considered optimized for a broad range of applications, but recent studies have demonstrated non-conventional bias techniques can significantly reduce background noise in dim conditions while still retaining signal, suggesting that SDA capabilities could be improved by a more sophisticated biasing strategy. By conducting a detailed study of how sensitivity, response speed, and noise rates scale with varied bias configurations, we aim to approach an optimal SNR bias configuration and demonstrate the maximal capabilities of current generation COTS EBS cameras for SDA. To systematically analyze and benchmark performance against a calibrated and repeatable stimulus, we developed a custom SDA test-bench to simulate stars/satellites as sub-pixel point source targets of variable speed and brightness. The set-up includes an integrating light box to provide a calibrated flat-field illumination source, a custom 170 mm radius anodized aluminum disk with precision drilled holes of diameters ranging from 100 to 250 microns, and a digitally programmable motor capable of precise speed control from ~0.1 to 800 RPM. The disk is backlit by the flat-field illumination source and connected to the motor shaft, and a 7 x 10 cm region is viewed through a Fujinon 1:1.8/7-70mm CS mount lens at a distance of 50 cm. The FOV and zoom are chosen such that the dimension of the largest holes is still sub-pixel in diameter when in focus. Even with the ability to rapidly collect measurements with this setup, the overall parameter space is still too large to fully explore without any a-priori knowledge about how the sensor responds to signal and noise, and how this depends on biases. As a result, we consider fundamental pixel behaviors to devise an efficient test strategy. We first consider strategies to limit noise rates, as these can overwhelm sensor readout when the background is dark. In prior work, this was presumably accomplished by either reducing the bandwidth biases or increasing threshold biases, but these approaches inherently limit signal. Instead of this naive approach, we draw inspiration from two recent studies: the first demonstrated an optimal balance between two bandwidth related biases accessible in some camera prototypes, and the second relies on a key observation about the statistical distribution of noise events to devise two additional biasing techniques to enhance SNR by allowing either lower thresholds or broader bandwidth settings. Using these techniques as a starting point, we examine the performance the DAVIS346 EBS. We first report baseline performance using manufacturer default biases. To quantify performance, we measure sensitivity (dimmest point source detected) and bandwidth (fastest point source detected). Next, we tune bias settings with specific detection goals (i.e. maximum velocity and/or minimum brightness) and analyze the results. Finally, we apply newly developed low-noise bias techniques and attempt to identify general principles that can be applied universally to any EBS camera to improve performance in SDA tasks. This paper provides a baseline for understanding EBS performance characteristics and will significantly lower the entry barrier for new researchers in the field of event-based SDA. More importantly, it adds insight for optimizing EBS behavior for SDA tasks and demonstrates the absolute performance limits of current generation cameras for detecting calibrated point source targets against a dark background. Finally, this study will enable follow-on work including the development of customized denoising, detection, and tracking algorithms that consider signal response and noise statistics as a function of the selected camera and bias configuration

Copper complex nanoformulations featuring highly promising therapeutic potential in murine melanoma models

Aim: Preclinical evaluation of a cytotoxic copper(II) complex formulated in long circulating nanoliposomes for melanoma treatment. Materials & methods: Liposomal nanoformulations of the copper complex were characterized in terms of thermodynamic behavior (differential scanning calorimeter), pH-sensitivity (spectrophotometry) and antiproliferative effects against murine melanoma B16F10 cells in vitro. Preclinical studies were performed in a C57BL/6 syngeneic melanoma model. Results: Nanoformulations were thermodynamically stable, and CHEMS-containing nanoliposomes were pH-sensitive and preserved the antiproliferative properties of the copper compound. These nanoformulations significantly impaired tumor progression in vivo, devoid of toxic side effects, compared with control mice or mice treated with the free metallodrug. Conclusion: Copper complex-containing nanoliposomes demonstrate high anticancer efficacy and safety, constituting a step forward to the development of more effective therapeutic strategies against melanoma

A 23μW Solar-Powered Keyword-Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction

Voice-controlled interfaces on acoustic Internet-of-Things (IoT) sensor nodes and mobile devices require integrated low-power always-on wake-up functions such as Voice Activity Detection (VAD) and Keyword Spotting (KWS) to ensure longer battery life. Most VAD and KWS ICs focused on reducing the power of the feature extractor (FEx) as it is the most power-hungry building block. A serial Fast Fourier Transform (FFT)-based KWS chip [1] achieved 510nW; however, it suffered from a high 64ms latency and was limited to detection of only 1-to-4 keywords (2-to-5 classes). Although the analog FEx [2]–[3] for VAD/KWS reported 0.2μW-to-1 μW and 10ms-to-100ms latency, neither demonstrated >5 classes in keyword detection. In addition, their voltage-domain implementations cannot benefit from process scaling because the low supply voltage reduces signal swing; and the degradation of intrinsic gain forces transistors to have larger lengths and poor linearity