Miracle-dz/UniFAR-FTUs huggingface dataset:
An 18.5nW, 62.9dB PSRR, Switched-Capacitor Bandgap Voltage Reference using Low Power Clock Generator Circuit for Biomedical Applications

This paper proposes a switched-capacitor network (SCN) based fractional bandgap voltage reference (BGR) circuit designed in 180nm CMOS process to achieve high accuracy and low power consumption for implantable biomedical applications. The design proposes a $V_{EB}$ generator that employs a 2x charge pump and an improved SCN to generate a temperature inde-pendent reference voltage $(V_{REF})$’. A low-power clock generator circuit is proposed, which reduces the leakage current by 37 % compared to previous works, thereby reducing the circuit's power consumption to 18.5nW at typical conditions. The design works from a supply voltage of 0.5V and has a TC of 74. Sppm/ ${}^{\circ} \mathrm{C}$ over a temperature range of $0-80^{\circ} \mathrm{C}$. The PSRR of the circuit is -62.9dB at 100Hz. Based on the Monte Carlo simulations of 500 samples, we obtain an untrimmed $3\sigma/\mu$ of 2.6%. The design occupies an active area of 0.027mm2.
When and Why Do People Want Ad Targeting Explanations? Evidence from a Four-Week, Mixed-Methods Field Study

Many people are concerned about how their personal data is used for online behavioral advertising (OBA). Ad targeting explanations have been proposed as a way to reduce this concern by improving transparency. However, it is unclear when and why people might want ad targeting explanations. Without this insight, we run the risk of designing explanations that do not address real concerns. To bridge this gap, we conducted a four-week, mixed-methods field study with 60 participants to understand when and why people want targeting explanations for the ads they actually encountered while browsing the web. We found that users wanted explanations for around 30% of the 4,251 ads we asked them about during the study, and that subjective perceptions of how their personal data was collected and shared were highly correlated with when users wanted ad explanations. Often, users wanted these explanations to confirm or deny their own preconceptions about how their data was collected or the motives of advertisers. A key upshot of our work is that one-size-fits-all approaches to ad explanations are likely to fail at addressing people’s lived concerns about ad targeting; instead, more personalized explanations are needed.
Introducing an Electrochemical Impedance Spectroscopy Methodology based on Volterra Filters

The paper proposes a novel Electrochemical Impedance Spectroscopy methodology that takes into account the nonlinearties present in the battery. For this purpose, the current-voltage relationship of the cell is modeled in discrete domain as a Volterra filter and the linear part of the nonlinear model is efficiently estimated using Orthogonal Periodic Sequences. Preliminary experimental results involving six lithium-ion cells show the soundness of the proposed approach also in comparison with the classical method.
Edge-Based Temporal Fusion Transformer for Multi-Horizon Blood Glucose Prediction

Deep learning models have achieved the state of the art in blood glucose (BG) prediction, which has been shown to improve type 1 diabetes (T1D) management. However, most existing models can only provide single-horizon prediction and face a variety of real-world challenges, such as lacking hardware implementation and interpretability. In this work, we introduce a new deep learning framework, the edge-based temporal fusion Transformer (E-TFT), for multi-horizon BG prediction, and implement the trained model on a customized wristband with a system on a chip (Nordic nRF52832) for edge computing. E-TFT employs a self-attention mechanism to extract long-term temporal dependencies and enables post-hoc explanation for feature selection. On a clinical dataset with 12 T1D subjects, it achieved a mean root mean square error of 19.09 ± 2.47 mg/dL and 32.31 ± 3.79 mg/dL for 30 and 60-minute prediction horizons, respectively, and outperformed all the considered baseline methods, such as N-BEATS and N-HiTS. The proposed model is effective for multi-horizon BG prediction and can be deployed on wearable devices to enhance T1D management in clinical settings.
Extraction of Overhead Transmission Towers from UAV Images

To ensure the integrity of power lines, electrical transmission towers must be monitored. Monitoring vegetation encroachment, which can lead to power outages, is a significant challenge. The majority of current monitoring techniques rely on manual labor and traditional methods of observation such as unmanned aerial vehicles (UAV) and airborne photography. Monitoring large areas with these methods, however, is expensive and time consuming. Our paper describes a method for monitoring power line corridors with UAV images. A two-stage procedure is proposed. Background clustering was performed using Fuzzy C-means in the first stage. Our second step was to detect the presence of transmission towers using state-of-the-art deep learning technologies AlexNet and DenseNet-121. By comparing the two deep learning architectures, the proposed methodology detects the transmission tower from VAV images with an accuracy of 94.8% for AlexNet and 98.6% for DenseNet - 121 with better precision, recall, and F1-score.
Autonomous change of behavior for environmental context: An intermittent search model with misunderstanding search pattern

Although foraging patterns have long been predicted to autonomously adapt to environmental conditions, empirical evidence has been found in recent years. This evidence suggests that the search strategy of animals is open to change so that animals can flexibly respond to their environment. In this study, we began with a simple computational model that possesses the principal features of an intermittent strategy, ie, careful local searches separated by longer steps, as a mechanism for relocation, where an agent in the model follows a rule to switch between two phases, but it could misunderstand this rule, ie, the agent follows an ambiguous switching rule. Thanks to this ambiguity, the agent's foraging strategy can continuously change. First, we demonstrate that our model can exhibit an autonomous change of strategy from Brownian‐type to Lévy type depending on the prey density, and we investigate the distribution of time intervals for switching between the phases. Moreover, we show that the model can display higher search efficiency than a correlated random walk.
The Mathematical Career of Pierre de Fermat

Fisher begins by sketching his achievements and denigrating those of Karl Pearson, who died 20 years before the first edition appeared. He then reviews the work of Bayes and Laplace in scientific inference, and discusses the criticisms of them made by Boole and others. His conclusion is that the data may sometimes permit an application of Bayes' theorem but that usually tests of significance and procedures of estimation are what is required. The main part of the book now follows. In the next two chapters, Fisher derives the fiducial distribution of an unknown parameter from the likelihood function when a sufficient statistic is available, and he gives an exhaustive discussion of significance tests. There are severe attacks on the use of confidence limits, and on the idea that a significance test is a means of taking decisions in an acceptance procedure. The last two chapters form the best part of the book. By now, the noise of battle has largely died away, and Fisher feels able to develop his ideas in comparative peace. Almost at once he states his attitude to mathematics, summarised in the following remark (p. Ill): "The axiomatic theory of mathematics has not been, and ought not to be, taken very seriously in those branches of the subject in which applications to real situations are in view. " A general discussion of inductive reasoning leads to more examples of Bayesian and fiducial arguments. The book concludes with a review of the Fisherian theory of estimation, which illustrates the use of ancillary statistics and culminates with a simultaneous fiducial distribution for the parameters of a bivariate normal distribution. Statistical inference is concerned with subtle questions which mathematics can partly but not wholly elucidate. For this reason, the views of all those who have made searching enquiries into the logic of induction continue to be relevant, from Jacob Bernoulli down to the present day. Fisher's book is concerned with the state of knowledge in 1962, recommends a particular viewpoint while disparaging others, and is difficult to read without previous knowledge of the problems involved and the solutions available. Thus, anyone who requires a modern and balanced introduction to statistical inference had better look elsewhere. On the other hand, Statistical methods and scientific inference remains essential reading, not only for those engaged in research who want an authoritative statement of Fisher's views on inference, but also for historians of statistics, presenting them as it does with a self-portrait by a man of genius. R. L. PLACKETT Department of Statistics, School of Mathematics, University of Newcastle upon Tyne NE1 7RU
A 94.6dB-SNDR 50kHz-BW 1-1-1 MASH ADC Using OTA-FIA Based Integrators

This paper presents a novel two-stage amplifier, which cascades a duty-cycled inverter-based OTA and a floating-inverter amplifier (FIA). The proposed OTA-FIA can achieve 72.0dB gain under a 1.2V supply, whose output swing is 420mV. Additionally, it exhibits intrinsic loop stability without compensation and reduces thermal noise during integration. The proposed OTA-FIA is adopted in a low distortion 1-1-1 MASH structure to obtain high resolution. Simulated in a 55 nm CMOS process, the proposed ADC can achieve an SNDR of 94.6dB with a bandwidth of 50kHz. It consumes $363.8\mu \mathrm{W}$ from a 1.2V supply at a 5MS/s sampling frequency, resulting in a 176.0dB SNDR-based Schreier FoM.
Investigation on the Potential of Biomethane Production from Abattoir Waste by Mono-digestion and Co-digestion

This study aimed to examine the potential of abattoir waste in producing bio-methane through mono and co-digestion. The potential of bio-methane production by mono-digestion of blood, cow dung and paunch content as well as the co-digestion of the same substrates was carried out at a ratio of 1:1:1. The digestion process was done using a Bioprocess Automatic Methane Potential Test System (AMPTS II) system at a mesophilic temperature of 37°C. The highest bio-methane yield was recorded in the ternary mixture at 2,178 NmL and for mono-digestion paunch content produced the highest volume of gas at 992 NmL. A volatile solids reduction of 81% was reported in the digestion of paunch content, which was the highest in all reactors. Higher volatile and total solids reduction results in higher biogas yield and blood were observed to have the lowest reduction in volatile and total solids and the lowest bio-methane yield at 518 NmL. A synergic effect with the highest synergic ratio was found in the ternary mixture at 2.95 and the lowest was for a binary mixture of paunch content and cow dung at 1.48. Kinetic analysis showed that the quadratic model was the best fit for the data compared to the linear model for both the mono and co-digested substrates.
A Spiking Neural Network Accelerator based on Ping-Pong Architecture with Sparse Spike and Weight

Spiking neural networks (SNNs) have attracted widespread interest due to their event-driven and low-power nature. Compared to Artificial Neural Networks (ANNs), SNNs have time dimension information and present more realistic brain-inspired computing models. However, it is challenging to deploy sparse spiking neuron network models on dense neuromorphic processors. In this paper, a spiking neural network accelerator with sparse spike and weight is presented, using ping-pong architecture to improve system data throughput. To reduce the inference delay, the proposed accelerator supports the decoupling of calculation of membrane potential and leaky integrate-and-fire (LIF) dynamics computing in the feedforward neural networks. Implemented on Xilinx Kintex UltraScale FPGA, the accelerator can achieve the peak performance of 65.7 GSOP/s and the energy efficiency of 41.7 GSOP/W in the task of classifying MNIST dataset. Under the full load, the whole system can run ping-pong when more than 43 time steps are calculated at a time.
Exact Box-Cox Analysis

The Box-Cox method has been widely used to improve estimation accuracy in different fields, especially in econometrics and time series. In this thesis, we initially review the BoxCox transformation [Box and Cox, 1964] and other alternative parametric power transformations. Following, the maximum likelihood method for the Box-Cox transformation is presented by discussing the problems of previous approaches in the literature. This work consists of the exact analysis of Box-Cox transformation taking into account the truncation effect in the transformed domain. We introduce a new family of distributions for the Box-Cox transformation in the original and transformed data scales. A likelihood analysis of the Box-Cox distribution is presented when truncation is considered. It is shown that numerical problems may arise in prediction and simulation when the truncation effect is ignored. A new algorithm has been developed for simulating Box-Cox transformed time series since previous methods are inefficient or unreliable. An application to sunspot data is discussed. Box-Cox analysis is employed for random forest regression prediction using cross-validation instead of MLE to estimate the transformation. An application to Boston housing dataset demonstrates that this technique can substantially improve prediction accuracy.
Solar-Powered Visible Light Communication: A Sustainable and Reliable Solution

The current communication method is by using radio frequency communication But due to various drawbacks of radio frequency such as the limitation of bandwidth, less secure and also we cannot use it for higher ranges as it can be harmful for human being. It can cause severe disease and has become expensive due to less availability of bandwidth we are facing drawbacks in wireless communication which involves RF. The visible light communication (VLC) technology can be used in place of radio frequency (RF) based wireless communication. It is an optical wireless technology which utilizes visible light of wavelengths (380-780nm), by using the visible light source as a signal transmitter, the air as the channel for the transmission of signal, and the suitable photodiode as a signal receier. VLC is an imaginative and capable optical remote innovation for short-range transmissions. Additionally, radio frequency (RF) holds a few downsides of fixed spectrum bandwidth and less security.LED is the foremost best choice for end of the future illumination and information transmission since of high power efficiency withhout any consequences on human body. This paper is introducing communication through visible light i.e. visible light Communication (VLC) with orthogonal frequency division multiplexing and On-off keying modulation techniques. It will be using solar panel as photo detector at receiver end instead of PIN (positive-intrinsic-negative) or Avalanche photodiodes (APDs) as it doesn't require any external power source more over this paper brings a future insight and cost effective method for communication. The major advantage and future scope of this technology is that it is very cheap and harmless to environment plan to solve the RF spectrum trouble and power shortage for future communication systems.
A 36 GHz Bandwidth, High Linear, Low Power, Driver Modulator, in 28 nm CMOS Technology Based on Quantized-Analog Signal Processing

In this work we present a wide-band amplifier that uses a novel analog pre-distioriton technique based on the quantized-analog (QA) signal processing. Such a technique is exploited to reach an almost rail-to-rail output swing with low distortion compatible with optical driver applications. Based on post layout simulations a 36 GHz −3 dB bandwidth prototype, integrated in 28 nm CMOS technology, shows a 3% Total Harmonic Distortion for 2 V peak-to-peak differential output swing at 1 GHz. The circuit operates under a 1.2 V supply voltage with a dynamic power consumption of 152 mW.
Unicode Analogies: An Anti-Objectivist Visual Reasoning Challenge

Analogical reasoning enables agents to extract relevant information from scenes, and efficiently navigate them in familiar ways. While progressive-matrix problems (PMPs) are becoming popular for the development and evaluation of analogical reasoning in computer vision, we argue that the dominant methodology in this area struggles to expose the lack of meaningful generalisation in solvers, and rein-forces an objectivist stance on perception - that objects can only be seen one way - which we believe to be counter-productive. In this paper, we introduce the Unicode Analogies challenge, consisting of polysemic, character-based PMPs to benchmark fluid conceptualisation ability in vision systems. Writing systems have evolved characters at multiple levels of abstraction, from iconic through to symbolic representations, producing both visually interrelated yet exceptionally diverse images when compared to those exhibited by existing PMP datasets. Our framework has been designed to challenge models by presenting tasks much harder to complete without robust feature extraction, while remaining largely solvable by human participants. We therefore argue that Unicode Analogies elegantly captures and tests for a facet of human visual reasoning that is severely lacking in current-generation AI.
Carbon dynamics after five decades of different crop residue management in temperate climate

Increasing soil organic carbon (SOC) in agricultural soils is nowadays receiving growing attention also due to the COP21 initiative of “4 per 1000”. In this study, the effect of five decades of different residue management (residue removal, residue incorporation, and residue incorporation + poultry manure) was investigated on SOC stock and related to the 4 per 1000 and C saturation concepts. Preliminary results showed that higher 0-60 cm SOC stock was found after 54 years of the 10 experiment when residues were incorporated into the soil compared to residue removal (75.0 vs 69.0 t ha -1 ) while poultry manure had a negligible effect. Comparing the 0-30 cm SOC stock with pre-existent data series, a general decreasing trend was observed from the start of the experiment in 1966 up to 1986, being greater in residual removal (-8.6 t ha -1 ) than residual incorporation (-4.8 t ha -1 , irrespective of poultry manure addition). In 2020, the difference between the above-mentioned systems was 4.1 t ha -1 corresponding to a 2.2 ‰ which is lower than what was suggested by the 4 per 1000 initiative. This 15 SOC stock attributed to residue retention arose in response to 141 t C ha -1 residue resulting in a 0.1% yearly conversion rate that is sensibly lower than what is generally reported in the literature. Therefore, an alternative use (e.g., bioenergy production) of at least part of crop residues is conceivable in temperate climate for a more efficient C cycle. The studied soil was demonstrated also to be far from C saturation, being in the 30-47% degree of saturation range. Therefore, specific studies on how both organic and inorganic (i.e., carbonates) C fractions related to different soil aggregates and aggregate
Сlinical features of asthma-COPD overlap syndrome with comorbid type 2 diabetes mellitus

Background. Comorbidity profiles are a common subject of research in patients with asthma-COPD (chronic obstructive pulmonary disease) overlap (ACO), but in case of concurrent type 2 diabetes mellitus (T2DM), there is a lack of targeted research on the quality of life, clinical course, and lung function. The aim of the study was to clarify the clinical features of asthma-COPD overlap in combination with T2DM. Materials and methods. Sixty-nine patients were examined: 24 with ACO and T2DM (group 1), 21 with asthma and T2DM (group 2), and 24 with COPD and T2DM (group 3). A diagnosis of ACO was made according to GINA and GOLD 2017 guidelines. Quality of life was assessed using the CAT, ACQ, and SGRQ, and the severity of dyspnea was assessed using the mMRC scale, disease severity and prognosis using the BODE index. Spirometry with bronchodilation test, 6-minute walk test, and bioimpedance analysis were performed. Results. Patients in the main group had a higher total SGRQ score than those in group 3 (by 33 %, p = 0.001). Higher ACQ and total SGRQ scores indicate a trend toward worse asthma control and lower quality of life in patients with ACO and T2DM compared to the asthma + T2DM group (p = 0.056 and p = 0.054, respectively). Body mass index was higher than in patients with COPD and T2DM (by 16.3 %, p = 0.001). Higher serum glucose levels were found in patients with ACO and T2DM than in those with COPD and T2DM (by 18.3 %, p = 0.028). The FEV1 in the ACO and T2DM group was lower than in the asthma + T2DM group (by 18.7 %, p = 0.027), and the SVC was lower by 33 % (p = 0.021). There was a tendency to a lower result in the 6-minute walk test in the main group compared to patients from group 3 (p = 0.0548), and a higher frequency of exacerbations per year compared to groups 2 (p = 0.08) and 3 (p = 0.06). Conclusions. Patients with asthma-COPD overlap and concurrent type 2 diabetes mellitus have worse quality of life, lower FEV1 and SVC, submaximal exercise tolerance, higher fasting glucose levels, and a tendency towards increased exacerbation frequency.
proximal balloon occlusion of the internal carotid Intracavernous aneurysms: treatment by

Seven patients with intracavernous aneurysms were treated by proximal balloon occlusion of the carotid artery, with no attempt to preserve carotid blood flow, After a 15-minute occlusion trial, two balloons were detached proximal to the neck of these aneurysms. Major clinical improvement occurred in six patients and no procedure related complications were encountered (the follow-up period was 4-14 months). Be cause these aneurysms arise proximal to major collateral pathways, proximal carotid occlusions via endovascular techniques are simple and safe and carry with them little risk of thromboembolism.
Understanding Spanish University Students’ Monitoring Failures and Regulatory Actions When Reading in EFL

The present paper analyses the reasons for comprehension monitoring failure and the regulatory actions performed by Spanish university students when reading in English as a Foreign Language (EFL). Two different but connected empirical studies were conducted to obtain data about students’ behaviour during a reading task. In Study 1, comprehension monitoring was assessed following the Error Detection Paradigm. Then, semi-structured interviews were conducted to analyse subjects’ regulatory actions. In Study 2, a questionnaire was proposed to classify subjects’ detection X regulation actions when reading in EFL. Results showed that participants’ comprehension monitoring level was not very high according to other literature findings. Moreover, the lack of language proficiency could imply additional processing and monitoring difficulties. The questionnaire accounted for a great percentage of participants’ behaviour: semantic obstacles, spurious detections, no re-reading, skip information or no detection. Knowing students’ reading obstacles is necessary for teachers and practitioners in order to help students become effective readers.