Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-stage Hardware-Friendly Epileptic Seizure Detection Method with a Dynamic Feature Selection

A novel low-complexity method of detecting epileptic seizures from intracranial encephalography (iEEG) signals is presented. In the proposed algorithm, coastline, energy and nonlinear energy features of iEEG signals are extracted in a patient-specific two-stage seizure detection system. The detection stage of the proposed system, which extracts two times more features than the monitoring stage, is only powered on when the monitoring stage detects a seizure occurrence. A new metric is defined to demonstrate the significance of the two-stage architecture and show the time duration over which the detection stage is activated. The new parameter is called detection stage activation ratio (DAR) and it is equal to 0.272 in this work. In addition, the proposed seizure detector outperforms other algorithms which utilize a single feature or multiple features continuously in terms of sensitivity, specificity and DAR. Therefore, it is highly suitable for seizure detector implants in which reducing the power consumption is a critical factor to increase the lifetime of the implanted battery. The algorithm is implemented on a Cyclone V FPGA and has a low dynamic power of 1 μW when tested on human iEEG signals of six patients from the Bern Inselspital dataset. It reaches a perfect sensitivity of 100% tested on 120 hours of iEEG data containing 24 seizure periods of six patients.
Kalman Filtering to Track Changes in Pupil Size for Automated Driving Systems

Automation has become indispensable in all walks of everyday life. In driving environments, Automated Driving Systems (ADS) aid the driver by reducing the required workload and by improving road safety. These systems require human drivers to remain vigilant and maintain supervisory control over ADS. Therefore, the cognitive attention of the drivers must be estimated accurately for the safe adoption of ADS. Because of the non-invasive recording setup used in low-cost infrared eye-trackers, pupil size measurements are increasingly becoming applicable in the estimation of cognitive load. However, pupil size measurements are highly noisy, resulting in the poor classification of cognitive load levels. In this paper, we propose a methodology for improved classification of changes in cognitive load through the introduction of a state-space model-based approach to filter the pupil size data. The proposed approach was demonstrated on data collected from 16 participants while they performed driving task and several secondary tasks that are designed to emulate three different levels of driving distraction.
Trajectory Design of UAV Aided Wireless Information and Energy Provision

A typical unmanned aerial vehicle (UAV) aided communication system with multiple user equipments (UEs) is investigated in this paper. The UE's information and energy maximization problem is proposed by optimizing the UAV's trajectory, transmit power and hovering time. The problem is decomposed into four sub-problems: dividing UEs, solving hovering positions of the UAV, designing UAV's trajectory and optimizing problem. Then, a K-clustering algorithm combined with Fermat Problem is considered to solve some sub-problems. In addition, UAV's trajectory is obtained by using dynamic programming (DP) to solve the TSP problem. The numerical results verify that our proposed algorithms effectively reduce the number of hovering positions of the UAV. Besides, the proposed optimization problems also improve the performance of information and energy transmission compared with the energy optimization only and information optimization only schema.
SIMC: ML Inference Secure Against Malicious Clients at Semi-Honest Cost

Secure inference allows a model owner (or, the server) and the input owner (or, the client) to perform inference on machine learning model without revealing their private information to each other. A large body of work has shown efﬁcient cryptographic solutions to this problem through secure 2-party computation. However, they assume that both parties are semi-honest, i.e., follow the protocol speciﬁcation. Recently, Lehmkuhl et al. showed that malicious clients can extract the whole model of the server using novel model-extraction attacks. To remedy the situation, they introduced the client-malicious threat model and built a secure inference system, M USE , that provides security guarantees, even when the client is malicious. In this work, we design and build S IMC , a new cryptographic system for secure inference in the client malicious threat model. On secure inference benchmarks considered by M USE , S IMC has 23 − 29 × lesser communication and is up to 11 . 4 × faster than M USE . S IMC obtains these improvements using a novel protocol for non-linear activation functions (such as ReLU ) that has > 28 × lesser communication and is up to 43 × more performant than M USE . In fact, S IMC ’s performance beats the state-of-the-art semi-honest secure inference system! Finally, similar to M USE , we show how to push the majority of the cryptographic cost of S IMC to an input independent preprocessing phase. While the cost of the online phase of this protocol, S IMC ++, is same as that of M USE , the overall improvements of S IMC translate to similar improvements to the preprocessing phase of M USE .
THE ENERGY REQUIREMENT OF WALKING WITH RESTRICTED BLOOD FLOW

Previous research has demonstrated favorable outcomes with restricted blood flow walking. The purpose of this study was to investigate if using elastic knee wraps as a mode of blood flow restriction (BFR) could increase oxygen consumption (VO2), energy expenditure (EE) and heart rate (HR) over control (CON) during low intensity walking. Ten healthy men and women performed two trials of treadmill walking with (BFR) and without (CON) restricted blood flow. Elastic knee wraps (76 mm wide) were placed around the upper thigh of both legs during BFR. Exercise consisted of five 2-min bouts of walking at 75 m/min with, 1-min rest between each bout. VO2, EE, and HR were measured following each exercise bout. VO2 and EE was significantly higher with BFR for bouts 2-5, but was not different after the first bout, or 3 minutes post exercise. HR was significantly elevated over control with BFR at every time point except baseline. In conclusion, there are differences for VO2, EE, and HR between BFR and CON, despite both walking at the same absolute workload. It remains unknown if subtle differences in EE between exercise conditions results in favorable physiologic change over time.
A Forty Year Assessment of Forecasting the Boat Race

We study the forecasting of the yearly outcome of the Boat Race between Cambridge and Oxford. We compare the relative performance of different dynamic models for forty years of forecasting. Each model is defined by a binary density conditional on a latent signal that is specified as a dynamic stochastic process with fixed predictors. The out-of-sample predictive ability of the models is compared between each other by using a variety of loss functions and predictive ability tests. We find that the model with its latent signal specified as an autoregressive process cannot be outperformed by the other specifications. This model is able to correctly forecast 30 out of 40 outcomes of the Boat Race.
Robust Model Predictive Control for Takagi-Sugeno Model with Bounded Disturbances – Pólya Approach

This paper proposes a general robust model predictive control (MPC) approach for the constrained Takagi-Sugeno (T-S) fuzzy model with additive bounded disturbances. We adopt the homogeneous polynomially parameter-dependent (HPP) Lyapunov matrix with the arbitrary complexity degree and the corresponding HPP control law for the controller design. By applying the Pólya’s theorem and the extended nonquadratic boundedness property, a systematic approach to construct a set of sufficient conditions for assessing robust stability described by parameter-dependent linear matrix inequalities (LMIs) is established. The proposed approach is an improvement over existing approaches in terms of control performance and stabilizable model range. Numerical examples are provided to show the effectiveness of the proposed robust MPC approach.
Uni- and Bimodal Threat Cueing with Vibrotactile and 3D Audio Technologies in a Combat Vehicle

An experiment investigated uni- and bimodal cueing of horizontal threat directions to the driver of the Combat Vehicle 90 (CV 90). 3D audio in headphones or tactile vibration onto the torso, or both in combination were utilized for threat cueing. Ten male CV 90 drivers from the Swedish Army Combat School were required to turn the vehicle toward the threat as quickly and accurate as possible. Each driver handled 45 threats in total. Each of five threat directions was presented three times for each of the three threat cueing conditions. The results show that the drivers had good overall performance, albeit the 3D audio needs improvement with regard to front - back confusion if not used with tactile cueing. That is, the 3D audio generated greater localization errors and reaction times with threats straight behind the vehicle compared with the tactile and the 3D audio/tactile combination, respectively.
Reliable Processing in Flash With High Temperature

Flash’s endurance limits its employment in data-intensive processing in-memory (PiM) applications. We propose a high-temperature environment and Circadian Rhythm adoption to tackle the endurance limitation of flash memory that is used as a processing element. We found that flash memory behaves more reliably at higher temperatures, and Circadian Rhythm prevents most of the permanent damage. Even though data retention decreases with increasing temperature, flash operations (read, erase, program) yield more correct outcomes and are less destructive (causing less stress) at high temperatures. Therefore, in contrast to storage applications, PiM applications perform more reliably at high temperatures. We propose a solid-state drive architecture that consists of both hot (for processing) and cold (for storage) flash memories. Our results indicate that lifetime without an Error Correction Code (ECC) (i.e., considering the first occurrence of an error) increases by 100%, and raw byte error at 180k Program/Erase cycle count decreases by 99.975% while increasing the temperature from 50 °C to 95 °C. Employment of Circadian Rhythms “500-1h” (i.e., 500 P/E cycles followed by 1 hour of recovery) increases lifetime without an ECC of the flash by 82%, and decreases raw byte error by 95.5% over “200k-10h”. This promising increase in lifetime paves the way for processing data-intensive applications in flash.
The influence of dogs’ presence on children’s performance on cognitive tests: Implications for clinical practice.

Evidence suggests that cognitive assessments can evoke feelings of stress for some children, potentially inhibiting cognitive performance and undermining the validity of results. Dogs have been found to be an unobtrusive form of social support for children in other settings, potentially offering a solution to this problem. The aim of this paper was to critically review the literature to explore what effect, if any, dogs may have on children’s performance on cognitive tests, and consider implications for clinical practice. To do so, five databases were systematically searched and returns were screened for eligibility. Studies were collectively described and then appraised using a common appraisal framework. Nine studies exploring the relationship between dogs and cognitive functioning in children (≤18 years) were identified in the literature search. All used an experimental methodology and were of good to fair quality. Together, results indicated that the presence of a dog could reduce stress and enhance cognitive performance across various domains, lending experimental evidence to support the idea that dogs may support children undergoing cognitive assessments. Further trials are now required to explore the generalizability of these associations to clinical settings and implications for test validity. Further implications for policy and practice are discussed.
Silicon micro-levers and a multilayer graphene membrane studied via laser photoacoustic detection

Abstract. Laser photoacoustic spectroscopy (PAS) is a method that utilizes the sensing of the pressure waves that emerge upon the absorption of radiation by absorbing species. The use of the conventional electret microphone as a pressure sensor has already reached its limit, and a new type of microphone – an optical microphone – has been suggested to increase the sensitivity of this method. The movement of a micro-lever or a membrane is sensed via a reflected beam of light, which falls onto a position-sensing detector. The use of one micro-lever as a pressure sensor in the form of a silicon cantilever has already enhanced the sensitivity of laser PAS. Herein, we test two types of home-made sensing elements – four coupled silicon micro-levers and a multilayer graphene membrane – which have the potential to enhance this sensitivity further. Graphene sheets possess outstanding electromechanical properties and demonstrate impressive sensitivity as mass detectors. Their mechanical properties make them suitable for use as micro-/nano-levers or membranes, which could function as extremely sensitive pressure sensors. Graphene sheets were prepared from multilayer graphene through the micromechanical cleavage of basal plane highly ordered pyrolytic graphite. Multilayer graphene sheets (thickness ∼102 nm) were then mounted on an additional glass window in a cuvette for PAS. The movements of the sheets induced by acoustic waves were measured using an He–Ne laser beam reflected from the sheets onto a quadrant detector. A discretely tunable CO2 laser was used as the source of radiation energy for the laser PAS experiments. Sensitivity testing of the investigated sensing elements was performed with the aid of concentration standards and a mixing arrangement in a flow regime. The combination of sensitive microphones and micromechanical/nanomechanical elements with laser techniques offers a method for the study and development of new, reliable and highly sensitive chemical sensing systems. To our knowledge, we have produced the first demonstration of the feasibility of using four coupled silicon micro-levers and graphene membranes in an optical microphone for PAS. Although the sensitivity thus far remains inferior to that of the commercial electret microphone (with an S / N ratio that is 5 times lower), further improvement is expected to be achieved by adjusting the micro-levers and membrane elements, the photoacoustic system and the position detector.
Hemoglobin A1c levels do not predict primary arteriovenous fistula failure in hemodialysis patients

Objectives: In this study, we aimed to assess whether higher preoperative levels of glycated hemoglobin (HbA1c) could predict primary arteriovenous fistula (AVF) failure and to investigate the effect of diabetes mellitus on primary arteriovenous failure. Patients and methods: Between July 2018 and August 2019, a total of 127 newly created AVFs in 117 patients (67 males, 50 females; mean age: 62.4±12.2 years; range, 18 to 86 years) who underwent primary AVF operation in our cardiovascular surgery clinic were retrospectively analyzed. Medical data were obtained from the institutional database. Arteriovenous f istula failure was evaluated during follow-up. Results: Primary AVF failure was seen in 24 (18.9%) patients. Patients with diabetes mellitus had a higher ratio of failure compared to those without (62.5% vs. 38.8%, respectively; p=0.035). After adjustment, diabetes mellitus was not found to be an independent risk factor for AVF failure (p>0.05). There was no significant correlation between HbA1c levels and fistula failure (p>0.05). Conclusion: Our study results suggest that diabetes is associated with AVF failure, but it is not an independent risk factor for AVF failure. Higher HbA1c levels fail to predict AVF failure.
Study of Heart Rate Variability in Middle-Aged Adults with Hypertension

Introduction: Hypertension is one of the important causes of coronary heart disease and cerebrovascular disease. The autonomic nervous system has a significant role in the circulatory system and blood pressure regulation. Analysis of heart rate variability (HRV) is a non-invasive tool that is widely used to assess autonomic nervous function. Aims & Objectives: The study aimed to analyze HRV in Hypertensive individuals. Materials & Methods: An analytical study was conducted on 50 normotensives and 50 hypertensives in the age group of 40–60 years. Blood pressure was measured by using a sphygmomanometer in sitting position. According to JNC VII criteria, normotensives are those with SBP ≤ 120 mmHg and DBP ≤ 80 mmHg. Hypertensives are those with SBP ≥ 140 mmHg and DBP ≥ 90 mmHg. HRV is measured for 2min using Polar H10 chest strap and data is analyzed using Elite HRV software. In Time-domain methods Mean RR, SDNN, RMSSD, and PNN50 were assessed. In Frequency domain methods LF, HF, and LF/HF were assessed. The data was entered into Excel 2016 and SPSS version 21 was used for analysis. An unpaired “t” test was used to compare the HRV values between normotensive and hypertensive groups. Results: Mean HR, SDNN, RMSSD, PNN50, and HF were found to be decreased and LF, LF/HF were increased in hypertensives suggesting increased sympathetic activity and reduced parasympathetic activity in hypertensives. All the values were statistically significant (p<0.01). Conclusion: There is increased sympathetic activity and a decreased vagal tone associated with hypertension. Thus HRV can be used as a routine screening test to predict the future risk of hypertension at an earlier stage and also for a better prognosis during treatment.
Continuous-wave singly-resonant intracavity optical parametric oscillator based on periodically-poled LiNbO3

A singly-resonant optical parametric oscillator using PPLN and operating intracavity to a continuous-wave Ti:sapphire laser is described. The oscillator exhibits multi-parameter pump- and grating-tuning of signal and idler wavelengths over the ranges 1.073–1.275 µm and 2.30–3.33 µm and 280 mW output power. Observation of thermal lensing in PPLN is also reported.
Isolation and characterization of acid-soluble collagen from the skin of Rutilus frisii

This study proceeds to extract collagen from the skin of Rutilus kutum, one of the main and economical species of the Caspian Sea. Acid-soluble collagen (ASC) from the skin of R. kutum was extracted and characterized by SDS-PAGE, FTIR and UV spectrophotometry. Based on the data from the SDS-PAGE and the composition of amino acid, it was probable that the obtained collagen classified as type I collagen. Collagen consists of two different types of α chain, including α1 and α2, and β components. Also, FTIR analysis revealed the presence of the helical arrangements of the collagen. Moreover, UV spectrophotometry exhibited this collagen has an absorbance at 220 nm. On the basis of dry weight, the yield of ASC was calculated as 15.6%. The amount of proline in ASC was 89.6 residues per 706.1 residues, and 25.7% of the collagen was composed of glycine. These results showed that R. kutum skin could be considered as a possible source of collagen and can supply the theoretical basis for further research.
CMAR_A_255072 6755..6766

*These authors contributed equally to this work Purpose: This study was done to investigate the influence of PDL1-gene polymorphism on the prognosis and safety of postoperative patients with non–small cell lung cancer (NSCLC) who had received platinum-based adjuvant chemotherapy. Methods: A total of 289 postoperative patients with NSCLC who had received platinumbased adjuvant chemotherapy from January 2012 to June 2019 participated in this study. Recurrence status and adverse reactions were documented during adjuvant chemotherapy. Overall survival (OS) data were obtained through telephone follow-up. DNA extracted from hematologic specimens was genotyped for PDL1-gene polymorphism. Associations between genotype status and prognosis were assessed using Kaplan–Meier survival analysis, and multivariate adjustment was performed using Cox regression analysis. Results: Median disease-free survival of the 289 patients with NSCLC was 3.3 years and median OS 4.9 years. With regard to the PDL1 gene polymorphism, only rs822336 was of clinical significance in the subsequent analysis. The minor-allele frequency of rs822336 was 0.21, and distribution of the three genotypes was in accordance with the Hardy–Weinberg equilibrium (P=0.807). Survival analysis according to genotype status suggested that median disease-free survival of patients with GG and GC/CC genotypes was 2.8 and 4.1 years, respectively (P=0.01). Median OS of patients with GG and GC/CC genotypes was 4.1 and 5.4 years, respectively (P=0.008). However, the safety analysis failed to find a significant association between the polymorphism and adverse reactions. Interestingly, expression analysis of RNA extracted from peripheral blood mononuclear cells indicated that PDL1-mRNA expression of patients with the GG genotype was significantly higher than for the GC/CC genotype (P<0.001). Conclusion: The prognosis of postoperative patients with NSCLC who have received platinum-based adjuvant chemotherapy may be influenced by the rs822336 polymorphism through mediation of the mRNA expression of PDL1.
Managerial Horizon and Corporate Labor Policies: Evidence from Fixed-Term Boards

We examine the relationship between managerial incentives and firms’ human resources policies by combining Italian social security records with newly collected data on board terms. We exploit the fact that boards of listed companies are appointed every three years as a source of cyclical variation in the horizon of bord members. Our evidence shows that wages drop sharply as managers approach the end of their tenure, consistent with executives trying to cut labor expenses and, hence, maximize cash flow when they are up for re-appointment. Consistent with a simple theoretical framework, these effects are not present in firms where managers are entrenched, such as family-managed firms, and when executives have a long tenure. By leveraging from individual high frequency administrative data, we show that workers employed by listed companies are disproportionately more likely to be separated exactly 12 months before the election and the month following the appointment of a new board. We relate these findings with existing agency models and empirical evidence on managerial preferences. Preliminary Draft: Please do not cite or circulate without permission ∗Corresponding author: Raffaele Saggio, Industrial Relations Section, Princeton University; Email: rsaggio@princeton.edu. We would like to thank Patrick Kline, Alex Mas, Terry Moon, Alan Morrison, Marco Pagano, Annalisa Scognamiglio, Alexander Wagner and Owen Zidar for useful comments. The views expressed in this article are those of the authors and do not necessarily reflect the views of the Bank of Italy. All errors are our own.