Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Logistic Regression for Classification in Single-Channel SSVEP-based BCIs

Steady-State Visual Evoked Potentials (SSVEPs) are electroencephalography (EEG) signals which, recently, have attracted a notable interest in the field of Brain Computer Interfaces (BCIs) due to their little training requirement. Similar to other EEG signals, SSVEPs are captured by means of EEG devices characterized by multiple wet electrodes. Unfortunately, these EEG devices are very uncomfortable for users to be worn. As a consequence, there is a strong interest in developing more comfortable single-channel EEG devices equipped with dry sensors. However, if, on one hand, these innovative EEG devices are less invasive and more simple to be used by an average user, on the other hand, the exploitation of a single dry sensor leads to the collection of a weaker and noisy signal which is more difficult to be opportunely processed and classified. The aim of this paper is to improve the performance of signal classification tasks of SSVEPs captured by single-channel EEG devices with dry sensors by logistic regression. As shown by experimental results, the proposed approach improves the state-of-the-art methods in terms of accuracy.
DMS: Dynamic Model Scaling for Quality-Aware Deep Learning Inference in Mobile and Embedded Devices

Recently, deep learning has brought revolutions to many mobile and embedded systems that interact with the physical world using continuous video streams. Although there have been significant efforts to reduce the computational overheads of deep learning inference in such systems, previous approaches have focused on delivering ‘best-effort’ performance, resulting in unpredictable performance under variable environments. In this paper, we propose a runtime control method, called DMS (Dynamic Model Scaling), that enables dynamic resource-accuracy trade-offs to support various QoS requirements of deep learning applications. In DMS, the resource demands of deep learning inference can be controlled by adaptive pruning of computation-intensive convolution filters. DMS avoids irregularity of pruned models by reorganizing filters according to their importance so that varying number of filters can be applied efficiently. Since DMS’s pruning method incurs no runtime overhead and preserves the full capacity of original deep learning models, DMS can tailor the models at runtime for concurrent deep learning applications with their respective resource-accuracy trade-offs. We demonstrate the viability of DMS by implementing a prototype. The evaluation results demonstrate that, if properly coordinated with system level resource managers, DMS can support highly robust and efficient inference performance against unpredictable workloads.
Drain-Extended FinFET With Embedded SCR (DeFinFET-SCR) for High-Voltage ESD Protection and Self-Protected Designs

This article presents device design insights and design challenges for drain-extended FinFET devices with embedded silicon-controlled rectifier (SCR) (DeFinFET-SCR), which can be used as an electrostatic discharge (ESD) protection device and a self-protected high-voltage switch/driver for system-on-chip applications. The tradeoff between maximizing ESD robustness without hindering the transistor’s operation is discussed in detail. An interplay between parasitic p-n-p turn-on and space charge modulation (SCM) is revealed, which strongly influences the strength of parasitic SCR and its turn-on efficiency during ESD and DC operations. Developed physical insights show that engineering p-n-p turn-on and onset of SCM are the key to maximize ESD robustness without causing early SCR turn-on during transistor operation. Based on new findings and developed physical insights, design guidelines have been derived for ESD robust DeFinFET-SCR.
Lane Change Maneuver based on Bezier Curve providing Comfort Experience for Autonomous Vehicle Users

Comfort driving has emerged as an important topic in the autonomous car research field. This study focuses on lane change maneuvering (LCM) of autonomous vehicles to provide a comfortable driving experience for passengers. For this purpose, we propose an LCM algorithm for determining a desired trajectory by evaluating the allowable lateral acceleration value obtained from Bezier curves at a local path planning stage for comfortable and smooth motion of the vehicle. The performance of the proposed LCM algorithm was verified through computer simulations and real driving tests.
Current Harmonics Injection Method for Simultaneous Torque and Radial Force Ripple Mitigation to Reduce Acoustic Noise and Vibration in SRMs

Switched Reluctance Machines (SRMs) have high torque and radial force ripples compared to other type electric machines resulting in more acoustic noise and vibration. This paper introduces a new control method to reduce both the torque and radial force ripples as well as the specific harmonics of the radial force generation to minimize the acoustic noise and vibration in SRMs. The proposed method achieves these three objectives by injecting harmonics to the motor phase currents. The harmonic numbers of the phase currents to be injected are studied in detail in achieving the objectives. The magnitude and the phase of the injected currents are optimized globally through the multi-objective optimizations run iteratively during control design stage. Finite Element Analysis is performed to develop dynamic simulation of the SRM and implement the optimization to generate the current waveforms for various operating conditions. The current waveforms are applied to FEA models to predict the torque ripple and the acoustics noise through Multiphysics simulation packages. The final FEA simulations demonstrated that the proposed control method reduces the acoustic noise by 26.44 dBA, peak to peak torque ripple by 67% while achieving similar torque density compared with the conventionally controlled SRMs.
Relationship education and counselling: recent research findings

This paper reviews the research on relationship education and relationship counselling. The paper investigates the effectiveness of these strategies in working with couples who are at varying stages of their relationship - from highly satisfied at the beginning of their relationship, to highly distressed and considering separation. The paper addresses some of the complexities and issues surrounding how and why these strategies work in order to assist practitioners in engaging more effectively with couples and families. Key messages: Relationship education programs have been found to produce significant moderate improvements in couple communication and relationship satisfaction in the short term. There is a lack of research demonstrating the effectiveness of relationship education in the longer term. There is an inconsistent evidence base, with a lack of long-term follow up, supporting the use of relationship education as a universal prevention program. Relationship education may work best as a selective intervention aimed at couples at high-risk of relationship deterioration, although this is still a growing area of research with some inconsistent findings. Many groups, such as cohabiting couples, are under-served by relationship education programs. Incorporating relationship education in to other programs, such as those run by nurses and midwives at the transition to parenthood, offers a potential opportunity to reach such under-serviced couples. The effectiveness of relationship education programs may be influenced by the individual characteristics of the couples undertaking the program. Some couples are at higher or lower risk for relationship distress, and the couples’ experiences of these risk factors may affect the likelihood of a successful outcome. Several approaches to relationship counselling have been found to be moderately effective in reducing relationship distress or increasing relationship satisfaction compared to no treatment. However, there has been limited new research in the past decade. There are a number of widely practiced approaches to relationship counselling that still remain largely untested. Research to date suggests that relationship counselling does not work for approximately 25-30% of those who attend, regardless of approach. Couples facing the most relationship difficulties and the highest levels of distress tend to have worse outcomes in counselling. The relationship between couple distress and mental health problems (such as depression) is cyclical with both negatively affecting each other. As the two are interlinked, mental health practitioners should assess for relationship difficulties and those working with couples should assess for individual mental health problems that may need to be addressed. There is continued debate, although currently limited evidence, regarding exactly why relationship counselling is effective, with research focusing on explanations of change based on specific theoretical models or factors common to all approaches.
Recent Developments in Fine Pitch Wafer-To-Wafer Hybrid Bonding with Copper Interconnect

3D architectures are increasingly making their way into commercial products such as image sensors and 3D memory. While hybrid bonding exists today in wafer-to-wafer (W2W) format in high volume manufacturing, the proliferation of this technology continues to accelerate. A wide range of new products may be considered by leveraging the ability to connect circuit elements fabricated with two different process technologies. For example, some NAND architectures are monolithic 3D devise which are formed using processes with divergent thermal requirements such as the high temperature memory technology and the lower temperature logic. This monolithic approach is the standard today but leads to a final product that is a compromise of the thermal budget constraints. Alternatively, disaggregation of the memory components and the logic components onto separate wafers would allow each technology to be optimized independently with potentially different thermal budgets. Using Cu based hybrid bonding, a fine pitch Cu interconnect may be used to then join the two wafers at temperatures well below 400°C while achieving superior I/O performance within a smaller footprint [1]. Direct Bond Interconnect (DBI®) technology, is a low temperature hybrid bonding process that forms a dielectric-to-dielectric bond at room temperature and a metal-to-metal bond at the appropriately designed temperature. It is the key enabling technology for advanced products because of its unique ability to bond wafers at low temperature and to successfully bond pads ranging from $1.9\ \mu \mathrm{m}$ to $15\ \mu \mathrm{m}$ diameter. The corresponding pitches range from $3.8\ \mu \mathrm{m}$ to 40 um. Generally, a low temperature anneal process of 150–400°C can be achieved. The all-Cu interconnect across the bond interface provides good electrical performance and enhanced reliability. [2] This paper presents bonding and electrical yield results with a test vehicle design that demonstrates high-density, fine pitch bonding with high-yield. The test vehicle consists of daisy chain test patterns with $4\ \mu \mathrm{m}$ bonding pitch with 115k links and covers a bond area of 3.61 mm2. The process flow enables high throughput processing with room temperature bonding and post-bond batch anneal. The process shows minimum electrical yield greater than 98% across all wafers. Longer chains of 500k links with a $3\ \mu \mathrm{m}$ diameter pad with a $10\ \mu \mathrm{m}$ pitch show similar yields. Temperature cycling and autoclave tests of the $3\ \mu \mathrm{m}$ diameter pad test structures showed a robust Cu/Cu interconnection and superior reliability performance.
Relationship between Pre-Pregnancy Body Mass Index and Childbirth Outcomes in Primiparous Women

Background and Aim: Pregnancy is a physiological event that may cause significant complications (5-20%) in mother and fetus. One of the dangerous factors in the pregnancy is abnormal Body Mass Index (BMI) before pregnancy. The purpose of this study was to determine the relationship between maternal pre-pregnancy body mass index and childbirth outcomes in primiparous women. Material and Method: This was a correlation and Ex-post facto study. Through consecutive sampling method, 300 primiparous women with the singleton pregnancy who received prenatal care in the first trimester (14 weeks) were selected. A record sheet (questionnaire) was used to collect data. Result: The findings (cid:2) showed that there was a statistically significant relationship (cid:2) between body mass index and duration of first (P=0.007) and second stage of labor (P=0.01). Besides, increase in the body mass index was correlated with higher in cesarean rate. So, statistically significant relationship were found between body mass index and mode of delivery (P=0.03). However, no statistical significant relationship was found between body mass index and postpartum hemorrhage. Conclusion: According to the finding, it seems that it would be necessary to plan educational and counseling programs before the pregnancy for the mothers.
1 Reciprocity , Altruism , and Implicit Worldviews †

The main purpose of this paper is to study how the individual differences in implicit worldviews regarding categories versus relationships and reciprocal expectation affect altruistic decision towards parents, children, and non-family members, using the data obtained through internet surveys conducted in Japan. Our analyses revealed that individuals who put more weight on relationships than categories become less altruistic towards parents and children, which suggests that relation-based worldviews negatively affect an individual’s altruistic decision regarding the recipients who are related to them. We hypothesized that one possible mechanism behind the association between altruistic behavior and relation-based worldviews might be attributable to reciprocal expectation. We found that if individuals with relation-based worldviews expect that their parents would return when they do a favor, they become generous, whereas their generosity is reduced if the reciprocal return from parents is not expected. Our main finding about the implicit worldview in association the conditional reciprocal expectation suggests that individuals’ generosity depends on their perception at the implicit level on their relationship with the recipients in regards to expected reciprocation.
Epidemiological study on tuberculosis patients in Ahvaz East Center during 2009- 2013

To study TB incidence trend and its epidemiological aspects in recent years in Ahvaz East Center. As national and international Emphasis for detecting Smear positive pulmonary tuberculosis and eliminate the disease rate and global target internationally to eliminate TB by 2050 based on 1990 rate. In this cross – sectional descriptive-analytic study the records of all TB patients referred to Health centers and preventive diseases units in East of Ahvaz in 5 years (2009-2013) were evaluated. Data were derived from patients' records and entered to check lists and then analyzed using SPSS 17 software. During the studied years a total of 990 cases were reported by all centers and units under cover of Ahwaz Main East Health Center. Among them 232 cases (23.43%) was external pulmonary TB. Male subjects had a higher incidence of 62% compared to females. The age group between 25 - 45 year, was the most affected group. Smear positive rate varied from 58% to 76%. Cure rate in 5 studied years has not too differentiation, was varied 81% to 87%. The results show most affected TB cases in 5 studied years were pulmonary (73-84.5%), this obey the national pattern of the disease. Smear positive rate that varied from 58% to 76% was more than the national rate (53%). Morbidity in centers and units under cover of Ahwaz Main East Health Center was younger age pattern in compare to whole country rate. Incidence rate of TB was higher than national rate.
Reverse Power Flow (RPF) Detection and Impact on Protection Coordination of Distribution Systems

Due to the inclusion of Distributed Generation (DG) in modern power systems, there are certain changes in the distribution and transmission stage, either by impedance reflected by the lines and the increase of short circuit currents. This context has a direct impact on protection coordination which is the priority of study in this paper. One of the significant impacts due to DG is the reverse power flow (RPF), which generally occur when the generation of a distributed power plant exceeds the local load demand, causing power to flow in the opposite direction to normal. The consequences can be evidenced in the power system with voltage peaks; therefore the sensitivity and various parameters of protection coordination are critically affected. This work proposes a tool to identify possible scenarios of reverse power flows and a feasible solution is introduced. A comparative assessment is done in order to minimize the possibility of an RPF in the IEEE 13 Node radial system with conclusive results.
An Adaptable and Immersive Real Time Interface for Resolving System Limitations of Automated Vehicles with Teleoperation

Due to the challenges of autonomous driving backup options like teleoperation become a relevant solution for critical scenarios an automated vehicle might face. To enable teleoperated systems two main problems have to be solved: Safely controlling the vehicle under latency, and presenting the sensor data from the vehicle to the operator in such a way, that the operator can easily understand the vehicle’s environment and the vehicles current state. The focus of this paper is solving the second problem and therefore the development of a novel human-machine-interface for the teleoperation of automated vehicles. For the development, the human-centered-design process is used, in which the whole teleoperation system is analyzed in the context of autonomous driving and requirements for the new interface are derived. Based on those requirements the new concept is designed and implemented. Finally, first results from real driving scenarios and novel features, like adaptive camera projection or scene configuration, are presented.
Multi-spectral Reuse Distance: Divining Spatial Information from Temporal Data

The problem of efficiently feeding processing elements and finding ways to reduce data movement is pervasive in computing. Efficient modeling of both temporal and spatial locality of memory references is invaluable in identifying superfluous data movement in a given application. To this end, we present a new way to infer both spatial and temporal locality using reuse distance analysis. This is accomplished by performing reuse distance analysis at different data block granularities: specifically, 64B, 4KiB, and 2MiB sizes. This process of simultaneously observing reuse distance with multiple granularities is called multi-spectral reuse distance. This approach allows for a qualitative analysis of spatial locality, through observing the shifting of mass in an application’s reuse signature at different granularities. Furthermore, the shift of mass is empirically measured by calculating the Earth Mover’s Distance between reuse signatures of an application. From the characterization, it is possible to determine how spatially dense the memory references of an application are based on the degree to which the mass has shifted (or not shifted) and how close (or far) the Earth Mover’s Distance is to zero as the data block granularity is increased. It is also possible to determine an appropriate page size from this information, and whether or not a given page is being fully utilized. From the applications profiled, it is observed that not all applications will benefit from having a larger page size. Additionally, larger data block granularities subsuming smaller ones suggest that larger pages will allow for more spatial locality exploitation, but examining the memory footprint will show whether those larger pages are fully utilized or not.
Analysis of Drain Current in Polycrystalline MgZnO/ZnO and MgZnO/CdZnO HFET

In this article, we report on estimating the drain current (<inline-formula> <tex-math notation="LaTeX">${I}_{d}$ </tex-math></inline-formula>) characteristics of polycrystalline MgZnO/ZnO (MZO) and MgZnO/CdZnO (MCO) heterojunctions-based heterostructure FET (HFET). The developed model utilizes ionized interface state density (<inline-formula> <tex-math notation="LaTeX">${Q}_{i}$ </tex-math></inline-formula>) and its interrelationship with the barrier layer thickness (<inline-formula> <tex-math notation="LaTeX">${d}$ </tex-math></inline-formula>), Mg content (<inline-formula> <tex-math notation="LaTeX">${x}$ </tex-math></inline-formula>), and electron mobility (<inline-formula> <tex-math notation="LaTeX">${\mu }$ </tex-math></inline-formula>) to account for the interface defects and their variations with electrical and physical parameters of polycrystalline heterointerface-based ZnO HFETs. The results suggest that the saturation drain current (<inline-formula> <tex-math notation="LaTeX">${I}_{{\text {dsat}}}$ </tex-math></inline-formula>) in MCO HFET can be comparable to that in MZO HFET when <inline-formula> <tex-math notation="LaTeX">${Q}_{i}$ </tex-math></inline-formula> enhancement is considered along with the reduction in <inline-formula> <tex-math notation="LaTeX">${\mu }$ </tex-math></inline-formula>. This article has extensively explored major relationships of <inline-formula> <tex-math notation="LaTeX">${Q}_{i}$ </tex-math></inline-formula>, which governs <inline-formula> <tex-math notation="LaTeX">${I}_{d}$ </tex-math></inline-formula> in HFETs, with <inline-formula> <tex-math notation="LaTeX">${d}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${x}$ </tex-math></inline-formula> to convincingly postulate that the experimental <inline-formula> <tex-math notation="LaTeX">${I}_{d}$ </tex-math></inline-formula> in polycrystalline MZO-and MCO-based HFETs could be a combination of the two extreme cases of <inline-formula> <tex-math notation="LaTeX">${Q}_{i}$ </tex-math></inline-formula> dependent and independent on <inline-formula> <tex-math notation="LaTeX">${d}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${x}$ </tex-math></inline-formula>. This article is significant to enhance the understanding and therefore optimizing the direct current (dc) performance of polycrystalline ZnO HFETs.
Model-based Predictive Variable Speed Limit Control on Multi-lane Freeways with A Line of Connected Automated Vehicles

This paper proposes a Model Predictive Control (MPC) strategy of a novel variable speed limit control (VSL) using a line of connected automated vehicles. A discrete first-order model which considers capacity drop of jam waves is extended in this study to incorporate impact of the novel VSL control. Based on the extended model, we cast an MPC scheme into a multi-layer control structure to develop a VSL control strategy in a connected vehicle environment. For the purposes of validation of the extended model and evaluation of the proposed control strategy, a set of microscopic simulation experiments are conducted on a hypothetical multi-lane freeway with temporary jam waves. Simulation results show that the traffic flow model can reproduce traffic evolution under VSL control and a 3.7% reduction of total delay time of mainline traffic can be witnessed.
Validation of a nomogram to aid fluid resuscitation in paediatric burns

We performed a double blinded randomised study to compare the accuracy and speed of three different techniques (pen & paper, electronic calculator and a novel graphic device: “nomogram”) for calculation of resuscitation and maintenance fluid requirements for paediatric patients in the first 24hr of burn injury, based on the Parkland formula. [The Parkland Formula Nomogram for Paediatric generated simulated patient data.