Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomic Silicon Quantum Dot: A New Designing Paradigm of an Atomic Logic Circuit

The recent fabrication progress in logic circuits using atomic-scale silicon dangling bond (DB) makes it a promising candidate for field coupled nanocomputing. Moreover, the use of silicon substrate opens the possibilities to integrate DB circuits with existing infrastructure for the complementary metal-oxide-semiconductors (CMOS) devices. However, this emerging technology is still in its initial stage. This paper presents a T-shape structure to realize logic circuits. In addition, fundamental logic gates, such as, two-input AND, NAND, OR, XOR, and XNOR gates, are reported using the T-shape structure. Besides, a novel three-input majority (Si-DBM3) gate and a three-input XOR (Si-DBX3) gate, based on DB pairs, have been presented. Using the proposed Si-DBX3 and Si-DBM3 logic gates, a Full-adder (FA) is designed. All the logic gates are designed and verified using the SiQAD simulation tool.
Relation between Functional Brain Networks and Fluid Intelligence Using Information Theory

Human intelligence is a mental capability that can describe the level of individual behavioral and cognitive abilities. Recent works suggest that the resting state graph metrics and similarity measures that capture the nonlinear interactions between regions are better than other conventional approaches to link neuroimaging data to intelligence metrics. In this study, for the first time, we investigated the capacity of mutual information (MI) in predicting the intelligence. To this end, the network edges are defined based on MI and the relationship between graph metrics extracted from resting state brain networks and intelligence is explored. Results show that graphs constructed based on MI have stronger relationship with intelligence in comparison to those constructed based on Pearson correlation.
Short-Channel Effects Improvement of Carbon Nanotube Field Effect Transistors

With the advancement of electronic device technology and the development of nanometer dimensions in this field, as well as decreasing dimensions for higher integration and better device performance, power consumption as well as more sophisticated functions require the use of material with physical and chemical properties. Suitable for nanometers, it is becoming increasingly popular as carbon nanotubes are a viable alternative. With the increase in the electric charge density, the emergence of quantum phenomena, such as quantum tunneling, has created problems for the creation of destructive and leaky currents. Meanwhile, structure simulation plays a key role in understanding and improving device performance. This article uses MOSCNT 1.0 software. This software is programmed with MATLAB code and is executable with MATLAB software The Poisson-Schrödinger equations can be solved automatically using the Non-Equilibrium Green Function (NEGF) by MOSCNT 1.0 software. In fact, MOSCNT 1.0 software presents a mathematical model describing the mechanism of Carbon Nanotube Field Effect Transistors (CNFETs) operation. Simulations by solving all equations are able to derive some of the characteristics of a carbon nanotube effect transistor, including I-V diagram.
Evaluation of The Old People Balance Control Using Delayed Parallel Model

Falling and lack of control are some of the most essential problems of elderly people's lives. This phenomenon can be studied and modelled by mathematical equations. Besides, several models have been proposed to simulate the human body in recent years. The reverse pendulum is one of the most crucial procedures of these models. In this paper, human balance control system - similar to a two-legged robot- is examined. First, the mathematical equations of the human controller system are determined by the concept of a reverse pendulum model and indicate this is a parallel time delay system model. Then, the stability conditions of this model are expressed as a matrix linear inequality, with choosing the appropriate Lyapunov function. Finally, the performance and operation efficiency of the balancing system is determined by simulating a variety of time delays which creates the proper balance.
Experimental Auger Recombination Study of a 2 µm GaSb-Based Quantum Well Laser via Sidewall Spontaneous Emission

Auger recombination, a process closely related to the device reliability, of a working 2 µm InGaSb/AlGaAsSb quantum well (QW) laser is first investigated via measuring its spontaneous emission. By extracting and analyzing the Z power parameter, severe Auger recombination at relatively low current density/carrier density of GaSb-based lasers has been experimentally revealed.
Evaluation of Deep Learning architectures for System Identification. Applications for a household heating system

Model Predictive Controllers are widely used in the industry to control a dynamic system. They require a good model for the controlled process. In this paper I try to perform system identification using promising current neural network architectures. I frame the problem as a regression setup but allow for future possible commands to be integrated in the response. I test six architectures on three datasets. I adapt successful neural network architectures from Computer Vision and Natural Language Processing to predict the output of a system for some future time steps, given current knowledge plus some future commands. Results are promising but the models are not ready to be integrated in a real time, resource constrained environment.
Prediction of the Brain Surprise in Sequences of Oddball Stimuli

Certain features of the Event Related Potential (ERP) signal such as the P300 and N200 components are known to reflect the surprise of the brain when encountering unlikely samples in a sequence of stimuli. In this paper, we propose a method to learn the amplitude of these components for an arbitrary random stimuli sequence. First, a Fisher optimization method is developed for binary prediction of the P300 occurrence. Then, a Generalized Linear Method (GLM) is employed to predict the amplitude of the P300 component. The proposed method is applied to an auditory oddball experiment with recorded Electroencephalogram (EEG) data. Both developed methods are shown to yield promising results with an acceptable prediction error.
Estimating patterns in the under-reporting of suicide deaths in India: comparison of administrative data and Global Burden of Disease Study estimates, 2005–2015

Background It has been proposed that the National Crime Records Bureau (NCRB), which reports suicides in India, differentially underenumerates suicides by geographic and demographic factors. We assessed the extent of potential underenumeration by comparing suicides recorded in NCRB data with recent estimates of Indian suicides developed by the Global Burden of Disease (GBD) initiative. Methods Age-standardised suicide rates were calculated for both data sources by sex, age and state, and rate ratios of NCRB to GBD estimates by corresponding strata were compared to ascertain the relative under-reporting in the NCRB report. Results The GBD Study reported an additional 802 684 deaths by suicide (333 558 male and 469 126 female suicide deaths) compared with the NCRB report between 2005 and 2015. Among males, the average under-reporting was 27% (range 21%–31%) per year, and among females, the average under-reporting was 50% (range 47%–54%) per year. Under-reporting was more evident among younger (15–29 years) and older age groups (≥60 years) compared with middle age groups. Indian states belonging to low Socio-Demographic Index (SDI) generally had greater underenumeration compared with middle and high-SDI states. Conclusion NCRB data under-report suicides in India, and differentially by sex, age and geographic area, possibly because of lack of community-level reporting of suicides due to social stigma and legal consequences. While the recent decriminalisation of suicide is expected to improve community-level reporting of suicides, suicide prevention policies should be developed, with a priority to address social stigma attached with suicide and suicidal behaviour, especially among females.
Physical Modeling the Impact of Self-Heating on Hot-Carrier Degradation in pNWFETs

We develop and validate a physics-based modeling framework for coupled hot-carrier degradation (HCD) and self-heating (SH). Within this framework, we obtain the lattice temperature distribution throughout the device by solving the lattice heat flow equation coupled with the drift-diffusion approach. Then, the evaluated temperature spatial profile in the transistor is taken into account while solving the Boltzmann transport equation for carriers to obtain the carrier energy distribution functions, which are needed to compute the rates of the single-and multiple-carrier mechanisms of bond dissociation. The effect of SH on HCD is threefold: ($i$) it results in a significant distortion of the carrier distribution function, (ii) device heating decreases vibrational lifetime of the Si-R bond, thereby suppressing the multiple-carrier mechanism, and (iii) the rate of thermal bond-breakage becomes higher due to SH. The model is capable of accurately reproducing relative changes in the saturation drain current with stress time measured in p-channel nanowire field-effect transistors subjected to HCD under different stress conditions. We show that neglecting SH leads to substantial underestimation of HCD.
“Gradual Entrainment Lake Inverter” (GELI): A novel device for experimental lake mixing

A Gradual Entrainment Lake Inverter (GELI) designed to destroy thermal stratification was constructed and used to destratify a darkly stained humic lake. The GELI was developed to gain insight to the effects of altered lake‐mixing regimes, but has utility in other mixing applications. The GELI comprises an 8.25 m diameter rubber membrane with a tubular inflatable ring around its circumference that can be raised and lowered repeatedly through the water column using compressed air to control the buoyancy of the ring. Three mixing mechanisms for the GELIs were observed: (i) the increase of high‐frequency internal waves (ii), shear and circulation resulting from lateral exchange flows, and (iii) generation of turbulence via both surface spreading and a trailing wake. Field experiments of the GELI reset vertically stratified variables to a near‐homogeneous state. As the surface to bottom water column temperature differential changed from 19.2°C to 0.2°C, dissolved oxygen concentrations increased transiently from below detection to 2.8 mg L−1 in the hypolimnion and decreased from 7.0 to 3.2 mg L−1 in the epilimnion. Results demonstrate that the GELI is an efficient lake‐mixing device that can minimize gas exchange associated with traditional mixing methods, and the GELI is particularly useful when circumstances require nondisruption of this parameter. The GELI can also be useful in hydrodynamic studies as an internal wave generation device.
Semantic 3D Obstacle Detection Using an Enhanced Probabilistic Voxel Octree Representation

In this paper we present a solution to overcome specific drawbacks of 3D obstacles detection and image based semantic segmentation, by combining the two approaches into an enhanced 3D octree. The 3D obstacle detection will be performed on the enhanced octree. Semantic information is added to the voxel octree representation in a probabilistic fashion, during the building step of the octree. Using the voxels’ semantic labels and probabilities, more accurate obstacle primitives are extracted during octree traversal. Later, the semantic information helps for a better strategy in merging the 3D primitives. A better detection bounding box and pixel wise accuracy is achieved; as well a higher precision rate, as it allows easy introduction of 3D properties filtering. The evaluation metric is applied on KITTI’s 3D object detection dataset. Semantic values are obtained using an already trained R-CNN model, while the 3D point cloud is generated with the semi-global block matching algorithm.
A Content Fingerprint-Based Cluster-Wide Inline Deduplication for Shared-Nothing Storage Systems

Deduplication has been principally employed in distributed storage systems to improve storage space efficiency. Traditional deduplication research ignores the design specifications of shared-nothing distributed storage systems such as no central metadata bottleneck, scalability, and storage rebalancing. Likewise, inline deduplication integration poses serious threats to storage system read/write performance, consistency, and scalability. Mainly, this is due to ineffective and error-prone deduplication metadata, duplicate lookup I/O redirection, and placement of content fingerprints and data chunks. Further, transaction failures after deduplication integration often render inconsistencies in data chunks, deduplication metadata, and garbage data chunks. results in rendering inconsistencies in data chunks, deduplication metadata, and garbage data chunks. In this paper, we propose Grate, a high-performance inline cluster-wide data deduplication, complying with the design constraints of shared-nothing storage systems. In particular, Grate eliminates duplicate copies across the cluster for high storage space efficiency without jeopardizing performance. We employ a distributed deduplication metadata shard, which promises high-performance deduplication metadata and duplicate fingerprint lookup I/Os without introducing a single point of failure. The placement of data and deduplication metadata is made cluster-wide based on the content fingerprint of chunks. We decouple the deduplication metadata shard from read I/O path and replace it with a read manifestation object to further speedup read performance. To guarantee deduplication-enabled transaction consistency and efficient garbage identification, we design a flag-based asynchronous consistency scheme, capable of repairing the missing data chunks on duplicate arrival. We design and implement Grate in Ceph. The evaluation shows an average of 18% performance bandwidth improvement over the content addressable deduplication approach at smaller chunk sizes, i.e., less than 128KB while maintaining high storage space savings.
Trends in Premature Deaths among Women Living with HIV/AIDS and Cervical Cancer

Objectives There is a lack of updated information on premature death and years of potential life lost (YPLL) among human immunodeficiency (HIV)–positive women with cervical cancer. We hypothesize that increased access to preventive resources such as antiretroviral therapy, preexposure prophylaxis, and human papillomavirus vaccines has reduced premature mortality and YPLL in these women in the previous decades. Methods We used data from the National Inpatient Sample database from 2003 to the third quarter of 2015, and restricted the analysis to HIV-positive women with or without cervical cancer. Joinpoint regression models were run to identify trends in the rates of HIV and cervical cancer. Overall and age-stratified YPLL were calculated for HIV-positive women with cervical cancer. Adjusted survey logistic regression models were built to determine the predictive factors of in-hospital mortality among women living with HIV. Results Among hospitalized women, low-income, non-Hispanic Blacks, and patients aged 40 to 59 years experienced greater frequencies of HIV/cervical cancer comorbidity. The prevalence of HIV hospitalizations increased by an average annual percentage of 0.9% (95% confidence interval 0.3–1.6). YPLL decreased in HIV-positive women living with and without cervical cancer by 4.9% and 4.3%, respectively. The trajectory for YPLL was not uniform across age groups. YPLL decreased substantially in women aged 20 to 29 years with HIV/cervical cancer comorbidity. Cervical cancer remained a significant predictor of mortality among HIV-positive women when adjusted for age, race, and insurance coverage. Conclusions Within a large, national sample from 2003 to 2015, we found an overall declining trend in YPLL in women living with HIV/cervical cancer comorbidity. In-hospital mortality among HIV-positive women was associated with cervical cancer, age, race, and insurance coverage. We recommend further investigation into the quality of HIV and cervical cancer treatment and prevention services for the sociodemographic groups described.
A Comparison of International Normalized Ratio Results by Point-of-Care Device and Clinical Laboratory Analyzers in a Vascular Surgery Department

Purpose This prospective comparative study aims to evaluate the accuracy and validity of CoaguChek XS point-of-care system (Roche Diagnostics GmbH, Mannheim, Germany), compared with the standard central laboratory international normalized ratio (INR) results, in a vascular surgery ward. Methods Data based on 54 INR pairs, measured by the central laboratory analyzer and CoaguChek XS, were compared using the intraclass correlation coefficient. Other outcomes included the time and cost of the service from the patient's perspectives. Correlation was assessed using Pearson correlation test. Bland-Altman analysis was done to determine mean difference and 95% limits of agreement. Cohen κ test was done to assess agreement between the 2 methods. Results The mean INR values for CoaguChek XS and standard laboratory (Sysmex Ca-1500 system; Siemens Healthcare Diagnostics, Erlangen, Germany) were 1.21 ± 0.28 and 1.24 ± 0.43, respectively. The Pearson correlation coefficient in all 108 measurements was (r) = 0.591 (95% confidence interval, 0.38–0.74; P < 0.0001), indicating a moderately positive correlation. Overall intraclass correlation coefficient was 0.803 (95% confidence interval, 0.324–0.707) indicating good reliability. Bland-Altman analysis showed a bias of 0.035 and a 95% limits of agreement ranging from −0.63 to 0.70. There was substantial agreement between the 2 methods (κ = 0.694; SE, 0.108; 95% confidence interval, 0.481–0.907). CoaguChek XS results were obtained, on average, 213 minutes faster than the standard laboratory. Conclusions CoaguChek XS appears to have positive correlation, substantial agreement, and good reliability when compared with the standard laboratory. Thus, it is recommended to be used in hospital settings.
Critical Care Nurses' Views and Experiences of Preanalytical Factors Influencing Point-of-Care Testing

Abstract The main users of point-of-care testing devices placed outside the central laboratory are clinicians, predominantly nurses. Understanding the factors influencing sample accuracy is important to ensure appropriate clinical decision making. Previous studies focus on the analysis process; however, errors can also occur during the preanalytical phase, linked to user knowledge, skills, and other factors associated with the wider context of care. This study explored adult critical care nurses' views about point-of-care testing, the challenges they experience, and their suggestions on how the preanalytical phase might be improved. Using a qualitative design, 4 focus group discussions took place with 60 critical care nurses studying at 2 London-based universities between April and July 2019. Anonymized and verbatim-transcribed focus group data were uploaded into NVivo11 and underwent a standard process of inductive thematic analysis. Findings suggest that nurses' concerns focus on 3 key areas: training and competence; sample frequency and volume; and impacts on patients, relatives, and staff. Critical care nurses view point-of-care testing as a necessary task, which aids timely patient management. However, the process can detract nurses from performing other care duties. Being able to draw less blood was identified as an important way to increase patient comfort and to reduce risks. Collaborative working is key to ensure that improvements made to the preanalytical process reflect users' needs. Ensuring best use of nurses' time by streamlining preanalytical processes and ensuring equipment is readily available for use are important to ensure other clinical priorities can be achieved.
Harvesting Energy from an Organic Pollutant Model Using a New 3D-Printed Microfluidic Photo Fuel Cell.

The combination of a fuel cell and photocatalysis in the same device, called a photo fuel cell, is the next generation of energy converters. These systems aim to convert organic pollutants and oxidants into energy using solar energy as the driving force. However, they are mostly designed in conventional stationary batch systems, generating low power besides being barely applicable. In this context, membraneless microfluidics allows the use of flow, porous electrodes, and mixed media, improving reactant utilization and output power accordingly. Here, we report an unprecedented reusable three-dimensional (3D) printed microfluidic photo fuel cell (μpFC) assembled with low-content PtOx/Pt dispersed on a BiVO4 photoanode and a Pt/C dark cathode, both immobilized on carbon paper. We use fused deposition modeling for additive manufacturing a US$ 2.5 μpFC with a polylactic acid filament. The system shows stable colaminar flow and a short time light distance. As a proof-of-concept, we used the pollutant-model rhodamine B as fuel, and O2 in an acidic medium at the cathode side. The mixed-media 3D printed μpFC with porous electrodes produces remarkable 0.48 mW cm-2 and 4.09 mA cm-2 as maximum power and current densities, respectively. The system operates continuously for more than 5 h and converts 73.6% rhodamine by photoelectrochemical processes. The 3D printed μpFC developed here shows promising potential for pollutant mitigation concomitantly to power generation, besides being a potential platform of tests for new (photo)electrocatalysts.
The Relationship Between Images Posted by New Mothers on WeChat Moments and Postpartum Depression: Cohort Study

Background As social media posts reflect users’ emotions, WeChat Moments, the most popular social media platform in China, may offer a glimpse into postpartum depression in the population. Objective This study aimed to investigate the features of the images that mothers posted on WeChat Moments after childbirth and to explore the correlation between these features and the mothers' risk of postpartum depression. Methods We collected the data of 419 mothers after delivery, including their demographics, factors associated with postpartum depression, and images posted on WeChat Moments. Postpartum depression was measured using the Edinburgh Postnatal Depression Scale. Descriptive analyses were performed to assess the following: content of the images, presence of people, the people’s facial expressions, and whether or not memes were posted on WeChat Moments. Logistic regression analyses were used to identify the image features associated with postpartum depression. Results Compared with pictures of other people, we found that pictures of their children comprised the majority (3909/6887, 56.8%) of the pictures posted by the mothers on WeChat Moments. Among the posts showing facial expressions or memes, more positive than negative emotions were expressed. Women who posted selfies during the postpartum period were more likely to have postpartum depression (P=.003; odds ratio 2.27, 95% CI 1.33-3.87). Conclusions The vast majority of mothers posted images conveying positive emotions during the postpartum period, but these images may have masked their depression. New mothers who have posted selfies may be at a higher risk of postpartum depression. Trial Registration International Clinical Trials Registry Platform ChiCTR-ROC-16009255; http://www.chictr. org.cn/showproj.aspx? proj=15699