Miracle-dz/UniFAR-FTUs huggingface dataset:
Wireless Charger Design of Robot Vacuum Cleaners with Power Repeaters for High Compatibility

Curved coils constructed by flexible printed circuit board (PCB) or hand-wound Litz-wire have been steadily becoming popular due to its applicable potential on devices that have a curved body. Inductive Power Transfer (IPT) systems based on curved coils and flexible ferrite sheets may provide more flexible charging solutions for various electronic devices such as rice cookers and robot vacuum cleaners. Power repeaters are also used in IPT systems to extend wireless charging range by guiding magnetic fields to the receiving coil. The interaction of these three topics could be inspiring. In this paper, two adjustable power repeaters are applied to an IPT charging system with various curved receiving coils designed for vacuum cleaners. Two power repeaters share the identical structure as the Tx coil and could be rotated to mirror symmetrically. The input and output power are calculated by analyzing the equivalent circuit model. The self-inductance, mutual inductance, and coupling coefficient of the proposed system are obtained via finite element method simulation with variable rotating angles. Three typical IPT designs have also been simulated in ANSYS Maxwell and compared with the proposed magnetic design. The comparison indicates the enhancing feature of the passive power repeaters on coupling performance and the ability to guide the magnetic flux for better magnetic field coupling. Furthermore, two types of co-simulations defined by the power source via Simplorer are conducted to explore how much power could be transferred. The tuned system is shown to be able to provide about 32 W under 100 kHz operating frequency for charging the battery of a robot vacuum cleaner. The results from theoretical calculation and simulation align well with each other.
Spatial Disparity of Visitors Changes during Particulate Matter Warning Using Big Data Focused on Seoul, Korea

This study examined the changes in the number of visitors to regions during periods of high particulate matter (PM) concentrations in Seoul and analyzed the regional differences of these changes. Further, it examined the spatial characteristics that affect these regional differences. This study mapped the regional differences by conducting a spatial cluster analysis using GIS and examined factors affecting the regional differences using logistic regression analysis. The visiting population data used in this study were obtained from the Big Data on the de facto population measured every hour at mobile base stations, and all analyses were conducted in terms of weekdays and weekends. The results indicated that the visiting population decreases significantly on weekdays when there are high PM concentrations; however, visits increase on weekends, even during periods of high PM concentrations. Moreover, there was a huge regional gap in visiting population changes. Regions with more commercial use, higher bus accessibility, and better pedestrian environment (pedestrian paths, Walk Score) were more likely to be hotspots, whereas regions with high residential and industrial use were more likely to be cold spots. These results can be used as the basic data for PM policies based on regional characteristics.
Analyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution Layer

Email: isaurabhsh@gmail.com Abstract: Research conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address the challenges of vanishing gradients in deep networks by employing residual learning via skip connections and lowering model training computational costs using parallel convolution rather than sequential convolution operations by employing inception blocks. These studies also don't discuss in detail the impact of sparing features on feature learning, which has been identified as the second research gap. Diagnosis of infectious patterns in chest X-rays using residual learning is chosen as the problem statement for this study. Results show that ResNet50 architecture achieved improved accuracy by 0.6218% and declined error rate by 2.6326% if gradually narrowing FC layers are employed between core residual learning schema and output layer. Also, independent implementation of inception blocks (google net v2) before skip-connections in ResNet50 architecture boosts accuracy by 0.961% and lowers the error rate by 4.2438%. These performance improvements were achieved without regularization and thus, encourage future work in this direction.
Contribution of rare mutational outcomes to broadly neutralizing antibodies

Antibodies are important immune molecules that are elicited by B cells to protect our bodies during viral infections or vaccinations. In humans, the antibody repertoire is diversified by programmed DNA lesion processes to ensure specific and high affinity binding to various antigens. Broadly neutralizing antibodies (bnAbs) are antibodies that have strong neutralizing activities against different variants of a virus. bnAbs such as anti-HIV bnAbs often have special characteristics including insertions and deletions, long complementarity determining region 3 (CDR3), and high frequencies of mutations, often at improbable sites of the variable regions. These unique features are rare mutational outcomes that are acquired during antibody diversification processes. In this review, we will discuss possible mechanisms that generate these rare antibody mutational outcomes. The understanding of the mechanisms that generate these rare mutational outcomes during antibody diversification will have implications in vaccine design strategies to elicit bnAbs.
Self-heating analysis of monolithically integrated hybrid III-V/Si PIN diode

Self-heating is a crucial effect in integrated nanophotonic devices regarding their power consumption. In this work, we employ coupled 3D thermo-electrical simulations to gain insight into the thermal behavior related to traps in a monolithic InP-InGaAs-InP pin-diode fabricated at IBM-Research Zurich. From transport study, two types of defects are found to be very likely present in the studied device: (i) positive oxide charges close to the interface between III-V materials and top oxide layer and (ii) electron-type traps at the p-InP/i-InGaAs interface. Thermal simulations show that the presence of electron-type traps at the p/i interface enhances the self-heating in the device
Graphene Nanoribbon Field-Effect Transistors with Top-Gate Polymer Dielectrics

: Graphene nanoribbons (GNRs) have demonstrated great potential for nanoscale devices owing to their excellent electrical properties. However, the application of the GNRs in large-scale devices still remains elusive mainly due to the absence of facile, nonhazardous, and nondestructive transfer methods. Here, we develop a simple acid (HF)-free transfer method for fabricating ﬁ eld-e ﬀ ect transistors (FETs) with a monolayer composed of a random network of GNRs. A polymer layer that is typically used as mechanical support for transferring GNR ﬁ lms is utilized as the gate dielectric. The resultant GNR-FETs exhibit excellent FET characteristics with a large on/o ﬀ switching current ratio of >10 4 . The transfer process enables the demonstration of the ﬁ rst GNR-based nonvolatile memory. The process o ﬀ ers a simple route for GNRs to be utilized in various optoelectronic devices.
A Genomic Information Management System for Maintaining Healthy Genomic States and Application of Genomic Big Data in Clinical Research

Improvements in next-generation sequencing (NGS) technology and computer systems have enabled personalized therapies based on genomic information. Recently, health management strategies using genomics and big data have been developed for application in medicine and public health science. In this review, I first discuss the development of a genomic information management system (GIMS) to maintain a highly detailed health record and detect diseases by collecting the genomic information of one individual over time. Maintaining a health record and detecting abnormal genomic states are important; thus, the development of a GIMS is necessary. Based on the current research status, open public data, and databases, I discuss the possibility of a GIMS for clinical use. I also discuss how the analysis of genomic information as big data can be applied for clinical and research purposes. Tremendous volumes of genomic information are being generated, and the development of methods for the collection, cleansing, storing, indexing, and serving must progress under legal regulation. Genetic information is a type of personal information and is covered under privacy protection; here, I examine the regulations on the use of genetic information in different countries. This review provides useful insights for scientists and clinicians who wish to use genomic information for healthy aging and personalized medicine.
Incels, violence and mental disorder: a narrative review with recommendations for best practice in risk assessment and clinical intervention

SUMMARY In recent years, mass violence associated with men who identify as involuntary celibates (incels) has been of increasing concern. Incels engage in an online community where misogyny and incitements to violence against women are prevalent, often owing to the belief that women are denying them a ‘right’ to sex. Indeed, inceldom can be considered a form of extremism. Information released about the prepetrators of incel-associated violence consistently suggests that mental disorder is a contributory factor and may increase vulnerability to engaging with the incel community. Depression, autism and personality disorder are particularly relevant. To date, there has been little research into the mental health of incels and how, in some, this contributes to violence. This article considers the associations between mental disorder and inceldom, including the risk factors for incel-related violence, and makes recommendations for best practice in risk assessment and clinical intervention.
Electric-field poling of silicon nitride waveguides for the linear phase modulation

Stoichiometric silicon nitride (Si3N4) constitutes a mature platform for integrated photonics. Its pertinent properties, including wide transparency window from the visible to the mid-IR, low propagation loss, and high third-order nonlinearity, are exploited in many linear and nonlinear applications. However, due to the centrosymmetric nature of the Si3N4, the absence of the second-order susceptibility (χ(2)) impedes a realization of three-wave mixing processes as well as the linear electro-optic effect, relevant for many applications on an optical chip. Here, we implement the electric-field poling technique to induce the effective χ(2) inside a Si3N4 waveguide, thus enabling the linear electro-optic modulation. Using numerical simulations, we estimated the concentration and the diffusion coefficient of the charges responsible for the space-charge electric field formation. In addition, the DC third-order susceptibility of Si3N4 previously unknown in the literature is measured using a free-space Mach-Zehnder interferometer.
Relative insensitivity to sample sizes in judgments of frequency distributions: People are similarly confident in the results from 30 versus 3,000 observations.

Six experiments test whether people are sensitive to variations in the sample size or relatively insensitive to sample sizes varying by one or two orders of magnitude. We posit that past studies found that people are increasingly con ﬁ dent in the sample mean as the sample size increases because variations in the sample size were likely highlighted by the within-participant designs used in many of these studies. Using between-participant designs, we ﬁ nd that people are only slightly sensitive to variations in the sample size by a factor of 50, 100, and 400 when they are making con ﬁ dence judgments. Our ﬁ nding suggests that the psychological law of small numbers applies not only to people ’ s judgments about sample variances but also to their judgments of sample means. An intervention that provided people with the results of a statistical test about the extent to which the data are consistent with the null hypothesis versus the alternate hypothesis helped reduce people ’ s insensitivity to variations in the sample size.
The frequency of facial muscles engaged in expressing emotions in people with visual disabilities via cloud-based video communication

Abstract As technology is advancing quickly, and various assistive technology applications are introduced to users with visual disabilities, many people with visual disabilities use smartphones and cloud-based video communication platforms such as Zoom. This study aims at advancing knowledge of how people with visual disabilities visualize voluntary emotions via facial expressions, especially in online contexts. A convenience sample of 28 participants with visual disabilities were observed as to how they show voluntary facial expressions via Zoom. The facial expressions were coded using the Facial Action Coding System (FACS) Action Units (AU). Individual differences were found in the frequency of facial action units, which were influenced by the participants’ visual acuity levels (i.e., visual impairment and blindness) and emotion characteristics (i.e., positive/negative valence and high/low arousal levels). The research findings are anticipated to be widely beneficial to many researchers and professionals in the field of facial expressions of emotions, such as facial recognition systems and emotion sensing technologies. Relevance to human factors/ergonomics theoryThis study advanced knowledge of facial muscle engagements while people with visual disabilities visualize their emotions via facial expressions, especially in online contexts. The advanced understanding would contribute to building a fundamental knowledge foundation, ultimately applicable to universal designs of emotion technology that can read users’ facial expressions to customize services with the focus on adequately accommodating the users’ emotional needs (e.g., ambient intelligence) regardless of users’ visual ability/disability.
Comparative morphology of part of the integumental fine structure of two Erythroneurine species: Singaporashinshana (Matsumura, 1932) and Empoascanarasipra Dworakowska, 1980 (Hemiptera, Cicadellidae, Typhlocybinae)

﻿Abstract This study describes the fine structure of the mouthparts, antennae, forewings, and brochosomes of two leafhopper species belonging to the typhlocybine tribe Erythroneurini collected from the Karst area of Guizhou Province, southern China: Singaporashinshana, which prefers woody dicot hosts, and Empoascanarasipra, which feeds on grasses. As in other leafhoppers, the piercing-sucking mouthparts consist of a conical labrum, a cylindrical three-segmented labium, and a slender stylet fascicle. The labrum of both species has no sensilla and the labium has several common types of sensilla, but the two species differ in the numbers, types, and distribution of sensilla and in other aspects of the surface sculpture of the mouthparts. The stylet fascicle has distinctive dentition on both the maxillary and mandibular stylets. The antennae of the two species differ in several respects, including the sensilla and sculpture of the scape, pedicel, and flagellum, as well as the degree of sub-segmentation of the flagellum. Except for the variable scaly structure and rounded protrusions on the surface of S.shinshana, the fine structure of the forewing surfaces of the two species are similar to those of other leafhoppers. Only small spherical brochosomes were found on the body surface of S.shinshana and E.sipra. Similar studies of additional erythroneurine species are needed to determine whether differences in mouthpart and antennal fine structure may reflect adaptation to different host plant.
RESPON FISIOLOGIS AYAM JANTAN TIPE MEDIUM YANG DIBERI RANSUM DENGAN KADAR SERAT KASAR BERBEDA Physiological Responses of The Rooster Medium Type Which Were Given Rations in Different Levels of Crude Fiber

The objective of this experiment was to find out the physiological responses of roosters medium type which were given rations in different levels of crude fiber (4, 6, 8, or 10% of dietary dry matter). This research was conducted for 60 days at cage trial installations in PT. Rama Jaya, Fajar Baru Village, Jati Agung Subdistrict, South Lampung Regency. There are fourty eight of roosters medium type that have been used and divided into 12 cages, so that each cage consisted of four roosters. The roosters were divided into four treatments. The treatment were levels of crude fiber 4, 6, 8, and 10% of dietary dry matter. Each treatment was repeated three times. The design used Completely Randomized Design (CRD) with Nested Data. Result of the experiment should that different levels of crude fiber 4, 6, 8, or 10% had no significant effect (P> 0.05) on the physiological response of rooster medium type and there was no physiological responses of the best rooster medium type in the giving of rations in levels of crude fiber 4, 6, 8, or 10%.
Survey on Issues and Recent Advances in Vehicular Public-Key Infrastructure (VPKI)

Public-key infrastructure (PKI) provides the essential foundation for public-key cryptography, and security is often bootstrapped from a PKI. Standardization bodies, organizations, researchers, and experts reached a consensus that deploying Vehicular PKI (VPKI) can ensure the security and privacy requirements of Cooperative Intelligent Transportation Systems (C-ITS). Given the importance of VPKI, researchers and experts have worked to ensure VPKI meets the high security and privacy requirements of C-ITS. This survey focuses on VPKI schemes designed to securely and privately manage and revoke public-key certificates in three parts. The first part presents evaluation metrics that help to compare the existing VPKI proposals systematically. The second part classifies VPKI schemes and provides an overview of each. The third part focuses on observations made using the evaluation metrics through a systematic comparison of VPKI schemes. Finally, suggestions for future VPKI research are presented.
Emerging neutrosophic C means clustering based segmentation for rice plant leaf disease detection

One of the main determinations of India is agriculture and the quantity of production is very essential in the field of cultivation. The rice crops are crucially admitted as one of the powerful energy streams for the production of resources. But rice plants suffer from various diseases due to infections that occur in leaf, fruit and stem. Hence, the production of rice plant is decreased and reflects severe issues in economic, agriculture and communal loss. The usage of image processing in leaf disease detection plays a vital role to diagnose and control it effectively. Though there are many existing works are done too detect rice plant leaf disease, still the presence of vagueness, impreciseness due to noise and outliers are primary challenges. The main aim of this paper is to optimize rice plant leaf disease detection by developing neutrosophic C-means clustering for segmentation. The features are extracted and their similarity is evaluated using neutrosophic Hausdorff distance. The degree of similarity is done based on truthiness, indeterminacy and falsity. The simulation results proved that enhance neutrosophic C-means clustering achieves highest rate of accuracy in rice plant leaf disease detection with less error rate compared to K-means, DBSCAN and FCM
Deep-Learning-Based Stair Detection Using 3D Point Cloud Data for Preventing Walking Accidents of the Visually Impaired

Visually impaired individuals worldwide are at a risk of accidents while walking. In particular, falling from a raised place, such as stairs, can lead to serious injury. Therefore, we attempted to determine the best accident prevention method that can notify visually impaired individuals of the existence, height, and step information when they approach stairs. In this study, we have investigated stair detection through deep learning. First, the three-dimensional point cloud data generated from depth information are learned by deep learning. Stairs were detected using the results of deep learning. To apply the point cloud data for deep learning-based training, we proposed preprocessing stages to reduce the weight of the point cloud data. The accuracy of stair detection was 97.3%, which is the best performance compared to other conventional methods. Therefore, we confirmed the effectiveness of the proposed method.
Clinical Value of PLR, MLR, and NWR in Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer

Objective The clinical value of platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-white blood cell ratio (NWR) in predicting the prognosis of patients with locally advanced gastric cancer after neoadjuvant chemotherapy (NACT) was studied. Methods A total of 131 patients with locally advanced gastric cancer treated with neoadjuvant chemotherapy in our hospital from May 2015 to June 2018 were selected as the study subjects, and all were treated with neoadjuvant chemotherapy. The relationship between the values of PLR, MLR, and NWR and the efficacy of neoadjuvant chemotherapy and clinical staging was analyzed; all patients were followed up for 3 years. Patients were divided into death group and survival group according to the survival of patients. The predictive value of PLR, MLR, and NWR values for patients' prognosis was analyzed, and the survival rates of patients with different PLR, MLR, and NWR values were compared. Results The effective rate of neoadjuvant chemotherapy in patients with locally advanced gastric cancer was 62.60% (82/131), and the PLR, MLR, and NWR values in the effective group were lower than those in the ineffective group (P < 0.05). The AUC of combined PLR, MLR, and NWR in evaluating the efficacy of neoadjuvant chemotherapy was greater than that of PLR and NWR alone (P < 0.05). The PLR value of patients with stage IIIa, IIIb, and IIIc was greater than that of patients with stage II, the MLR value of patients with stage IIIb and IIIc was greater than that of patients with stage II and IIIa, and the NMR value of patients with stage IIIc was greater than that of patients with stage II, IIIa, and IIIb (P < 0.05). PLR, MLR, and NWR values were positively correlated with clinical stage (P < 0.05). The PLR, MLR, and NWR values in the survival group were lower than those in the death group (P < 0.05). The AUC of combined PLR, MLR, and NWR in predicting the prognosis of patients was greater than that of MLR and NWR alone (P < 0.05). The survival rate of patients with PLR ≥ 162.11 (36.21%) was lower than that of patients with PLR < 162.11 (80.82%), and the survival rate of patients with MLR ≥ 0.31 (42.86%) was lower than that of patients with MLR < 0.31 (74.67%), and the survival rate of patients with NWR ≥ 0.62 (45.00%) was lower than that of patients with NWR < 0.62 (74.65%) (P < 0.05). Conclusions PLR, MLR, and NWR values are correlated with clinical stage, and the combined detection has value in evaluating the clinical efficacy of neoadjuvant chemotherapy and predicting the prognosis of patients with locally advanced gastric cancer.