Application of Self-Attention Generative Adversarial Network for Electromagnetic Imaging in Half-Space.

In this paper, we introduce a novel artificial intelligence technique with an attention mechanism for half-space electromagnetic imaging. A dielectric object in half-space is illuminated by TM (transverse magnetic) waves. Since measurements can only be made in the upper space, the measurement angle will be limited. As a result, we apply a back-propagation scheme (BPS) to generate an initial guessed image from the measured scattered fields for scatterer buried in the lower half-space. This process can effectively reduce the high nonlinearity of the inverse scattering problem. We further input the guessed images into the generative adversarial network (GAN) and the self-attention generative adversarial network (SAGAN), respectively, to compare the reconstruction performance. Numerical results prove that both SAGAN and GAN can reconstruct dielectric objects and the MNIST dataset under same measurement conditions. Our analysis also reveals that SAGAN is able to reconstruct electromagnetic images more accurately and efficiently than GAN.

Research and Evaluation on an Optical Automatic Detection System for the Defects of the Manufactured Paper Cups.

In this paper, the paper cups were used as the research objects, and the machine vision detection technology was combined with different image processing techniques to investigate a non-contact optical automatic detection system to identify the defects of the manufactured paper cups. The combined ring light was used as the light source, an infrared (IR) LED matrix panel was used to provide the IR light to constantly highlight the outer edges of the detected objects, and a multi-grid pixel array was used as the image sensor. The image processing techniques, including the Gaussian filter, Sobel operator, Binarization process, and connected component, were used to enhance the inspection and recognition of the defects existing in the produced paper cups. There were three different detection processes for paper cups, which were divided into internal, external, and bottom image acquisition processes. The present study demonstrated that all the detection processes could clearly detect the surface defect features of the manufactured paper cups, such as dirt, burrs, holes, and uneven thickness. Our study also revealed that the average time for the investigated Automatic Optical Detection to detect the defects on the paper cups was only 0.3 s.

Application of a custom haplotype caller to analyze sequence-based data of 56 microhaplotypes.

Microhaplotypes (microhaps) are recently introduced markers that aim to complement the limitations of conventional forensic markers such as short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs). With the potential of microhaps in forensics becoming clearer through massively parallel sequencing (MPS), MPS-based studies on microhaps are being actively reported. However, simpler workflow schemes for the generation and analysis of MPS data are still required to facilitate the practical application of MPS in forensics. In this study, we developed an in-house MPS panel that simultaneously amplifies 56 microhaps and a custom haplotype caller, Visual Microhap. The developed tool works on a web browser and provides four analysis options to extract SNP-based haplotypes from sequence-based data obtained by STRait Razor 3.0. To demonstrate the utility of the MPS panel and data analysis workflow scheme, we also analyzed 56 microhaps of 286 samples from four populations (African-American, Caucasian, Hispanic, and Korean). The average effective number of alleles (Ae) for the four groups was 3.45, ranging from 1.74 to 6.98. Forensic statistical parameters showed that this microhap panel is more powerful than conventional autosomal STRs for human identification. Meanwhile, the 56-plex panel mostly comprised microhaps with high Ae; however, the four populations were grossly distinguishable from each other by cluster analysis. Consequently, the developed in-house MPS panel for 56 microhaps and the adopted workflow using open-source tools can increase the utility of microhap MPS in forensic research and practice.

Epigenetic age signatures in bones.

Age prediction can help identify skeletal remains by limiting the search range for a missing person. Although age prediction methods based on odontology and anthropology are frequently used in the forensic field, DNA methylation is particularly promising age-predictive biomarker. In this study, we generated genome-wide DNA methylation profiles of bone samples from 32 identified skeletal remains with an age at death ranging from 31 to 96 years. Only 12 provided more than 800 K quality-filtered CpG methylation values using Illumina's Infinium MethylationEPIC BeadChip array. Methylation ages of the bone samples calculated using a recently developed skin & blood clock composed of 391 CpG sites were found to be very similar to their actual ages (MAD = 6.4 years). However, the low success rate in methylation profiling of bone DNA samples may prevent researchers from applying the array to this type of samples. Therefore, we selected a set of CpG sites that would enable age prediction based on only a few CpG sites in bone DNA samples. Nineteen age-associated CpG marker candidates were selected from 720 K quality-filtered CpG values of 21 male skeletal remain samples. Because age signatures for blood, such as markers on the ELOVL2, FHL2, KLF14 and TRIM59 genes, had showed strong age associations in 12 bone samples, we further tested the age association of the 5 well-known markers in a blood-based model and the 13 out of 19 CpG markers from the array of 21 bone samples with an independent set of 30 skeletal remain samples using SNaPshot multiplex based on single nucleotide primer extension. Four CpG sites on TMEM51, TRIM59, ELOVL2, and EPHA6 genes showed moderate or weak correlations between methylation and age, which suggests further investigation of these markers to predict the age of bones.

Application of hematoxylin reagent for sperm cell separation in sexual crime evidence.

Seminal evidence obtained from a sexual crime scene provides clues for solving a case through forensic analysis. However, most evidence collected from sexual crime scenes is a mixture of sperm cells and vaginal discharge. Therefore, separating the sperm cells from the seminal evidence is very important. In this study, we developed a separation method for effectively separating sperm cells using differential extraction with commercially available sperm staining reagents such as hematoxylin and nigrosin. Hematoxylin (0.03 % v/v) effectively stained the sperm cells in ATL and TNE lysis buffer, while nigrosin did not. The loss of sperm cells during washing of the specimen was minimized using the differential extraction method. Subsequently, genomic DNA was extracted from the hematoxylin-stained sperm cells and subjected to short tandem repeat genotyping. We observed no interference from hematoxylin. These results indicate that hematoxylin can be used to stain sperm cells and thus facilitate subsequent genetic identification.

Validation of the Mobile App-Recorded Circadian Rhythm by a Digital Footprint.

BACKGROUND: Modern smartphone use is pervasive and could be an accessible method of evaluating the circadian rhythm and social jet lag via a mobile app. OBJECTIVE: This study aimed to validate the app-recorded sleep time with daily self-reports by examining the consistency of total sleep time (TST), as well as the timing of sleep onset and wake time, and to validate the app-recorded circadian rhythm with the corresponding 30-day self-reported midpoint of sleep and the consistency of social jetlag. METHODS: The mobile app, Rhythm, recorded parameters and these parameters were hypothesized to be used to infer a relative long-term pattern of the circadian rhythm. In total, 28 volunteers downloaded the app, and 30 days of automatically recorded data along with self-reported sleep measures were collected. RESULTS: No significant difference was noted between app-recorded and self-reported midpoint of sleep time and between app-recorded and self-reported social jetlag. The overall correlation coefficient of app-recorded and self-reported midpoint of sleep time was .87. CONCLUSIONS: The circadian rhythm for 1 month, daily TST, and timing of sleep onset could be automatically calculated by the app and algorithm.

Development of a mobile application (App) to delineate "digital chronotype" and the effects of delayed chronotype by bedtime smartphone use.

The widespread use and deep reach of smartphones motivate the use of mobile applications to continuously monitor the relationship between circadian system, individual sleep patterns, and environmental effects. We selected 61 adults with 14-day data from the "Know Addiction" database. We developed an algorithm to identify the "sleep time" based on the smartphone behaviors. The total daily smartphone use duration and smartphone use duration prior to sleep onset were identified respectively. We applied mediation analysis to investigate the effects of total daily smartphone use on sleep through pre-sleep use (PS). The results showed participants' averaged pre-sleep episodes within 1 h prior to sleep are 2.58. The duration of three pre-sleep uses (PS1∼3) maybe a more representative index for smartphone use before sleep. Both total daily duration and the duration of the last three uses prior to sleep of smartphone use significantly delayed sleep onset, midpoint of sleep and reduced total sleep time. One hour of increased smartphone use daily, delays the circadian rhythm by 3.5 min, and reduced 5.5 min of total sleep time (TST). One hour of increased pre-sleep smartphone use delayed circadian rhythm by 1.7 min, and reduced 39 s of TST. The mediation effects of PS1∼3 significantly impacted on these three sleep indicators. PS1∼3 accounted for 14.3% of total daily duration, but the proportion mediated of delayed circadian rhythm was 44.0%. We presented "digital chronotype" with an automatic system that can collect high temporal resolution data from naturalistic settings with high ecological validity. Smartphone screen time, mainly mediated by pre-sleep use, delayed the circadian rhythm and reduced the total sleep time.

Prediction of Y haplogroup by polymerase chain reaction-reverse blot hybridization assay.

BACKGROUND: The analysis of Y-SNPs from crime scene samples is helpful for investigators in narrowing down suspects by predicting biogeographical ancestry. OBJECTIVE: In this study, a PCR-reverse blot hybridization assay (REBA) for predicting Y-chromosome haplogroups was employed to determine the major haplogroups worldwide, including AB, DE, C, C3, F, K, NO, O, O2, and O3 and evaluated. METHODS: The REBA detects nine biallelic Y chromosome markers (M9, M89, M122, M145, M175, M214, M217, P31, and RPS4Y711) simultaneously using multiple probes. RESULTS: The REBA for Y-single nucleotide polymorphisms (SNP) genotyping was performed using 40 DNA samples from Asians-14 Koreans, 10 Indonesians, six Chineses, six Thais, and four Mongolians. 40 Asian samples were identified as haplogroup O2 (40%), O3 (32.5%), C3 (17.5%), O (7.5%) and K (2.5%). These cases were confirmed by DNA sequence analysis (κ = 1.00; P < 0.001). CONCLUSION: PCR-REBA is a rapid and reliable method that complements other SNP detection methods. Therefore, implementing REBA for Y-SNP testing may be a useful tool in predicting Y-chromosome haplogroups.

Genetic characteristics of Y-chromosome short tandem repeat haplotypes from cigarette butt samples presumed to be smoked by North Korean men.

Korea has been divided into South Korea and North Korea for over 70 years. DNA profiles of the North Korean population have never been reported in the Y-chromosome STR Haplotype Reference Database (YHRD; https://yhrd.org ). To investigate genetic features of Y-chromosome STR haplotypes of the North Korean population for the first time. Genomic DNA was isolated from 838 cigarette butts assumed to have been smoked by North Korean men and amplified with PowerPlex Y23 (PPY23) kit. Statistical parameters were calculated using Nei's formula and analysis of molecular variance (AMOVA). Multidimensional scaling (MDS) plot was constructed by the AMOVA tool and neighbor-joining (NJ) tree was constructed by MEGA 6.06. A total of 121 haplotypes were analyzed for PPY23 loci from a sample population. Haplotype diversity and discrimination capacity were 0.9992 and 0.9837, respectively. Genetic diversities ranged from 0.2981 to 0.9716. For the 16 Y-filer loci and eight minimal loci, respectively 90.9 and 82.6% of the matched haplotypes were estimated to belong to haplogroup O, representing the Southeast and East Asian type. The MDS plot and NJ tree indicated that the samples are most closely related to South Korean. In addition, p-value in the pairwise comparison to the South Korean was slightly above statistical significance (p = 0.0534). The Y-STR haplotypes of the samples were unique and highly genetically polymorphic. Despite the separation between North and South Korea for 70 years, they can still be considered a single genetic population, based on Y-STR haplotypes.

Identification of female-specific blood stains using a 17ß-estradiol-targeted aptamer-based sensor.

Blood stain evidence obtained from a violent crime scene provides decisive clues that can enable a case to be solved through forensic analyses such as genetic identification. However, collected samples usually contain a mixture of biological material from different sources, making genetic identification difficult. To address this issue, we developed an activatable aptamer sensor targeting 17ß-estradiol for detection of female-specific blood in mixed samples. With the sensor, we were able to detect blood originating from females using a variable light source (495 nm). The sensor was especially sensitive to blood from young females (10-40 years) but not to blood from older females (≥ 50 years). Genomic DNA was extracted from the female blood specimens identified by this method and used for quantification and short tandem repeat genotyping. We confirmed that there was no fluorescence interference from the aptamer sensor. These results indicate that this novel aptamer sensor can be used to analyze evidentiary blood samples and thereby facilitate subsequent genetic identification.

Validation of Reduced Reagent Volumes in the Implementation of the Quantifiler® Trio Quantification Kit.

The Quantifiler® Trio Quantification Kit has been developed to quantify the total amount of amplifiable and human male DNA in samples and to estimate the extent of DNA degradation. To minimize the cost of DNA quantification, we evaluated kit performance using a reduced volume of reagents (1/10-volume) using DNA samples of varying types and concentrations. Our results demonstrated concordance between the manufacturer's method and the low-volume method for DNA quantification, DNA degradation index estimation, and human male DNA quantification. We confirmed the practical utility of the low-volume method with 109 casework samples by evaluating short tandem repeat (STR) profiling success with respect to DNA quantity and quality. We also defined a cutoff value for DNA quantity to ensure reliable STR results. Using a reduced volume of reagents, 10 times more reactions per kit are possible; accordingly, this method reduces the cost of DNA quantification, while maintaining performance.

A Simple Method of VNTR D1S80 Locus Allelic Ladder Construction for Capillary Electrophoresis-based Genotyping.

VNTR D1S80 locus genotyping has been largely replaced in forensics by STR. As the statute of limitations on murder cases was abolished in the Republic of Korea in July 2015, the demand for re-analysis of DNA from unresolved murder cases has increased. The National Forensic Service includes several recorded D1S80 genotypes as crucial clues. Here, we re-established the D1S80 analysis system using capillary electrophoresis and confirmed the reproducibility of the system by comparison with the genotypes of eight DNA samples that had been analyzed using PAGE in 2006. In addition, we created an allelic ladder via new methodology using flanking region sequences. A single DNA sample (K562) and seven primers were used for the new ladder, which contains 12 alleles. Although artificial owing to the use of the flanking region rather than repeat unit reduction, the method is rapid and simple, and could be applicable in any laboratory.

Incorporation of Mobile Application (App) Measures Into the Diagnosis of Smartphone Addiction.

OBJECTIVE: Global smartphone expansion has brought about unprecedented addictive behaviors. The current diagnosis of smartphone addiction is based solely on information from clinical interview. This study aimed to incorporate application (app)-recorded data into psychiatric criteria for the diagnosis of smartphone addiction and to examine the predictive ability of the app-recorded data for the diagnosis of smartphone addiction. METHODS: Smartphone use data of 79 college students were recorded by a newly developed app for 1 month between December 1, 2013, and May 31, 2014. For each participant, psychiatrists made a diagnosis for smartphone addiction based on 2 approaches: (1) only diagnostic interview (standard diagnosis) and (2) both diagnostic interview and app-recorded data (app-incorporated diagnosis). The app-incorporated diagnosis was further used to build app-incorporated diagnostic criteria. In addition, the app-recorded data were pooled as a score to predict smartphone addiction diagnosis. RESULTS: When app-incorporated diagnosis was used as a gold standard for 12 candidate criteria, 7 criteria showed significant accuracy (area under receiver operating characteristic curve [AUC] > 0.7) and were constructed as app-incorporated diagnostic criteria, which demonstrated remarkable accuracy (92.4%) for app-incorporated diagnosis. In addition, both frequency and duration of daily smartphone use significantly predicted app-incorporated diagnosis (AUC = 0.70 for frequency; AUC = 0.72 for duration). The combination of duration, frequency, and frequency trend for 1 month can accurately predict smartphone addiction diagnosis (AUC = 0.79 for app-incorporated diagnosis; AUC = 0.71 for standard diagnosis). CONCLUSIONS: The app-incorporated diagnosis, combining both psychiatric interview and app-recorded data, demonstrated substantial accuracy for smartphone addiction diagnosis. In addition, the app-recorded data performed as an accurate screening tool for app-incorporated diagnosis.

Proposed Diagnostic Criteria for Smartphone Addiction.

BACKGROUND: Global smartphone penetration has led to unprecedented addictive behaviors. The aims of this study are to develop diagnostic criteria of smartphone addiction and to examine the discriminative ability and the validity of the diagnostic criteria. METHODS: We developed twelve candidate criteria for characteristic symptoms of smartphone addiction and four criteria for functional impairment caused by excessive smartphone use. The participants consisted of 281 college students. Each participant was systematically assessed for smartphone-using behaviors by psychiatrist's structured diagnostic interview. The sensitivity, specificity, and diagnostic accuracy of the candidate symptom criteria were analyzed with reference to the psychiatrists' clinical global impression. The optimal model selection with its cutoff point of the diagnostic criteria differentiating the smartphone addicted subjects from non-addicted subjects was then determined by the best diagnostic accuracy. RESULTS: Six symptom criteria model with optimal cutoff point were determined based on the maximal diagnostic accuracy. The proposed smartphone addiction diagnostic criteria consisted of (1) six symptom criteria, (2) four functional impairment criteria and (3) exclusion criteria. Setting three symptom criteria as the cutoff point resulted in the highest diagnostic accuracy (84.3%), while the sensitivity and specificity were 79.4% and 87.5%, respectively. We suggested determining the functional impairment by two or more of the four domains considering the high accessibility and penetration of smartphone use. CONCLUSION: The diagnostic criteria of smartphone addiction demonstrated the core symptoms "impaired control" paralleled with substance related and addictive disorders. The functional impairment involved multiple domains provide a strict standard for clinical assessment.

Ascorbic acid and vitamin C-containing beverages delay the leucomalachite green reaction to detect latent bloodstains.

The leucomalachite green (LMG) test is one of catalytic tests for the detection of latent bloodstains and generally used in forensic field because of convenience and cost/time-effectiveness. However, contamination of latent bloodstains at crime scenes can interfere with the LMG reaction, resulting in false-negative or false-positive decisions. Herein, we examined if ascorbic acid and vitamin C (l-ascorbic acid or ascorbate)-containing beverages affect the LMG reaction. Ascorbic acid showed the inhibitory activities on the LMG reaction in a dose-dependent manner. Similarly, vitamin C-containing beverages also inhibited the LMG reaction and the inhibitory effects were proportional to the concentrations of vitamin C in beverages. It was also identified that as incubation time after adding LMG reagent to the mixtures of blood and ascorbic acid or beverages was increased, the inhibitory effects of ascorbic acid vitamin C-containing beverages on LMG test were disappeared. These results suggest that the LMG reaction is delayed but not stopped by ascorbic acid and vitamin C-containing beverages. Neither incubation at room temperature around 20-25°C nor the addition of acetic acid affects the inhibitory activity of ascorbic acid on LMG reaction. We also showed that ascorbic acid does not affect DNA stability, allowing us to obtain full short tandem repeat (STR) profiles through amplification of DNA using commercial STR kits. In conclusion, ascorbic acid and vitamin C-containing beverages delayed the LMG reaction, suggesting that it should be considered that negative results of LMG test could be false negative due to contamination of bloodstains with inhibitory factors on LMG test.

A collaborative exercise on DNA methylation based body fluid typing.

A collaborative exercise on DNA methylation based body fluid identification was conducted by seven laboratories. For this project, a multiplex methylation SNaPshot reaction composed of seven CpG markers was used for the identification of four body fluids, including blood, saliva, semen, and vaginal fluid. A total of 30 specimens were prepared and distributed to participating laboratories after thorough testing. The required experiments included four increasingly complex tasks: (1) CE of a purified single-base extension reaction product, (2) multiplex PCR and multiplex single-base extension reaction of bisulfite-modified DNA, (3) bisulfite conversion of genomic DNA, and (4) extraction of genomic DNA from body fluid samples. In tasks 2, 3 and 4, one or more mixtures were analyzed, and specimens containing both known and unknown body fluid sources were used. Six of the laboratories generated consistent body fluid typing results for specimens of bisulfite-converted DNA and genomic DNA. One laboratory failed to set up appropriate conditions for capillary analysis of reference single-base extension products. In general, variation in the values obtained for DNA methylation analysis between laboratories increased with the complexity of the required experiments. However, all laboratories concurred on the interpretation of the DNA methylation profiles produced. Although the establishment of interpretational guidelines on DNA methylation based body fluid identification has yet to be performed, this study supports the addition of DNA methylation profiling to forensic body fluid typing.

Massively parallel sequencing of the entire control region and targeted coding region SNPs of degraded mtDNA using a simplified library preparation method.

The application of next-generation sequencing (NGS) to forensic genetics is being explored by an increasing number of laboratories because of the potential of high-throughput sequencing for recovering genetic information from multiple markers and multiple individuals in a single run. A cumbersome and technically challenging library construction process is required for NGS. In this study, we propose a simplified library preparation method for mitochondrial DNA (mtDNA) analysis that involves two rounds of PCR amplification. In the first-round of multiplex PCR, six fragments covering the entire mtDNA control region and 22 fragments covering interspersed single nucleotide polymorphisms (SNPs) in the coding region that can be used to determine global haplogroups and East Asian haplogroups were amplified using template-specific primers with read sequences. In the following step, indices and platform-specific sequences for the MiSeq(®) system (Illumina) were added by PCR. The barcoded library produced using this simplified workflow was successfully sequenced on the MiSeq system using the MiSeq Reagent Nano Kit v2. A total of 0.4 GB of sequences, 80.6% with base quality of >Q30, were obtained from 12 degraded DNA samples and mapped to the revised Cambridge Reference Sequence (rCRS). A relatively even read count was obtained for all amplicons, with an average coverage of 5200 × and a less than three-fold read count difference between amplicons per sample. Control region sequences were successfully determined, and all samples were assigned to the relevant haplogroups. In addition, enhanced discrimination was observed by adding coding region SNPs to the control region in in silico analysis. Because the developed multiplex PCR system amplifies small-sized amplicons (<250 bp), NGS analysis using the library preparation method described here allows mtDNA analysis using highly degraded DNA samples.

Predicting Aggressive Tendencies by Visual Attention Bias Associated with Hostile Emotions.

The goal of the current study is to clarify the relationship between social information processing (e.g., visual attention to cues of hostility, hostility attribution bias, and facial expression emotion labeling) and aggressive tendencies. Thirty adults were recruited in the eye-tracking study that measured various components in social information processing. Baseline aggressive tendencies were measured using the Buss-Perry Aggression Questionnaire (AQ). Visual attention towards hostile objects was measured as the proportion of eye gaze fixation duration on cues of hostility. Hostility attribution bias was measured with the rating results for emotions of characters in the images. The results show that the eye gaze duration on hostile characters was significantly inversely correlated with the AQ score and less eye contact with an angry face. The eye gaze duration on hostile object was not significantly associated with hostility attribution bias, although hostility attribution bias was significantly positively associated with the AQ score. Our findings suggest that eye gaze fixation time towards non-hostile cues may predict aggressive tendencies.

Development of real-time PCR assay for genetic identification of the mottled skate, Beringraja pulchra.

The mottled skate, Beringraja pulchra is one of the commercially important fishes in the market today. However, B. pulchra identification methods have not been well developed. The current study reports a novel real-time PCR method based on TaqMan technology developed for the genetic identification of B. pulchra. The mitochondrial cytochrome oxidase subunit 1 (COI) nucleotide sequences of 29 B. pulchra, 157 skates and rays reported in GenBank DNA database were comparatively analyzed and the COI sequences specific to B. pulchra was identified. Based on this information, a system of specific primers and Minor Groove Binding (MGB) TaqMan probe were designed. The assay successfully discriminated in 29 specimens of B. pulchra and 27 commercial samples with unknown species identity. For B. pulchra DNA, an average Threshold Cycle (Ct) value of 19.1±0.1 was obtained. Among 27 commercial samples, two samples showed average Ct values 19.1±0.0 and 26.7±0.1, respectively and were confirmed to be B. pulchra based on sequencing. The other samples tested showed undetectable or extremely weak signals for the target fragment, which was also consistent with the sequencing results. These results reveal that the method developed is a rapid and efficient tool to identify B. pulchra and might prevent fraud or mislabeling during the distribution of B. pulchra products.

Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App).

BACKGROUND: Global smartphone penetration has brought about unprecedented addictive behaviors. AIMS: We report a proposed diagnostic criteria and the designing of a mobile application (App) to identify smartphone addiction. METHOD: We used a novel empirical mode decomposition (EMD) to delineate the trend in smartphone use over one month. RESULTS: The daily use count and the trend of this frequency are associated with smartphone addiction. We quantify excessive use by daily use duration and frequency, as well as the relationship between the tolerance symptoms and the trend for the median duration of a use epoch. The psychiatrists' assisted self-reporting use time is significant lower than and the recorded total smartphone use time via the App and the degree of underestimation was positively correlated with actual smartphone use. CONCLUSIONS: Our study suggests the identification of smartphone addiction by diagnostic interview and via the App-generated parameters with EMD analysis.