Large-Scale Analysis of Defects in Atomically Thin Semiconductors using Hyperspectral Line Imaging.

Point defects play a crucial role in determining the properties of atomically thin semiconductors. This work demonstrates the controlled formation of different types of defects and their comprehensive optical characterization using hyperspectral line imaging (HSLI). Distinct optical responses are observed in monolayer semiconductors grown under different stoichiometries using metal-organic chemical vapor deposition. HSLI enables the simultaneous measurement of 400 spectra, allowing for statistical analysis of optical signatures at close to a centimeter scale. The study discovers that chalcogen-rich samples exhibit remarkable optical uniformity due to reduced precursor accumulation compared to the metal-rich case. The utilization of HSLI as a facile and reliable characterization tool pushes the boundaries of potential applications for atomically thin semiconductors in future devices.

Ammonium Phosphate as Inhibitor to Mitigate the Corrosion of Steel Rebar in Chloride Contaminated Concrete Pore Solution.

In the present study, different amounts, i.e., 1-3 v/v% of 1 M ammonium phosphate monobasic, were used as an eco-friendly corrosion inhibitor to mitigate the corrosion of steel rebar exposed to simulated concrete pore (SCP) + 3.5 wt% NaCl solution at a prolonged duration. Potentiodynamic polarization results show that as the amount of inhibitor is increased, the corrosion resistance of steel rebar is increased. The steel rebar exposed to 3% inhibitor-containing SCP + 3.5 wt% NaCl solution exhibited nobler corrosion potential (Ecorr), the lowest corrosion current density (icorr), and 97.62% corrosion inhibition efficiency after 1 h of exposure. The steel rebars exposed to 3% inhibitor-containing SCP + 3.5 wt% NaCl solution revealed higher polarization resistance (Rp) and film resistance (Ro) with exposure periods compared to other samples owing to the formation of passive film. The scanning electron microscopy (SEM) of steel rebar exposed to 3% inhibitor-containing SCP + 3.5 wt% NaCl solution showed homogenous and uniform dendritic passive film which covers all over the surface, whereas, bare, i.e., SCP + 3.5 wt% NaCl solution exposed samples exhibited pitting and irregular morphology. Raman spectroscopy results confirm the formation of goethite (α-FeOOH), maghemite (γ-Fe2O3), and iron phosphate (FePO4) as a passive film onto the steel rebar surface exposed to 3% inhibitor-containing SCP + 3.5 wt% NaCl solution. These phases are responsible for the corrosion mitigation of steel rebar which are very protective, adherent, and sparingly soluble.

An Overview on Graphene-Metal Oxide Semiconductor Nanocomposite: A Promising Platform for Visible Light Photocatalytic Activity for the Treatment of Various Pollutants in Aqueous Medium.

Graphene is one of the most favorite materials for materials science research owing to its distinctive chemical and physical properties, such as superior conductivity, extremely larger specific surface area, and good mechanical/chemical stability with the flexible monolayer structure. Graphene is considered as a supreme matrix and electron arbitrator of semiconductor nanoparticles for environmental pollution remediation. The present review looks at the recent progress on the graphene-based metal oxide and ternary composites for photocatalysis application, especially for the application of the environmental remediation. The challenges and perspectives of emerging graphene-based metal oxide nanocomposites for photocatalysis are also discussed.

Accurate Driver Detection Exploiting Invariant Characteristics of Smartphone Sensors.

Distracted driving jeopardizes the safety of the driver and others. Numerous solutions have been proposed to prevent distracted driving, but the number of related accidents has not decreased. Such a deficiency comes from fragile system designs where drivers are detected exploiting sensory features from strictly controlled vehicle-riding actions and unreliable driving events. We propose a system called ADDICT (Accurate Driver Detection exploiting Invariant Characteristics of smarTphone sensors), which identifies the driver utilizing the inconsistency between gyroscope and magnetometer dynamics and the interplay between electromagnetic field emissions and engine startup vibrations. These features are invariantly observable regardless of smartphone positions and vehicle-riding actions. To evaluate the feasibility of ADDICT, we conducted extensive experiments with four participants and three different vehicles by varying vehicle-riding scenarios. Our evaluation results demonstrated that ADDICT identifies the driver's smartphone with 89.1% average accuracy for all scenarios and >85% under the extreme scenario, at a marginal cost of battery consumption.

Estimating the Composition of Food Nutrients from Hyperspectral Signals Based on Deep Neural Networks.

There is an increasing demand for acquiring details of food nutrients especially among those who are sensitive to food intakes and weight changes. To meet this need, we propose a new approach based on deep learning that precisely estimates the composition of carbohydrates, proteins, and fats from hyperspectral signals of foods obtained by using low-cost spectrometers. Specifically, we develop a system consisting of multiple deep neural networks for estimating food nutrients followed by detecting and discarding estimation anomalies. Our comprehensive performance evaluation demonstrates that the proposed system can maximize estimation accuracy by automatically identifying wrong estimations. As such, if consolidated with the capability of reinforcement learning, it will likely be positioned as a promising means for personalized healthcare in terms of food safety.

Human-level blood cell counting on lens-free shadow images exploiting deep neural networks.

In point-of-care testing, in-line holographic microscopes paved the way for realizing portable cell counting systems at marginal cost. To maximize their accuracy, it is critically important to reliably count the number of cells even in noisy blood images overcoming various problems due to out-of-focus blurry cells and background brightness variations. However, previous studies could detect cells only on clean images while they failed to accurately distinguish blurry cells from background noises. To address this problem, we present a human-level blood cell counting system by synergistically integrating the methods of normalized cross-correlation (NCC) and a convolutional neural network (CNN). Our comprehensive performance evaluation demonstrates that the proposed system achieves the highest level of accuracy (96.7-98.4%) for any kinds of blood cells on a lens-free shadow image while others suffer from significant accuracy degradations (12.9-38.9%) when detecting blurry cells. Moreover, it outperforms others by up to 36.8% in accurately analyzing noisy blood images and is 24.0-40.8× faster, thus maximizing both accuracy and computational efficiency.

Security-Enhanced Push Button Configuration for Home Smart Control.

With the emergence of smart and converged home services, the need for the secure and easy interplay of various devices has been increased. Push Button Configuration (PBC) is one of the technologies proposed for easy set-up of a secure session between IT and consumer devices. Although the Wi-Fi Direct specification explicitly states that all devices must support the PBC method, its applicability is very limited. This is because the security vulnerability of PBC can be maliciously exploited so that attackers can make illegitimate sessions with consumer devices. To address this problem, this paper proposes a novel Security-enhanced PBC (SePBC) scheme with which we can uncover suspicious or malicious devices. The proposed mechanism has several unique features. First, we develop a secure handshake distance measurement protocol by preventing an adversary sitting outside the region from maliciously manipulating its distance to be fake. Second, it is compatible with the original Wi-Fi PBC without introducing a brand-new methodology. Finally, SePBC uses lightweight operations without CPU-intensive cryptography computation and employs inexpensive H/W. Moreover, it needs to incur little overhead when there is no attack. This paper also designs and implements the proposed SePBC in the real world. Our experimental results and analysis show that the proposed SePBC scheme effectively defeats attacks on PBC while minimizing the modification of the original PBC equipment.

Reliable Identification of Vehicle-Boarding Actions Based on Fuzzy Inference Syste.

Existing smartphone-based solutions to prevent distracted driving suffer from inadequate system designs that only recognize simple and clean vehicle-boarding actions, thereby failing to meet the required level of accuracy in real-life environments. In this paper, exploiting unique sensory features consistently monitored from a broad range of complicated vehicle-boarding actions, we propose a reliable and accurate system based on fuzzy inference to classify the sides of vehicle entrancebyleveragingbuilt-insmartphonesensorsonly. Theresultsofourcomprehensiveevaluation on three vehicle types with four participants demonstrate that the proposed system achieves 91.1%∼94.0% accuracy, outperforming other methods by 26.9%∼38.4% and maintains at least 87.8 %accuracy regardless of smartphone positions and vehicle types.

Anisakiasis: Report of 15 Gastric Cases Caused by Anisakis Type I Larvae and a Brief Review of Korean Anisakiasis Cases.

The present study was performed to report 15 anisakiasis cases in Korea and to review the Korean cases reported in the literature. Total 32 Anisakis type I larvae were detected in the stomach of 15 patients by the endoscopy. Single worm was detected from 12 cases, and even 9 larvae were found from 2 cases. Epigastric pain was most commonly manifested in almost all cases, and hemoptysis and hematemesis were seen in 1 case each. Symptom manifestations began at 10-12 hr after eating fish in 73.3% cases. Endoscopy was performed 1-2 days after the symptom onset in most cases. The common conger, Conger myriaster, was the probable infection source in 7 cases. In the review of Korean anisakiasis cases, thus far, total 645 cases have been reported in 64 articles. Anisakis type I larva was the most frequently detected (81.3%). The favorable infection site of larvae was the stomach (82.4%). The common conger was the most probable source of human infections (38.6%). Among the total 404 cases which revealed the age and sex of patients, 185 (45.8%) were males, and the remaining 219 (54.2%) were female patients. The age prevalence was the highest in forties (34.7%). The seasonal prevalence was highest in winter (38.8%). By the present study, 15 cases of gastric anisakiasis are added as Korean cases, and some epidemiological characteristics of Korean anisakiasis were clarified.

Energy-efficient privacy protection for smart home environments using behavioral semantics.

Research on smart environments saturated with ubiquitous computing devices is rapidly advancing while raising serious privacy issues. According to recent studies, privacy concerns significantly hinder widespread adoption of smart home technologies. Previous work has shown that it is possible to infer the activities of daily living within environments equipped with wireless sensors by monitoring radio fingerprints and traffic patterns. Since data encryption cannot prevent privacy invasions exploiting transmission pattern analysis and statistical inference, various methods based on fake data generation for concealing traffic patterns have been studied. In this paper, we describe an energy-efficient, light-weight, low-latency algorithm for creating dummy activities that are semantically similar to the observed phenomena. By using these cloaking activities, the amount of  fake data transmissions can be flexibly controlled to support a trade-off between energy efficiency and privacy protection. According to the experiments using real data collected from a smart home environment, our proposed method can extend the lifetime of the network by more than 2× compared to the previous methods in the literature. Furthermore, the activity cloaking method supports low latency transmission of real data while also significantly reducing the accuracy of the wireless snooping attacks.

Self-configuring indoor localization based on low-cost ultrasonic range sensors.

In smart environments, target tracking is an essential service used by numerous applications from activity recognition to personalized infotaintment. The target tracking relies on sensors with known locations to estimate and keep track of the path taken by the target, and hence, it is crucial to have an accurate map of such sensors. However, the need for manually entering their locations after deployment and expecting them to remain fixed, significantly limits the usability of target tracking. To remedy this drawback, we present a self-configuring and device-free localization protocol based on genetic algorithms that autonomously identifies the geographic topology of a network of ultrasonic range sensors as well as automatically detects any change in the established network structure in less than a minute and generates a new map within seconds. The proposed protocol significantly reduces hardware and deployment costs thanks to the use of low-cost off-the-shelf sensors with no manual configuration. Experiments on two real testbeds of different sizes show that the proposed protocol achieves an error of 7.16~17.53 cm in topology mapping, while also tracking a mobile target with an average error of 11.71~18.43 cm and detecting displacements of 1.41~3.16 m in approximately 30 s.

Optimization of a cell counting algorithm for mobile point-of-care testing platforms.

In a point-of-care (POC) setting, it is critically important to reliably count the number of specific cells in a blood sample. Software-based cell counting, which is far faster than manual counting, while much cheaper than hardware-based counting, has emerged as an attractive solution potentially applicable to mobile POC testing. However, the existing software-based algorithm based on the normalized cross-correlation (NCC) method is too time- and, thus, energy-consuming to be deployed for battery-powered mobile POC testing platforms. In this paper, we identify inefficiencies in the NCC-based algorithm and propose two synergistic optimization techniques that can considerably reduce the runtime and, thus, energy consumption of the original algorithm with negligible impact on counting accuracy. We demonstrate that an AndroidTM smart phone running the optimized algorithm consumes 11.5× less runtime than the original algorithm.

Unraveling the anti-corrosion mechanisms of a novel hydrazone derivative on steel in contaminated concrete pore solutions: An integrated study.

INTRODUCTION: Corrosion-induced deterioration of infrastructure is a growing global concern. The development and application of corrosion inhibitors are one of the most effective approaches to protect steel rebar from corrosion. Hence, this study focuses on a novel hydrazone derivative, (E)-N'-(4-(dimethylamino)benzylidene)-2-(5-methoxy-2-methyl-1H-indol-3-yl)aceto-hydrazide (HIND), and its potential application to mitigate corrosion in steel rebar exposed to chloride-contaminated concrete pore solutions (ClSCPS). OBJECTIVES: The research aims to evaluate the anti-corrosion capabilities of HIND on steel rebar within a simulated corrosive environment, focusing on the mechanisms of its inhibitory effect. METHODS: The corrosion of steel rebar exposed to the ClSCPS was studied through weight loss and electrochemical methods. The surface morphology of steel rebar surface was characterized by FE-SEM-EDS, AFM; oxidation states of the steel rebar and crystal structures were examined using X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) methods. Further, experimental findings were complemented by theoretical studies using self-consistent-charge density-functional tight-binding (SCC-DFTB) simulations. The performance of HIND was monitored at an optimal concentration over a period of 30 days. RESULTS: The results indicated a significant reduction in steel rebar corrosion upon introducing HIND. The inhibitor molecules adhered to the steel surface, preventing further deterioration and achieving an inhibition efficiency of 88.4% at 0.5 mmol/L concentration. The surface morphology analysis confirmed the positive effect of HIND on the rebar surface, showing a decrease in the surface roughness of the steel rebar from 183.5 in uninhibited to 50 nm in inhibited solutions. Furthermore, SCC-DFTB simulations revealed the presence of coordination between iron atoms and HIND active sites. CONCLUSION: The findings demonstrate the potential of HIND as an effective anti-corrosion agent in chloride-contaminated environments. Its primary adsorption mechanism involves charge transfer from the inhibitor molecules to iron atoms. Therefore, applying HIND could be an effective strategy to address corrosion-related challenges in reinforced infrastructure.

Theoretical and experimental study of waste-heat-recovery boiler with water injection.

The waste-heat-recovery boiler with water injection (HR-B/W) applies the heat exchange between the intake air and exhaust gas with the water injection into the intake air. Previous theoretical studies have discussed that the HR-B/W would increase the thermal efficiency of the boiler by the active heat exchange between the intake air and exhaust gas. It has also been discussed that the increased fraction of water vapor in the air would reduce the flame temperature which in turn decreases the NOx emission. However, the potential performance of the HR-B/W has not been validated through practical boiler tests by considering the evaporation characteristics of the injected water, which plays a critical role in the performance of the HR-B/W. In this study the effects of water injection into the intake air on the thermal efficiency and pollutant emissions of the waste-heat-recovery boiler are investigated using a commercial 24 kW condensing boiler in full load condition. Thermodynamic analysis is performed to evaluate the adequate amount of water injection and trace the physical properties in the boiler upon the water injection amount and evaporation characteristics. The boiler test results showed water injection can increase thermal efficiency to 4.4% point and reduce NOx and CO emissions by 69% and 33% respectively compared to those without water injection. These advantages can be further enhanced if the atomization and evaporation performance of injected water is improved.

Potential association of DCBLD2 polymorphisms with fall rates of FEV(1) by aspirin provocation in Korean asthmatics.

Aspirin exacerbated respiratory disease (AERD) is a clinical syndrome characterized by chronic rhinosinusitis with nasal polyposis and aspirin hypersensitivity. The aspirin-induced bronchospasm is mediated by mast cell and eosinophilic inflammation. Recently, it has been reported that the expression of discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is up-regulated in lung cancers and is regulated by transcription factor AP-2 alpha (TFAP2A), a component of activator protein-2 (AP-2) that is known to regulate IL-8 production in human lung fibroblasts and epithelial cells. To investigate the associations between AERD and DCBLD2 polymorphisms, 12 common variants were genotyped in 163 AERD subjects and 429 aspirin tolerant asthma (ATA) controls. Among these variants, seven SNPs (rs1371687, rs7615856, rs828621, rs828618, rs828616, rs1062196, and rs8833) and one haplotype (DCBLD2-ht1) show associations with susceptibility to AERD. In further analysis, this study reveals significant associations between the SNPs or haplotypes and the percentage of forced expiratory volume in one second (FEV(1)) decline following aspirin challenge using multiple linear regression analysis. Furthermore, a non-synonymous SNP rs16840208 (Asp723Asn) shows a strong association with FEV(1) decline in AERD patients. Although further studies for the non-synonymous Asp723Asn variation are needed, our findings suggest that DCBLD2 could be related to FEV(1)-related phenotypes in asthmatics.

Undeflatable balloon guide catheter (BGC) during endovascular procedure: Rescue strategy.

The use of a balloon guide catheter (BGC) in the endovascular management of acute ischemic stroke is known to improve the efficacy and efficiency of the procedure by reducing the risk of distal embolization. During the procedure, the balloon of the catheter causes a temporary arrest of cerebral blood flow. However, failure of the balloon to deflate during the BGC procedure can result in catastrophic complications, including aggravated hypoxic damage.
This paper aims to share the resolution and methodological analysis of our experience with BGC balloon deflation failure, which was confirmed by a reproducible experiment under similar conditions.

Solution and solid-state NMR structural studies of antimicrobial peptides LPcin-I and LPcin-II.

Lactophoricin (LPcin-I) is an antimicrobial, amphiphatic, cationic peptide with 23-amino acid residues isolated from bovine milk. Its analogous peptide, LPcin-II, lacks six N-terminal amino acids compared to LPcin-I. Interestingly, LPcin-II does not display any antimicrobial activity, whereas LPcin-I inhibits the growth of both Gram-negative and Gram-positive bacteria without exhibiting any hemolytic activity. Uniformly (15)N-labeled LPcin peptides were prepared by the recombinant expression of fusion proteins in Escherichia coli, and their properties were characterized by electrospray ionization mass spectrometry, circular dichroism spectroscopy, and antimicrobial activity tests. To understand the structure-activity relationship of these two peptides, they were studied in model membrane environments by a combination of solution and solid-state NMR spectroscopy. We determined the tertiary structure of LPcin-I and LPcin-II in the presence of dodecylphosphorylcholine micelles by solution NMR spectroscopy. Magnetically aligned unflipped bicelle samples were used to investigate the structure and topology of LPcin-I and LPcin-II by solid-state NMR spectroscopy.

A possible association of EMID2 polymorphisms with aspirin hypersensitivity in asthma.

Aspirin-intolerant asthma (AIA) is an asthma phenotype characterized by the development of bronchoconstriction following ingestion of aspirin. Despite the well-defined pathological trigger, the underlying mechanisms of AIA are still unclear. With the biophysical characteristics of the human EMI domain-containing protein 2 (EMID2) gene in relation to the extracellular matrix deposition and epithelial-mesenchymal transition as pivotal characteristics of airway remodeling in asthma, we hypothesized that genetic polymorphisms of EMID2 might affect the development of AIA. In this study, the allelic associations of 49 single-nucleotide polymorphisms (SNPs) of the human EMID2 gene were evaluated from 163 AIA patients and 429 aspirin-tolerant asthma (ATA) subjects as controls in a Korean population. Logistic analysis showed that five SNPs (P = 0.01-0.04, but P (corr) > 0.05) and EMID2_BL2_ht2 haplotype (unique to the minor alleles of rs4727494 and rs13233066; P = 0.02; P (corr) = 0.02) were significantly associated with AIA. More interestingly, regression analysis of the decline of forced expiratory volume in one second (FEV(1)) by aspirin provocation revealed that 10 SNPs (P = 0.003-0.04) and four relevant haplotypes (P = 0.002-0.02) were significantly associated with the fall rate of FEV(1) by aspirin provocation, indicating that genetic polymorphisms of EMID2 could cause meaningful deficits in the upper and lower airways among AIA patients. These findings provide evidence that EMID2 may be a susceptible genetic factor for aspirin hypersensitivity among asthmatics in Korean population.

Lack of association of RAD51 genetic variations with hepatitis B virus clearance and occurrence of hepatocellular carcinoma in a Korean population.

The RecA homolog, E. coli (S. cerevisiae) (RAD51) may modulate hepatitis B virus (HBV) infection by maintaining genome integrity and mediating homologous DNA repairs. In this study, 16 sequence variations were detected by resequencing all exons, the exon-intron boundary, and promoter regions of the human RAD51 gene in DNA samples of 24 unrelated individuals. To investigate the association of common variations in the RAD51 locus with HBV infection and hepatocellular carcinoma (HCC) occurrence, six common polymorphisms were genotyped in a total of 1,103 Korean HBV cohort, composed of 433 spontaneously recovered patients as controls and 670 chronic carriers of HBV, who were stratified further into 327 cirrhosis/chronic hepatitis patients and 343 patients with HCC infected with HBV. Logistic analyses revealed no significant association of RAD51 polymorphisms and haplotypes with HBV clearance and HCC occurrence (P > 0.05). Furthermore, with age of infection as an important factor in disease progression to HCC, results from the Cox proportional hazards analysis showed no significant associations between any of the tested RAD51 variants and the age of onset of HCC (P > 0.05), suggesting that genetic polymorphisms of RAD51 may not play an important role in clearance of HBV and disease progression to HCC. Although studies in other populations are needed to confirm these findings, this preliminary data may contribute to the current knowledge on the pathogenesis of hepatitis.

Possible association of SLC22A2 polymorphisms with aspirin-intolerant asthma.

BACKGROUND: Aspirin-intolerant asthma (AIA) is a clinical syndrome characterized by acute bronchoconstriction following the ingestion of aspirin. Solute carrier family 22, member 2 (SLC22A2), also known as organic cation transporter 2 (OCT2), is predominantly expressed in the luminal membrane of airway epithelial cells and has been shown to mediate the transport of prostaglandins on the cyclooxygenase pathway which is regulated by aspirin blockage. Recently, SLC22A2-mediated uptake inhibition by several nonsteroidal anti-inflammatory drugs and decreased SLC22A2 transport activity by its genetic variants have been elucidated in asthma. METHODS: To investigate the associations between AIA and genetic polymorphisms of the SLC22A2 gene, 18 variants were genotyped in 163 AIA subjects and 429 aspirin-tolerant asthma (ATA) controls. Logistic analyses were used to evaluate p values for the associations of SLC22A2 polymorphisms with AIA. RESULTS: One common polymorphism in intron 5, i.e. rs316021, was significantly associated with susceptibility to AIA (p = 0.004, P(corr) = 0.05, OR = 0.60, 95% CI = 0.43-0.85 in a codominant model). The minor allele frequency of rs316021 in the AIA group was significantly lower than that in the ATA controls. In addition, a polymorphism in intron 4 (rs3912161) and a haplotype (SLC22A2-ht3) showed significantly stronger association signals with the FEV(1) fall rate induced by aspirin provocation in AIA subjects compared with ATA controls (p = 0.004, P(corr) = 0.05). CONCLUSION: Our findings suggest that SLC22A2 could be a susceptibility gene for aspirin intolerance in asthmatics.