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This paper presents a membrane computation error-minimized mixed-mode spiking neural network (SNN) crossbar array. Our approach involves imple-menting an embedded dummy switch scheme and a mid-node pre-charge scheme to construct a high-precision current-mode synapse. We effectively suppressed charge sharing between membrane capacitors and the parasitic capacitance of synapses that results in membrane computation error. A 400 X 20 SNN crossbar prototype chip is fabricated via a 28-nm FDSOI CMOS process, and 20 MNIST patterns with their sizes reduced to 20 X 20 pixels are successfully recognized under 411 μW of power consumed. Moreover, the peak-to-peak deviation of the normalized output spike count measured from the 21 fabricated SNN prototype chips is within 16.5% from the ideal value, including sample-wise random variations.

To expand the scale of spiking neural networks (SNNs), an interface circuit that supports multiple SNN cores is essential. This circuit should be designed using an asynchronous approach to leverage characteristics of SNNs similar to those of the human brain. However, the absence of a global clock presents tim-ing issues during implementation. Hence, we propose an intermediate latching template to establish asynchronous nonlinear connectivity with multipipeline processing between multiple SNN cores. We design arbitration and distribu-tion blocks in the interface circuit based on the proposed template and fabri-cate an interface circuit that supports four SNN cores using a full-custom approach in a 28-nm CMOS (complementary metal-oxide-semiconductor) FDSOI (fully depleted silicon on insulator) process. The proposed template can enhance throughput in the interface circuit by up to 53% compared with the conventional asynchronous template. The interface circuit transmits spikes while consuming 1.7 and 3.7 pJ of power, supporting 606 and 59 Mevent/s in intrachip and interchip communications, respectively.

Abstract After the occurrences of large-scale earthquakes, secondary damage (e.g., fire following earthquake) can result in tremendous losses of life, properties, and buildings. To reduce these disaster risks, fire following earthquake assessment methods composed of ignition and fire-burned rate estimation models have been utilized. However, previous methods required for large amounts of building and GIS information, and complex modeling and analysis processes, leading to significant time consumption. This paper proposed a static analysis-based rapid fire following earthquake assessment method using simple information and implemented it in Pohang City, South Korea. Based on previous studies, the best-fit model for the ignition rate estimation was selected, and a cluster-based fire-burned rate estimation model was developed using simple building information (e.g., construction year, building occupancy, story, and total floor area) from the public building database (e.g., building registration data). For the fire-burned rate estimation model, fire-resistant structure types were defined using simple building information, and this was utilized to generate clusters of buildings at a regional level by comparing fire-spread distances for each fire-resistant structure type with adjacent distances among the buildings. This proposed method was applied to Pohang City, South Korea, and validated as follows: (1) the selected ignition rate model predicted similar ignition numbers to the actual reported number (actual number of ignitions = 4 vs. predicted number of ignitions = 3), and (2) the fire-burned rate model estimated fire-burned areas with a marginal difference compared to the fire spread simulation (fire-burned area using the proposed model = 13,703.6 m2 vs. results of fire spread simulation = 16,800.0 m2, with an error of approximately 18%).

Abstract The rapid evolution of mass spectrometry-based single-cell proteomics now enables the cataloging of several thousand proteins from single cells. We investigated whether we could discover cellular heterogeneity beyond proteome, encompassing post-translational modifications (PTM), protein-protein interaction, and variants. By optimizing the mass spectrometry data interpretation strategy to enable the detection of PTMs and variants, we have generated a high-definition dataset of single-cell and nuclear proteomic-states. The data demonstrate the heterogeneity of cell-states and signaling dependencies at the single-cell level and reveal epigenetic drug-induced changes in single nuclei. This approach enables the exploration of previously uncharted single-cell and organellar proteomes revealing molecular characteristics that are inaccessible through RNA profiling.

Accurate earthwork quantity estimation is essential for effective project planning and cost management in the Architecture, Engineering, and Construction (AEC) industry. Traditional methods for quantity takeoff are often time-consuming and susceptible to human error, particularly when working with unstructured datasets such as CAD drawings. This study introduces the Earthwork Network Architecture (ENA), a novel deep learning framework that incorporates Large Language Models (LLMs), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM) networks, and Transformers to automate and enhance the accuracy of earthwork quantity estimation. We assume that if LLMs can be trained effectively using such unstructured construction dataset, the effects such as improved accuracy and the challenges of LLMs can be clearly examined. Among the architectures tested, the LLM-based ENA demonstrated superior performance, achieving faster convergence, greater loss reduction, and higher classification accuracy, with a Quantity Takeoff Classification accuracy of 97.17%. However, the LLMs required significantly more computational resources compared with other models. These findings suggest that LLMs, typically used in natural language processing, can be effectively adapted for complex AEC datasets. This study lays the groundwork for future AI-driven solutions in the AEC industry, underscoring the potential of LLMs and Transformers to automate the quantity takeoff process and manage multimodal data in construction projects.

Mn2+-doped β-Zn2SiO4, a metastable phase of zinc silicate, is widely acknowledged for the uncertainties linked to its crystal structure and challenging synthesis process along with its distinctive yellowish luminescence. In this study, a vivid yellow luminescence originating from Mn2+-doped metastable zinc silicate (BZSM) nanophosphor is suggested, achieved through a straightforward single-step annealing process. The reliable production of this phosphor necessitates substantial doping, surplus SiO2, a brief annealing duration, and prompt cooling. The verification of the phase is demonstrated based on its optical and crystallographic characteristics. Moreover, the effective utilization of excimer lamps in practical scenarios is effectively demonstrated as a result of the vacuum ultraviolet excitation property of BZSM nanophosphor. This outcome paves the way for additional deployment of metastable zinc silicate in various fields, consequently generating novel prospects for future advancements.

This paper presents a low-power and lightweight human body communication (HBC) receiver with an embedded dummy electrode for improved signal acquisition. The clock data recovery (CDR) circuit in the receiver operates with a low supply voltage and utilizes a clock phase inversion scheme. The receiver is equipped with a main electrode and dummy electrode that strengthen the capacitive-coupled signal at the receiver frontend. The receiver CDR circuit exploits a clock inversion scheme to allow 0.9-V operation while achieving a shorter lock time than at 3.3-V operation. In experiments, a receiver chip fabricated using 130-nm complementary metal–oxide–semiconductor technology was demonstrated to successfully receive the transmitted signal when the transmitter and receiver are placed separately on each hand of the user while consuming only 4.98 mW at a 0.9-V supply voltage.

Abstract Background Biportal endoscopic surgery has recently been performed in lumbar discectomy, with advantages over conventional surgery, such as less skin scarring and muscle damage. However, the clinical results have not been established. Although previous studies reported no difference between the biportal endoscopic and microscopic discectomy clinical results, the evidence was weak. Therefore, this study aims to evaluate the efficacy and safety of the biportal endoscopic discectomy versus the microscopic discectomy. Methods This prospective multicenter randomized controlled equivalence trial is designed to compare the efficacy and safety outcomes of patients who underwent lumbar discectomy using biportal endoscopy or microscopy. We will include 100 participants (50 per group) with a lumbar herniated disc. The primary outcome will be the Oswestry Disability Index (ODI) score 12 months after surgery based on a modified intention-to-treat strategy. The secondary outcomes will include the visual analog scale score for low back and lower extremity radiating pain, the ODI score, the Euro-Qol-5-Dimensions score, surgery satisfaction, walking time, postoperative return to daily life period, postoperative surgical scar, and surgery-related variables, such as postoperative drainage, operation time, admission duration, postoperative creatine kinase, and implementation status of conversion to open surgery. Radiographic outcomes will also be analyzed using magnetic resonance imaging (MRI) or computed tomography (CT) and simple radiographs. Safety will be assessed by evaluating all adverse and severe adverse events and surgery-related effects. The participants will be assessed by a blinded assessor before surgery (baseline) and 2 weeks and 3, 6, and 12 months after surgery. Discussion This trial will be the first prospective, multicenter, randomized controlled trial to analyze the efficacy and safety of biportal endoscopic discectomy in lumbar herniated disc. This trial is designed for evaluating the equivalence of the results between biportal endoscopic and microscopic discectomy including adequate sample size, blinded analyses, and prospective registration to reduce bias. This trial will provide enough data on the effectiveness and safety of biportal endoscopic surgery and will be an important study that allows clear conclusions. Trial registration Clinical Research Information Service (cris.nih.go.kr.) ( KCT0006191 ). Registered on 27 March 2021

Abstract Background Recent studies on biportal endoscopic spine surgery in patients with lumbar spinal stenosis have reported good clinical results. However, these studies have been limited by the small sample sizes and use of a retrospective study design. Therefore, we aim to compare the efficacy and safety of biportal endoscopic decompressive laminectomy with those of conventional decompressive laminectomy in a multicenter, prospective, randomized controlled trial. Methods This study will include 120 patients (60 per group, aged 20–80 years) with 1- or 2-level lumbar spinal stenosis, who will be recruited from six hospitals. The study will be conducted from July 2021 to December 2024. The primary outcome (Oswestry Disability Index at 12 months after surgery) will be evaluated through a modified intention-to-treat method. The secondary outcomes will include the following: visual analog scale score for low back and lower extremity radiating pain, EuroQol 5-dimensions score, surgery satisfaction, walking time, postoperative return to daily life period, postoperative surgical scars, and some surgery-related variables. Radiographic outcomes will be analyzed using magnetic resonance imaging or computed tomography. All outcomes will be evaluated before the surgery and at 2 weeks, 3 months, 6 months, and 12 months postoperatively. This protocol adheres to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines for reporting of clinical trial protocols. Discussion It is hypothesized that the efficacy and safety of biportal endoscopic and conventional decompressive laminectomy will be comparable in patients with lumbar spinal stenosis. The results of this trial will provide a high level of evidence for the efficacy and safety of the biportal endoscopic technique in patients with lumbar spinal stenosis and facilitate the development of clinical practice guidelines. Furthermore, the results of this study may indicate the feasibility of the biportal endoscopic technique for other types of spinal surgery. Trial registration The ENDO-B trial is registered at Clinical Research Information Service (CRIS, cris.nih.go.kr ) (KCT0006057; April 52,021).

Abstract Kidney organoids derived from the human pluripotent stem cells (hPSCs) recapitulating human kidney are the attractive tool for kidney regeneration, disease modeling, and drug screening. However, the kidney organoids cultured by static conditions have the limited vascular networks and immature nephron-like structures unlike human kidney. Here, we developed a kidney organoid-on-a-chip system providing fluidic flow mimicking shear stress with optimized extracellular matrix (ECM) conditions. We demonstrated that the kidney organoids cultured in our microfluidic system showed more matured podocytes and vascular structures as compared to the static culture condition. Additionally, the kidney organoids cultured in microfluidic systems showed higher sensitivity to nephrotoxic drugs as compared with those cultured in static conditions. We also demonstrated that the physiological flow played an important role in maintaining a number of physiological functions of kidney organoids. Therefore, our kidney organoid-on-a-chip system could provide an organoid culture platform for in vitro vascularization in formation of functional three-dimensional (3D) tissues.

This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud Data (PCD) of Airborne Laser Scanning (ALS). Advanced scanning techniques capture detailed geometry from the physical site and generate high-resolution point clouds, which are processed to create 3D models for GIS integration. The critical contribution of this research lies in a scalable Scan to BIM mapping process, which can be used for generating building footprints and masses, including attributes, on 3D GIS. The resulting integrated BIM–GIS dataset provides an accurate building mass, facade information, facility asset management, and architectural design and facilitates improved decision-making in urban planning based on enhanced visualization, analysis, and simulation. This study suggests a flexible Scan to BIM mapping process description based on use cases, including algorisms. Through prototype development, a case study demonstrates the effectiveness of the process approach, the automatic generation of BIM on a 3D GIS platform, and reducing the manual efforts. The proposed method automatically creates DEM, SHP, GeoJSON, IFC, and coordinate system information from scan data and can effectively map building objects in 3D GIS.

AbstractThis paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin‐film beta‐radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.

This paper presents an efficient hardware random‐number generator based on a beta source. The proposed generator counts the values of “0” and “1” and provides a method to distinguish between pseudo‐random and true random numbers by comparing them using simple cumulative operations. The random‐number generator produces labeled data indicating whether the count value is a pseudo‐ or true random number according to its bit value based on the generated labeling data. The proposed method is verified using a system based on Verilog RTL coding and LabVIEW for hardware implementation. The generated random numbers were tested according to the NIST SP 800‐22 and SP 800‐90B standards, and they satisfied the test items specified in the standard. Furthermore, the hardware is efficient and can be used for security, artificial intelligence, and Internet of Things applications in real time.

Abstract Although postoperative delirium is a common complication in older patients, few papers have described risk factors after of spinal surgery. The purpose of this study was to analyze various perioperative risk factors for delirium after spinal surgery in older patients. This study was performed on retrospective data collection with prospective design. We analyzed 138 patients over 65 years of age who underwent spinal surgery. Preoperative factors were cognitive function (Mini-Mental State Examination-Korean (MMSE-K) and the Korean version of the Delirium Rating Scale-Revised-98 (K-DRS 98)), age, sex, type of admission, American Society of Anesthesiologist classification, metabolic equivalents, laboratory findings, visual analog scale, and Oswestry Disability Index. Intraoperative factors were operation time, blood loss, and type of procedure. Postoperative factors were blood transfusion and type of postoperative pain control. Postoperative delirium developed in 25 patients (18.16%). Patients were divided into two groups: Group with delirium (group A) and group without delirium (group B). MMSE-K scores in Group A were significantly lower than in Group B (p

In this research, the potential anti-obesity efficacy of Lactobacillus rhamnosus BST-L.601 and its fermented product (named SPY) with mashed sweet potato paste were investigated using 3T3-L1 preadipocytes and high-fat diet (HD)-induced obese mice. SPY (0–0.5 mg/mL) dose-dependently and significantly reduced lipid accumulation and TG content and the expression of adipogenic markers (C/EBPα, PPAR-γ, and aP2) and fatty acid synthetic pathway proteins (ACC and FAS) in 3T3-L1 adipocytes, demonstrating that SPY suppresses adipocyte differentiation and lipogenesis. Oral administration of SPY (4 × 107 CFU/kg body weight) to HD-induced obese mice for 12 weeks significantly reduced the body and liver weight, the size of adipocytes, and the weight of epididymal, visceral, and subcutaneous fat tissues. SPY was more effective in decreasing body weight gain in HD mice than in treatment with BST-L.601 alone. Administration of SPY or BST-L.601 also reduced the serum level of total cholesterol and LDL cholesterol and leptin secretion at a similar level. These results revealed that both SPY and BST-L.601 effectively suppress HD-induced adipogenesis and lipogenesis, suggesting that these materials would be useful in the functional foods industry to ameliorate and/or prevent obesity.

Human recognition technologies for security systems require high reliability and easy accessibility in the advent of the internet of things (IoT). While several biometric approaches have been studied for user recognition, there are demands for more convenient techniques suitable for the IoT devices. Recently, electrical frequency responses of the human body have been unveiled as one of promising biometric signals, but the pilot studies are inconclusive about the characteristics of human body as a transmission medium for electric signals. This paper provides a multi-domain analysis of human body impulse responses (HBIR) measured at the receiver when customized impulse signals are passed through the human body. We analyzed the impulse responses in the time, frequency, and wavelet domains and extracted representative feature vectors using a proposed accumulated difference metric in each domain. The classification performance was tested using the k-nearest neighbors (KNN) algorithm and the support vector machine (SVM) algorithm on 10-day data acquired from five subjects. The average classification accuracies of the simple classifier KNN for the time, frequency, and wavelet features reached 92.99%, 77.01%, and 94.55%, respectively. In addition, the kernel-based SVM slightly improved the accuracies of three features by 0.58%, 2.34%, and 0.42%, respectively. The result shows potential of the proposed approach for user recognition based on HBIR.

Motivated by the idea that there should be a close relationship between biological significance and low power driving of spike neural networks (SNNs), this paper aims to focus on spike-frequency adaptation, which deviates significantly from existing biological meaningfulness, and develop a new spike-frequency adaptation with more biological characteristics. As a result, this paper proposes the sensoryadaptation method that reflects the mechanisms of the human sensory organs, and studies network architectures and neuron models for the proposed method. Next, this paper introduces a dedicated SNN simulator that can selectively apply the conventional spike-frequency adaptation and the proposed method, and provides the results of functional verification and effectiveness evaluation of the proposed method. Through intensive simulation, this paper reveals that the proposed method can produce a level of training and testing performance similar to the conventional method while significantly reducing the number of spikes to 32.66% and 45.63%, respectively. Furthermore, this paper contributes to SNN research by showing an example based on in-depth analysis that embedding biological meaning in SNNs may be closely related to the low-power driving characteristics of SNNs.

The multi-stimuli responsive drug delivery system has recently attracted attention in cancer treatments, since it can reduce several side effects and enhance cancer therapeutic efficacy. Herein, we present the intracellular antioxidant (glutathione, GSH), enzyme (hyaluronidase, HAase), and hydrogen peroxide (H2O2) triggered mesoporous organo-silica (MOS) nanocomposites for multi-modal treatments via chemo-, photothermal, and photodynamic cancer therapies. A MOS nanoparticle was synthesized by two-types of precursors, tetraethyl orthosilicate (TEOS) and bis[3-(triethoxysilyl)propyl] tetrasulfide (BTES), providing large-sized mesopores and disulfide bonds cleavable by GSH. Additionally, we introduced a new β-cyclodextrin-hyaluronic acid (CDHA) gatekeeper system, enabling nanocomposites to form the specific interaction with the ferrocene (Fc) molecule, control the drug release by the HAase and H2O2 environment, as well as provide the targeting ability against the CD44-overexpressing melanoma (B16F10) cells. Indocyanine green (ICG) and doxorubicin (Dox) were loaded in the MOS-Fc-CDHA (ID@MOS-Fc-CDHA) nanocomposites, allowing for hyperthermia and cytotoxic reactive oxygen species (ROS) under an 808 nm NIR laser irradiation. Therefore, we demonstrated that the ID@MOS-Fc-CDHA nanocomposites were internalized to the B16F10 cells via the CD44 receptor-mediated endocytosis, showing the controlled drug release by GSH, HAase, and H2O2 to enhance the cancer therapeutic efficacy via the synergistic chemo-, photothermal, and photodynamic therapy effect.

Objective To determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag.Design This is a nationwide population-based ecological study from 2008 to 2017.Setting Eight large metropolitan areas in Korea.Participants Of 8 093 820 patients with fractures reported in the Korea National Health Insurance database, 2 129 955 were analysed after the data set containing patient data (age, sex and site of fractures) were merged with MFAPs. Data on meteorological factors were obtained from the National Climate Data Center of the Korea Meteorological Administration. Additionally, data on air pollutants (atmospheric particulate matter ≤2.5 µm in diameter (PM2.5), PM10, ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide) were obtained from the Air Korea database.Primary and secondary outcome measures We hypothesised that there would be an association between MFAPs and the incidence of fracture. A generalised additive model was used while factoring in the non-linear relationship between MFAPs and fractures as well as a time lag ≤7 days. Multivariate analysis was performed. Backward elimination with an Akaike information criterion was used to fit the multivariate model.Results Overall, in eight urban areas, 2 129 955 patients with fractures were finally analysed. These included 370 344, 187 370, 173 100, 140 358, 246 775, 6501, 228 346, 57 183 and 719 978 patients with hip, knee, shoulder, elbow, wrist, hand, ankle, foot and spine fractures, respectively. Various MFAPs (average temperature, daily rain, wind speed, daily snow and PM2.5) showed significant association with fractures, with positive correlations at time lags 7, 5–7, 5–7, 3–7 and 6–7 days, respectively.Conclusions Various MFAPs could affect the occurrence of fractures. The average temperature, daily rain, wind speed, daily snow and PM2.5 were most closely associated with fracture. Thus, improved public awareness on these MFAPs is required for clinical prevention and management of fractures.

The dissolved gas concentration in a stirred tank has significant importance in the chemical and biological processing industries as mass transfer from the injected gas to an aqueous solution must occur for the gas to be usable. As the solubility of the gas in the solution is low and there are no probes for measuring dissolved gas concentration, a volumetric mass transfer coefficient is selected as a criterion of design for the scale-up of stirred reactors. However, it is difficult to accurately predict the non-equilibrium state dissolved gas distribution using only the volumetric mass transfer coefficient. In this study, computational fluid dynamics (CFD)-based numerical analysis was conducted to systematically evaluated the effects of mass transport by convective flow on the distribution of dissolved carbon monoxide in a stirred tank. The dissolved carbon monoxide distribution and the volumetric mass transfer coefficient were compared at various rotational speeds of the impellers. At a rotational speed of 900 RPM, the Pearson correlation coefficient was about 0.52, which denotes a moderate correlation. In contrast, Pearson correlation coefficients less than 0.20 were obtained for speeds less than 700 RPM, indicating a weak correlation. By considering the dissolved carbon monoxide transport that occurs during convective flow in stirred tanks, we can provide more accurate information about the dissolved carbon monoxide distribution.

Distinct from conventional energy‐harvesting (EH) technologies, such as the use of photovoltaic, piezoelectric, and thermoelectric effects, betavoltaic energy conversion can consistently generate uniform electric power, independent of environmental variations, and provide a constant output of high DC voltage, even under conditions of ultra‐low‐power EH. It can also dramatically reduce the energy loss incurred in the processes of voltage boosting and regulation. This study realized betavoltaic cells comprised of p‐i‐n junctions based on silicon carbide, fabricated through a customized semiconductor recipe, and a Ni foil plated with a Ni‐63 radioisotope. The betavoltaic energy converter (BEC) includes an array of 16 parallel‐connected betavoltaic cells. Experimental results demonstrate that the series and parallel connections of two BECs result in an open‐circuit voltage Voc of 3.06 V with a short‐circuit current Isc of 48.5 nA, and a Voc of 1.50 V with an Isc of 92.6 nA, respectively. The capacitor charging efficiency in terms of the current generated from the two series‐connected BECs was measured to be approximately 90.7%.

Coenzyme Q10 (CoQ10), also known as ubiquinone, is a fat-soluble antioxidant. Although CoQ10 has not been approved as medication by the Food and Drug Administration, it is widely used in dietary supplements. Some studies have shown that CoQ10 has anti-inflammatory effects on various autoimmune disorders. In this study, we investigated the anti-inflammatory effects of liposome/gold hybrid nanoparticles encoded with CoQ10 (LGNP-CoQ10). Both CoQ10 and LGNP-CoQ10 were administered orally to mice with collagen-induced arthritis (CIA) for 10 weeks. The inflammation pathology of joint tissues of CIA mice was then analyzed using hematoxylin and eosin and Safranin O staining, as well as immunohistochemistry analysis. We obtained immunofluorescence staining images of spleen tissues using confocal microscopy. We found that pro-inflammatory cytokines were significantly decreased in LGNP-CoQ10 injected mice. Th17 cell and phosphorylated STAT3-expressed cell populations were also decreased in LGNP-CoQ10 injected mice. When human peripheral blood mononuclear cells (PBMCs) were treated with CoQ10 and LGNP-CoQ10, the IL-17 expression of PBMCs in the LGNP-CoQ10-treated group was significantly reduced. Together, these results suggest that LGNP-CoQ10 has therapeutic potential for the treatment of rheumatoid arthritis.

Human body communications (HBC) have been studied as an enabling technology to meet the recently increased demands for low-power and high-simplicity in wireless body area networks for wearable-device applications. Previous works on HBC focused mainly on channel modeling with a measurement method, signal transmission scheme, and transceiver implementation. In particular, the digital transmission, invented as a customized approach for the human body channel, has contributed to develope low-complexity HBC systems. This paper addresses on-going research on capacitive coupling HBC based on digital transmission by exploring recent literature.

To extract comprehensive and accurate interface state density ( D _it ) distribution for a low-temperature polysilicon (LTPS) thin film, three well-established methods based on capacitance–voltage ( C – V ) measurements were compared: high–low frequency capacitance, conductance, and quasi-static (QS) capacitance methods. Because of the strong frequency-dependent response of grain boundary traps within the LTPS, C – V measurements are necessary on p- as well as n-type LTPS films, as they provide D _it distribution across the entire LTPS band gap. The QS capacitance method, which uses an optimal high-frequency C – V curve with a minimal grain boundary trap response, provided the best and most comprehensive estimate of D _it distribution across the LTPS band gap, even at room temperature (25 °C). Although the narrow extraction ranges of D _it were extended toward the mid-gap region by increasing the measurement temperature in both high–low frequency capacitance and conductance methods, the responses of the grain boundary traps still overestimated the D _it values near the band edges.

Pavement markings play a critical role in reducing crashes and improving safety on public roads. As road pavements age, maintenance work for safety purposes becomes critical. However, inspecting all pavement markings at the right time is very challenging due to the lack of available human resources. This study was conducted to develop an automated condition analysis framework for pavement markings using machine learning technology. The proposed framework consists of three modules: a data processing module, a pavement marking detection module, and a visibility analysis module. The framework was validated through a case study of pavement markings training data sets in the U.S. It was found that the detection model of the framework was very precise, which means most of the identified pavement markings were correctly classified. In addition, in the proposed framework, visibility was confirmed as an important factor of driver safety and maintenance, and visibility standards for pavement markings were defined.

The number of scan-to-BIM projects that convert scanned data into Building Information Modeling (BIM) for facility management applications in the Mechanical, Electrical and Plumbing (MEP) fields has been increasing. This conversion features an application purpose-oriented process, so the Scan-to-BIM work parameters to be applied vary in each project. Inevitably, a modeler manually adjusts the BIM modeling parameters according to the application purpose, and repeats the Scan-to-BIM process until the desired result is achieved. This repetitive manual process has adverse consequences for project productivity and quality. If the Scan-to-BIM process can be formalized based on predefined rules, the repetitive process in various cases can be automated by re-adjusting only the parameters. In addition, the predefined rule-based Scan-to-BIM pipeline can be stored and reused as a library. This study proposes a rule-based Scan-to-BIM Mapping Pipeline to support application-oriented Scan-to-BIM process automation, variability and reusability. The application target of the proposed pipeline method is the plumbing system that occupies a large number of MEPs. The proposed method was implemented using an automatic generation algorithm, and its effectiveness was verified.

A technology for low-power high data-rate digital capsule endoscopy with human body communication (CEHBC) is presented in this paper. To transfer the image data stably with low power consumption, the proposed system uses three major schemes: Frequency selective digital transmission (FSDT) modulation with HBC, the use of an algorithm to select electrode pairs, and the LineSync algorithm. The FSDT modulation supports high-data rate transmission and prevents the signal attenuation effect. The selection algorithm of the electrode pair finds the best receiving channel. The LineSync algorithm synchronizes the data and compensates for data polarity during the long data transmission section between the capsule endoscope and the receiver. Because all the major functional blocks of the CEHBC transmitter can be implemented as digital logics, they can be easily fabricated using the field programmable gate array (FPGA). Moreover, this CEHBC transmitter can achieve low power-consumption and can support a relatively high data rate in spite of using its clock a few tens of MHz slower. The proposed CEHBC-TXD is the digital portion of the CEHBC transmitter that provides low-power (3.7 mW) and high data-rate (6 Mbps) performance while it supports a high-resolution image (480 × 480 byte) at 3.13 fps.

This paper presents an energy management integrated circuit for multiple energy harvesters in wireless body area network applications. The electrical power acquired from a single energy harvester around a human body is limited to micro watts, which is insufficient to drive a wearable electronic device. To increase this small amount, the energy from a number of harvesters has to be combined. By combining the energy from multiple distributed harvesters, each one producing negligible energy, significant energy for wearable devices can be obtained. In designing an energy management circuit for a wearable device, there are two issues to be resolved. The first is related to the power consumption of the circuit, and the second issue is related to the methods needed to manage the wide range of power that occurs as the energy input changes during harvesting. In this paper, an energy management circuit that resolves the two issues above is described. The circuit was integrated using 0.13 µm Taiwan Semiconductor Manufacturing Company complementary metal-oxide-semiconductor technology. The energy management circuit is designed to combine up to three sources of harvested energy with more than 90% operating efficiency over the entire power range of the energy harvested.

This study introduces the BIM (building information modeling)-GIS (geographic information system) conceptual mapping (B2GM) standard ISO N19166 and proposes a mapping mechanism. In addition, the major issues concerning BIM-GIS integration, and the considerations that it requires, are discussed. The B2GM is currently being standardized by the spatial-information international standardization organization TC211. Previous studies on BIM-GIS integration seem to focus on the integration of different types of model schemas and on the implementation of service interfaces. B2GM concerns the clear definition of the conditions and methods for mapping the object information required from the user’s use-case viewpoint for city-scale mapping. The benefits of the B2GM approach are that the user is able directly control the BIM-GIS linkage and integration process in order to acquire the necessary objection information. This can reveal cases of possibly unclear BIM-GIS integration outside the black box in an explicit and standard way, so that the user can distinctively predict the final output obtainable from the BIM-GIS integration. This study examined B2GM in terms of its development background, components, and several utilization examples, as well as the levels and considerations of the integration of different BIM-GIS models.

Interactions between protein aggregates and a cellular membrane have been strongly implicated in many protein conformational diseases. However, such interactions for the case of Cu/Zn superoxide dismutase (SOD1) protein, which is related to fatal neurodegenerative disorder amyotrophic lateral sclerosis (ALS), have not been explored yet. For the first time, we report the direct observation of defect formation and increased ion permeability of a membrane induced by SOD1 aggregates using a supported lipid bilayer and membrane patches of human embryonic kidney cells as model membranes. We observed that aggregated SOD1 significantly induced the formation of defects within lipid membranes and caused the perturbation of membrane permeability, based on surface plasmon resonance spectroscopy, atomic force microscopy and electrophysiology. In the case of apo SOD1 with an unfolded structure, we found that it bound to the lipid membrane surface and slightly perturbed membrane permeability, compared to other folded proteins (holo SOD1 and bovine serum albumin). The changes in membrane integrity and permeability were found to be strongly dependent on the type of proteins and the amount of aggregates present. We expect that the findings presented herein will advance our understanding of the pathway by which structurally disordered SOD1 aggregates exert toxicity in vivo.