Shared comorbidity of depression, migraine, insomnia, and fibromyalgia in a population-based sample.

BACKGROUND: Depression, migraine, insomnia, and fibromyalgia are reportedly comorbidities. Nevertheless, no study has evaluated the comorbidity of all four of these disorders. This study aimed to investigate the comorbidity of these four disorders. METHODS: Cross-sectional analyses were performed using data of the Circannual Change in Headache and Sleep study, an online nationwide population-based survey. Validated questionnaires were used to diagnose the disorders and measure quality of life. The change of clinical characteristics by addition of any comorbidity was analyzed using the Jonckheere-Terpstra trend test. RESULTS: The prevalence rates of depression, migraine, insomnia, and fibromyalgia were 7.2 %, 5.6 %, 13.3 %, and 5.8 %, respectively. Among the 3030 included participants, 494 (16.3 %), 164 (5.4 %), 40 (1.3 %), and 6 (0.2 %) had one, two, three, and four of these conditions, respectively. The number of headache days per 30 days (Jonckheere-Terpstra trend test, p = 0.011) and migraine-related disability (migraine disability assessment score, p = 0.021) increased with an increase in the number of comorbidities but not with the intensity of headache (visual analog scale, p = 0.225) among participants with migraine. The severity of insomnia (Insomnia Severity Index, p < 0.001) and fibromyalgia (fibromyalgia severity score, p = 0.002) increased with additional comorbidities; however, depression (Patient Health Questionnaire-9, p = 0.384) did not show such an increase. LIMITATIONS: The diagnoses of conditions were based on self-reported questionnaires. CONCLUSIONS: The findings confirmed significant comorbidity between depression, migraine, insomnia, and fibromyalgia. Health professionals should be aware of the probable comorbidity of depression, migraine, insomnia, and fibromyalgia when caring for individuals with any of these four disorders.

A review of utilization of industrial waste materials as cement replacement in pervious concrete: An alternative approach to sustainable pervious concrete production.

Around 8% of the global carbon dioxide emissions, are generated during cement manufacturing, which also involves significant use of raw materials, leading to adverse environmental effects. Consequently, extensive research is being conducted worldwide to explore the feasibility of utilizing different industrial waste by-products as alternatives to cement in concrete production. Fly ash (FA), Metakaolin (MK), Silica fume (SF), and ground granulated blast furnace slag (GGBS) are potential industrial materials that can serve as cement substitutes in pervious concrete. However, there exist conflicting findings in the literature regarding the impact of industrial supplementary cementitious materials (ISCMs) as partial cement replacements on the physical, mechanical, and durability properties of pervious concrete. The aim of this review is to investigate the feasibility and potential benefits of using ISCMs and compare them as partial cement replacements in the production of pervious concrete. The analysis primarily examines the effect of ISCMs as partial cement replacements on cementitious properties, including properties of ISMCs, mechanical properties, and durability of pervious concrete. The influence of ISCMs primarily stems from their pozzolanic reaction and filler characteristics. SF has the highest reactivity due to its high surface area and amorphous structure, resulting in a rapid pozzolanic reaction. GGBS and FA have moderate reactivity, while MK has relatively low reactivity due to its crystalline structure. Results from various studies indicate that the addition of FA, SF, and MK up to approximately 20% leads to a reduction in porosity and permeability while improving compressive strength and durability due to the filler effect of SF and MK. Incorporating GGBS increases permeability slightly while causing a slight decrease in compressive strength. The range of permeability and compressive strength for pervious concrete incorporating FA, SF, GGBS and MK were 0.17-1.46 cm/s and 4-35 MPa, 0.56-2.28 cm/s and 3.1-35 MPa, 0.19-0.64 cm/s and 8-42 MPa, 0.10-1.28 cm/s and 5.5-41 MPa, respectively, which are in the acceptable range for non-structural application of pervious concrete. In conclusion, it is possible to produce sustainable pervious concrete by substituting up to 20% of cement with FA, SF, GGBS, and MK, thereby reducing cement consumption, carbon footprint, energy usage, and air pollution associated with conventional cement production. However, further research is required to systematically assess the durability properties, long-term behavior, and, develop models for analyzing CO2 emissions and cost considerations of pervious concrete containing ISMCs.

Effect of multiple quantum well periods on structural properties and performance of extended short-wavelength infrared LEDs.

We present research on the role of multiple quantum well periods in extended short-wavelength infrared InGaAs/InAsPSb type-I LEDs. The fabricated LEDs consisted of 6, 15, and 30 quantum well periods, and we evaluated the structural properties and device performance through a combination of theoretical simulations and experimental characterization. The strain and energy band offset was precisely controlled by carefully adjusting the composition of the InAsPSb quaternary material, achieving high valence and conduction band offsets of 350 meV and 94 meV, respectively. Our LEDs demonstrated a high degree of relaxation of 94-96 %. Additionally, we discovered that the temperature-dependent dark current characterization attributed to generation-recombination and trap-assign tunneling, with trap-assign tunneling being more dominant at lower current injections. Electroluminescence analysis revealed that the predominant emission mechanism of the LEDs originated from localized exciton and free exciton radiative recombination, which the 30 quantum wells LED exhibited the highest contribution of the localized exciton/free exciton radiative recombination. We observed that increasing the quantum well periods from 6 to 15 led to an increase in the 300 K electroluminescence intensity of the LED. However, extending the quantum well period to 30 resulted in a decline in emission intensity due to the degradation of the epitaxial film quality.

GAILS: an effective multi-object job shop scheduler based on genetic algorithm and iterative local search.

The job shop scheduling problem (JSSP) is critical for building one smart factory regarding resource management, effective production, and intelligent supply. However, it is still very challenging due to the complex production environment. Besides, most current research only focuses on classical JSSP, while flexible JSSP (FJSSP) is more usual. This article proposes an effective method, GAILS, to deal with JSSP and FJSSP based on genetic algorithm (GA) and iterative local search (ILS). GA is used to find the approximate global solution for the JSSP instance. Each instance was encoded into machine and subtask sequences. The corresponding machine and subtasks chromosome could be obtained through serval-time gene selection, crossover, and mutation. Moreover, multi-objects, including makespan, average utilization ratio, and maximum loading, are used to choose the best chromosome to guide ILS to explore the best local path. Therefore, the proposed method has an excellent search capacity and could balance globality and diversity. To verify the proposed method's effectiveness, the authors compared it with some state-of-the-art methods on sixty-six public JSSP and FJSSP instances. The comparative analysis confirmed the proposed method's effectiveness for classical JSSP and FJSSP in makespan, average utilization ratio, and maximum loading. Primarily, it obtains optimal-like solutions for several instances and outperforms others in most instances.

Ecological changes in subtidal macrobenthic communities of the Taean coast following the Hebei Spirit oil spill: A 10-year longitudinal study.

We examined long-term response (2008-2017) of the macrobenthos to the Hebei Spirit oil spill that occurred around the Taean coast, Korea, in December 2007. Oil concentrations were below the Korea/US environmental standards as of January 2008. Organic matter, chlorophyll-a, and zooplankton abundance dominated by Noctiluca scintillans were higher after the spill. Macrobenthic diversity recovered to pre-incident (2007) level in 2011. Biomass exceeded that level in 2011 and the increase prolonged for 5 years. Cross-correlation and regression analyses showed that chlorophyll-a at year t and zooplankton abundance at t-2 had a significant relationship with macrobenthic biomass at t (p < 0.05 for both), suggesting the transfer of increased organic matter (transformed from crude oil within the pelagic ecosystem) into the benthic ecosystem. Coastal wetlands around the incident area, vulnerable to oil pollution and slowly remobilizing accumulated oil, seemed to affect pelagic ecosystem processes and the unexpectedly increased and sustained biomass.

Dataset on the assessment of pervious concrete containing palm oil kernel shell and seashell in heavy metal removal from stormwater.

The dataset currently available comprises data on the removal rates of heavy metals (Ba, Se, Cr, Fe, Cd, As, and Co) through the incorporation of seashells and palm oil kernel shells into pervious concrete for stormwater treatment. Stormwater runoff was collected from commercial areas in Taman University, Skudai, Johor, Malaysia. The stormwater samples underwent filtration and were preserved in high-density polyethylene (HDPE) bottles at a temperature of 4 °C for use as incoming water. The outgoing water, referred to as effluent, was obtained from tests performed on pervious concrete samples after a curing period of 28 days. The pervious concrete mixes were created with a water-to-binder ratio (w/b ratio) of 32% and a sand ratio of 10%. Three different levels of palm oil kernel shell and seashell content were used as coarse aggregate replacements: 0%, 25%, and 50%. Two single-size group were considered for both palm oil kernel shell and seashell: (6.3-9.5 mm) and (4.75-6.3 mm). Heavy metal analyses were conducted on the influent and effluent using a PerkinElmer ELAN 6100 Series Inductively Coupled Plasma- Mass Spectrometer (ICP-MS). The available datasets consist of both raw and analyzed data.

Detection of microplastic traces in four different types of municipal wastewater treatment plants through FT-IR and TED-GC-MS.

Large amounts of microplastics are discharged into wastewater treatment plants (WWTPs), from where some of them are released into natural waterbodies on account of their not being fully eliminated by WWTPs. To investigate the behavior and emission of microplastics from WWTPs, we selected four WWTPs with different treatment technologies, including anaerobic-anoxic-aerobic (A2O), sequence batch reactor (SBR), media, and membrane bioreactor (MBR). The number of microplastics detected using Fourier transform infrared (FT-IR) spectroscopy ranged from 520 to 1820 particles/L in influent and from 0.56 to 2.34 particles/L in effluent. The microplastic removal efficiencies of four WWTPs were over 99%, indicating that the type of treatment technologies did not significantly affect the removal rate of microplastics. In the unit process for each WWTP, the major stages relating to microplastic removal were the secondary clarifier and tertiary treatment processes. Most microplastics detected were categorized as fragments and fibers, while other types were hardly detected. The size of more than 80% of microplastic particles detected in WWTPs ranged between 20 and 300 µm, indicating that they were significantly smaller than the size threshold defined for microplastics. Therefore, we used thermal extraction-desorption coupled with gas chromatography-mass spectroscopy (TED-GC-MS) to evaluate the microplastic mass content in all four WWTPs, and the results were compared with those of the FT-IR analysis. In this method, only four components, namely polyethylene, polypropylene, polystyrene, and polyethylene terephthalate, were analyzed because of the analysis limitation, and the total microplastic concentration represented the sum of four components concentrations. The influent and effluent microplastic concentrations estimated by TED-GC-MS ranged from not detectable to 160 µg/L and 0.04-1.07 µg/L, respectively, indicating a correlation coefficient of 0.861 (p < 0.05) between the TED-GC-MS and FT-IR results, when compared to the combined abundance of the four microplastic components by FT-IR analysis.

Functional Lignin Building Blocks: Reactive Vinyl Esters with Acrylic Acid.

Introducing vinyl groups onto the backbone of technical lignin provides an opportunity to create highly reactive renewable polymers suitable for radical polymerization. In this work, the chemical modification of softwood kraft lignin was pursued with etherification, followed by direct esterification with acrylic acid (AA). In the first step, phenolic hydroxyl and carboxylic acid groups were derivatized into aliphatic hydroxyl groups using ethylene carbonate and an alkaline catalyst. The lignin was subsequently fractionated using a downward precipitation method to recover lignin of defined molar mass and solubility. After recovery, the resulting material was then esterified with AA, resulting in lignin with vinyl functional groups. The first step resulted in approximately 90% of phenolic hydroxyl groups being converted into aliphatic hydroxyls, while the downward fractionation resulted in three samples of lignin with defined molar masses. For the esterification reaction, the weight ratio of reagents, reaction temperature, and reaction time were evaluated as factors that would influence the modification efficacy. 13C NMR spectroscopy analysis of lignin samples before and after esterification showed that the optimized reaction conditions could reach approximately 40% substitution of aliphatic hydroxyl groups. Both steps only used lignin and the modifying reagent (no solvent), with the possibility of recovery and reuse of the reagent by dilution and distillation. An additional second esterification step of the resulting lignin sample with acetic acid or propionic acid converted 90% of remaining hydroxyl groups into short-chain carbon aliphatic esters, making a hydrophobic material suitable for further copolymerization with synthetic hydrophobic monomers.

A deep learning model based on concatenation approach to predict the time to extract a mandibular third molar tooth.

BACKGROUND: Assessing the time required for tooth extraction is the most important factor to consider before surgeries. The purpose of this study was to create a practical predictive model for assessing the time to extract the mandibular third molar tooth using deep learning. The accuracy of the model was evaluated by comparing the extraction time predicted by deep learning with the actual time required for extraction. METHODS: A total of 724 panoramic X-ray images and clinical data were used for artificial intelligence (AI) prediction of extraction time. Clinical data such as age, sex, maximum mouth opening, body weight, height, the time from the start of incision to the start of suture, and surgeon's experience were recorded. Data augmentation and weight balancing were used to improve learning abilities of AI models. Extraction time predicted by the concatenated AI model was compared with the actual extraction time. RESULTS: The final combined model (CNN + MLP) model achieved an R value of 0.8315, an R-squared value of 0.6839, a p-value of less than 0.0001, and a mean absolute error (MAE) of 2.95 min with the test dataset. CONCLUSIONS: Our proposed model for predicting time to extract the mandibular third molar tooth performs well with a high accuracy in clinical practice.

Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing.

Fault diagnosis (FD) plays a vital role in building a smart factory regarding system reliability improvement and cost reduction. Recent deep learning-based methods have been applied for FD and have obtained excellent performance. However, most of them require sufficient historical labeled data to train the model which is difficult and sometimes not available. Moreover, the big size model increases the difficulties for real-time FD. Therefore, this article proposed a domain adaptive and lightweight framework for FD based on a one-dimension convolutional neural network (1D-CNN). Particularly, 1D-CNN is designed with a structure of autoencoder to extract the rich, robust hidden features with less noise from source and target data. The extracted features are processed by correlation alignment (CORAL) to minimize domain shifts. Thus, the proposed method could learn robust and domain-invariance features from raw signals without any historical labeled target domain data for FD. We designed, trained, and tested the proposed method on CRWU bearing data sets. The sufficient comparative analysis confirmed its effectiveness for FD.

One-Pot, One-Step Synthesis of Drug-Loaded Magnetic Multimicelle Aggregates.

Lipid-based formulations provide a nanotechnology platform that is widely used in a variety of biomedical applications because it has several advantageous properties including biocompatibility, reduced toxicity, relative ease of surface modifications, and the possibility for efficient loading of drugs, biologics, and nanoparticles. A combination of lipid-based formulations with magnetic nanoparticles such as iron oxide was shown to be highly advantageous in a growing number of applications including magnet-mediated drug delivery and image-guided therapy. Currently, lipid-based formulations are prepared by multistep protocols. Simplification of the current multistep procedures can lead to a number of important technological advantages including significantly decreased processing time, higher reaction yield, better product reproducibility, and improved quality. Here, we introduce a one-pot, single-step synthesis of drug-loaded magnetic multimicelle aggregates (MaMAs), which is based on controlled flow infusion of an iron oxide nanoparticle/lipid mixture into an aqueous drug solution under ultrasonication. Furthermore, we prepared molecular-targeted MaMAs by directional antibody conjugation through an Fc moiety using Cu-free click chemistry. Fluorescence imaging and quantification confirmed that antibody-conjugated MaMAs showed high cell-specific targeting that was enhanced by magnetic delivery.

Sprayable nanomicelle hydrogels and inflammatory bowel disease patient cell chips for development of intestinal lesion-specific therapy.

All-in-one treatments represent a paradigm shift in future medicine. For example, inflammatory bowel disease (IBD) is mainly diagnosed by endoscopy, which could be applied for not only on-site monitoring but also the intestinal lesion-targeted spray of injectable hydrogels. Furthermore, molecular conjugation to the hydrogels would program both lesion-specific adhesion and drug-free therapy. This study validated this concept of all-in-one treatment by first utilizing a well-known injectable hydrogel that underwent efficient solution-to-gel transition and nanomicelle formation as a translatable component. These properties enabled spraying of the hydrogel onto the intestinal walls during endoscopy. Next, peptide conjugation to the hydrogel guided endoscopic monitoring of IBD progress upon adhesive gelation with subsequent moisturization of inflammatory lesions, specifically by nanomicelles. The peptide was designed to mimic the major component that mediates intestinal interaction with Bacillus subtilis flagellin during IBD initiation. Hence, the peptide-guided efficient adhesion of the hydrogel nanomicelles onto Toll-like receptor 5 (TLR5) as the main target of flagellin binding and Notch-1. The peptide binding potently suppressed inflammatory signaling without drug loading, where TLR5 and Notch-1 operated collaboratively through downstream actions of tumor necrosis factor-alpha. The results were produced using a human colorectal cell line, clinical IBD patient cells, gut-on-a-chip, a mouse IBD model, and pig experiments to validate the translational utility.

Catalytic conversion of waste corrugated cardboard into lactic acid using lanthanide triflates.

The efficient strategy for waste conversion and resource recovery is of great interest in the sustainable bioeconomy context. This work reports on the catalytic upcycling of waste corrugated cardboard (WCC) into lactic acid using lanthanide triflates catalysts. WCC, a primary contributor to municipal solid wastes, has been viewed as a feedstock for producing a wide range of renewable products. Hydrothermal conversion of WCC was carried out in the presence of several lanthanide triflates. The reaction with erbium(III) triflate (Er(OTf)3) and ytterbium(III) triflate (Yb(OTf)3) resulted in high lactic acid yields, 65.5 and 64.3 mol%, respectively. In addition, various monomeric phenols were readily obtained as a co-product stream, opening up opportunities in waste management and resource recovery. Finally, technoeconomic analysis was conducted based on the experimental results, which suggests a significant economic benefit of chemocatalytic upcycling of WCC into lactic acid.

The use of steam pretreatment to enhance pellet durability and the enzyme-mediated hydrolysis of pellets to fermentable sugars.

Although densified wood pellets are an attractive biomass feedstock for bioenergy and biofuels production, partly due to their ease of transport, their friability and hygroscopic nature (attraction of moisture) have proven problematic in terms of storage and handling. Pre-steaming the biomass was shown to reduce the need for size reduction, significantly increasing pellet durability by relocating the plant cell wall lignin to the fibre surface and consequently enhancing binding between particles. Although steam pretreatment has been shown to facilitate enzyme-mediated hydrolysis of biomass, by increasing cellulose accessibility, drying and pelletization partially impeded enzymatic hydrolysis. However, the incorporation of alkaline deacetylation or neutral sulfonation step prior to pre-steaming was shown to mitigate many of the negative effects of drying. Although drying and pelletization did not significantly impact the redistribution of lignin, a mild mechanical refining step was shown to further enhance the hydrolysis of the cellulose component of the pelletized biomass.

Disability and Economic Loss Caused by Headache among Information Technology Workers in Korea.

BACKGROUND AND PURPOSE: Headache disorders are a leading cause of disability globally. However, there is inadequate information available about these disorders and the related economic loss in the workplace in Asian countries. Information technology (IT) jobs are intellectually and cognitively challenging, and hence IT workers are a suitable population for assessing headache disorders and related economic loss. METHODS: We sent invitation emails to all employees of selected IT companies. A comprehensive Web-based questionnaire regarding headache characteristics, disability, quality of life, and economic loss was completed by 522 participants from 8 companies. RESULTS: The participants included 450 (86.2%) who had experienced headache more than once during the previous year. The frequencies of migraine, probable migraine (PM), and tension-type headache (TTH) were 18.2%, 21.1%, and 37.0%, respectively. The Migraine Disability Assessment score was higher for participants with migraine [median and interquartile range, 3.0 (0.0-6.0)] than for those with PM [0.0 (0.0-2.0), p<0.001] and TTH [0.0 (0.0-1.0), p<0.001]. The estimated annual economic losses caused by migraine per person associated with absenteeism and presenteeism were USD 197.5±686.1 and USD 837.7±22.04 (mean±standard deviation), respectively. The total annual economic loss per person caused by migraine (USD 1,023.3±1,972.7) was higher than those caused by PM (USD 424.8±1,209.1, p<0.001) and TTH (USD 197.6±636.4, p<0.001). CONCLUSIONS: Migraine, PM, and TTH were found to be prevalent among IT workers in Korea. Disability and economic loss were significantly greater in participants with migraine than in those with PM or TTH.

Clinically translatable quantitative molecular photoacoustic imaging with liposome-encapsulated ICG J-aggregates.

Photoacoustic (PA) imaging is a functional and molecular imaging technique capable of high sensitivity and spatiotemporal resolution at depth. Widespread use of PA imaging, however, is limited by currently available contrast agents, which either lack PA-signal-generation ability for deep imaging or their absorbance spectra overlap with hemoglobin, reducing sensitivity. Here we report on a PA contrast agent based on targeted liposomes loaded with J-aggregated indocyanine green (ICG) dye (i.e., PAtrace) that we synthesized, bioconjugated, and characterized to addresses these limitations. We then validated PAtrace in phantom, in vitro, and in vivo PA imaging environments for both spectral unmixing accuracy and targeting efficacy in a folate receptor alpha-positive ovarian cancer model. These study results show that PAtrace concurrently provides significantly improved contrast-agent quantification/sensitivity and SO2 estimation accuracy compared to monomeric ICG. PAtrace's performance attributes and composition of FDA-approved components make it a promising agent for future clinical molecular PA imaging.

Engineered biochars from catalytic microwave pyrolysis for reducing heavy metals phytotoxicity and increasing plant growth.

Pb, Ni, and Co are among the most toxic heavy metals that pose direct risks to humans and biota. There are no published studies on biochars produced at low temperatures (i.e., 300 °C), which possess high sorption capacity for heavy metal remediation and reclamation of contaminated sandy soils. This research studied the effect of catalytic microwave pyrolysis of switchgrass (SG) using bentonite and K3PO4 to produce biochar at low temperature (300 °C) with high sorption capacity for reducing the phytotoxicity of heavy metals, and investigated the synergistic effects of catalyst mixture on biochar sorption capacity. The quality of the biochars was examined in terms of their impacts on plant growth, reducing phytotoxicity and uptake of heavy metals in sandy soil spiked with Pb, Ni, and Co. All catalysts increased the micropore surface area and cation-exchange capacity of biochars, and resulted in biochars rich in plant nutrients, which not only decreased heavy metal phytotoxicity, but also boosted plant growth in the spiked soil by up to 140% compared to the sample without biochar. By mixing bentonite and K3PO4 with SG during microwave pyrolysis, the efficacy of biochar in reducing phytotoxicity and heavy metals uptake was further enhanced because of the highest micropore surface area (402 m2/g), moderate contents of Ca, Mg, K, and Fe for ion-exchange and moderate concentration of phosphorus for the formation of insoluble heavy metal compounds. Generally, the biochar created at 300 °C (300-30KP) showed similar performance to the biochar created at 400 °C (400-30KP) in terms of reducing heavy metal bioavailability.

Dilation-Responsive Microshape Programing Prevents Vascular Graft Stenosis.

Shape memory materials have been successfully applied to minimally invasive implantation of medical devices. However, organ-movement-specific shape programing at a microscale level has never been demonstrated despite significant unmet needs. As vein-to-artery grafting induces vein dilation and stenosis, a polymeric self-enclosable external support (SES) is designed to wrap the vascular out-wall. Its micropores are programmed to increase sizes and interconnections upon dilation. Vessel dilation promotes venous maturation, but overdilation induces stenosis by disturbed blood flow. Therefore, the unique elastic shape-fixity of SES provides a foundation to enable a stable microscale shape transition by maintaining the vein dilation. The shape transition of micropore architecture upon dilation induces beneficial inflammation, thereby regenerating vasa vasorum and directing smooth muscle cell migration toward adventitia with the consequent muscle reinforcement of veins. This game-changer approach prevents the stenosis of vein-to-artery grafting by rescuing ischemic disorders and promoting arterial properties of veins.

Color three-dimensional imaging based on patterned illumination using a negative pinhole array.

Reflectance confocal microscopy is widely used for non-destructive optical three-dimensional (3D) imaging. In confocal microscopy, a stack of sequential two-dimensional (2D) images with respect to the axial position is typically needed to reconstruct a 3D image. As a result, in conventional confocal microscopy, acquisition speed is often limited by the rate of mechanical scanning in both the transverse and axial directions. We previously reported a high-speed parallel confocal detection method using a pinhole array for color 3D imaging without any mechanical scanners. Here, we report a high-speed color 3D imaging method based on patterned illumination employing a negative pinhole array, whose optical characteristics are the reverse of the conventional pinhole array for transmitting light. The negative pinhole array solves the inherent limitation of a conventional pinhole array, i.e., low transmittance, meaning brighter color images with abundant color information can be acquired. We also propose a 3D image processing algorithm based on the 2D cross-correlation between the acquired image and filtering masks, to produce an axial response. By using four-different filtering masks, we were able to increase the sampling points in calculation of height and enhance the lateral resolution of the color acquisition by a factor of four. The feasibility of high-speed non-contact color 3D measurement with the improved lateral resolution and brightness provided by the negative pinhole array was demonstrated by imaging various specimens. We anticipate that this high-speed color 3D measurement technology with negative pinhole array will be a useful tool in a variety of fields where rapid and accurate non-contact measurement are required, such as industrial inspection and dental scanning.

Stroke and systemic embolism in patients with atrial fibrillation and heart failure according to heart failure type.

AIMS: This study aimed to elucidate the risk for stroke and systemic embolism (SE) in patients with atrial fibrillation and heart failure (HF) according to HF type. METHODS AND RESULTS: A total of 10 780 patients with atrial fibrillation were enrolled in a multicentre prospective registry and divided according to HF type: no-HF, HF with preserved ejection fraction (EF) (HFpEF), HF with mid-range EF (HFmrEF), and HF with reduced EF (HFrEF). Each group included 237 age-matched and sex-matched patients (age, 69.0 ± 10.3 years; men, 69.6%). The baseline characteristics, cumulative incidence, and hazard ratios for stroke/SE and major bleeding were compared across the groups. Patients with HF accounted for 10.3% of the total population; HFpEF, HFmrEF, and HFrEF represented 43.7%, 23.6%, and 32.7% of the patients with HF, respectively. The CHA2 DS2 -VASc score was significantly higher in the HFpEF, HFmrEF, and HFrEF groups than in the no-HF group. The annual stroke/SE incidence rates were 2.8%, 0.7%, 1.1%, and 0.9% in the HFpEF, HFmrEF, HFrEF, and no-HF groups, respectively. The cumulative incidence of stroke/SE was significantly highest in the HFpEF group at 22.8 ± 10.0 months (P = 0.020). The stroke/SE risk was higher in the HFpEF group than in the HFmrEF and HFrEF groups (hazard ratio, 3.192; 95% confidence interval, 1.039-9.810; P = 0.043). E/e' value was an independent risk factor for stroke/SE. There were no significant differences in the incidence of major bleeding across the groups. CONCLUSIONS: The stroke/SE risk was the highest in the HFpEF group and comparable between the HFmrEF and HFrEF groups.