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According to a study by the Insurance Institute for Highway Safety (IIHS), the driving collision rate of using only the reversing camera system is lower than that of using both the reversing camera system and the reversing radar. In this article, we implemented a reversing camera system with artificial intelligence object detection to increase the information of the reversing image. Our system consists of an image processing chip (IPC) with wide-angle image distortion correction and an image buffer controller, a low-power KL520 chip and an optimized artificial intelligence model MobileNetV2-YOLOV3-Optimized (MNYLO). The results of the experiment show the three advantages of our system. Firstly, through the image distortion correction of IPC, we can restore the distorted reversing image. Secondly, by using a public dataset and collected images of various weathers for artificial intelligence model training, our system does not need to use image algorithms that eliminate bad weathers such as rain, fog, and snow to restore polluted images. Objects can still be detected by our system in images contaminated by weather. Thirdly, compared with the AI model Tiny_YOLOV3, not only the parameters of our MNYLO have been reduced by 72.3%, the amount of calculation has been reduced by 86.4%, but the object detection rate has also been maintained and avoided sharp drops.

Laccases that are tolerant to organic solvents are powerful bio-catalysts with broad applications in biotechnology. Most of these uses must be accomplished at high concentration of organic solvents, during which proteins undergo unfolding, thereby losing enzyme activity. Here we show that organic-solvent pre-incubation provides effective and reversible 1.5- to 4.0-fold enhancement of enzyme activity of fungal laccases. Several organic solvents, including acetone, methanol, ethanol, DMSO, and DMF had an enhancement effect among all laccases studied. The enhancement was not substrate-specific and could be observed by using both phenolic and non-phenolic substrates. Laccase preincubated with organic solvents was sensitive to high temperature but remained stable at 25 °C, for an advantage for long-term storage. The acetone-pre-incubated 3-D structure of DLac, a high-efficiency fungal laccase, was determined and confirmed that the DLac protein structure remains intact and stable at a high concentration of organic solvent. Moreover, the turnover rates of fungal laccases were improved after organic-solvent pre-incubation, with DLac showing the highest enhancement among the fungal laccases examined. Our investigation sheds light on improving fungal laccase usage under extreme conditions and extends opportunities for bioremediation, decolorization, and organic synthesis.

Background Lignocellulolytic enzymes are essential for agricultural waste disposal and production of renewable bioenergy. Many commercialized cellulase mixtures have been developed, mostly from saprophytic or endophytic fungal species. The cost of complete cellulose digestion is considerable because a wide range of cellulolytic enzymes is needed. However, most fungi can only produce limited range of highly bioactive cellulolytic enzymes. We aimed to investigate a simple yet specific method for discovering unique enzymes so that fungal species producing a diverse group of cellulolytic enzymes can be identified. Results The culture medium of an endophytic fungus, Daldinia caldariorum D263, contained a complete set of cellulolytic enzymes capable of effectively digesting cellulose residues into glucose. By taking advantage of the unique product inhibition property of β-glucosidases, we have established an improved zymography method that can easily distinguish β-glucosidase and exoglucanase activity. Our zymography method revealed that D263 can secrete a wide range of highly bioactive cellulases. Analyzing the assembled genome of D263, we found over 100 potential genes for cellulolytic enzymes that are distinct from those of the commercially used fungal species Trichoderma reesei and Aspergillus niger. We further identified several of these cellulolytic enzymes by mass spectrometry. Conclusions The genome of Daldinia caldariorum D263 has been sequenced and annotated taking advantage of a simple yet specific zymography method followed by mass spectrometry analysis, and it appears to encode and secrete a wide range of bioactive cellulolytic enzymes. The genome and cellulolytic enzyme secretion of this unique endophytic fungus should be of value for identifying active cellulolytic enzymes that can facilitate conversion of agricultural wastes to fermentable sugars for the industrial production of biofuels.

IntroductionPrimary aldosteronism (PA) is a common form of secondary hypertension that has significant cardiovascular events and increased prevalence of metabolic syndrome and diabetics. Although plasma aldosterone concentration is positively correlated with visceral fat area (VFA) in non-PA individuals, the role of visceral adiposity associated with clinical success after surgery is not known.Research design and methodsWe analyzed patients who underwent adrenalectomy for aldosterone-producing adenoma (APA) at the Taiwan PA Investigator group. VFA was calculated from the abdominal CT scan at APA diagnosis, and all patients received adrenalectomy.ResultsThe study involved 100 consecutive patients with APA (42 males; mean age 49.3 years) matched with 41 essential hypertension (EH) patients. Patients with APA had smaller VFA (p=0.010) than their EH counterparts. Multiple linear regression analysis revealed that the duration of hypertension (p=0.007), but not plasma aldosterone, was negatively correlated with VFA in patients with APA. Logistic regression analysis showed that log VFA (OR=0.065, p<0.001) and duration of hypertension before PA diagnosis (OR=0.919, p=0.011) can predict complete clinical success after adrenalectomy. Multifactor-adjusted generalized additive model demonstrated that log VFA ConclusionsPatients with APA had smaller VFA than their EH counterparts, and VFA increased after adrenalectomy. Clinical complete cure of hypertension after surgery was associated with smaller VFA and shorter duration of hypertension at PA diagnosis, suggesting a potential interplay of visceral adiposity and aldosterone of the patients with APA.

AKI-dialysis patients had a higher incidence of long-term ESRD and mortality than the patients without AKI. The patients who recovered from dialysis were associated with a lower incidence of long-term ESRD and mortality than in the patients who still required dialysis.

This paper presents a memory-efficient motion estimation (ME) technique for high-resolution video compression. The main objective is to reduce the external memory access, especially for limited local memory resource. The reduction of memory access can successfully save the notorious power consumption. The key to reduce the memory accesses is based on center-biased algorithm in that the center-biased algorithm performs the motion vector (MV) searching with the minimum search data. While considering the data reusability, the proposed dual-search-windowing (DSW) approaches use the secondary windowing as an option per searching necessity. By doing so, the loading of search windows can be alleviated and hence reduce the required external memory bandwidth. The proposed techniques can save up to 81% of external memory bandwidth and require only 135 MBytes/sec, while the quality degradation is less than 0.2dB for 720p HDTV clips coded at 8Mbits/sec.

This paper addresses on VLSI design of rank-order filtering (ROF) with a maskable memory for real-time speech and image processing applications. Based on a generic bit-sliced ROF algorithm, the proposed design uses a special-defined memory, called the dual-cell random-access memory (DCRAM), to realize major operations of ROF: threshold decomposition and polarization. Using the memory-oriented architecture, the proposed ROF processor can benefit from high flexibility, low cost and high speed. The DCRAM can perform the bit-sliced read, partial write, and pipelined processing. The bit-sliced read and partial write are driven by maskable registers. With recursive execution of the bit-slicing read and partial write, the DCRAM can effectively realize ROF in terms of cost and speed. The proposed design has been implemented using TSMC [email protected] 1P6M technology. As shown in the result of physical implementation, the core size is [email protected]^2 and the VLSI implementation of ROF can operate at 256MHz for 1.8V supply.

The purpose of pulse analysis system is to provide a platform for researchers to analyze, share, and store patients' pulse data. Researchers can use the system to extract features through Fast Fourier Transform (FFT), harmonics, Ensemble Empirical Mode Decomposition (EEMD), and then take advantage of the former result to gather statistics and classify patients through two-sample t-test or paired-sample t-test. A group of researchers working in National Taiwan University Hospital (NTUH) have done an experiment to examine whether to find out acute kidney injury (AKI) through this system is feasible. The experimental subjects were patients who received open heart surgery. The experiment result shows that after surgery the mean value of harmonic 2 and 3 of patients with postoperative AKI from the proposed pulse analysis system decreased significantly, but not in patients without AKI. This system may have a potential for clinical use to detect AKI after open heart surgery and probably other disease. However, we need more cases to verify this experiment result because the number of AKI patients is limited.

Light regulates growth and developmental processes in plants via global transcriptome adjustment, translational control, and multilayered posttranslational modification of proteins. The transcriptional activation and repression of light-responsive genes has been well documented; however, the impact of posttranscriptional regulation on conveying light signals has been less addressed. Here, we examined whether optimal photomorphogenesis in Arabidopsis thaliana requires the proper biogenesis of small regulatory RNAs that play pivotal roles in the posttranscriptional regulation of gene expression. Arabidopsis carrying a mutation in HUA ENHANCER1 (HEN1), required for stabilization of small regulatory RNAs, showed defects in multiple aspects of photomorphogenic and skotomorphogenic development. HEN1 negatively regulated Arabidopsis photomorphogenesis. Light-activated HEN1 expression depended on the photoreceptors phytochrome A (phyA), phyB, cryptochrome 1 (cry1), and cry2 and key transcriptional regulators ELONGATED HYPOCOTYL5 (HY5) and HY5-HOMOLOG. We also demonstrate the involvement of the small regulatory RNAs miR157d and miR319 in modulating the expression of a positive regulator, HY5, and negative regulators TEOSINTE BRANCHED1, CYCLOIDEA AND PCF family proteins, respectively, for optimal photomorphogenic development in Arabidopsis.

Many prior studies have shown that, in critically ill patients, acute kidney injury (AKI) commonly occurs in association with sepsis and its presence portends an increased likelihood of poor outcomes. In contrast, few studies have focused specifically on the influence of AKI on the long-term risk of developing sepsis. In a previous issue of Critical Care, a population-based cohort study by Lai and colleagues reported a long-term increased risk of severe sepsis for patients surviving beyond 90 days following hospitalization with an episode of AKI requiring renal replacement therapy. While the pathophysiologic mechanisms that underpin this finding remain to be elucidated and causality cannot be proven, this study suggests that severe AKI confers long-term susceptibility to infection and focuses further attention on the critical importance of long-term surveillance for survivors of severe AKI. Further mechanistic and clinical studies are required to more precisely define the extent and duration of any increased risk of severe sepsis beyond which a need for ongoing renal replacement therapy following AKI might be associated. Nonetheless, this novel study by Lai and colleagues could lead to a number of important new avenues for clinical inquiry, such as whether it might be possible to identify those most susceptible to severe sepsis after AKI and, ultimately, whether such episodes might be preventable.

Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn’s Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. There are two classes of GI endoscopy; wired active endoscopy and wireless passive capsule endoscopy. The wired active endoscopy can enable efficient diagnosis based on real images and biopsy samples; however, it causes discomfort for the patients to push flexible, relatively bulky cables into the digestive tube. To relief the patients’ discomfort, wireless passive capsule endoscopes are being developed worldwide (1)-(6).

In the design of capsule endoscope, the trade-offs between battery-life and video-quality is imperative. Typically, the resolution of capsule gastrointestinal (GI) image is limited for the power consumption and bandwidth of RF transmitter. Many fast compression algorithms for reducing computation load; however, they may result in a distortion of the original image, which is not suitable for the use of medical care. This paper presents a novel image compression for capsule gastrointestinal endoscopy, called GICam-II, motivated by the reddish feature of GI image. The reddish feature makes the luminance or sharpness of GI image sensitive to the red component as well as the green component. We focus on a series of mathematical statistics to systematically analyze the color sensitivity in GI images from the RGB color space domain to the two-dimensional discrete-cosine-transform spatial frequency domain. To reduce the compressed image size, GICam-II downsamples the blue component without essential loss of image detail and also subsamples the green component from the Bayer-patterned image. From experimental results, the GICam-II can significantly save the power consumption by 38.5% when compared with previous one and 98.95% when compared with JPEG compression, while the average peak signal-to-noise ratio of luminance (PSNRY) is 40.73 dB.

The block-matching motion estimation has been aggressively developed for years. Many papers have presented fast block-matching algorithms (FBMAs) for the reduction of computation complexity. Nevertheless, their results, in terms of video quality and bitrate, are rather content-varying. Very few FBMAs can result in stationary or quasi-stationary video quality or bitrate for different types of video content. This paper presents a content-motion-aware motion estimation for quality-stationary video coding. By adaptively specifying the subsample ratio, the proposed algorithm can adjust the computational load for acceptable quality loss under the rate control mechanism. As the simulation result, the proposed algorithm can produce stationary quality at the PSNR of 0.36 dB for a given bitrate while saving about 69.6% power consumption.

This paper intends to reduce the power dissipation of the GICam image compressor for capsule endoscope or swallowable imaging capsules while the gastrointestinal images are cardinal. In order to further extend the battery life of capsule endoscope, we firstly attempt to analyze the energy distribution and variation of DC/AC coefficients in 2D-DCT domain for twelve tested GI images. According to the analysis results, we can efficiently take advantages of the subsample technique to reduce the memory requirements of green and blue components and hence propose an improved ultra-low-power subsample-based GICam image compressor, called SGICam, to reduce the power dissipation of compression process. Simulation results have been shown that the SGICam image compressor can significantly save 38.5% power dissipation than GICam image one and the average PSNR is 32.18 dB, while the compression ratio can be as low as 4:1.

Background Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam. Methods We developed an ultra-low-power image compression processor for capsule endoscope or swallowable imaging capsules. In applications of capsule endoscopy, it is imperative to consider battery life/performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much battery power. There are many fast compression algorithms for reducing computation load; however, they may result in distortion of the original image, which is not good for use in the medical care. Thus, this paper will first simplify traditional video compression algorithms and propose a scalable compression architecture. Conclusion As the result, the developed video compressor only costs 31 K gates at 2 frames per second, consumes 14.92 mW, and reduces the video size by 75% at least.