Broadband lens and graphene/silicon photodiode for wide spectral imaging.

We designed a broadband lens along with a graphene/silicon photodiode for wide spectral imaging ranging from ultraviolet to near-infrared wavelengths. By using five spherical glass lenses, the broadband lens, with the modulation transfer function of 0.38 at 100 lp/mm, corrects aberrations ranging from 340 to 1700 nm. Our design also includes a broadband graphene/silicon Schottky photodiode with the highest responsivity of 0.63 A/W ranging from ultraviolet to near-infrared. By using the proposed broadband lens and the broadband graphene/silicon photodiode, several single-pixel imaging designs in ultraviolet, visible, and near-infrared wavelengths are demonstrated. Experimental results show the advantages of integrating the lens with the photodiode and the potential to realize broadband imaging with a single set of lens and a detector.

Revealing an association between HPV and systemic lupus erythematosus: A bidirectional two-sample Mendelian randomization study.

BACKGROUND: An increasing number of studies have focused on the association between Human papillomavirus (HPV) infection and systemic lupus erythematosus (SLE). However, current evidence is largely based on retrospective studies, which are susceptible to confounding factors and cannot establish causation. METHODS: A bidirectional two-sample Mendelian randomization (MR) design was used to evaluate the causal relationship between HPV and SLE. Mononucleoside polymers (SNPS) with strong evidence for genome-wide association studies (GWAS) were selected from the HPV exposure dataset and used as an instrumental variable (IV) for this study. For the MR Analysis results, the MR-Egger intercept P test, MR-Presso global test, CochranQ test and leave-one test were used for sensitivity analysis. RESULTS: Based on the evidence of MR Analysis, this study finally determined that there was no causal association between HPV16 and HPV18 and SLE. CONCLUSIONS: Possible regulation of HPV infection is not significantly associated with regulation of SLE. These findings provide new insights into the underlying mechanisms of HPV and SLE and need to be validated by further studies.

Robustness improvement for cyber physical system based on an optimization model of interdependent constraints.

With the rapid development of information technology, traditional infrastructure networks have evolved into cyber physical systems (CPSs). However, this evolution has brought along with it cyber failures, in addition to physical failures, which can affect the safe and stable operation of the whole system. In light of this, in this paper, we propose an interdependence-constrained optimization model to improve the robustness of the cyber physical system. The proposed model includes not only the realistic physical law but also the interdependence between the physical network and the cyber network. However, this model is highly nonlinear and cannot be solved directly. Therefore, we transform the model into a bi-level mixed integer linear programming problem, which can be easily and effectively solved in polynomial time. We conduct the simulation based on standard Institute of Electrical and Electronics Engineers test cases and study the impact of the disaster level and coupling strength on the robustness of the whole system. The simulation results show that our proposed model can effectively improve the robustness of the cyber physical system. Moreover, we compare the performance of the power supply in different CPSs, which have different network structures of the cyber network. Our work can provide useful instructions for system operators to improve the robustness of CPSs after extreme events happen in them.

Wavefront reconstruction based on deep transfer learning for microscopy.

The application of machine learning in wavefront reconstruction has brought great benefits to real-time, non-invasive, deep tissue imaging in biomedical research. However, due to the diversity and heterogeneity of biological tissues, it is difficult to train the dataset with a unified model. In general, the utilization of some unified models will result in the specific sample falling outside the training set, leading to low accuracy of the machine learning model in some real applications. This paper proposes a sensorless wavefront reconstruction method based on transfer learning to overcome the domain shift introduced by the difference between the training set and the target test set. We build a weights-sharing two-stream convolutional neural network (CNN) framework for the prediction of Zernike coefficient, in which a large number of labeled randomly generated samples serve as the source-domain data and the unlabeled specific samples serve as the target-domain data at the same time. By training on massive labeled simulated data with domain adaptation to unlabeled target-domain data, the network shows better performance on the target tissue samples. Experimental results show that the accuracy of the proposed method is 18.5% higher than that of conventional CNN-based method and the peak intensities of the point spread function (PSF) are more than 20% higher with almost the same training time and processing time. The better compensation performance on target sample could have more advantages when handling complex aberrations, especially the aberrations caused by various histological characteristics, such as refractive index inhomogeneity and biological motion in biological tissues.

An asymmetric interdependent networks model for cyber-physical systems.

Cyber-physical systems (CPSs) are integrations of information technology and physical systems, which are more and more significant in society. As a typical example of CPSs, smart grids integrate many advanced devices and information technologies to form a safer and more efficient power system. However, interconnection with the cyber network makes the system more complex, so that the robustness assessment of CPSs becomes more difficult. This paper proposes a new CPS model from a complex network perspective. We try to consider the real dynamics of cyber and physical parts and the asymmetric interdependency between them. Simulation results show that coupling with the communication network makes better robustness of power system. But since the influences between the power and communication networks are asymmetric, the system parameters play an important role to determine the robustness of the whole system.

Lighting Deviation Correction for Integrating-Sphere Multispectral Imaging Systems.

In an integrating sphere multispectral imaging system, measurement inconsistency can arise when acquiring the spectral reflectances of samples. This is because the lighting condition can be changed by the measured samples, due to the multiple light reflections inside the integrating sphere. Besides, owing to non-uniform light transmission of the lens and narrow-band filters, the measured reflectance is spatially dependent. To deal with these problems, we propose a correction method that consists of two stages. The first stage employs a white board to correct non-uniformity and a small white patch to correct lighting deviation, both under the assumption of ideal Lambertian reflection. The second stage uses a polynomial regression model to further remove the lighting inconsistency when measuring non-Lambertian samples. The method is evaluated on image data acquired in a real multispectral imaging system. Experimental results illustrate that our method eliminates the measurement inconsistency considerably. This consequently improves the spectral and colorimetric accuracy in color measurement, which is crucial to practical applications.

Machine learning guided rapid focusing with sensor-less aberration corrections.

Non-invasive, real-time imaging and deep focus into tissue are in high demand in biomedical research. However, the aberration that is introduced by the refractive index inhomogeneity of biological tissue hinders the way forward. A rapid focusing with sensor-less aberration corrections, based on machine learning, is demonstrated in this paper. The proposed method applies the Convolutional Neural Network (CNN), which can rapidly calculate the low-order aberrations from the point spread function images with Zernike modes after training. The results show that approximately 90 percent correction accuracy can be achieved. The average mean square error of each Zernike coefficient in 200 repetitions is 0.06. Furthermore, the aberration induced by 1-mm-thick phantom samples and 300-µm-thick mouse brain slices can be efficiently compensated through loading a compensation phase on an adaptive element placed at the back-pupil plane. The phase reconstruction requires less than 0.2 s. Therefore, this method offers great potential for in vivo real-time imaging in biological science.

Bidirectional texture function image super-resolution using singular value decomposition.

The bidirectional texture function (BTF) is widely employed to achieve realistic digital reproduction of real-world material appearance. In practice, a BTF measurement device usually does not use high-resolution (HR) cameras in data collection, considering the high equipment cost and huge data space required. The limited image resolution consequently leads to the loss of texture details in BTF data. This paper proposes a fast BTF image super-resolution (SR) algorithm to deal with this issue. The algorithm uses singular value decomposition (SVD) to separate the collected low-resolution (LR) BTF data into intrinsic textures and eigen-apparent bidirectional reflectance distribution functions (eigen-ABRDFs) and then improves the resolution of the intrinsic textures via image SR. The HR BTFs can be finally obtained by fusing the reconstructed HR intrinsic textures with the LR eigen-ABRDFs. Experimental results show that the proposed algorithm outperforms the state-of-the-art single-image SR algorithms in terms of reconstruction accuracy. In addition, thanks to the employment of SVD, the proposed algorithm is computationally efficient and robust to noise corruption.

Hypoxia-Induced MicroRNA-429 Promotes Differentiation of MC3T3-E1 Osteoblastic Cells by Mediating ZFPM2 Expression.

BACKGROUND/AIMS: Hypoxia has been reported to regulate osteoblastic differentiation of bone cells and cartilage development. However, information concerning the molecular mechanisms remains largely unknown. METHODS: The expression of miR-429 was evaluated by quantitative real-time PCR analysis. To test whether miR-429 directly regulate the expression level of ZFPM2 at transcription level, dual-luciferase reporter gene assay was performed. Western blotting was performed to detect osteogenesis related protein expression. The cell proliferation, apoptosis, alkaline phosphatase activity and matrix mineralization were performed to assess the functions of miR-429 in vitro and in vivo the effects of miR-429 on fracture healing. RESULTS: Expression of miR-429 was increased in MC3T3-E1 cells treated with 200 µM CoCl2 by qRT-PCR, and overexpression of miR-429 promoted cell differentiation, and enhanced alkaline phosphatase activity and matrix mineralization. Luciferase reporter assays suggested that miR-429 directly targets the 3'UTR of ZFPM2. In addition, knockdown of ZFPM2 could phenocopy the effects of miR-429 expression. Furthermore, overexpression of ZFPM2 in miR-429-expressing MC3T3-E1 cells suppressed cell differentiation. CONCLUSIONS: Our results provide valuable insight into the potential role of hypoxia in regulation of osteoblastic cell differentiation.

Spectral bidirectional texture function reconstruction by fusing multiple-color and spectral images.

Spectral bidirectional texture function (BTF) is essential for accurate reproduction of material appearance due to its nature of conveying both spatial and spectral information. A practical issue is that the acquisition of raw spectral BTFs is time-consuming. To resolve the limitation, this paper proposes a novel framework for efficient spectral BTF acquisition and reconstruction. The framework acquires red-green-blue (RGB) BTF images and just one spectral image. The full spectral BTFs are reconstructed by fusing the RGB and spectral images based on nonnegative matrix factorization (NMF). Experimental results indicate that the accuracy of spectral reflectance reconstruction is higher than that of existing algorithms. With the reconstructed spectral BTFs, the material appearance can be reproduced with high fidelity under various illumination conditions.

Design, synthesis and antithrombotic evaluation of novel dabigatran etexilate analogs, a new series of non-peptides thrombin inhibitors.

Thrombin is a serine protease that plays a key role in blood clotting, which makes it a promising target for the treatment of thrombotic diseases. Dabigatran is direct potent thrombin inhibitor. Based on bioisosteric and scaffold hopping principle, two dabigatran mimics (I-1 and II-1) in which the benzamidine moiety of dabigatran was replaced by a tricyclic fused scaffold were designed, synthesized and evaluated for their in vitro activities for inhibiting thrombin. The results reveal that compounds I-1 (IC50=9.20nM) and II-1 (IC50=7.48nM) are potent direct thrombin inhibitors and the activity is in the range of reference drug. On this basis, twenty-two ester and carbamate derivatives of I-1 or II-1 were prepared and evaluated for their anticoagulant activity. Prodrugs I-4a (IC50=0.73µM), I-4b (IC50=0.75µM), II-2a (IC50=1.44µM) and II-2b (IC50=0.91µM) display excellent effects of inhibiting thrombin induced-platelet aggregation. Moreover, compounds I-9 and II-4, which contain a cleavable moiety with anti-platelet activity, show the best anticoagulant efficacy among the tested compounds in the rat venous thrombosis model. The compounds which have better in vitro and in vivo activity were subjected to rat tail bleeding test, and the result demonstrates that compound I-9 is less likely to have bleeding risk than dabigatran etexilate.

Empirical model for matching spectrophotometric reflectance of yarn windings and multispectral imaging reflectance of single strands of yarns.

The state-of-the-art multispectral imaging system can directly acquire the reflectance of a single strand of yarn that is impossible for traditional spectrophotometers. Instead, the spectrophotometric reflectance of a yarn winding, which is constituted by yarns wound on a background card, is regarded as the yarn reflectance in textile. While multispectral imaging systems and spectrophotometers can be separately used to acquire the reflectance of a single strand of yarn and corresponding yarn winding, the quantitative relationship between them is not yet known. In this paper, the relationship is established based on models that describe the spectral response of a spectrophotometer to a yarn winding and that of a multispectral imaging system to a single strand of yarn. The reflectance matching function from a single strand of yarn to corresponding yarn winding is derived to be a second degree polynomial function, which coefficients are the solutions of a constrained nonlinear optimization problem. Experiments on 100 pairs of samples show that the proposed approach can reduce the color difference between yarn windings and single strands of yarns from 2.449 to 1.082 CIEDE2000 units. The coefficients of the optimal reflection matching function imply that the reflectance of a yarn winding measured by a spectrophotometer consists of not only the intrinsic reflectance of yarn but also the nonignorable interreflection component between yarns.

Immediate reduction under general anesthesia and single-staged anteroposterior spinal reconstruction for fracture-dislocation of lower cervical spine.

Fracture-dislocation of the lower cervical spine is a severe traumatic lesion, most frequently resulting in tetraplegia. Treatment is usually painful and time consuming. This retrospective study evaluated the clinical curative effect of immediate reduction under general anesthesia and single-staged anteroposterior spinal reconstruction for fracture-dislocation of the lower cervical spine. Twelve cases of traumatic lower cervical spinal fracture-dislocation were retrospectively analyzed from January 2006 to December 2011. The injury level was C4/C5 in 4, C5/C6 in 5, and C6/C7 in 3 patients. The spinal cord function grades according to the American Spinal Injury Association impairment scale (2000 edition amended) before operation were as follows: grade A in 2 cases, grade B in 2 cases, grade C in 5 cases, grade D in 2 cases, and grade E in 1 case. On admission, all patients underwent immediate reduction under general anesthesia and single-staged anteroposterior spinal reconstruction by circumferential fixation/fusion. The spinal cord function grades according to American Spinal Injury Association after operation were as follows: grade A in 1 case, grade B in 1 case, grade C in 3 cases, grade D in 3 cases, and grade E in 4 cases. All 12 patients showed evidence of stability at the instrumented level on the final follow-up examination (mean follow-up, 3.7 y). Immediate reduction under general anesthesia followed by a single-stage combined anteroposterior spinal reconstruction is a safe and reliable way of treating patients with lower cervical spine fracture-dislocations.

[Comparison of single versus and multi-level vertebral compression fractures in elders].

OBJECTIVE: To compare the characteristics, causes and relationship to osteoporosis between single and multi-level vertebral compression fractures in elders. METHODS: A total of 126 subjects (147 vertebrae) with acute back pain between September 2010 and December 2012 were diagnosed as vertebral fracture through magnetic resonance imaging. And single and multi-level vertebral compression fractures were evaluated on the basis of age, gender, bone mineral density (BMD), level of affected vertebrae and cause of injury. RESULTS: The subjects with multi-level vertebral fractures were much older and there were more females. Among 39 multi-level fractures, the sites were thoracolumbar junction (n=18, 46.2%) and lumbar (n=11, 28.2%). The causes were metastatic carcinoma (n=9, 23.1%) and mild trauma (n=30, 76.9%). And 16 (41.1%) subjects were of mixed type. The mean BMD, as measured by dual-emission X-ray absorptiometry, was 0.51 and 0.68 g/cm3 for multi and single-level vertebral fractures respectively. In subjects with single-level vertebral fracture, 43 (49.4%) had vertebral fractures in thoracolumbar junction and 26 (29.9%) in lumbar vertebrae. The causes were metastatic carcinoma (n=2, 2.1%) and high-energy trauma (n=73, 83.7%). And 30 (34.5%) subjects suffered wedge compression fractures. CONCLUSION: The patients with multi-level vertebral fracture are often older females with a lower BMD, a mixed type and vertebral metastatic carcinoma. And their causes are mild outer forces. Yet those with single-level vertebral fracture result from high-energy trauma and belong to the compression type.

Channel selection for multispectral color imaging using binary differential evolution.

In multispectral color imaging, there is a demand to select a reduced number of optimal imaging channels to simultaneously speed up the image acquisition process and keep reflectance reconstruction accuracy. In this paper, the channel selection problem is cast as the binary optimization problem, and is consequently solved using a novel binary differential evolution (DE) algorithm. In the proposed algorithm, we define the mutation operation using a differential table of swapping pairs, and deduce the trial solutions using neighboring self-crossover. In this manner, the binary DE algorithm can well adapt to the channel selection problem. The proposed algorithm is evaluated on the multispectral color imaging system on both synthetic and real data sets. It is verified that high color accuracy is achievable by only using a reduced number of channels using the proposed method. In addition, as binary DE is a global optimization algorithm in nature, it performs better than the traditional sequential channel selection algorithm.

TFDet: Target-Aware Fusion for RGB-T Pedestrian Detection.

Pedestrian detection plays a critical role in computer vision as it contributes to ensuring traffic safety. Existing methods that rely solely on RGB images suffer from performance degradation under low-light conditions due to the lack of useful information. To address this issue, recent multispectral detection approaches have combined thermal images to provide complementary information and have obtained enhanced performances. Nevertheless, few approaches focus on the negative effects of false positives (FPs) caused by noisy fused feature maps. Different from them, we comprehensively analyze the impacts of FPs on detection performance and find that enhancing feature contrast can significantly reduce these FPs. In this article, we propose a novel target-aware fusion strategy for multispectral pedestrian detection, named TFDet. The target-aware fusion strategy employs a fusion-refinement paradigm. In the fusion phase, we reveal the parallel-and cross-channel similarities in RGB and thermal features and learn an adaptive receptive field to collect useful information from both features. In the refinement phase, we use a segmentation branch to discriminate the pedestrian features from the background features. We propose a correlation-maximum loss function to enhance the contrast between the pedestrian features and background features. As a result, our fusion strategy highlights pedestrian-related features and suppresses unrelated ones, generating more discriminative fused features. TFDet achieves state-of-the-art performance on two multispectral pedestrian benchmarks, KAIST and LLVIP, with absolute gains of 0.65% and 4.1% over the previous best approaches, respectively. TFDet can easily extend to multiclass object detection scenarios. It outperforms the previous best approaches on two multispectral object detection benchmarks, FLIR and M3FD, with absolute gains of 2.2% and 1.9%, respectively. Importantly, TFDet has comparable inference efficiency to the previous approaches and has remarkably good detection performance even under low-light conditions, which is a significant advancement for ensuring road safety. The code will be made publicly available at https://github.com/XueZ-phd/TFDet.git.

Real-time highlight removal using intensity ratio.

In this paper, we propose an efficient method to separate the diffuse and specular reflection components from a single image. The method is built on the observation that, for diffuse pixels, the intensity ratios between the maximum values and range values (maximums minus minimums) are independent of surface geometry. The specular fractions of the image pixels can then be computed by using the intensity ratio. For textured surfaces, image pixels are classified into clusters by constructing a pseudo-chromaticity space, and the intensity ratio of each cluster is robustly estimated. Unlike existing techniques, the proposed method works in a pixel-wise manner, without specular pixel identification and any local interaction. Experimental results show that the proposed method runs 4× faster than the state of the art and produces improved accuracy in specular highlight removal.

[Risk factors for delirium of elderly patients undergoing hip fracture operation].

OBJECTIVE: To explore the causes for delirium of elderly patients after hip fracture operation. METHODS: A total of 68 cases of delirium were selected from 458 patients aged over 65 years undergoing hip fracture operation via spinal anesthesia from 2009 to 2011. There were 26 males and 42 females with an average age of 72.9 (66-98) years. Their clinical features, such as gender, operative duration, blood loss volume, saturation of arterial oxygen, were observed. After single factor risk analysis, multiple factor analysis was performed by binary Logistic regression. RESULTS: Delirium occurred at certain timepoints during the first postoperative days. The incidence of delirium was 14.9%. The Logistic stepwise regression analysis showed that significant differences existed between delirium and non-delirium in age (P = 0.042), operative duration (P = 0.042), blood loss volume (P = 0.027), hypoxemia (P = 0.019) and preoperative comorbidity (P = 0.029). CONCLUSION: The independent risk factors for postoperative delirium include age, operative duration, blood loss volume, preoperative comorbidity and hypoxemia.

Keloids After Herpes Zoster: Report of Wolf's Isotopic Phenomenon and Literature Review.

Wolf's isotopic response (WIR) refers to the appearance of a new skin disorder at the exact site of an unrelated skin disorder that had previously been cured. The most common primary skin disease in which WIR occurs is herpes zoster. Despite numerous theories being put forward to explain this occurrence, including viral, vascular, immunological, and neurological hypotheses, the pathogenesis of WIR after herpes zoster remains unclear. We report the case of a 76-year-old patient who presented with keloids at the site of the original herpes zoster. Based on this observation and a review of the literature, The clinical characteristics and possible theoretical reasons for keloids after herpes zoster will be discussed.

Successful Treatment of Multiple Plantar and Periungual Warts by Local Hyperthermia Treatment: A Case Report.

Local hyperthermia treatment, a common immunoadjuvant therapy, has been used in treating various human papillomavirus (HPV) infections. For multiple warts, it can clear off all warts of the body through targeted irradiation on one wart. We reported a case of a 22-year-old patient with multiple plantar warts combined with periungual warts, in which previous treatments were ineffective. Therefore, we utilized local hyperthermia treatment at 44°C using the largest fused-wart plaque on the right plantar as the treatment target for 30-minute irradiation each time. The hyperthermia induction therapy was performed on day 1, 2, 3, 12 and 13, followed by weekly maintenance therapy for 6 times. After 2 months of treatment, both irradiated and non-irradiated lesions disappeared, and no recurrence occurred during the follow-up period. This case indicates that local hyperthermia treatment may be a safe and effective approach for patients with multiple, recalcitrant, and site-specific viral warts due to the ineffectiveness of conventional treatment.