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The unsatisfactory energy density of the state-of-art batteries imposes constraints on the practical application of unmanned aerial vehicles (UAVs). Establishing a UAV airport network that integrates energy supply and information exchange functionalities represents an ideal solution for enabling synergistic UAV operations. However, devising efficient distribution protocols for these airports remains a challenge. By leveraging modeling and analysis of the energy density of existing UAV batteries, we can forecast the flight range and distances achievable by UAVs. Here, we propose a distribution protocol for UAV airport platforms aimed at enhancing distribution accuracy by the use of AI principles. Furthermore, considering the possibility of emergency UAV stop, we introduce an emergency stop system in conjunction with standard stopping procedures to optimize distribution efficiency and enhance UAV inspection safety. Moreover, existing UAV airports usually provide energy to UAVs without harnessing UAVs to facilitate interconnection and interoperability among different airports. This inefficiency leads to significant resource wastage in energy distribution. To address this, we introduce a shared energy network that allows different companies to operate according to energy distribution needs. This network not only supplies energy to UAVs but also employs UAVs for energy collection and transportation, facilitating energy trading, business collaboration, and data transmission among diverse organizations. By enabling ubiquitous energy trading, this study provides us an ideal strategy for the future construction of energy network with interconnection and interoperability, which can be extended to other applications calling for energy distribution.

Chip seal is widely used for preventive maintenance to mitigate pavement deterioration, but it is prone to aggregate loss during pavement service. To further promote the development and application of chip seals in road engineering in China, the research progress of the adhesion behavior of aggregate and binder in chip seals was reviewed in this paper, focusing on the adhesion mechanism of emulsified asphalt and alkaline aggregate. The Influencing factors and evaluation methodology of chip seals' aggregate adhesion behavior were also discussed. The results demonstrate that the adhesion process between emulsified asphalt and alkaline aggregate is divided into three processes including infiltration, demulsification, and cluster, which is more complicated when compared to hot asphalt. When designing a chip seal, not only the characteristics of single material should be paid attention to, but also the combination of binder and aggregate matters a lot. To form good adhesion between aggregate and asphalt binder, various influencing factors such as material selection, design method, and construction technical index should be considered comprehensively in the whole design, construction, and operation process. Three methods for evaluating adhesion behavior are summarized, including macroscopic adhesion performance tests, image analysis technology, and model prediction. It is not objective to evaluate the aggregate adhesion behavior of chip seal only by a single evaluation method. A comprehensive evaluation based on the micro-macro multi-scale method should be considered in the future.

Abstract Background Giant cell-rich solitary fibrous tumour (GCR-SFT), previously referred to as giant cell angiofibroma, is an uncommon soft tissue tumour that classically occurs in the orbit but very rarely presents in deep organs. Here, we present a case of GCR-SFT occurring in the urinary bladder, which is one of the unusual histological subtypes of SFT. Case presentation A 56-year-old man was incidentally found to have a mass measuring 4.5 × 4.3 × 4.0 cm located in the left posterior wall of the bladder by computed tomography during a physical examination. The lesion was confirmed as GCR-SFT by pathological examination after laparoscopic radical surgery. Histopathologically, the tumour was a well-circumscribed, nonencapsulated lesion that was composed of bland spindle-ovoid tumour cells alternating with hypocellular and hypercellular areas, staghorn-like vasculatures and scattered large dark-stained multinucleate giant cells lining pseudovascular spaces. The spindle-ovoid cells and multinucleate giant cells showed strong and diffuse expression of CD34 and nuclear STAT6. In addition, the hallmark of the NAB2ex4-STAT6ex5 fusion gene was detected by RT‒PCR. The patient was classified as having a low risk of recurrence or metastasis according to the risk stratification criteria. The patient underwent regular follow-up for 34 months after surgery, and there was no evidence of local recurrence or metastasis. Conclusion This is the first reported case of GCR-SFT occurring in the urinary bladder with underlying NAB2ex4-STAT6ex5 fusion. Complete surgical excision of the tumour and long-term follow-up are recommended to ensure no local recurrence or metastasis.

Abstract Malignant pleural mesothelioma (MPM) is a malignant tumor originating from the pleura, and its incidence has been increasing in recent years. Due to the insidious onset and strong local invasiveness of MPM, most patients are diagnosed in the late stage and early screening and treatment for high‐risk populations are crucial. The treatment of MPM mainly includes surgery, chemotherapy, and radiotherapy. Immunotherapy and electric field therapy have also been applied, leading to further improvements in patient survival. The Mesothelioma Group of the Yangtze River Delta Lung Cancer Cooperation Group (East China LUng caNcer Group, ECLUNG; Youth Committee) developed a national consensus on the clinical diagnosis and treatment of MPM based on existing clinical research evidence and the opinions of national experts. This consensus aims to promote the homogenization and standardization of MPM diagnosis and treatment in China, covering epidemiology, diagnosis, treatment, and follow‐up.

Background: Given the differential expression and biological functions of protein arginine methylation (PAM) regulators in lung adenocarcinoma (LUAD), it may be of great value in the diagnosis, prognosis, and treatment of LUAD. However, the expression and function of PAM regulators in LUAD and its relationship with prognosis are unclear. Methods: 8 datasets including 1798 LUAD patients were selected. During the bioinformatic study in LUAD, we performed (i) consensus clustering to identify clusters based on 9 PAM regulators related expression profile data, (ii) to identify hub genes between the 2 clusters, (iii) principal component analysis to construct a PAM.score based on above genes, and (iv) evaluation of the effect of PAM.score on the deconstruction of tumor microenvironment and guidance of immunotherapy. Results: We identified two different clusters and a robust and clinically practicable prognostic scoring system. Meanwhile, a higher PAM.score subgroup showed poorer prognosis, and was validated by multiple cohorts. Its prognostic effect was validated by ROC (Receiver operating characteristic curve) curve and found to have a relatively good prediction efficacy. High PAM.score group exhibited lower immune score, which associated with an immunosuppressive microenvironment in LUAD. Finally, patients exhibiting a lower PAM.score presented noteworthy therapeutic benefits and clinical advantages. Conclusion: Our PAM.score model can help clinicians to select personalized therapy for LUAD patients, and PAM.score may act a part in the development of LUAD.

Abstract Thymic epithelial tumors (TETs) are a relatively rare type of thoracic tumor, accounting for less than 1% of all tumors. The incidence of TETs is about 3.93/10000 in China, slightly higher than that of European and American countries. For resectable TETs, complete surgical resection is recommended. Radiotherapy or chemotherapy may be used as postoperative adjuvant treatment. Treatment for advanced, unresectable TETs consist mainly of radiotherapy and chemotherapy, but there is a lack of standard first‐ and second‐line treatment regimens. Recently, targeted therapies and immune checkpoint inhibitors have shown promising outcomes in TETs. Based on the currently available clinical evidences and the opinions of the national experts, the Thymic Oncology Group of Yangtze River Delta Lung Cancer Cooperation Group (East China LUng caNcer Group, ECLUNG; Youth Committee) established this Chinese expert consensus on the clinical diagnosis and treatment of TETs, covering the epidemiology, diagnosis, treatment, prognosis and follow‐up of TETs.

Adequate vascularization is crucial for the repair of bone defects. Platelet-derived growth factor-BB (PDGF-BB) has been shown to promote H-type vessel formation, a specialized blood vessel, strongly positive for CD31 and endomucin, coupling angiogenesis and osteogenesis. However, the lack of a controllable growth factor delivery limits its clinical application, causing certain complications associated with PDGF-BB administration. This study developed an injectable heparin-conjugated hydrogel (GHH) for controlled delivery to facilitate the effective binding of PDGF-BB and rapid vascularized bone regeneration. Herein, in vitro experiments involving the controlled release of PDGF-BB showed that the PDGF-BB-loaded GHH (GHHP) hydrogel demonstrated excellent cytocompatibility and osteogenic properties. The subcutaneous implantation model in rats revealed that the GHHP hydrogel has the potential to induce the formation of H-type blood vessels in vivo. Furthermore, the healing of distal femoral condyle defects in rat models in vivo demonstrated that GHHP could substantially promote H-type angiogenesis and effectively repair bone defects. Our injectable heparin-conjugated sustained-release PDGF-BB hydrogel has excellent angiogenic and osteogenic properties, thus providing a novel and promising solution for bone defect repair.

Click-Through Rate (CTR) prediction is important in many industrial applications, such as E-commerce, news, and information. Understanding sophisticated feature interactions behind users’ behaviors is essential for CTR prediction. Although existing methods have made significant improvements, there exist some problems: (1) only concentrate on modeling implicit information from the user side, while ignoring the interest hidden in the historical interactive behaviors; (2) insufficient feature extraction, only focusing on high-order feature interactions or low-order feature interactions. To overcome these limitations, we propose a Deep Adaptive Interest Network (DAIN) for CTR Prediction in the local and global views, respectively. Specifically, to extract user’s interest, we first develop a local attention mechanism applied to the user behaviors and candidate ads, which can adaptively calculate users’ interest representation given a candidate ad in the local views. To capture feature interactions, we propose a feature interaction extractor containing Multi-layer Perceptrons (MLP) and Factorization Machines (FM) components to capture high-order and low-order feature interactions. To adaptively learn the influences of high-order and low-order feature interactions on the target item, we finally employ a linear-based global attention mechanism in the feature interaction extractor. The effectiveness of DAIN is verified by comprehensive experiments on three datasets.

Several excavations at the Hemudu site in Zhejiang Province have led to the discovery of more than 100 pieces of bird bones that were likely used to create a kind of musical instrument. However, in contrast to the Jiahu bone flute, it is not clear for what the Hemudu bone whistle was used, although it was probably used for musical purposes. In this paper, the 7000-year-old Hemudu bone whistle is reproduced with 3D scanning and printing technology. Therefore, we propose a robust scan point detection and tracking method that includes three main stages. First, we conducted robust point detection and selection where noise and irrelevant points were removed. Then, we propose to track the key points and conduct 3D model optimization. With the above efforts, we obtained the 3D model of the bone whistle, and the audio of the bone whistle is replicated. The purpose of the bone whistles is inferred and evaluated through audio analyses. The experimental results show that the method is feasible.

Spatial language understanding (SLU) is an important task in the field of information extraction, and it involves complex spatial analyses and reasoning processes. Unlike English SLU, in the case of the Chinese language, there may be some language-specific challenges, such as the phenomenon of polysemia and the substitution of synonyms. In this work, we explore Chinese SLU by taking advantage of large language models. Inspired by recent chain-of-thought (CoT) strategies, in this study, we propose the Spatial-CoT template to help improve LLMs’ reasoning abilities in order to deal with the challenges of Chinese SLU. Spatial-CoT offers LLMs three steps of instructions from different perspectives, namely, entity extraction, context analysis, and common knowledge analysis. We evaluate our framework on the Chinese SLU dataset SpaCE, which contains three subtasks: abnormal spatial semantics recognition, spatial role labeling, and spatial scene matching. The experimental results show that our Spatial-CoT outperforms vanilla prompt learning on ChatGPT and achieves competitive performance in comparison with traditional supervised models. Further analysis revealed that our method could address the phenomenon of polysemia and the substitution of synonyms in Chinese spatial language understanding.

Abstract Background As a rare salivary gland malignancy, clear cell carcinoma (CCC) is easily misdiagnosed. This study identified the features that allow better recognition of the clinicopathological and molecular characteristics and the prognosis of CCC, focusing on high-grade transformation (HGT) in this tumor and cases arising in uncommon sites. Methods Clinicopathological and follow-up data for 10 CCC samples were retrieved. Immunohistochemical (IHC) staining was performed, and fluorescence in situ hybridization (FISH) was used to detect EWSR1 gene rearrangements, EWSR1–ATF1 gene fusions, and MAML2 gene rearrangements. Results Histologically, typical CCCs comprised bland polygonal or round cells with clear cytoplasm. In contrast with typical CCCs, HGT tumor cells exhibited nuclear pleomorphism, high nuclear-to-cytoplasmic ratios, high mitotic activity, and necrosis. Rare morphologic features such as pseudopapillae, gland-like spaces, and entrapped ducts were also observed. Occasionally, tumors involving the oral cavity might arise from the overlying epithelium of the mucosal surface. Immunohistochemically, all the cases expressed p63, p40, and CK5/6, while myoepithelial-related markers were uniformly negative in all cases. HGT exhibited a wild type p53 expression pattern. FISH demonstrated EWSR1 rearrangement (10/10) and EWSR1–ATF1 fusion (4/5); however, MAML2 remained intact (0/3). Conclusions CCCs with HGT or occurring in uncommon sites are extremely rare. Combining morphology based IHC and molecular detection provided reliable evidence that the HGT component represented a transformation of CCC rather than the coexistence of another tumor and helped differentiating CCCs in uncommon sites from their mimics, avoiding potential misdiagnosis and inappropriate therapy. The overall prognosis for CCCs is good, except for the HGT cases, which needed continued treatment.

BackgroundIn this work, radiomics characteristics based on CT scans were used to build a model for preoperative evaluation of CD3 and CD8 T cells expression levels in patients with non-small cell lung cancer (NSCLC).MethodsTwo radiomics models for evaluating tumor-infiltrating CD3 and CD8 T cells were created and validated using computed tomography (CT) images and pathology information from NSCLC patients. From January 2020 to December 2021, 105 NSCLC patients with surgical and histological confirmation underwent this retrospective analysis. Immunohistochemistry (IHC) was used to determine CD3 and CD8 T cells expression, and all patients were classified into groups with high and low CD3 T cells expression and high and low CD8 T cells expression. The CT area of interest had 1316 radiomic characteristics that were retrieved. The minimal absolute shrinkage and selection operator (Lasso) technique was used to choose components from the IHC data, and two radiomics models based on CD3 and CD8 T cells abundance were created. Receiver operating characteristic (ROC), calibration curve, and decision curve analyses were used to examine the models’ ability to discriminate and their clinical relevance (DCA).ResultsA CD3 T cells radiomics model with 10 radiological characteristics and a CD8 T cells radiomics model with 6 radiological features that we created both demonstrated strong discrimination in the training and validation cohorts. The CD3 radiomics model has an area under the curve (AUC) of 0.943 (95% CI 0.886-1), sensitivities, specificities, and accuracy of 96%, 89%, and 93%, respectively, in the validation cohort. The AUC of the CD8 radiomics model was 0.837 (95% CI 0.745-0.930) in the validation cohort, with sensitivity, specificity, and accuracy values of 70%, 93%, and 80%, respectively. Patients with high levels of CD3 and CD8 expression had better radiographic results than patients with low levels of expression in both cohorts (p

Emotional clues are always expressed in many ways in our daily life, and the emotional information we receive is often represented by multiple modalities. Successful social interactions require a combination of multisensory cues to accurately determine the emotion of others. The integration mechanism of multimodal emotional information has been widely investigated. Different brain activity measurement methods were used to determine the location of brain regions involved in the audio-visual integration of emotional information, mainly in the bilateral superior temporal regions. However, the methods adopted in these studies are relatively simple, and the materials of the study rarely contain speech information. The integration mechanism of emotional speech in the human brain still needs further examinations. In this paper, a functional magnetic resonance imaging (fMRI) study was conducted using event-related design to explore the audio-visual integration mechanism of emotional speech in the human brain by using dynamic facial expressions and emotional speech to express emotions of different valences. Representational similarity analysis (RSA) based on regions of interest (ROIs), whole brain searchlight analysis, modality conjunction analysis and supra-additive analysis were used to analyze and verify the role of relevant brain regions. Meanwhile, a weighted RSA method was used to evaluate the contributions of each candidate model in the best fitted model of ROIs. The results showed that only the left insula was detected by all methods, suggesting that the left insula played an important role in the audio-visual integration of emotional speech. Whole brain searchlight analysis, modality conjunction analysis and supra-additive analysis together revealed that the bilateral middle temporal gyrus (MTG), right inferior parietal lobule and bilateral precuneus might be involved in the audio-visual integration of emotional speech from other aspects.

Abstract Background Corona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. The purpose of this study is to explore the diagnostic value of the quantitative computed tomography (CT) method by using different threshold segmentation techniques to distinguish between patients with or without COVID-19 pneumonia. Methods A total of 47 patients with suspected COVID-19 were retrospectively analyzed, including nine patients with positive real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR) test (confirmed case group) and 38 patients with negative RT-PCR test (excluded case group). An improved 3D convolutional neural network (VB-Net) was used to automatically extract lung lesions. Eight different threshold segmentation methods were used to define the ground glass opacity (GGO) and consolidation. The receiver operating characteristic (ROC) curves were used to compare the performance of various parameters with different thresholds for diagnosing COVID-19 pneumonia. Results The volume of GGO (VOGGO) and GGO percentage in the whole lung (GGOPITWL) were the most effective values for diagnosing COVID-19 at a threshold of − 300 HU, with areas under the curve (AUCs) of 0.769 and 0.769, sensitivity of 66.67 and 66.67%, specificity of 94.74 and 86.84%. Compared with VOGGO or GGOPITWL at a threshold of − 300 Hounsfield units (HU), the consolidation percentage in the whole lung (CPITWL) with thresholds at − 400 HU, − 350 HU, and − 250 HU were statistically different. There were statistical differences in the infection volume and percentage of the whole lung, right lung, and lobes between the two groups. VOGGO, GGOPITWL, and volume of consolidation (VOC) were also statistically different at the threshold of − 300 HU. Conclusions Quantitative CT provides an image quantification method for the auxiliary diagnosis of COVID-19 and is expected to assist in confirming patients with COVID-19 pneumonia in suspected cases.

BackgroundAlthough emerging evidence supports the relationship between necroptosis (NEC) related genes and hepatocellular carcinoma (HCC), the contribution of these necroptosis-related genes to the development, prognosis, and immunotherapy of HCC is unclear.MethodsThe expression of genes and relevant clinical information were downloaded from TCGA-LIHC, LIRI-JP, GSE14520/NCI, GSE36376, GSE76427, GSE20140, GSE27150, and IMvigor210 datasets. Next, we used an unsupervised clustering method to assign the samples into phenotype clusters base on 15 necroptosis-related genes. Subsequently, we constructed a NEC score based on NEC phenotype-related prognostic genes to quantify the necroptosis related subtypes of individual patients.ResultsWe divided the samples into the high and low NEC score groups, and the high NEC score showed a poor prognosis. Simultaneously, NEC score is an effective and stable model and had a good performance in predicting the prognosis of HCC patients. A high NEC score was characterized by activation of the stroma and increased levels of immune infiltration. A high NEC score was also related to low expression of immune checkpoint molecules (PD-1/PD-L1). Importantly, the established NEC score would contribute to predicting the response to anti-PD-1/L1 immunotherapy.ConclusionsOur study provide a comprehensive analysis of necroptosis-related genes in HCC. Stratification based on the NEC score may enable HCC patients to benefit more from immunotherapy and help identify new cancer treatment strategies.

In this paper, we propose a Robust Breast Cancer Diagnostic System (RBCDS) based on multimode Magnetic Resonance (MR) images. Firstly, we design a four-mode convolutional neural network (FMS-PCNN) model to detect whether an image contains a tumor. The features of the images generated by different imaging modes are extracted and fused to form the basis of classification. This classification model utilizes both spatial pyramid pooling (SPP) and principal components analysis (PCA). SPP enables the network to process images of different sizes and avoids the loss due to image resizing. PCA can remove redundant information in the fused features of multi-sequence images. The best accuracy of this model achieves 94.6%. After that, we use our optimized U-Net (SU-Net) to segment the tumor from the entire image. The SU-Net achieves a mean dice coefficient (DC) value of 0.867. Finally, the performance of the system is analyzed to prove that this system is superior to the existing schemes.

BackgroundAngiofibroma of soft tissue (AFST) is a rare mesenchymal neoplasm of fibroblastic differentiation. Due to its diverse morphology and the lack of specific immunohistochemistry (IHC) markers, AFST could elicit a broad range of differential diagnosis. Several studies have disclosed in AFST recurrent gene fusions involving NCOA2, mainly AHRR–NCOA2 fusion, providing a useful approach to diagnosing this lesion. We report eight additional cases of this rare entity with emphasis on the diagnostic utility of fluorescence in situ hybridization (FISH) detection for NCOA2 rearrangement.MethodsClinicopathological data for eight AFSTs were retrieved. IHC was performed, and FISH was used to detect rearrangements involving NCOA2, DDIT3, and FUS loci.ResultsThere were five female and three male patients, ranging in age from 29 to 69 years (median: 55 years). The patients presented mostly with a slow-growing mass in the extremities, with or without intermittent pain. All tumors were located in the lower extremities with three (27.5%) involving or adjacent to the knee joints. Tumor size ranged from 1.5 to 3.8 cm (median: 3.0 cm). Morphologically, the tumors consisted of a proliferation of uniform, bland spindle cells set in alternating myxoid and collagenous stroma with a prominent vascular network composed of countless small, branching, thin-walled blood vessels. Foci of “chicken wire”-like capillaries and medium- to large-sized blood vessels with prominent staghorn morphology were evident in two and four cases, respectively. In addition, sheets of small round cells and foci of cystic changes were observed in one each case. Degenerative nuclear atypia was identified in three cases, while mitosis and tumor necrosis were absent. By IHC, the stromal cells were variably positive for epithelial membrane antigen, desmin, and CD68. By FISH analysis, seven out of eight cases (87.5%) showed NCOA2 rearrangement, and the remaining one had increased gene copy numbers of intact NCOA2; rearrangements involving FUS (0/4) and DDIT3 (0/3) were not identified in the cases analyzed. All tumors were surgically removed, and none had recurrence at follow-up from 5 to 73 months.ConclusionsFISH analysis for NCOA2 rearrangement represents a practical method for confirming the diagnosis of AFST on the basis of appropriate histomorphological backgrounds.

Digital watermarking is an effective covert communication technique in the military field, which can solve the problems in traditional encryption. In general, the Spread Spectrum (SS) algorithm can well satisfy the requirements of concealment and anti-interference in the covert communication process. However, it has a natural defect in resisting desynchronization attacks. In this paper, we propose a Robust Feature Points Scheme (RFPS) against desynchronization attacks by calculating the maximum response value of the second-order derivative of the original audio signal. The maximum response value will be used as a feature point and the audio segments centering at the detected feature points are extracted for both watermark embedding and extraction process. This study mainly focuses on cropping attacks and pitch invariant Time-Scale Modification (TSM) attacks. The experimental results show that under non-uniform cropping attacks, the proposed method can extract the watermark information without any bit error rate. Even in the case of the pitch-invariant TSM attacks, the proposed scheme has great improvement compared with the existing works.

Do financial inclusion and stock market development play the deterministic role of attracting foreign capital flows in developing countries. With this study, we tried to figure out the answer by investigating the magnitude of financial inclusion and stock market development towards capital flows in the economy considering a panel of 58 developing countries for the span of 1993–2017. Dynamic panel System-GMM estimation was performed by decomposing the development and degradation namely, positive and negative shocks in financial inclusion and stock market development. Study findings ascertain the asymmetric relationship between financial inclusion, stock market development, and cross-broader capital flows in developing countries. We also observed positive shock in financial inclusion and stock market development positive linked with cross-broader capital flows. In particular, development in financial inclusion in the financial system encourages foreign capital flows in the form of FDI, on the other hand well developed and efficient financial market particularly stock market development encourage the positive trend in foreign portfolio investment. The study also revealed that past behavior of foreign capital flows could consider as the future predictor for foreign capital flows in recipients countries. Dumitrescu and Hurlin (2012) Panel Causality Test was performed and estimation unveiled bidirectional causality between stock market development and capital flows and unidirectional causality from financial inclusion to foreign capital flows in the short-run.

Single image dehazing has always been a challenging problem in the field of computer vision. Traditional image defogging methods use manual features. With the development of artificial intelligence, the defogging method based on deep learning has developed rapidly. In this paper, we propose a novel image defogging approach called NIN-DehazeNet for single image. This method estimates the transmission map by NIN-DehazeNet combining Network-in-Network with MSCNN(Single Image Dehazing via Multi-Scale Convolutional Neural Networks). In the test stage, we estimate the transmission map of the input hazy image based on the trained model, and then generate the dehazed image using the estimated atmospheric light and computed transmission map. Extensive experiments have shown that the proposed algorithm overperformance traditional methods.

Significant objects in a scene can make a great contribution to scene recognition. Besides the three scene-selective regions: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA), some neuroimaging studies have shown that the lateral occipital complex (LOC) is also engaged in scene recognition processing. In this study, the multivariate pattern analysis was adopted to explore the object-scene association in scene recognition when different amounts of significant objects were masked. The scene classification only succeeded in the intact scene in the ROIs. In addition, the average signal intensity in LOC [including the lateral occipital cortex (LO) and the posterior fusiform area (pF)] decreased when there were masked objects, but such a decrease was not observed in scene-selective regions. These results suggested that LOC was sensitive to the loss of significant objects and mainly involved in scene recognition by the object-scene semantic association. The performance of the scene-selective areas may be mainly due to the fact that they responded to the change of the scene's entire attribute, such as the spatial information, when they were employed in the scene recognition processing. These findings further enrich our knowledge of the significant objects' influence on the activation pattern during the process of scene recognition.

This study examines whether the number of forward patent citations (along with alternative patent data)—when used as a proxy for the mixing variable—could infer the aggregate amount of economic-innovation information arriving at the New York Stock Exchange (NYSE) in the United States. The results show that the number of forward patent citations, when used as a mixing variable, fails to eliminate total volatility persistence in the conditional variance equation of the exponential generalized autoregressive conditional heteroscedastic (EGARCH) model. However, the trading volume successfully eliminates total volatility persistence, thus confirming the validity of the framework used. When the volatility is modeled with an expectation of mean return, the persistence of conditional variance is deterministically increased, and the sum of the volatility coefficients exceeds unity. The inclusion of trading volume with a time trend in the variance equation rectifies the deterministic increase in the conditional volatility. These findings suggest that the form of heteroscedasticity (i.e., as per the autoregressive conditional heteroscedastic model, ARCH model) in NYSE portfolio returns is based on the type of shocks to volatility (e.g., deterministic vs. stochastic), which manifests as news arrivals (i.e., new information arrivals proxied by trading volume) at the stock market. The volume therefore reflects the time dependence in the innovations to the ARCH error generation process. The response of volatility to volume persists over time when the volatility estimates are derived from the EGARCH model with an expectation for the mean of return. Backward patent citations, patent applications, and patents issued have been found to interact somewhat with trading volume, suggesting that each of these variables could play the role of an absorptive capacity variable as the new information flow associated with economic innovation (i.e., flow of firms’ stock of new knowledge) could be picked up by the trading volume. Keywords: Economic innovation, Patent citations, Market efficiency, Information flow, EGARCH, Trading volume, JEL classification: G12, G14, G17, D53, C58, O31

This paper examines the presence of herding on foreign trading at individual stock level and portfolio level in the Colombo Stock Exchange as a response to a long-standing trading belief that investors mimic the trading strategies of foreign investors. The standard CSAD framework of Chang et al (2000) is extended replacing return on market portfolio with return on market foreign portfolio holding in the model specification. The standard CSAD specification is also used to identify the presence of herding towards the market under high market volatility, bullish market condition, high trading and transaction volume, domestic and global market crisis and up and down market conditions. Except for the evidence on herding towards the market under bullish market condition at portfolio level, the regression results under other market conditions do not provide reasonable evidence for the presence of herding on foreign trading or herding towards the market on average. Further, taking CSAD as a proxy for heteroskedastic residuals following the framework of Banz (1981), the capital asset pricing model of Black (1972) is used to test the specification of CSAD. The findings suggest that the form of herding accounted for by CSAD is a manifestation of residual heteroskedasticity.

Lymphoepithelioma-like carcinoma (LELC) of the liver is uncommon, only 20 cases have been reported in the English-language literature so far, and the majority has been identified as cholangiocarcinomas, only four cases were hepatocellular LELC. Here we described a rare case of lymphoepithelioma-like hepatocellular carcinoma (HCC). A 42-year-old Chinese female who was incidentally found to have a liver-occupying lesion during a routine medical examination. Ultrasonography revealed a 47 mm × 33 mm × 36 mm hypoechoic mass in the left lobe. Computed tomography and magnetic resonance imaging displayed a nodular lesions in the left liver lobe. The patient underwent a left-side hepatectomy. Histopathological examination of the resected specimen revealed an undifferentiated carcinoma with a dense lymphocytic infiltrate, predominantly composed of CD3(+) T cells, morphologically similar to nasopharyngeal carcinoma. Immunohistochemically, the tumor cells were positive for CK, EMA, Glypican-3 and hepatocyte, but negative for alpha-fetoprotein, CK19, CK7 and CK20. Epstein–Barr virus (EBV) in situ hybridization was negative. The final histopathological diagnosis was lymphoepithelioma-like HCC without EBV infection.

Burkitt lymphoma (BL) is a highly aggressive neoplasm, which arising from the germinal center or post germinal center B-cell. Primary breast lymphomas are extremely rare, and the most common histologic type is diffuse large B-cell lymphoma. Primary BL of the breast is much less common than the other types of lymphoma. Here, we report an extremely rare case of a 37-year-old Chinese female with localized bilateral breast, who was referred to our institution for bilateral breast swelling. The left breast tissue ultrasonography showed the short axis measuring 20.3 mm × 18.8 mm and the long axis measuring 22.1 mm × 20.8 mm soft tissue mass. The right breast tissue ultrasonography showed the short axis measuring 30.2 mm × 26.9 mm and the long axis measuring 33.5 mm × 2.18 mm. Coarse needle biopsy of breast masses demonstrated a non-Hodgkin's B-cell lymphoma. The patient underwent a bilateral mastectomy. Histological examination of the tumor showed a characteristic "starry sky" pattern, the medium-sized tumor cells were a monotonous pattern of growth, and there were many abnormal mitotic figures. The neoplastic cells strongly expressed CD20, CD79-μ, MUM-1, PAX-5, CD43 and Bcl-6, Ki-67 were nearly 100% positive, but negative for CD10, Bcl-2 and TdT. By fluorescence in situ hybridization an IGH-MYC gene fusion was detected in the tumor tissue which indicating the presence of a typical BL translocation t(8;14)(q24;q32). The final histopathological diagnosis was primary BL of the breast.

In this study, Fe(III)-cross-linked chitosan beads (Fe(III)-CBs) were synthesized and employed to explore the characteristics and primary mechanism of their hexavalent chromium (Cr(VI)) adsorption under low concentration Cr(VI) (less than 20.0 mg l−1) and a pH range from 2.0 to 8.0. Batch tests were conducted to determine the Cr(VI) adsorption capacity and kinetics, and the effects of pH and temperature on the adsorption under low concentration Cr(VI) and a pH range from 2.0 to 8.0. Scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy were employed to explore the characteristics of Fe(III)-CBs and their Cr(VI) adsorption mechanisms. The results show that, unlike the adsorption of other absorbents, the Cr(VI) adsorption was efficient in a wide pH range from 2.0 to 6.0, and well described by the pseudo-first-order model and the Langmuir–Freundlich isotherm model. The capacity of Cr(VI) adsorption by Fe(III)-CBs was as high as 166.3 mg g−1 under temperature 25°C and pH 6.0. The desorption test was also carried out by 0.1 mol l−1 NaOH solution for Fe(III)-CBs regeneration. It was found that Fe(III)-CBs could be re-used for five adsorption–desorption cycles without significant decrease in Cr(VI) adsorption capacity. Ion exchange was confirmed between functional groups (i.e. amino group) and Cr(VI) anions (i.e. CrO42−). The amino-like functional groups played a key role in Cr(VI) distribution on the Fe(III)-CBs surface; Cr(VI) adsorbed on Fe(III)-CBs was partially reduced to Cr(III) with alcoholic group served as electron donor, and then formed another rate-limiting factor. So, Fe(III)-CBs has a good prospect in purifying low concentration Cr(VI) water with a pH range from 2.0 to 6.0.

This paper examines the nexus between financial inclusion and financial innovation while incorporating financial development and remittance inflows in the case of six South Asian countries—Bangladesh, India, Pakistan, Nepal, Bhutan, and Srilanka—by employing the panel autoregressive distributed lagged model under a linear and nonlinear framework using monthly data over the period 1990M1−2018M12. Further, a Granger-causality test with System GMM specification was performed for assessing directional causality. The study findings from Panel ARDL confirmed the positive association between financial innovation and financial inclusion, which was observed both in the long run and short-run. Considering the nonlinearity in the estimation, the standard Wald test confirms the existence of an asymmetric relationship both in the short-run and in long run horizon regarding causality test results. The study findings support the feedback hypothesis that the presence of bidirectional causality between the financial innovation and financial inclusion is both in the short-run and long run. Since the study findings established a critical relationship between financial innovation and financial inclusion, therefore effective policy guidelines are suggested so that the contribution from financial inclusion and financial innovation can assist in developing a vibrant financial sector.

This study aims to explore the relationship between economic growth, financial innovation, and stock market development of Bangladesh for the period 1980–2016. To investigate long-run cointegration, this study used the autoregressive distributed lagged (ARDL) bounds testing approach. In addition, the Granger-causality test is used to identify directional causality between research variables under the error correction term. Study findings from the ARDL bound testing approach confirm the existence of a long-run association between financial innovation, stock market development, and economic growth. Furthermore, the findings from the Granger-causality test support bidirectional causality between financial innovation, economic growth and stock market development, and economic growth both in the long run and short run. These findings support the theory that market-based financial development and financial innovation in the financial system can spur economic development.

In this paper, a novel imperceptible, fragile and blind watermark scheme is proposed for speech tampering detection and self-recovery. The embedded watermark data for content recovery is calculated from the original discrete cosine transform (DCT) coefficients of host speech. The watermark information is shared in a frames-group instead of stored in one frame. The scheme trades off between the data waste problem and the tampering coincidence problem. When a part of a watermarked speech signal is tampered with, one can accurately localize the tampered area, the watermark data in the area without any modification still can be extracted. Then, a compressive sensing technique is employed to retrieve the coefficients by exploiting the sparseness in the DCT domain. The smaller the tampered the area, the better quality of the recovered signal is. Experimental results show that the watermarked signal is imperceptible, and the recovered signal is intelligible for high tampering rates of up to 47.6%. A deep learning-based enhancement method is also proposed and implemented to increase the SNR of recovered speech signal.

In this paper, we demonstrate a method using a frequency comb, which can precisely measure the refractive index of water. We have developed a simple system, in which a Michelson interferometer is placed into a quartz-glass container with a low expansion coefficient, and for which compensation of the thermal expansion of the water container is not required. By scanning a mirror on a moving stage, a pair of cross-correlation patterns can be generated. We can obtain the length information via these cross-correlation patterns, with or without water in the container. The refractive index of water can be measured by the resulting lengths. Long-term experimental results show that our method can measure the refractive index of water with a high degree of accuracy—measurement uncertainty at 10−5 level has been achieved, compared with the values calculated by the empirical formula.

We propose a l0 sparsity based approach to remove additive white Gaussian noise from a given image. To achieve this goal, we combine the local prior and global prior together to recover the noise-free values of pixels. The local prior depends on the neighborhood relationships of a search window to help maintain edges and smoothness. The global prior is generated from a hierarchical l0 sparse representation to help eliminate the redundant information and preserve the global consistency. In addition, to make the correlations between pixels more meaningful, we adopt Principle Component Analysis to measure the similarities, which can be both propitious to reduce the computational complexity and improve the accuracies. Experiments on the benchmark image set show that the proposed approach can achieve superior performance to the state-of-the-art approaches both in accuracy and perception in removing the zero-mean additive white Gaussian noise.

Extended reality (XR) is a general term for virtual reality (VR), augmented reality (AR), and mixed reality (MR). By converting abstract digital expressions into intelligent feedback through figures, one can effectively compensate for the poor performance of traditional learning in deep cognitive processing and operational skills training. However, the extant results are uncertain, and only a limited number of studies have investigated the influence mechanism of heterogeneity among VR, AR, and MR on procedural knowledge learning, higher-level presence and generative cognitive processing, higher-quality operational behavior, and knowledge transfer. This study explored and analyzed the influence of XR heterogeneity on procedural knowledge gain and operation training. Participants (n = 127) were recruited from junior undergraduate students majoring in rail traffic signal and control. Based on the procedural disassembly and assembly of the ZD6 electric switch machine, an XR pretraining system and a 3-D-printed combined virtual-real procedural training system were developed to collect three types of data regarding knowledge gain, procedural training, and a set of questionnaires. Subsequently, a one-way analysis of variance was conducted with XR as the moderator variable. The results indicate that fully immersive VR is more conducive to procedural operation training; however, space and real factors must be considered. AR is consistent with the learner's operating habits, but the corresponding lack of immersion and interactivity restricts the improvement of procedural learning effects. MR multimodal perception leads to an increase in cognitive load, but moderate cognitive pressure is conducive to the cultivation of procedural cognition skills. Furthermore, this study proposes suggestions for using XR to intensify the perception and understanding of procedural cognitive actions.