Miracle-dz/UniFAR-FTUs huggingface dataset:
Sediment Stocks of Carbon, Nitrogen, and Phosphorus in Danish Eelgrass Meadows

Seagrass ecosystems provide an array of ecosystem services ranging from habitat provision to erosion control. From a climate change and eutrophication mitigation perspective, the ecosystem services include burial and storage of carbon and nutrients in the sediments. Eelgrass (Zostera marina) is the most abundant seagrass species along the Danish coasts, and while its function as a carbon and nutrient sink has been documented in some areas, the spatial variability of these functions, and the drivers behind them, are not well understood. Here we present the first nationwide study on eelgrass sediment stock of carbon (Cstock), nitrogen (Nstock), and phosphorus (Pstock). Stocks were measured in the top 10 cm of eelgrass meadows spanning semi-enclosed estuaries (inner and outer fjords) to open coasts. Further, we assessed environmental factors (level of exposure, sediment properties, level of eutrophication) from each area to evaluate their relative importance as drivers of the spatial pattern in the respective stocks. We found large spatial variability in sediment stocks, representing 155-4413 g C m-2, 24-448 g N m-2, and 7-34 g P m-2. Cstock and Nstock were significantly higher in inner fjords compared to outer fjords and open coasts. Cstock, Nstock, and Pstock showed a significantly positive relationship with the silt-clay content in the sediments. Moreover, Cstock was also significantly higher in more eutrophied areas with high concentrations of nutrients and chlorophyll a (chl a) in the water column. Conversely, silt-clay content was not related to nutrients or chl a, suggesting a spatial dependence of the importance of these factors in driving stock sizes and implying that local differences in sediment properties and eutrophication level should be included when evaluating the storage capacity of carbon, nitrogen, and phosphorus in Danish eelgrass meadows. These insights provide guidance to managers in selecting priority areas for carbon and nutrient storage for climate- and eutrophication mitigation initiatives. (Less)
Group Cognitive-Behavior Therapy or Group Metacognitive Therapy for Obsessive-Compulsive Disorder? Benchmarking and Comparative Effectiveness in a Routine Clinical Service

Cognitive-behavior therapy (CBT), delivered in an individual or group format, is the recommended treatment of choice for Obsessive-Compulsive Disorder (OCD), but no studies have benchmarked the outcomes for group CBT in real-world clinical settings. The first aim of this evaluation was to benchmark the outcomes for group CBT in a sample of 125 patients who attended a routine clinical service for OCD. The results showed that the outcomes for the group CBT were comparable to those reported in previous treatment studies. However, consistent with the CBT for OCD literature, 28% of patients receiving CBT reported minimal improvement. The second aim of this evaluation was to carry out a benchmarking analysis for group metacognitive therapy (MCT) to determine if this could provide any advantages in a sample of 95 patients who also attended this clinical service over a subsequent period. The clinically significant results obtained for group MCT improved upon or equaled those obtained for group CBT and those typically found in treatment studies. The group MCT cohort improved significantly more than the group CBT cohort even after controlling for important pre-treatment variables including age, gender, number of diagnoses, symptoms of depression, and psychotropic medication. MCT had significantly higher clinical response rates. Based on international expert consensus criteria, 86.3% of patients in the MCT cohort responded compared with 64% in CBT. The implications of these findings are discussed.
Antichronic Gastric Ulcer Effect of Zinc-Baicalin Complex on the Acetic Acid-Induced Chronic Gastric Ulcer Rat Model

Background Baicalin (BA) has been shown to have anti-inflammatory and antioxidant activity. Zinc is a nutrient element. Objective This study is aimed at investigating the antichronic gastric ulcer activity of Zn-Baicalin complex (BA-Zn) and its related mechanisms in an acetic acid-induced gastric ulcer rat model. Results The severely ulcerated gastric mucosa of model rats had lower GSH-Px (52.21 ± 7.13) and SOD (7.03 ± 0.10) activity, and higher MDA (2.39 ± 0.03) content compared to sham rats. BA-Zn reduced the gastric ulcer index in a dose-dependent manner, significantly increased SOD activity and GSH-Px level, and reduced the MDA content and IL-8 and TNF-α levels in the gastric mucosa. BA-Zn (6.5 and 13 mg/kg) exerted a greater antiulcerogenic effect than both BA and zinc-gluconate, leading to a reduced ulcer index (18.43 ± 1.11, 15.00 ± 1.44), decreased MDA content (1.33 ± 0.07, 0.63 ± 0.01), and increased SOD activity (17.62 ± 0.11, 20.12 ± 0.32) and GSH-Px levels (102.12 ± 9.11, 120.25 ± 9.07). In addition, our results from Western blot suggested that BA-Zn (6.5 and 13 mg/kg) has a greater antiulcerogenic effect than both BA and zinc-gluconate. Conclusion The BA-Zn complex possesses greater antichronic gastric ulcer properties compared to BA and zinc-gluconate due to its ability of oxidation resistance and anti-inflammatory effects.
STUDIES ON THE PATHOGENICITY OF GROUP A STREPTOCOCCI

A quantitative study of the combined antiphagocytic effects of the M protein and the hyaluronic acid capsules of four strains of Group A streptococci revealed the following facts relating to their intraperitoneal virulence in mice and rats: 1. The most virulent strain, S23M (matt), produced both a large hyaluronic acid capsule and a full complement of M protein, the combined effects of which rendered the organism highly resistant to surface phagocytosis. 2. The slightly less virulent strain, T14/46 (matt virulent) was somewhat more susceptible to surface phagocytosis owing to the fact that its smaller capsule was less antiphagocytic than that of the S23M organism. 3. The glossy variant of the S23 strain (S23G), which ranked third in virulence, was still more susceptible to surface phagocytosis because of its lack of detectable M substance. Its large hyaluronic acid capsule, however, was capable of protecting it against phagocytosis on glass. 4. The least virulent strain, T14 (matt avirulent), was the most susceptible of all to phagocytosis. Though it possessed both M substance and capsule, which together prevented its phagocytosis on glass, each of them was shown to be quantitatively and functionally deficient as compared to Strain S23M. The differences in phagocytability, which appear to be directly related to the pathogenicity of the organisms, could be adequately demonstrated in vitro only by phagocytic tests designed to measure surface phagocytosis in the absence of opsonins. This fact is in keeping with the observation, previously reported, that surface phagocytosis plays a critical role in the defense of the host, particularly during the earliest stages of experimental streptococcal infections. Its possible relation to suppuration during the later stages of infection is also discussed.
Effective Deep Multi-source Multi-task Learning Frameworks for Smile Detection, Emotion Recognition and Gender Classification

Automatic human facial recognition has been an active reasearch topic with various potential applications. In this paper, we propose effective multi-task deep learning frameworks which can jointly learn representations for three tasks: smile detection, emotion recognition and gender classification. In addition, our frameworks can be learned from multiple sources of data with different kinds of task-specific class labels. The extensive experiments show that our frameworks achieve superior accuracy over recent state-of-the-art methods in all of three tasks on popular benchmarks. We also show that the joint learning helps the tasks with less data considerably benefit from other tasks with richer data.
Nomogram application to predict overall and cancer-specific survival in osteosarcoma

Purpose A prognostic nomogram was applied to predict survival in osteosarcoma patients. Patients and methods Data collected from 2,195 osteosarcoma patients in the Surveillance, Epidemiology, and End Results (SEER) database between 1983 and 2014 were analyzed. Independent prognostic factors were identified via univariate and multivariate Cox analyses. These were incorporated into a nomogram to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates. Internal and external data were used for validation. Concordance indices (C-indices) were used to estimate nomogram accuracy. Results Patients were randomly assigned into a training cohort (n=1,098) or validation cohort (n=1,097). Age at diagnosis, tumor site, histology, tumor size, tumor stage, use of surgery, and tumor grade were identified as independent prognostic factors via univariate and multivariate Cox analyses (all P<0.05) and then included in the prognostic nomogram. C-indices for OS and CSS prediction in the training cohort were 0.763 (95% CI 0.761–0.764) and 0.764 (95% CI 0.762–0.765), respectively. C-indices for OS and CSS prediction in the external validation cohort were 0.739 (95% CI 0.737–0.740) and 0.740 (95% CI, 0.738–0.741), respectively. Calibration plots revealed excellent consistency between actual survival and nomogram prediction. Conclusion Nomograms were constructed to predict OS and CSS for osteosarcoma patients in the SEER database. They provide accurate and individualized survival prediction.
Visual Tracking Using Improved Multiple Instance Learning with Co-training Framework for Moving Robot

Object detection and tracking is the basic capability of mobile robots to achieve natural human–robot interaction. In this paper, an object tracking system of mobile robot is designed and validated using improved multiple instance learning algorithm. The improved multiple instance learning algorithm which prevents model drift significantly. Secondly, in order to improve the capability of classifiers, an active sample selection strategy is proposed by optimizing a bag Fisher information function instead of the bag likelihood function, which dynamically chooses most discriminative samples for classifier training. Furthermore, we integrate the co-training criterion into algorithm to update the appearance model accurately and avoid error accumulation. Finally, we evaluate our system on challenging sequences and an indoor environment in a laboratory. And the experiment results demonstrate that the proposed methods can stably and robustly track moving object.
Telemental Health in Low- and Middle-Income Countries: A Systematic Review

Introduction The rising incidence of mental illness and its impact on individuals, families, and societies is becoming a major public health concern, especially in resource-constrained countries. Consequently, there is an increasing demand for mental health services in many middle- and low-income countries (LMIC). Challenges such as inequality in access, lack of staff and hospital beds, and underfunding, often present in the LMIC, might in part be addressed by telemental health services. However, little is known about telemental health in the LMIC. Methods A systematic review was performed, drawing on several electronic databases, including PubMed, PsycINFO, Web of Science, Springer Link, and Google Scholar. Original English language studies on the practice of telemental health in LMIC, involving patients and published between 1 January 2000 and 16 February 2017, were included. Results Nineteen studies met the inclusion criteria. Most of the articles were recent, which may reflect an increasing focus on telemental health in the LMIC. Eight of these studies were from Asia. Eight of the studies were interventional/randomized controlled trials, and 11 examined general mental health issues. Videoconferencing was the most frequently (6) studied telemental modality. Other modalities studied were online decision support systems (3), text messaging and bibliotherapy (1), e-chatting combined with videoconferencing (1), online therapy (2), e-counseling (1), store-and-forward technology (1), telephone follow-up (1), online discussion groups (1), audiovisual therapy and bibliotherapy (1), and computerized occupational therapy (1). Although many of the studies showed that telemental services had positive outcomes, some studies reported no postintervention improvements. Conclusion The review shows a rising trend in telemental activity in the LMIC. There is a greater need for telemental health in the LMIC, but more research is needed on empirical and theoretical aspects of telemental activity in the LMIC and on direct comparisons between telemental activity in the LMIC and the non-LMIC.
Composing network service chains at the edge: A Resilient and adaptive software‐defined approach

The scale of data and the demand for high data rates in applications are rapidly increasing over the years. By moving the computing resources closer to the users, edge computing minimizes the latency caused by otherwise pulling the data between the user and a centralized platform. Thus, data centers and computing nodes at the edge continue to overtake or replace traditional centralized cloud platforms in various 5G applications and use cases. Network functions virtualization virtualizes dedicated hardware network middleboxes into virtual network functions (VNFs) and deploys them on top of servers and data centers. Due to the inherent bandwidth cost associated with the distance between the network services and the end user, more and more third‐party VNF providers choose to deploy their services at the edge, rather than in a centralized cloud. A typical network service chaining (NSC) consumes various network services, where one's output becomes the input of another. As network services are often latency sensitive, NSC needs to be carried out, maintaining proximity to the user as well as among the services composing the NSC. In this paper, we present the design of a resilient and adaptive framework, following an approach inspired by software‐defined networking, for the remote users to construct network service chains in the mobile and edge computing environments. Our evaluations highlight the efficiency and optimality of the framework in finding the best fit among several third‐party edge VNFs in deploying the user network service chains, abiding by various user policies.
Loss of horizontal macular ganglion cell complex asymmetry: an optical coherence tomography indicator of chiasmal compression

Objective To estimate the macular ganglion cell complex (GCC) asymmetry in patients with suprasellar tumours, to compare its diagnostic performance to the nasal GCC thickness and visual field (VF) and to investigate how the parameters correlate with magnetic resonance imaging (MRI) findings. Methods and analysis Cross-sectional study of patients with suprasellar tumours affecting the optic chiasm. Macular optical coherence tomography (OCT) scans were evaluated for nasal GCC sector thinning and loss of normal GCC asymmetry between corresponding nasal-temporal sectors. Equivalently, VFs were analysed for defects compatible with chiasm dysfunction. The relationship between optic chiasm and tumour was measured on MRI. Results Thirty-three eyes of 33 patients were included. There were OCT findings in 14 eyes. Nasal GCC thinning was found in 9 eyes and loss of GCC asymmetry in 12 eyes; the two parameters were not significantly different with respect to number of positive findings (p=0.45). Loss of GCC asymmetry, however, occurred in 5 eyes among 24 without GCC thinning (proportion 0.21; 95% confidence interval 0.071 to 0.42). In 8 eyes, VF indicated pathology; of these, 7 had concurring OCT findings. The prevalence of OCT and VF findings increased significantly with suprasellar tumour extension on MRI. Conclusion The diagnostic capabilities of nasal GCC thinning and loss of GCC asymmetry were comparable, whilst their complementary performances increased the proportion of eyes in which OCT suggested compression. The prevalence of both OCT and VF findings grew with suprasellar tumour extension. In several cases, however, structural findings on OCT preceded detectable VF deficits.
Diagnosing Vocal Disorders using Cobweb Clustering of the Jitter, Shimmer, and Harmonics-to-Noise Ratio

A voice is one of the most significant non-verbal elements for communication. Disorders in vocal organs, or habitual muscular setting for articulatory cause vocal disorders. Therefore, by analyzing the vocal disorders, it is possible to predicate vocal diseases. In this paper, a method of predicting vocal disorders using the jitter, shimmer, and harmonics-to-noise ratio (HNR) extracted from vocal records is proposed. In order to extract jitter, shimmer, and HNR, one-second’s voice signals are recorded in 44.1khz. In an experiment, 151 voice records are collected. The collected data set is clustered using cobweb clustering method. 21 classes with 12 leaves are resulted from the data set. According to the semantics of jitter, shimmer, and HNR, the class whose centroid has lowest jitter and shimmer, and highest HNR becomes the normal vocal group. The risk of vocal disorders can be predicted by measuring the distance and direction between the centroids.
A Pixel‐Based Framework for Data‐Driven Clothing

We propose a novel approach to learning cloth deformation as a function of body pose, recasting the graph‐like triangle mesh data structure into image‐based data in order to leverage popular and well‐developed convolutional neural networks (CNNs) in a two‐dimensional Euclidean domain. Then, a three‐dimensional animation of clothing is equivalent to a sequence of two‐dimensional RGB images driven/choreographed by time dependent joint angles. In order to reduce nonlinearity demands on the neural network, we utilize procedural skinning of the body surface to capture much of the rotation/deformation so that the RGB images only contain textures of displacement offsets from skin to clothing. Notably, we illustrate that our approach does not require accurate unclothed body shapes or robust skinning techniques. Additionally, we discuss how standard image based techniques such as image partitioning for higher resolution can readily be incorporated into our framework.
Combined DCT‐Haar transforms for image compression

Discrete Cosine Transform and Haar wavelet transform are very important transforms in image compression. The objective of this paper is to combine the advantages of these 2 transforms into one transform in order to get better peak‐signal‐to‐noise‐ratio (PSNR) and keeping good compression ratio. Our first approach was to apply separately on each 8x8 block the Haar and the DCT transforms. A signaling bit along the transform which gave better PSNR are quantized and transmitted. Our second approach was to construct a new hybrid transform which is a combination of these 2 transforms. We mixed both DCT and Haar transforms into one transform. Results show that our approach outperforms the existing DCT and Haar methods giving a higher PSNR than DCT for the same compression ratio, and permitting better edge recovery than the Haar transform.
Clinicopathological Significance and Antitumor Effect of MPHOSPH1 in Testicular Germ Cell Tumor

MPHOSPH1, which is one of the kinesin superfamily proteins, has been reported to play an essential role in the carcinogenesis and progression of several kinds of cancers. MPHOSPH1 has also been suggested to be involved in STAT3 phosphorylation in hepatocellular carcinoma. However, the biological behavior of MPHOSPH1 in testicular germ cell tumors (TGCTs) is unclear at present. The purposes of this study were to investigate the correlation between the expression of MPHOSPH1 and clinicopathological factors and to examine the efficacy of MPHOSPH1 target therapy in TGCTs. We investigated 75 formalin-fixed paraffin-embedded TGCT samples, containing a total of 86 germ cell tumor components, by immunohistochemistry and 12 frozen samples by Western blotting. Moreover, we carried out in vitro studies to clarify the antitumor effect of MPHOSPH1 knockdown in embryonal carcinoma cell lines, NEC8 and NEC14, using small interference RNA (siRNA). A significantly high expression of MPHOSPH1 was recognized in embryonal carcinoma and yolk sac tumor components compared to the seminoma component (p<0.001, respectively). Clinically, non-seminoma cases are known to have worse prognosis than pure-seminoma cases. Interestingly, high MPHOSPH1 expression was associated with distant metastasis (p=0.001), and thus with advanced-stage disease in this study. High expression of MPHOSPH1 interacted with high expression of phosphorylated STAT3 (p=0.01). The in vitro experiments demonstrated that MPHOSPH1 interruption by siRNA resulted in a significant reduction of cell migration, invasion, proliferation and colony formation in both embryonal carcinoma cell lines (p<0.001, respectively). In conclusion, MPHOSPH1 may be a potential treatment option for TGCTs, and its expression may be a novel biomarker of poor prognosis.
Association of diabetes-related self-care activities with glycemic control of patients with type 2 diabetes in Pakistan

Objective Association of various self-care activities on glycemic control of people with diabetes (PWD) in Pakistan is yet to be explored. The current study aimed to evaluate the association of various diabetes-related self-care activities with glycated hemoglobin (HbA1c) levels and to examine the predictive relationship of patients’ demographic variables with their self-care activities. Patients and methods A cross-sectional study was conducted on adult PWD (N=218) who were diagnosed with type 2 diabetes mellitus of at least 1 year duration. Self-care activities were examined by using the Urdu version of Diabetes Self-management Questionnaire. Linear regression analysis was conducted to examine the significant predictors for diabetes-related self-care activities and glycemic control. Results Mean age of the patients was 50.77±13.3 years. Poor glycemic control (HbA1c $7%) was observed in majority of the patients (83%). Linear regression analysis revealed that glucose management (β=−0.44; 95% CI −0.438, −0.209; P<0.001) was the strongest predictor for low levels of patients’ HbA1c, followed by dietary control (β=−0.19; 95% CI −0.248, −0.018; P=0.024) and physical activity (β=−0.17; 95% CI −0.165, −0.023; P=0.010), respectively. Linear regression analysis showed that use of oral hypoglycemic agents only (β=−0.218; 95% CI −0.956, −0.200; P=0.003) and higher education level (β=0.204; 95% CI 0.138, 0.777; P=0.005) were significant predictors for higher scores of patients’ self-care activities. Conclusion The findings support that PWD having better self-reported self-care activities achieve better glycemic control. Patients’ self-care activities should be monitored on a regular basis, especially for those who are at risk of poor glycemic control.
The Rising Era of Immune Checkpoint Inhibitors in Myelodysplastic Syndromes

Myelodysplastic syndromes (MDS) are a heterogeneous group of diseases characterized by ineffective hematopoiesis and a wide spectrum of manifestations ranging from indolent and asymptomatic cytopenias to acute myeloid leukemia (AML). MDS result from genetic and epigenetic derangements in clonal cells and their surrounding microenvironments. Studies have shown associations between MDS and other autoimmune diseases. Several immune mechanisms have been identified in MDS, suggesting that immune dysregulation might be at least partially implicated in its pathogenesis. This has led to rigorous investigations on the role of immunomodulatory drugs as potential treatment options. Epigenetic modification via immune check point inhibition, while well established as a treatment method for advanced solid tumors, is a new approach being considered in hematologic malignancies including high risk MDS. Several trials are looking at the efficacy of these agents in MDS, as frontline therapy and in relapse, both as monotherapy and in combination with other drugs. In this review, we explore the utility of immune checkpoint inhibitors in MDS and current research evaluating their efficacy.