Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Neuropsychology and Bayesian Inference

Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine ‘prior’ beliefs with a generative (predictive) model to explain the causes of sensations. Under this view, neuropsychological deficits can be thought of as false inferences that arise due to aberrant prior beliefs (that are poor fits to the real world). This draws upon the notion of a Bayes optimal pathology – optimal inference with suboptimal priors – and provides a means for computational phenotyping. In principle, any given neuropsychological disorder could be characterized by the set of prior beliefs that would make a patient’s behavior appear Bayes optimal. We start with an overview of some key theoretical constructs and use these to motivate a form of computational neuropsychology that relates anatomical structures in the brain to the computations they perform. Throughout, we draw upon computational accounts of neuropsychological syndromes. These are selected to emphasize the key features of a Bayesian approach, and the possible types of pathological prior that may be present. They range from visual neglect through hallucinations to autism. Through these illustrative examples, we review the use of Bayesian approaches to understand the link between biology and computation that is at the heart of neuropsychology.
Real-Time Action Recognition With Deeply Transferred Motion Vector CNNs

The two-stream CNNs prove very successful for video-based action recognition. However, the classical two-stream CNNs are time costly, mainly due to the bottleneck of calculating optical flows (OFs). In this paper, we propose a two-stream-based real-time action recognition approach by using motion vector (MV) to replace OF. MVs are encoded in video stream and can be extracted directly without extra calculation. However, directly training CNN with MVs degrades accuracy severely due to the noise and the lack of fine details in MVs. In order to relieve this problem, we propose four training strategies which leverage the knowledge learned from OF CNN to enhance the accuracy of MV CNN. Our insight is that MV and OF share inherent similar structures which allow us to transfer knowledge from one domain to another. To fully utilize the knowledge learned in OF domain, we develop deeply transferred MV CNN. Experimental results on various datasets show the effectiveness of our training strategies. Our approach is significantly faster than OF based approaches and achieves processing speed of 390.7 frames per second, surpassing real-time requirement. We release our model and code to facilitate further research.11https://github.com/zbwglory/MV-release
Patient Preferences for Clinician Interactional Style in Treatment of Perinatal Depression

Most women with depression around the time of childbearing are not treated adequately, or at all. Clinical practice guidelines focus primarily on provision of information rather than on interaction factors. In this study, we explored clinician interactional style characteristics contributing to patient response to perinatal depression referral and treatment. Stratified purposeful sampling resulted in 23 participants selected by pregnancy, socioeconomic, and depression status. Participants completed semistructured interviews exploring their experiences with and preferences for clinician interactional style characteristics in the context of obstetrics-setting referral and delivery of depression treatment. Thematic analysis revealed a central theme related to interactional cues that influence women’s reactions to clinical encounters, summarized by the question, “Can this person help me? ” Women evaluated this question in four domains: feeling heard, developing trust in the clinician, perceiving technical competence in the clinician, and feeling that the intervention focus is effectively chosen and communicated. Our results imply that, in addition to informational factors, the way in which clinicians interact with patients about depression might strongly influence patient responses.
Isolates from Alpinia officinarum Hance attenuate LPS‐induced inflammation in HepG2: Evidence from in silico and in vitro studies

In an attempt to connect the legacy of centuries of invaluable knowledge from traditional medicine and the current understanding to the molecular mechanism of diseases, we took the advantage of the emergence of in silico screening as a promising tool for identification of potential leads from libraries of natural products. Traditional Chinese Medicine database was subjected to structure based virtual screening for identification of anti‐inflammatory compounds using the 3D crystal structure of p38 alpha mitogen activated protein kinase. The molecular docking studies revealed the potential activity of several classes of compounds known to be the constituents of the rhizomes of Alpinia officinarum Hance (Lesser galangal). Five compounds, galangin, kaempferide, isorhamnetin, and two diarylheptanoids, were isolated from the rhizomes of the plant using vacuum liquid chromatography and flash chromatography techniques. The anti‐inflammatory activity of these compounds was investigated on HepG2 cells stimulated by lipopolysaccharide. The latter induced the gene expression of proinflammatory cytokines; interleukin‐1β, interleukin‐6, tumor necrosis factor alpha. Addition of the 5 isolated compounds downregulated this increased gene expression in a dose dependent manner. Thus, these results indicate that the isolated compounds from A. officinarum could be used as a beneficial source for preventing and treating inflammatory diseases.
Nitrate modulates stem cell dynamics in Arabidopsis shoot meristems through cytokinins

Significance Plants generate organs throughout their life as a consequence of the maintenance of postembryonic stem cell niches in meristems. The molecular mechanisms controlling stem cell homeostasis and organ emergence in shoot meristems have been well described, but the manner in which environmental signals influence them to generate plasticity is largely unknown. Using the shoot apical meristem of Arabidopsis as a model system, we show that plants can adapt their organogenesis rate to changes in the availability of nitrate in the soil within a few days, thanks to long-range signaling by cytokinin hormone precursors that travel through the plant, are converted to active hormones at the shoot meristem, and modulate the expression of WUSCHEL, a key regulator of stem cell homeostasis. The shoot apical meristem (SAM) is responsible for the generation of all the aerial parts of plants. Given its critical role, dynamical changes in SAM activity should play a central role in the adaptation of plant architecture to the environment. Using quantitative microscopy, grafting experiments, and genetic perturbations, we connect the plant environment to the SAM by describing the molecular mechanism by which cytokinins signal the level of nutrient availability to the SAM. We show that a systemic signal of cytokinin precursors mediates the adaptation of SAM size and organogenesis rate to the availability of mineral nutrients by modulating the expression of WUSCHEL, a key regulator of stem cell homeostasis. In time-lapse experiments, we further show that this mechanism allows meristems to adapt to rapid changes in nitrate concentration, and thereby modulate their rate of organ production to the availability of mineral nutrients within a few days. Our work sheds light on the role of the stem cell regulatory network by showing that it not only maintains meristem homeostasis but also allows plants to adapt to rapid changes in the environment.
Workability and quality control of concrete

The importance of workability standard tests for workability flow properties of fresh concrete principles of measurement the two-point workability test workability expressed in terms of two constants extremely low workability concretes factors affecting workability - time and properties of mix components effect of mix proportions effect of chemical admixtures effect of cement replacements and fibres workability and practical processes specification of workability workability measurement as a means of quality control.
Clinical and Pathologic Predictors of Lymph Node Metastasis and Recurrence in Papillary Thyroid Microcarcinoma.

BACKGROUND The treatment for patients with papillary thyroid microcarcinoma (PTMC) is controversial because PTMC is often found incidentally and its prognosis is very good. Lymph node metastasis (LNM) is one of the main predictors of recurrence and survival. This retrospective study aimed to identify clinical and pathologic factors that increase the risk of metastasis or recurrence, in order to isolate clinically unfavorable PTMCs to help guide therapy. METHODS Clinical and pathologic data were collected from 273 patients diagnosed with PTMC at The University of Chicago Medical Center between 2000 and 2011. Data points included age, sex, race/ethnicity, tumor size, multifocality, thyroiditis, extrathyroidal extension (ETE), surgical margins, preoperative clinical suspicion of cancer, central/lateral lymph nodes removed and lymph nodes with metastatic carcinoma, treatment, local recurrence, distant recurrence, and survival. RESULTS Multivariate logistic regression showed that age <45 years (odds ratio [OR] = 3.565 [confidence interval (CI) 1.137-11.177]), multifocality (OR = 3.556 [CI 1.066-11.855]), and ETE (OR = 4.622 [CI = 1.068-20.011]) significantly increased the risk of central LNM (CLNM). However, sex, size of tumor, thyroiditis, positive margins, and clinical suspicion were not correlated with an increased risk for CLNM. Multivariate logistic regression showed that only ETE (OR = 16.066 [CI 1.850-139.488]) significantly increased the risk of lateral LNM. In the cohort of 202 patients with follow-up data, only six recurred. Median time to recurrence was approximately 12 months (range 3.5-120 months), and median follow-up was 42 months. No patient had distant metastasis, and no patients died. CONCLUSIONS PTMC is an indolent disease, but does pose a risk for LNM and local recurrence. More aggressive treatment or more frequent follow-up could be considered for patients with unfavorable features (age <45 years, multifocality, ETE), especially in the setting of involved lymph nodes at the time of surgical resection, as these patients may be at an increased risk for recurrence.
Image super-resolution via deep dilated convolutional networks

Deep learning techniques have been successfully applied in single image super-resolution (SR). Recently, researches have shown that increasing the depth of network can significantly improve SR performance. Very deep networks for SR achieved a large improvement than former methods. However, simply increasing depths basically introduce more parameters and this lead to cumbersome computational cost. In this paper, we present a general and effective method to accelerate very deep networks for single image SR. Our method is based on dilated convolution operation, which support exponential expansion of the receptive field without increasing filter size. With the help of dilated convolution, shallow networks can achieve large receptive field and exploit contextual information in an efficient way. Based on a very deep network, we propose a 12 layers dilated convolutional network for SR (DCNSR). While accelerating 2x speed, our shallow network achieves better performance than original deep networks and shows state-of-the-art reconstructed results.
Zirconia in fixed implant prosthodontics.

BACKGROUND CAD/CAM technology in combination with zirconia ceramic has increasingly gained popularity in implant dentistry. PURPOSE This narrative review presents the current knowledge on zirconia utilized as framework material for implant-borne restorations and implant abutments, laboratory tests and developments, clinical performance, and possible future trends for implant dentistry are addressed. MATERIAL AND METHODS A review of available literature from 1990 through 2010 was conducted with search terms zirconia,""implants,""abutment,""crown," and "fixed dental prosthesis" using electronic databases (PubMed) and manual searching. RESULTS Latest applications of zirconia in implant dentistry include implant abutments, multiple unit and full-arch frameworks as well as custom-made bars to support fixed and removable prostheses. High biocompatibility, low bacterial surface adhesion as well as favorable chemical properties of zirconia ceramics are reported. Zirconia stabilized with yttrium oxide exhibits high flexural strength and fracture toughness due to a transformation toughening mechanism. Preliminary clinical data confirmed the high stability of zirconia for abutments and as a framework material for implant borne crowns and fixed dental prostheses. Zirconia abutment or framework damage has rarely been encountered. However, veneering porcelain fractures are the most common technical complication in implant-supported zirconia restorations. These porcelain veneer failures have led to concerns regarding differences in coefficient of thermal expansions between core and veneering porcelain and their respective processing techniques. CONCLUSION As presently evidence of clinical long-term data is missing, caution with regard to especially extensive implant-borne zirconia frameworks is recommended.
Feasibility of Activation Energy Prediction of Gas-Phase Reactions by Machine Learning.

Machine learning based on big data has emerged as a powerful solution in various chemical problems. We investigated the feasibility of machine learning models for the prediction of activation energies of gas-phase reactions. Six different models with three different types, including the artificial neural network, the support vector regression, and the tree boosting methods, were tested. We used the structural and thermodynamic properties of molecules and their differences as input features without resorting to specific reaction types so as to maintain the most general input form for broad applicability. The tree boosting method showed the best performance among others in terms of the coefficient of determination, mean absolute error, and root mean square error, the values of which were 0.89, 1.95, and 4.49 kcal mol-1 , respectively. Computation time for the prediction of activation energies for 2541 test reactions was about one second on a single computing node without using accelerators.
The influence of media suggestions about links between criminality and autism spectrum disorder

We examined whether media reports linking criminal behaviour and autism spectrum disorder foster negative attitudes towards individuals with autism spectrum disorder. In a between-subjects design, participants were exposed to (a) a media story in which a murderer was labelled with autism spectrum disorder (media exposure condition) or not labelled with any disorder (control) and (b) an autism spectrum disorder-education condition attacking the myth that people diagnosed with autism spectrum disorder are likely to be violent criminals or a no-autism spectrum disorder-education condition. Participants attitudes towards three different crime perpetrators (one with autism spectrum disorder) described in separate vignettes were probed. The media exposure linking crime and autism spectrum disorder promoted more negative attitudes towards individuals with autism spectrum disorder, whereas the positive autism spectrum disorder–related educational message had the opposite effect.
Obstetric and Perinatal Complications in Placentas with Fetal Thrombotic Vasculopathy

Fetal thrombotic vasculopathy (FTV) is a placental lesion characterized by regionally distributed avascular villi and is often accompanied by upstream thrombosis in placental fetal vessels. Previous studies, using preselected populations, have shown associations of this lesion with adverse neurodevelopmental outcomes and potentially obstructive lesions of the umbilical cord. We investigated the prevalence of obstetric complications, perinatal disease, and placental abnormalities in cases with FTV. One hundred thirteen cases of placentas with FTV were identified in our pathology database over an 18-year period. Two hundred sixteen placentas without the diagnosis of FTV, frequency matched on year of birth, were selected as controls. Electronic medical records and pathology reports were used to extract maternal and gestational age, method of delivery, neonatal outcome, lesions of the umbilical cord, obstetric complications, and fetal abnormalities. Placentas with FTV were associated with a 9-fold increase in rate of stillbirth and a 2-fold increase in intrauterine growth restriction. The increase in pregnancy-induced hypertension/preeclampsia was not significant when adjusted for maternal and gestational age. Although the rate of potentially obstructive cord lesions was similar in both groups, there was an almost 6-fold increase in the presence of oligohydramnios in FTV placentas, compared with controls. Finally, FTV was associated with a 6-fold increase in fetal cardiac abnormalities. Fetal thrombotic vasculopathy is associated with a significantly higher rate of obstetric and perinatal complications. This study points to abnormal fetal circulation, either in the form of congenital heart disease or oligohydramnios predisposing to cord compression, as a risk factor for FTV.
Comparison of outcomes of tyrosine kinase inhibitor in first- or second-line therapy for advanced non-small-cell lung cancer patients with sensitive EGFR mutations

Direct comparisons between the use of first- and second-line EGFR tyrosine kinase inhibitor (TKI) in patients with sensitive EGFR mutations are limited. A total of 264 advanced non-small-cell lung cancer (NSCLC) patients with sensitive mutations received EGFR TKI therapy as the first-line therapy, and a total of 187 patients received TKI as the second-line therapy at Shanghai Chest Hospital. First-line EGFR TKI therapy [12.9 months, 95% confidence interval (CI), 10.7–15.2] provided longer progression-free survival (PFS) than did second-line EGFR TKI therapy (9.0 months, 95% CI, 7.7–10.2) [hazard ratio (HR): 0.78, P = 0.034]. The objective response rate (ORR) of first-, and second-line TKI therapy were 67.8% (159/233) and 55.6% (94/169), respectively (P = 0.001). The overall survival (OS) for patients (n = 141) receiving first-line TKI followed by second-line chemotherapy were longer than those for patients (n = 187) receiving first-line chemotherapy followed by second-line TKI (HR: 0.69, P = 0.02). Compared with second-line TKI, first-line therapy achieved a significant and longer PFS, and higher ORR in the sensitive EGFR mutated NSCLC patients. The therapeutic strategy of using TKI followed by chemotherapy achieved longer OS than that using chemotherapy followed by TKI.
Porous graphitic carbon-based metabolomics and development of an alternative biomass-derived carbon stationary phase

In contrast to standard reversed-phase liquid chromatography (RP-LC) columns, porous graphitic carbon (PGC) stationary phase offers one solution to the separation of polar compounds. The unique retention mechanism of PGC, owing to its planar graphite-like sheet functionality, enables the separation of isomeric compounds. The use of RP-LC solvent systems allows direct coupling with electrospray mass spectrometry (ESI-MS) which enhances the types of analyses that can be performed with this stationary phase type still further. This thesis describes the use of on-line PGC-LC-ESI-MSn methods for the analysis of metabolites extracted from leaf blade samples from plant systems subjected to water deficit. The quantitative analysis of targeted carbohydrates in the resurrection plant Haberlea rhodopensis along with the untargeted analysis of water soluble metabolites in the model plant species Arabidopsis thaliana and Thellungiella salsuginea was performed. In addition, this thesis describes the optimisation of an alternative biomass-derived mesoporous carbon stationary phase, termed Starbon®, utilising the naturally porous material formed by expansion of the algal polysaccharide alginic acid in water. The effect of pyrolysis rate on the textural properties of Starbon® is investigated and shows that increased rates of pyrolysis reduce the inherent mesoporosity of the final carbon material. Several strategies are investigated in order to improve the particle size and morphology properties of Starbon®. These investigations have led to the development of a novel method of producing alginic acid-derived mesoporous carbon microspheres (AMCS). Commercial PGC, Starbon®, and AMCS-packed columns are compared in the separation of several carbohydrate standards. The column efficiency of the AMCS-packed column compares well to commercial PGC at low mobile phase flow rates. A study of the chemical microstructure of commercial PGC, Starbon®, and AMCS using microscopy and spectroscopy techniques is described. Starbon® and AMCS show abnormally high amounts of fullerene character compared to model non-graphitising carbons.
Prognostic impact of renin-angiotensin system blockade in esophageal squamous cell carcinoma

Introduction: The aim of this study is to evaluate whether the administration of renin-angiotensin system (RAS) inhibitors, angiotensin-I converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs), is associated with treatment outcome in patients with esophageal squamous cell carcinoma. Materials and methods: A total of 141 esophageal squamous cell carcinoma patients receiving esophagectomy were identified, and were divided into two groups: an ACEI/ARB group (n=20), and a non-ACEI/ARB group (n=121). The effect of ACEIs or ARBs on cell proliferation and vascular endothelial growth factor (VEGF) secretion of esophageal squamous cell carcinoma cell lines, CE81T/VGH and TE2, were investigated by 3-(4.5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and Enzyme-linked immunosorbent assay (ELISA), respectively. Results: Use of ACEI/ARB (p=0.032), pathologic T stage (p<0.001), pathologic N stage (p=0.012), tumor stage (p=0.006), and tumor location (p=0.032) were significantly associated with superior overall survival. In multivariate comparison, use of ACEI/ARB (p=0.006), tumor stage (p=0.002), and tumor location (p=0.014) represented the independent prognosticators of superior overall survival. In cell lines, ACEIs/ARBs inhibit cell proliferation and VEGF secretion in a dose-dependent manner. Conclusions: ACEIs/ARBs administration is independently associated with superior overall survival in patients with esophageal squamous cell carcinoma receiving esophagectomy. Our data support further investigation of the role of RAS inhibitors as a potential therapy in esophageal squamous cell carcinoma.