Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of types of delusions and hallucinations with childhood abuse and neglect among inpatients with schizophrenia in South Korea: A preliminary study

ABSTRACT This study examined the association of several types of childhood trauma with types of delusions and hallucinations among 42 younger adult inpatients with a diagnosis of schizophrenia at a university-affiliated hospital in South Korea. Participants were administered the Childhood Trauma Questionnaire – short form and the Scale for Assessment of Positive symptoms. Emotional abuse had a positive correlation with delusions of reference, persecutory delusions, and delusions of being controlled. There was no statistically significant relationship between childhood abuse/neglect and hallucinations. The contents of some delusions reflected adverse childhood experiences, indicating a need for further exploration of the contribution of childhood trauma to current psychotic symptoms.
The Identification of Three Cancer Stem Cell Subpopulations within Moderately Differentiated Lip Squamous Cell Carcinoma

Aim To identify and characterize cancer stem cells (CSCs) in moderately differentiated lip squamous cell carcinoma (MDLSCC). Method MDLSCC samples underwent 3,3-diaminobenzidine (DAB) immunohistochemical (IHC) staining for squamous cell carcinoma marker EMA, CSC marker CD44 and embryonic stem cell markers NANOG, octamer-binding transcription factor 4 (OCT4), spalt-like transcription factor 4 (SALL4), sex-determining region Y-box 2 (SOX2), and phosphorylated signal transducer and activator of transcription 3 (pSTAT3). Immunofluorescent IHC staining was performed on two MDLSCC samples. Western blotting (WB) was used to confirm the expression of the aforementioned proteins and their transcription activation was investigated using NanoString and RT-qPCR. Results IHC staining demonstrated the presence of (1) an EMA+/CD44+/SALL4+/NANOG+/pSTAT3+/SOX2+/OCT4− CSC subpopulation within the tumor nests (TNs); (2) a CD44+/SALL4+/NANOG+/pSTAT3+/SOX2+/OCT4− CSC subpopulation; and (3) a CD44+/SALL4+/NANOG+/pSTAT3+/SOX2+/OCT4+ CSC subpopulation within the stroma, between the TNs. NanoString and RT-qPCR confirmed the presence of mRNA for CD44, SALL4, STAT3, SOX2, and OCT4, and WB confirmed the presence of NANOG, pSTAT3, SOX2, and OCT4. Conclusion This study demonstrates three putative CSC subpopulations within MDLSCC.
Cost-Aware Scalability of Applications in Public Clouds

Scalable applications deployed in public clouds can be built from a combination of custom software components and public cloud services. To meet performance and/or cost requirements, such applications can scale-out/in their components during run-time. When higher performance is required, new component instances can be deployed on newly allocated cloud services (e.g., virtual machines). When the instances are no longer needed, their services can be deallocated to decrease cost. However, public cloud services are usually billed over predefined time and/or usage intervals, e.g., per hour, per GB of I/O. Thus, it might not be cost efficient to scale-in public cloud applications at any moment in time, without considering their billing cycles. In this work we aid developers of scalable applications for public clouds to monitor their costs, and develop cost-aware scalability controllers. We introduce a model for capturing the pricing schemes of cloud services. Based on the model we determine and evaluate the application's costs depending on its used cloud services and their billing cycles. We further evaluate cost efficiency of cloud applications, analyzing which application component is cost efficient to deallocate and when. We evaluate our approach on a scalable platform for IoT, deployed in Flexiant, one of the leading European public cloud providers. We show that cost-aware scalability can achieve higher application stability and performance, while reducing its operation costs.
Random Parameter Sampling of a Generic Three-Tier MAPK Cascade Model Reveals Major Factors Affecting Its Versatile Dynamics

The mitogen-activated protein kinase (MAPK) pathway is considered to be a central block in many biological signaling networks. Despite the common core cascade structure, the activation of MAPK in different biological systems can exhibit different types of dynamic behaviors. Computer modeling may help to reveal the mechanisms underlying such variations. However, so far most computational models of the MAPK cascade have been system-specific, or to reflect a particular type among the wide spectrum of possible dynamics. To obtain a general and integrated view of the relationship between the dynamics of MAPK activation and the structures and parameters of the MAPK cascade, we constructed a generic model by comparing previous models covering different specific biological systems. We assumed that reliable qualitative results could be predicted through a qualitative model with pseudo parameters. We used randomly sampled parameters instead of a specific set of “best-fit” parameters to avoid biases towards any particular systems. A range of dynamics behaviors for MAPK activation, including ultrasensitivity, bistability, transient activation and oscillation, were successfully predicted by the generic model. The results indicated that the steady state dynamics (ultrasensitivity and bistability) was jointly determined by the three-tiered structure of the MAPK cascade and the competitive substrate binding in the dual-phosphorylation processes of the central components, while the temporal dynamics (transient activation and oscillation) was mainly affected by the upstream signaling pathway and feedbacks. Moreover, MAPK kinase (MAPKK) played more important roles than the other two components in determining the dynamics of MAPK activation. We hypothesize that this is an important and advantageous property for the regulation and for the functional diversity of MAPK pathways in real cells. Finally, to assist developing generic models for signaling motifs through model comparisons, we proposed a reaction-based database to make the model data more flexible and interoperable.
Rapid prototyped porous nickel–titanium scaffolds as bone substitutes

While calcium phosphate–based ceramics are currently the most widely used materials in bone repair, they generally lack tensile strength for initial load bearing. Bulk titanium is the gold standard of metallic implant materials, but does not match the mechanical properties of the surrounding bone, potentially leading to problems of fixation and bone resorption. As an alternative, nickel–titanium alloys possess a unique combination of mechanical properties including a relatively low elastic modulus, pseudoelasticity, and high damping capacity, matching the properties of bone better than any other metallic material. With the ultimate goal of fabricating porous implants for spinal, orthopedic and dental applications, nickel–titanium substrates were fabricated by means of selective laser melting. The response of human mesenchymal stromal cells to the nickel–titanium substrates was compared to mesenchymal stromal cells cultured on clinically used titanium. Selective laser melted titanium as well as surface-treated nickel–titanium and titanium served as controls. Mesenchymal stromal cells had similar proliferation rates when cultured on selective laser melted nickel–titanium, clinically used titanium, or controls. Osteogenic differentiation was similar for mesenchymal stromal cells cultured on the selected materials, as indicated by similar gene expression levels of bone sialoprotein and osteocalcin. Mesenchymal stromal cells seeded and cultured on porous three-dimensional selective laser melted nickel–titanium scaffolds homogeneously colonized the scaffold, and following osteogenic induction, filled the scaffold’s pore volume with extracellular matrix. The combination of bone-related mechanical properties of selective laser melted nickel–titanium with its cytocompatibility and support of osteogenic differentiation of mesenchymal stromal cells highlights its potential as a superior bone substitute as compared to clinically used titanium.
Who Wrote this Novel? Authorship Attribution across Three Languages

Based on different writing style definitions, various authorship attribution schemes have been proposed to identify the real author of a given text or text excerpt. In this article we analyze the relative performance of word types or lemmas assigned to re-present styles and texts. As a second objective we compare two authorship attribu-tion approaches, one based on principal component analysis (PCA), and a new au-thorship attribution method involving specific vocabulary (Z score classification scheme). As a third goal we carry out our experiments on data from three corpora written in three different languages (English, French, and German). In the first we ca-tegorize 52 text excerpts (taken from 19th century English novels) written by nine au-thors. In the second we work with 44 segments taken from French novels (mainly 19th century) written by eleven authors. In the third we extract 59 German text excerpts written by 15 authors and covering the 19th and early 20th centuries. Based on these collections and two specific features (word types or lemmas) we demonstrate that the Z score method performs better than the PCA, while demonstrating that lemmas tend to produce slightly better performance than word types.
A Study on NNS Teachers’ Language Awareness

The goal of the study is to examine non-native speaking (NNS) English teachers’ language awareness in relation to their metalinguistic knowledge and language proficiency. Data was collected from sixty-two (N=62) NNS in-service teachers who had teaching experiences in South Korea and forty-four (N=44) NS pre-service teachers in a TESOL certificate or degree program in the U.S. All participants were asked to complete a series of tests to check their levels of metalinguistic knowledge (MK). The tests of MK consisted of 34 test items asking participants’ grammaticality judgement and 15 items of metalanguage use. In addition, NNS participants answered a self-report questionnaire of their English language proficiency (LP). The results from the tests and questionnaire were examined using t-tests, correlation, and regression analyses. The findings indicated that the NNS group performed differently on the tests of two types of MK; the NNS group outperformed the NS group on the test of metalanguage use knowledge, whereas the NS group performed better than the NNS group on the test of grammaticality judgement. Also it was found that the scores of grammaticality judgement in the NNS group were correlated to the scores of LP at statistically significant levels. In regression analysis, the grammatical judgement on the indefinite article appeared to be the only predictor of LP. Implications and suggestions from the findings are discussed.
SNIPE for Memory-Limited PCA From Incomplete Data

The linear subspace model is pervasive in science and engineering and particularly in large datasets which are often incomplete due to missing measurements and privacy issues. Therefore, a critical problem in modeling is to develop algorithms for estimating a low-dimensional subspace model from incomplete data efficiently in terms of both computational complexity and memory storage. In this paper we study an algorithm that processes blocks of incomplete data to estimate the underlying subspace model. Our algorithm has a simple interpretation as optimizing the subspace to fit the observed data block but remain close to the previous estimate. We prove a linear rate of convergence for the algorithm and our rate holds with high probability.
Endoscopic Management of Portal Hypertension

Cirrhosis is the leading cause of portal hypertension worldwide, with the development of bleeding gastroesophageal varices being one of the most life-threatening consequences. Endoscopy plays an indispensible role in the diagnosis, staging, and prophylactic or active management of varices. With the expected future refinements in endoscopic technology, capsule endoscopy may one day replace traditional gastroscopy as a diagnostic modality, whereas endoscopic ultrasound may more precisely guide interventional therapy for gastric varices.
Application of computer-assisted interviews to sexual behavior research.

Collection of sensitive data with the use of video-enhanced, computer-assisted, self-administered interviews (V-CASI) has the potential to reduce interview bias and improve the validity of the study. The purpose of this study was to compare responses to sensitive questions elicited by V-CASI and by face-to-face interview (FTFI) methods. Women attending a New Orleans, Louisiana, public family planning or sexually transmitted disease clinic from July 1995 to July 1996, diagnosed with a Chlamydia trachomatis infection responded to eight close-ended behavioral questions (four socially undesirable, two socially desirable, and two neutral behaviors) using both FTFI and V-CASI techniques in a randomized crossover design. Of the 280 women included, the mean age was 23 years, 95 percent were African American, and 71 percent felt comfortable using computers. While kappa scores indicated good-to-excellent agreement between interview techniques, women tended to admit to socially undesirable behaviors more often on V-CASI compared with FTFI. Thirty percent of the women gave a discrepant response between V-CASI and FTFI toward social desirability. Women who reported a socially undesirable behavior in V-CASI (i.e., more than two sex partners and infrequent condom usage) were more likely to have a discrepant response. Utilization of the same logistic regression model to predict condom use yielded different results when data from V-CASI were used compared with data from FTFI. The V-CASI technique can reduce social desirability bias and improve validity in research requiring information on sensitive sexual behaviors.
Using Mutual Information Criterion to Design an Effective Lexicon for Chinese Pinyin-to-Character Conversion

Pinyin-to-character (P2C) conversion is mostly used to input Chinese characters into a computer. Its main problem is homophone words, which is solved through exploiting contextual information provided by lexicon and n-gram language model (LM). Our investigation about the state-of-the-art P2C technologies reveals that the methods of conventional optimization for them were almost based on minimizing text perplexity, however it is not directly related to the optimization of P2C performance. Therefore, we propose to use a new optimization criterion: mutual information (MI) between text corpus and its Pinyin script, to do self-supervised word segmentation, build a lexicon and estimate an n-gram LM, then use them to build P2C system. We realized the P2C system using newspaper corpus. Compared with the two baseline systems using handcrafted lexicon and perplexity based optimized lexicon, our system got relatively 19.7% and 10.3% error reductions on testing corpus respectively. The results show the efficiency of our proposal.
Detection and update method for attack behavior models in intrusion detection systems

Intrusion Detection Systems (IDSes) are very essential in network monitoring. Most IDSes store a large number of attack signatures and produce various alert logs. There are two problems in detection and update method of current IDSes. First, it is hard to decide which alerts will lead to real intrusion in the network systems because of massive amount of log data sent to the administrator. Second, it is known that signatures for bad network packets are stored in the database. As new attacks are recorded, the size of the database increases. In this paper, we proposed a Petri net-based method to detect attack behavior that leads to intrusion thus reducing number of alerts. Then, we proposed an update method by fusing two or more similar attack behavior models. Finally, we showed the effectiveness of those methods with an example and experiment.
Can CA-125 Predict Lymph Node Metastasis in Epithelial Ovarian Cancers in Turkish Population?

Objective. The role of single preoperative serum CA-125 levels in predicting pelvic or paraaortic lymph node metastasis in patients operated for epithelial ovarian cancer has been investigated. Methods. 176 patients diagnosed with epithelial ovarian carcinoma after staging laparotomy between January 2002 and May 2010 were evaluated retrospectively. Results. The mean, geometric mean, and median of preoperative serum CA-125 levels were 632,6, 200,29, and 191,5 U/mL, respectively. The cut-off value predicting lymph node metastases in the ROC curve was 71,92 U/mL, which is significant in logistic regression analysis (P = 0.005). The preoperative log CA-125 levels were also statistically significant in predicting lymph node metastasis in logistic regression analysis (P = 0.008). Conclusions. The tumor marker CA-125, which increases with grade independent of the effect of stage in EOC, is predictive of lymph node metastasis with a high rate of false positivity in Turkish population. The high false positive rate may obscure the predictive value of CA-125.
How abstract is risk for workers ?

Two studies were performed to test whether abstract concepts are grounded in experience and activate introspective/linguistic information. In Study 1, four groups of participants, each with different expertise in the domain of safety and security at the workplace (S&S), defined abstract concepts belonging to the S&S domain and differing in degree of abstractness. The definitions included mainly situations, confirming grounding of abstract concepts. In Study 2 the task was performed by students with no experience of S&S. The definitions were modulated by participants’ expertise; the role of introspection increased with more abstract concepts. Results support embodied theories on abstract concepts.
Breaking size segregation waves and particle recirculation in granular avalanches

Particle-size segregation is a common feature of dense gravity-driven granular free-surface flows, where sliding and frictional grain–grain interactions dominate. Provided that the diameter ratio of the particles is not too large, the grains segregate by a process called kinetic sieving, which, on average, causes the large particles to rise to the surface and the small grains to sink to the base of the avalanche. When the flowing layer is brought to rest this stratification is often preserved in the deposit and is known by geologists as inverse grading. Idealized experiments with bi-disperse mixtures of differently sized grains have shown that inverse grading can be extremely sharp on rough beds at low inclination angles, and may be modelled as a concentration jump or shock. Several authors have developed hyperbolic conservation laws for segregation that naturally lead to a perfectly inversely graded state, with a pure phase of coarse particles separated from a pure phase of fines below, by a sharp concentration jump. A generic feature of these models is that monotonically decreasing sections of this concentration shock steepen and eventually break when the layer is sheared. In this paper, we investigate the structure of the subsequent breaking, which is important for large-particle recirculation at the bouldery margins of debris flows and for fingering instabilities of dry granular flows. We develop an exact quasi-steady travelling wave solution for the structure of the breaking/recirculation zone, which consists of two shocks and two expansion fans that are arranged in a ‘lens’-like structure. A high-resolution shock-capturing numerical scheme is used to investigate the temporal evolution of a linearly decreasing shock towards a steady-state lens, as well as the interaction of two recirculation zones that travel at different speeds and eventually coalesce to form a single zone. Movies are available with the online version of the paper.
Fungal pan-sinusitis with severe visual loss in uncontrolled diabetes.

INTRODUCTION Invasive fungal pan-sinusitis can present atypically with severe acute visual loss with minimal anterior orbital inflammation. We describe 2 such cases with a background of uncontrolled diabetes. CLINICAL PICTURE Respective clinical presentations of orbital apex and cavernous sinus syndromes were associated with isolation of Aspergillus galactomannan and Rhizopus. TREATMENT Urgent extensive surgical debridement and systemic antifungal is necessary. OUTCOME Clinical improvement of the ocular motor nerves can be expected within 2 months of treatment but visual loss is usually permanent. CONCLUSION Underlying pansinusitis is an important differential for acute visual loss, especially in uncontrolled diabetics. Early treatment determines outcome.
Path Weights, Networked Partial Correlations and their Application to the Analysis of Genetic Interactions

Gene coexpression is a common feature employed in predicting buffering relationships that explain genetic interactions, which constitute an important mechanism behind the robustness of cells to genetic perturbations. The complete removal of such buffering connections impacts the entire molecular circuitry, ultimately leading to cellular death. Coexpression is commonly measured through Pearson correlation coefficients. However, Pearson correlation values are sensitive to indirect effects and often partial correlations are used instead. Yet, partial correlation values convey no information on the (linear) influence of the association within the entire multivariate system or, in other words, of the represented edge within the entire network. Jones and West (2005) showed that covariance can be decomposed into the weights of the paths that connect two variables within the corresponding undirected network. Here we provide a precise interpretation of path weights and show that, in the particular case of single-edge paths, this interpretation leads to a quantity we call networked partial correlation whose value depends on both the partial correlation between the intervening variables and their association with the rest of the multivariate system. We show that this new quantity correlates better with quantitative genetic interactions in yeast than classical coexpression measures.
A scale-out RDF molecule store for distributed processing of biomedical data

The computational analysis of protein-protein interaction and biomolecular pathway data paves the way to efficient in silico drug discovery and therapeutic target identification. However, relevant data sources are currently distributed across a wide range of disparate, large-scale, publicly-available databases and repositories and are described using a wide range of taxonomies and ontologies. Sophisticated integration, manipulation, processing and analysis of these datasets are required in order to reveal previously undiscovered interactions and pathways that will lead to the discovery of new drugs. The BioMANTA project focuses on utilizing Semantic Web technologies together with a scale-out architecture to tackle the above challenges and to provide efficient analysis, querying, and reasoning about protein-protein interaction data. This paper describes the initial results of the BioMANTA project. The fully-developed system will allow knowledge representation and processing that are not currently available in typical scale-out or Semantic Web databases. We present the design of the architecture, basic ontology and some implementation details that aim to provide efficient, scalable RDF storage and inferencing. The results of initial performance evaluation are also provided.