Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing product specifications to solve the cold start problem in a recommender system

Recommender systems are widely used applications to solve the problems of information overload, usually on websites. A well-known problem of recommender systems is the problem of cold start, which is caused by the lack of data. A recommendation system can only produce good recommendations after it has accumulated enough data The problem becomes even more challenging when the recommender system comes to deal with new products or the products have not been evaluated by consumers. This paper addresses this problem based on a comparison of product specifications, experiments were conducted in the recommendation domain of digital cameras.
Phaseguide-based optofluidic router for parallel analysis of serum samples

A phaseguide-based optofluidic router (PHASOR) is presented. By using phaseguides, DI-water can be pinned in the required angle so that light incident undergoes total internal reflection and can be reflected towards one of the six output channels without movable parts. In addition, the PHASOR is coupled to two enzymatically-functionalized photonic lab on a chip (PhLoC). Using real rat serum samples, we were able to monitor L-Lactate and Glucose in real time using a single light source.
Neutrophil gelatinase-associated lipocalin as a biomarker of cardiovascular disease: a systematic review

Abstract Background: Neutrophil gelatinase-associated lipocalin (NGAL) is a biomarker of acute kidney injury (AKI). Recently, elevated NGAL levels have also been reported in heart failure, coronary heart disease, and stroke. Other studies demonstrate that NGAL is upregulated in failing myocardium and in atherosclerotic plaque. Our aim was to synthesize the current evidence on NGAL and cardiovascular disease (CVD), and to clarify the prognostic significance of systemic NGAL levels in CVD. Methods: We performed a systematic review to identify experimental and human studies on NGAL and CVD. We excluded articles which specifically dealt with AKI or renal endpoints. Results: We identified 22 studies, including both animal and human data. NGAL is highly expressed in the heart, both in failing myocardium and myocarditis, and is also expressed in atherosclerotic plaques. Areas of co-localization of NGAL and matrix metalloproteinase (MMP)-9 exhibited increased MMP-9 proteolytic activity. Systemic NGAL levels correlated with renal function and severity of CVD in several, but not all, studies. An association between elevated systemic NGAL levels and clinical outcomes (e.g., death, hospital readmissions) were reported in six CVD studies, but these had limited adjustment for potential confounders. Conclusions: There is ample literature to support a putative role of NGAL in the pathophysiology of CVD, but at present there is insufficient data regarding the clinical utility of systemic NGAL levels in the management of CVD. Available evidence regarding NGAL as a predictor of outcomes in CVD is very limited.
Bmp2 is required for cephalic neural tube closure in the mouse

BMPs have been shown to play a role in neural tube development particularly as dorsalizing factors. To explore the possibility that BMP2 could play a role in the developing neural tube (NT) beyond the lethality of Bmp2 null embryos, we created Bmp2 chimeras from Bmp2 null ES cells and WT blastocysts. Analysis of Bmp2 chimeras reveals NT defects at day 9.5 (E9.5). We found that exclusion of Bmp2 null ES cells from the dorsal NT did not always prevent defects. For further comparison, we used a Bmp2 mutant line in a mixed background. Phenotypes observed were similar to chimeras including open NT defects, postneurulation defects, and abnormal neural ectoderm in heterozygous and homozygous null embryos demonstrating a pattern of dose‐dependent signaling. Our data exposes BMP2 as a unique player in the developing NT for dorsal patterning and identity, and normal cephalic neural tube closure in a dose‐dependent manner. Developmental Dynamics 238:110–122, 2009. Published 2008 Wiley‐Liss, Inc.
Finite Element Model of Aero Turbine Blades Investment Casting Process Based on Hypermesh

Mesh quality refers to the rational mesh geometry shape. Mesh quality will influence the precision of calculating, and poor quality will even stop calculation. Hypermesh is a finite element processor with high-performance; it can effectively solve the problems of FEM model establishment. This paper adopts Hypermesh to establish the complicated turbine blade FEM model; Not only the data integrity of the model is checked, but also the quality of mesh is examined. The file interface between Hypermesh and ProCAST is also established, which can simplify the simulation process. The methods which have been proposed in this paper can provide an accurate and simple way to analysis the complex turbine blades investment casting process based on numerical simulation technology.
Linear Logic for Non-Linear Storytelling

Whilst narrative representations have played a prominent role in AI research, there has been a renewed interest in the topic with the development of interactive narratives. A typical approach aims at generating narratives from baseline action representations, most often using planning techniques. However, this research has developed empirically, often as an application of planning. In this paper, we explore a more rigorous formalisation of narrative concepts, both at the action level and at the plot level. Our aim is to investigate how to bridge the gap between action descriptions and narrative concepts, by considering the latter from the perspective of resource consumption and causality. We propose to use Linear Logic, often introduced as a logic of resources, for it provides, through linear implication, a better description of causality than in Classical and Intuitionistic Logic. Besides advances in the fundamental principles of narrative formalisation, this approach can support the formal validation of scenario description as a preliminary step to their implementation via other computational formalisms.
Non-parametric Survival Analysis for Breast Cancer Using non-medical Data

Breast cancer is a major health problem in many parts of the world. Breast cancer has the highest prevalence rate among women in Saudi Arabia. This study aim to review the validity and workability of semi and non-parametric survival models in non-medical data. The methodology of sisterhood method for mortality data collection is used, by designing questionnaire. Non-medical variables; age, residence, weight, family history, fertility and marital status are used to show the differences in survival analysis. A total of 32 female breast cancer cases were studied. The results indicates that premenopausal, fertile cases were more survive and more diagnosis, while obese cases and those who live in Umluj were less survive and more diagnosis. The median survival time is (82.64) with mean age at diagnosis (45.59). The proportion surviving from general 10year survival study was decreased gradually with the time interval and the hazard rate increase shortly with the time interval. صهخخسمنا مناعنا هم ءاضخأ ًف تٍحص تهكشم يذثنا ناطشس ذعٌ , تٌدُعسنا ًف ءاسىنا هٍب ساشخوا لذعم ىهعأ مدس . تٍحلاص حٍضُح ىنإ تساسذنا يزٌ فذٍح تٍبطنا شٍغ ثاواٍبنا ًهع ءاقبنا جرامو قٍبطح تٍهعافَ . ثاواٍبنا عمدن ثاُخلأا تقٌشط تٍدٍىم جماذخخسا . تٍمهعمنا شٍغَ ًبش جرامىنا جمذخخسا ثاواٍبنا مٍهحخن . تٍبطنا شٍغ ثاشٍغخمنا : تبُصخنا ،نصُنا ،تماقلإا ناكم ،شمعنا , ثافلاخخلاا ساٍظلإ جمذخخسا تٍعامخخلاا تناحناَ ًهئاعنا خٌساخنا ةاٍحنا ذٍق ىهع ءاقبنا ًف . هم توُكم تىٍعنا 32 يذثنا ناطشسبحاباصمنا داولاا هم . مبق ام ةشخف ًف داولاا َ ثابصخنا داولاا نأ جىٍب حئاخىنا ذٍق ىهع أءاقب مقأ جواك حهمأتىٌذم مخاذىشٍعٌ ًئلانا َ تىمسنا ثلااح نأ هٍح ًف ،ضشمناب تباصا مقاَةاٍحنا ذٍق ًهع ءاقب شثكأ ذمطنا عاطقوا تباصا شثكاَ ةاٍحنا . ةاٍحنا ذٍق ًهعءاقبنا ظسُخم ( 82.64 ) صٍخشخنا ذىع شمعنا ظسُخم َاشٍش ( 45.6 ) . ذىع ةاٍحنا ذٍق ىهع هٍقابنا تبسو جضفخوا ةذمن تساسذنا قٍبطح 10 ثاُىس , همضناعم اٍدٌسذح , همضنا عم ءظبب ةسُطخنا ثلاذعم ثداص هٍح ًف .
Recent Progress on Liver Kinase B1 (LKB1): Expression, Regulation, Downstream Signaling and Cancer Suppressive Function

Liver kinase B1 (LKB1), known as a serine/threonine kinase, has been identified as a critical cancer suppressor in many cancer cells. It is a master upstream kinase of 13 AMP-activated protein kinase (AMPK)-related protein kinases, and possesses versatile biological functions. LKB1 gene is mutated in many cancers, and its protein can form different protein complexes with different cellular localizations in various cell types. The expression of LKB1 can be regulated through epigenetic modification, transcriptional regulation and post-translational modification. LKB1 dowcnstream pathways mainly include AMPK, microtubule affinity regulating kinase (MARK), salt-inducible kinase (SIK), sucrose non-fermenting protein-related kinase (SNRK) and brain selective kinase (BRSK) signalings, etc. This review, therefore, mainly discusses recent studies about the expression, regulation, downstream signaling and cancer suppressive function of LKB1, which can be helpful for better understanding of this molecular and its significance in cancers.
A sensitivity analysis of soil moisture retrieval from the tau-omega microwave emission model

The potential of the /spl tau/--/spl omega/ model for retrieving the volumetric moisture content of bare and vegetated soil from dual-polarization passive microwave data acquired at single and multiple angles is tested. Measurement error and several additional sources of uncertainty will affect the theoretical retrieval accuracy. These include uncertainty in the soil temperature, the vegetation structure, and consequently its microwave single-scattering albedo, and uncertainty in soil microwave emissivity based on its roughness. To test the effects of these uncertainties for simple homogeneous scenes, we attempt to retrieve soil moisture from a number of simulated microwave brightness temperature datasets generated using the /spl tau/--/spl omega/ model. The uncertainties for each influence are estimated and applied to curves generated for typical scenarios, and an inverse model used to retrieve the soil moisture content, vegetation optical depth, and soil temperature. The effect of each influence on the theoretical soil moisture retrieval limit is explored, the likelihood of each sensor configuration meeting user requirements is assessed, and the most effective means of improving moisture retrieval indicated.
A Randomized, Double-blinded, Open Label Study of the Efficacy and Safety of Cefcapene Pivoxil and Amoxicillin·Clavulanate in Acute Presumed Bacterial Rhinosinusitis

Objectives Currently established first line therapy of acute (presumed bacterial) rhinosinusitis (ARS) consists of 10 to 14 days of oral amoxicillin or cephalosporins. This study compared the clinical efficacy and tolerance of cefcapene pivoxil (CP) and amoxicillin-clavulanate (AMC) in patients with ARS. Methods A randomized, open labeled, double-blinded trial of ARS patients over 15 years of age was performed. Patients diagnosed with ARS received paranasal sinus X-rays and nasal endoscopies and 2 weeks of either CP (150 mg, 3 times/ day) or AMC (625 mg, amoxicillin 500 mg, 3 times/day). All patients revisited the clinic on days 7, 14, and 28 for evaluation of changes in symptoms, endoscopy, and monitoring of any adverse reactions. Demographics, clinical characteristics and drug efficacy were also compared between the two groups. Results Among the 60 initially enrolled patients (CP 30, AMC 30), 5 patients in the CP group and 6 in the AMC group were excluded due to poor compliance. There were no significant differences in demographic data including age, sex, initial signs and symptoms, endoscopic and X-ray findings between the two groups. Rates of improvement after 2 weeks were 96% and 95.8% in the CP and AMC group, respectively. Sinus symptoms were changed significantly after 2 and 4 weeks, however, there was no difference between groups (P=0.41). The most common adverse reaction was gastrointestinal complication, diarrhea occurred in 1 patient in the CP group and 6 in the AMC group (P=0.04). Conclusion CP and AMC were both effective in treating ARS. The difference of treatment outcome was not found between the two groups, however, gastrointestinal complications were less prevalent in the CP group.
Specific Detection and Typing of Mycoplasma synoviae Strains in Poultry with PCR and DNA Sequence Analysis Targeting the Hemagglutinin Encoding Gene vlhA

Abstract Mycoplasma synoviae is a major pathogen of chickens and turkeys, causing economic losses to the poultry industry worldwide. In this study, we validated and applied polymerase chain reaction (PCR) and DNA sequence analysis on the N-terminal end of the hemagglutinin encoding gene vlhA as an alternative for the detection and initial typing of field strains of M. synoviae in commercial poultry. PCR primers were tested against isolates of M. synoviae from various sources along with other avian mycoplasma and other bacterial species. The vlhA gene–targeted PCR assay was highly specific in the identification of M. synoviae, with a detection limit of 4.7 × 102 color changing units /ml. DNA sequence analysis of amplified products was also conducted to validate the potential for typing M. synoviae strains using the N-terminal region of the vlhA gene. To evaluate the test, we applied the PCR assay to tracheal swabs collected from chickens challenged with M. synoviae strain K1968 and compared the results to the serologic detection. The PCR assay was also evaluated directly on tracheal samples collected from commercial layers. Overall, this vlhA gene–targeted PCR is a useful tool for detection and initial typing of M. synoviae and can be applied in the preliminary identification of M. synoviae isolates directly from clinical samples.
Cyber Hate Classification: 'Othering' Language And Paragraph Embedding

Hateful and offensive language (also known as hate speech or cyber hate) posted and widely circulated via the World Wide Web can be considered as a key risk factor for individual and societal tension linked to regional instability. Automated Web-based hate speech detection is important for the observation and understanding trends of societal tension. In this research, we improve on existing research by proposing different data mining feature extraction methods. While previous work has involved using lexicons, bags-of-words or probabilistic parsing approach (e.g. using Typed Dependencies), they all suffer from a similar issue which is that hate speech can often be subtle and indirect, and depending on individual words or phrases can lead to a significant number of false negatives. This problem motivated us to conduct new experiments to identify subtle language use, such as references to immigration or job prosperity in a hateful context. We propose a novel 'Othering Lexicon' to identify these subtleties and we incorporate our lexicon with embedding learning for feature extraction and subsequent classification using a neural network approach. Our method first explores the context around othering terms in a corpus, and identifies context patterns that are relevant to the othering context. These patterns are used along with the othering pronoun and hate speech terms to build our 'Othering Lexicon'. Embedding algorithm has the superior characteristic that the similar words have a closer distance, which is helpful to train our classifier on the negative and positive classes. For validation, several experiments were conducted on different types of hate speech, namely religion, disability, race and sexual orientation, with F-measure scores for classifying hateful instances obtained through applying our model of 0.93, 0.95, 0.97 and 0.92 respective.
Translation and validation of the Nursing Outcomes Classification labels and definitions for acute care nursing in Iceland.

BACKGROUND The Nursing Outcomes Classification (NOC), second edition, consists of 260 patient outcomes with definitions. This has been translated into five languages, but has not been clinically validated outside the United States of America (USA). AIM The aim of this paper is to describe the translation of the labels and definitions from the NOC, second edition from English to Icelandic and validation for acute-care nursing in Iceland. METHOD A survey that has been designed to identify nurses' perception of the percentage of patients' for whom each NOC outcome is relevant in clinical nursing practice was used for clinical validation in this study. The translation procedure involved source to target language translation, parallel comparison, pilot test and field test. Validation included test-retest to measure the reliability for each of the 260 outcome variables. Data collected from 140 clinical nurses from 54 departments within 13 nursing specialties at Landspitali University-Hospital in Iceland, in November 2001, were analysed to establish construct validity by confirmatory factor analysis. Internal consistency was calculated. RESULTS Translation was successful. Test-retest showed that 181 of the 260 NOC outcomes were significant (P < 0.05) and moderately or highly correlated (r > 0.50) (Pearson's correlation). The confirmatory factor analysis showed that 22 of the 29 NOC classes had only one factor at the loading criteria > or =0.30. Of the 260 outcomes, 244 had loading on one factor (> or =0.30) within its class. Internal consistency was >0.80 (Cronbach's alpha). LIMITATIONS Low response rate was a limitation. The indicators of each NOC outcome were not addressed. CONCLUSION The Icelandic version of the NOC survey is a comprehensive tool that can be applied to nursing in acute-care for research purposes as well as to prepare for the implementation of NOC in clinical information systems.
Review of Functional Magnetic Resonance Imaging Language Mapping in Patients with Epilepsy

In cases where patients with epilepsy require surgery to help reduce the frequency and severity of their seizures, information about the areas of the brain involved with language function, such as the anterior temporal pole, can be valuable in predicting and minimising language difficulties that may arise after brain surgery. The aim of the project was to first evaluate the current group of functional magnetic resonance imaging (fMR.I) language tasks used in the Epilepsy Centre of St Vincent's Hospital Melbourne (SVHM). This group of task included sentence completion, verbal fluency, and picture-naming tasks. Secondly, two new language tasks, reading and semantic decision-making were examined in an attempt to improve upon the existing battery's ability to detect anterior temporal pole activation for patients undergoing anterior temporal lobectomy. Healthy controls and patients with epilepsy performed tasks in the original battery on one of two standard 1.5 tesla MRI scanners (an older Siemen Magnetom or a newer Siemen Avanto). With the older scanner, the sentence completion task was the only original SVHM fMRI language task to show consistent activation. In contrast, with the newer scanner, all four original tasks, along with the new reading and semantic decision tasks, demonstrated consistent language activation when thinner slices covering a larger area were obtained. When used on the newer MRI imager, the new reading, the picture naming, and the sentence completion tasks produce the highest levels of anterior temporal lobe activation. The reading and picture naming tasks tended to show more temporal lobe activation, while the semantic decision and verbal fluency tasks tended to show more frontal lobe activation. Practical and theoretical implications of the research for presurgical fMRI evaluation are discussed.
Spectral sparsification of simplicial complexes for clustering and label propagation

As a generalization of the use of graphs to describe pairwise interactions, simplicial complexes can be used to model higher-order interactions between three or more objects in complex systems. There has been a recent surge in activity for the development of data analysis methods applicable to simplicial complexes, including techniques based on computational topology, higher-order random processes, generalized Cheeger inequalities, isoperimetric inequalities, and spectral methods. In particular, spectral learning methods (e.g. label propagation and clustering) that directly operate on simplicial complexes represent a new direction for analyzing such complex datasets. To apply spectral learning methods to massive datasets modeled as simplicial complexes, we develop a method for sparsifying simplicial complexes that preserves the spectrum of the associated Laplacian matrices. We show that the theory of Spielman and Srivastava for the sparsification of graphs extends to simplicial complexes via the up Laplacian. In particular, we introduce a generalized effective resistance for simplices, provide an algorithm for sparsifying simplicial complexes at a fixed dimension, and give a specific version of the generalized Cheeger inequality for weighted simplicial complexes. Finally, we introduce higher-order generalizations of spectral clustering and label propagation for simplicial complexes and demonstrate via experiments the utility of the proposed spectral sparsification method for these applications.
MacPherson suspension system modeling and control with MDP

Simulation-based non-linear active suspension control design for MacPherson systems is considered. A nonlinear dynamic model for the MacPherson suspension system is derived. The model nonlinearities and the dynamic behaviour of the system is illustrated by simulations. The design of controllers and state estimators using finite state Markov models is briefly outlined, and applied for nonlinear active suspension control system. The study illustrates the potential of the finite Markov chains approach in non-linear active suspension control, emphasizing the possibility to move computational load due to simulations to off-line design.
Evidence of Vertical Transmission of Dengue Virus in Two Endemic Localities in the State of Oaxaca, Mexico

Background: Dengue virus is spread in tropical areas of the world and is the causative agent of dengue fever and dengue hemorrhagic fever. It is horizontally transmitted to humans by infected Aedes mosquitoes, but it is also able to be vertically or transovarially transmitted to insect progeny. Objective: In this work, we analyzed the vertical transmission of dengue virus in Aedes aegypti mosquitoes collected in two endemic localities in the state of Oaxaca, Mexico. Methods: The collected larvae were grown in the laboratory and transovarial transmission of dengue virus, either in larvae or newly emerged mosquitoes, was investigated using a semi-nested reverse transcription-polymerase chain reaction method. Results: Although the presence of dengue virus in larvae could not be demonstrated, the viral genome was amplified in 4 out of 43 pools of in-cage born mosquitoes: DEN 2, 3 and 4 serotypes were detected in 2 pools from Tuxtepec and two from Juchitán. Conclusion: The results presented here strongly suggest that dengue virus can be vertically transmitted in mosquitoes from Oaxaca, but more studies will be necessary to analyze the epidemiological impact of this mechanism of transmission.