Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bayesian Density Model Based Radio Signal Fingerprinting Positioning Method for Enhanced Usability

Indoor navigation and location-based services increasingly show promising marketing prospects. Indoor positioning based on Wi-Fi radio signal has been studied for more than a decade because Wi-Fi, a signal of opportunity without extra cost, is extensively deployed for internet connections. Bayesian fingerprinting positioning, a classical Wi-Fi-based indoor positioning method, consists of two phases: radio map learning and position inference. Thus far, the application of Bayesian fingerprinting positioning is limited due to its poor usability; radio map learning requires an adequate number of received signal strength indication (RSSI) observables at each reference point, long-term fieldwork, and high development and maintenance costs. In this paper, based on a statistical analysis of actual RSSI observables, a Weibull–Bayesian density model is proposed to represent the probability density of Wi-Fi RSSI observables. The Weibull model, which is parameterized with three parameters that can be calculated with fewer samples, can calculate the probability density with a higher accuracy than the traditional histogram method. Furthermore, the parameterized Weibull model can simplify the radio map by storing only three parameters that can restore the whole probability density, i.e., it is not necessary to store the probability distribution based on traditionally separated RSSI bins. Bayesian positioning inference is performed in the positioning phase using probability density rather than the traditional probability distribution of predefined RSSI bins. The proposed method was implemented on an Android smartphone, and the performance was evaluated in different indoor environments. Results revealed that the proposed method enhanced the usability of Wi-Fi Bayesian fingerprinting positioning by requiring fewer RSSI observables and improved the positioning accuracy by 19–32% in different building environments compared with the classic histogram-based method, even when more samples were used.
Automatic Wrapper Generation for Search Engines Based on Visual Representation

Normally web databases are provides the information based on query representation. All the results are displayed without any structure. All extracted results are not provides any specific or perfect generation. It can contain some number of unnecessary, noisy and irrelevant web pages of information. These web database are not contains any interfaces implementation and cannot provide any desirable results specification. Present System is going to display with minimization results at extraction phase by implementing some of the machine processable techniques. These machine processable events are provides inheritance based results identification. We are going to implement some of the interfaces and wrappers and provide desired, accurate results representation. It can contain two types of extraction phase. First phase web data record extraction phase and web data item extraction phase. Each and every phase identifies the results like visual block tree, alignment of nodes process. We are going to extract the information based on Label and language independent process.
Business Fixed Investment and "Bubbles": The Japanese Case

The two key questions which motivate our work are: do bubbles exist (in the sense that stock market prices do not always correspond to the present value of expected future profitability) and, if bubbles exist, do they have an effect on business fixed investment? The case of Japan is particularly interesting because of the dramatic movements in the Japanese stock market and the wide perception that these were associated with a bubble. We use a variety of techniques to analyze these questions. Fist, we examine financing and investment patterns to gauge firms' reactions to the 1980s stock market run-up. Second, we test subsets of the orthogonality conditions associated with the empirical first-order conditions for fixed investment. Third, we use a linear projection to decompose stock market prices into fundamental and bubble components, allowing us to carry out parametric estimates of the effect of the bubble component on fixed investment. The data strongly suggest that there was a bubble that had an economically important statistically significant effect on business fixed investment in Japan.
German Cockroach Extract Induces Matrix Metalloproteinase-1 Expression, Leading to Tight Junction Disruption in Human Airway Epithelial Cells

Purpose Cockroach exposure is a pivotal cause of asthma. Tight junctions are intercellular structures required for maintenance of the barrier function of the airway epithelium, which is impaired in this disease. Matrix metalloproteinases (MMPs) digest extracellular matrix components and are involved in asthma pathogenesis: MMP1 is a collagenase with a direct influence on airway obstruction in asthmatics. This study aimed to investigate the mechanism by which German cockroach extract (GCE) induces MMP1 expression and whether MMP1 release alters cellular tight junctions in human airway epithelial cells (NCI-H292). Materials and Methods mRNA and protein levels were determined using real-time PCR and ELISA. Tight junction proteins were detected using immunofluorescence staining. Epithelial barrier function was measured by transepithelial electrical resistance (TEER). The binding of a transcription factor to DNA molecules was determined by electrophoretic mobility shift assay, while the levels of tight junction proteins and phosphorylation were determined using Western blotting. Results GCE was shown to increase MMP1 expression, TEER, and tight junction degradation. Both an inhibitor and small interfering RNA (siRNA) of MMP1 significantly decreased GCE-induced tight junction disruption. Furthermore, transient transfection with ETS1 and SP1 siRNA, and anti-TLR2 antibody pretreatment prevented MMP1 expression and tight junction degradation. An extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) inhibitor also blocked MMP1 release, ETS1/SP1 DNA binding, and tight junction alteration. Conclusion GCE treatment increases MMP1 expression, leading to tight junction disruption, which is transcriptionally regulated and influenced by the ERK/MAPK pathway in airway epithelial cells. These findings may contribute to developing novel therapeutic strategies for airway diseases.
Response of maize (zea mays L.) to green manure from varying populations of cowpea in a derived savannah of Nigeria

A field experiment was carried out at the Teaching and Research farm of the University of Agriculture, Abeokuta, located between longitude 70 15’ N and latitude 30 25’E, a derived savannah in south western Nigeria. The study was carried out between April to September 2009 and March to August 2010 to investigate the effect of varying populations of two local cowpea varieties of contrasting growth habits on green manure production, using maize as test crop. Three population densities each of cowpea varieties Oloyin and Drum, and the control plots were arranged in a Randomized Complete Block Design and replicated three times. Six weeks after planting, the green manure was uprooted and incorporated in situ. The incorporated green manure was left for a week after which maize variety- SUWAN-IY was planted on all plots. All populations of cowpea variety Oloyin gave significantly higher biomass than all the populations of Drum in 2009; the highest significant fresh biomass was produced at 111,111 plants/ha. In 2010, Drum at 160,000 plants/ha and Oloyin at 111,111 plants/ha produced similar plant biomass (p>0.05) and were significantly higher than all other treatments. However, cowpea variety Drum at 80,000 plants/ha and Oloyin at 55,555 appeared to be more economical relative to other treatments in terms of seed requirements for optimum biomass production and maize grain yield. In 2009 maize grain yield was not significantly different between treatments. In 2010 however, both maize grain yield and cob girth were significantly increased (p<0.05) on green manure plots. Maize grain yield increased by 37-98% and 89-147% on green manure plots in 2009 and 2010, respectively relative to the control plots. In maize production systems in the derived savannah of Nigeria, 55,555 plants/ha of Oloyin and 80,000 plants/ha of Drum could be recommended for green manuring. This will be of immense benefit to the resource- poor farmers in this ecological zone.
On inference in parametric survival data models

The usual parametric models for survival data are of the following form. Some parametrically specified hazard rate a(s, 0) is assumed for possibly censored random life times X, . ,X'; one observes only X, = min{X? , ci} and 6& = Ir{X < c,} for certain censoring times c, that either are given or come from some censoring distribution. We study the following problems: What do the maximum likelihood estimator and other estimators really estimate when the true hazard rate a(s) is different from the parametric hazard rates? What is the limit distribution of an estimator under such outside-the-model circumstances? How can traditional model-based analyses be made model-robust? Does the model-agnostic viewpoint invite alternative estimation approaches? What are the consequences of carrying out model-based and model-robust bootstrapping? How do theoretical and empirical influence functions generalise to situations with censored data? How do methods and results carry over to more complex models for life history data like regression models and Markov chains?
Intersecting crises: migration, the economy and the right to health in Europe.

The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. doi:10.1093/eurpub/cky224 . Intersecting crises: migration, the economy and the right to health in Europe
Virus-Derived Small Interfering RNAs Affect the Accumulations of Viral and Host Transcripts in Maize

RNA silencing is a conserved surveillance mechanism against invading viruses in plants, which involves the production of virus-derived small interfering RNAs (vsiRNAs) that play essential roles in the silencing of viral RNAs and/or specific host transcripts. However, how vsiRNAs function to target viral and/or host transcripts is poorly studied, especially in maize (Zea mays L.). In this study, a degradome library constructed from Sugarcane mosaic virus (SCMV)-inoculated maize plants was analyzed to identify the cleavage sites in viral and host transcripts mainly produced by vsiRNAs. The results showed that 42 maize transcripts were possibly cleaved by vsiRNAs, among which several were involved in chloroplast functions and in biotic and abiotic stresses. In addition, more than 3000 cleavage sites possibly produced by vsiRNAs were identified in positive-strand RNAs of SCMV, while there were only four cleavage sites in the negative-strand RNAs. To determine the roles of vsiRNAs in targeting viral RNAs, six vsiRNAs were expressed in maize protoplast based on artificial microRNAs (amiRNAs), of which four could efficiently inhibit the accumulations of SCMV RNAs. These results provide new insights into the genetic manipulation of maize with resistance against virus infection by using amiRNA as a more predictable and useful approach.
Cerebral autoinflammatory disease treated with anakinra

Interest in autoimmune encephalitis has been growing since the discovery of various autoimmune antibodies, such as N‐methyl D‐aspartate receptors antibody and leucine‐rich glioma‐inactivated 1 antibody. However, in contrast to autoimmune encephalitis associated with dysregulated adaptive immunity in the brain, the question of whether innate immunity‐mediated autoinflammatory diseases exist in the brain has drawn much attention. Herein, we report a patient with microglia‐dominant acute autoinflammatory encephalitis successfully treated with anakinra, an including interleukin‐1 receptor blocker. In comparison to systemic autoinflammatory disease, we term this encephalitis cerebral autoinflammatory disease. Cerebral autoinflammatory disease could suggest new conceptual approaches to patients previously diagnosed with an unspecified encephalitis.
Parson's programming puzzles: a fun and effective learning tool for first programming courses

Mastery of basic syntactic and logical constructs is an essential part of learning to program. Unfortunately, practice exercises for programming basics can be very tedious, making it difficult to motivate students. In this paper we describe Parson's Programming Puzzles, an automated, interactive tool that provides practice with basic programming principles in an entertaining puzzle-like format. Careful design of the items in the puzzles allows the tutor to highlight particular topics and common programming errors. Since each puzzle solution is a complete sample of well-written code, use of the tool exposes students to good programming practice. This paper discusses the motivation of Parson's Programming Puzzles, and gives several examples. We describe the web-based authoring tool used to build the puzzles, and present our plans for future development.
Challenges and Progress with Diagnosing Pulmonary Tuberculosis in Low- and Middle-Income Countries

Case finding and the diagnosis of tuberculosis (TB) are key activities to reach the World Health Organization’s End TB targets by 2030. This paper focuses on the diagnosis of pulmonary TB (PTB) in low- and middle-income countries. Sputum smear microscopy, despite its many limitations, remains the primary diagnostic tool in peripheral health facilities; however, this is being replaced by molecular diagnostic techniques, particularly Xpert MTB/RIF, which allows a bacteriologically confirmed diagnosis of TB along with information about whether or not the organism is resistant to rifampicin within two hours. Other useful diagnostic tools at peripheral facilities include chest radiography, urine lipoarabinomannan (TB-LAM) in HIV-infected patients with advanced immunodeficiency, and the loop-mediated isothermal amplification (TB-LAMP) test which may be superior to smear microscopy. National Reference Laboratories work at a higher level, largely performing culture and phenotypic drug susceptibility testing which is complemented by genotypic methods such as line probe assays for detecting resistance to isoniazid, rifampicin, and second-line drugs. Tuberculin skin testing, interferon gamma release assays, and commercial serological tests are not recommended for the diagnosis of active TB. Linking diagnosis to treatment and care is often poor, and this aspect of TB management needs far more attention than it currently receives.
An Improved S-Metric Selection Evolutionary Multi-Objective Algorithm With Adaptive Resource Allocation

One of the main disadvantages of evolutionary multi-objective algorithms (EMOAs) based on hypervolume is the computational cost of the hypervolume computation. This deficiency gets worse either when an EMOA calculates the hypervolume several times or when it is dealing with problems having more than three objectives. In this sense, some researchers have designed strategies to reduce the number of hypervolume calculations. Among them, the use of the locality property of the hypervolume has emerged as an alternative to deal with this problem. This property states that if a solution is moving in its neighborhood, only its contribution is affected and the contributions of the rest of the solutions remain the same. In this paper, we present a novel evolutionary approach that exploits the locality property of the hypervolume. The proposed approach adopts a probability to use two or three individuals in its environmental selection procedure. In this way, it only needs to compute two or three hypervolume contributions per iteration. The proposed algorithm is evaluated by solving the standard benchmark test problems and two real-world applications where the features of the problems are unknown. According to the results, the proposed approach is a promising alternative for solving problems with a high number of objectives because of three main reasons: 1) it is competitive with respect to the state-of-the-art EMOAs based on hypervolume; 2) it does not need extra information about the problem (which is particularly essential when solving real-world applications); and 3) its computational cost is much lower than the other hypervolume-based EMOAs.
Cardiac Function and Type of Mitral Valve Surgery Affect Postoperative Blood Flow Pattern in the Left Ventricle.

BACKGROUND To determine the impact of cardiac function and type of mitral valve (MV) surgery on blood flow and energy loss in the left ventricle (LV). Methods and Results: This study enrolled patients with ejection fraction (EF) <35% or >50%; both groups had native (n=27 and n=16), repaired (n=19 and n=33), or prosthetic MVs (n=18 and n=19). They were examined by echocardiography-based vector flow mapping to assess the LV blood flow pattern and energy loss per heartbeat. Among patients with preserved EF, those with native MVs displayed a clockwise vortex and relatively low energy loss. In contrast, MV replacement induced a counterclockwise vortex producing higher energy loss than MV repair, which induced a normal clockwise vortex. This indicated the need for MV repair to minimize LV energy loss after surgery. Among the patients with reduced EF, those with native MVs showed a blood flow pattern similar to those with preserved EF and native MVs; furthermore, those with repaired MVs and half of the patients with prosthetic MVs displayed a clockwise vortex, resulting in no difference in energy loss between the 2 types of MV surgery. CONCLUSIONS Cardiac function and the type of MV surgery are factors affecting the postoperative LV blood flow pattern. MV replacement resulted in abnormal blood flow with normal cardiac function, whereas advanced cardiomyopathy modified the blood flow pattern post-MV replacement.
Analysis of End-of-Life Content in Selected Introductory Health Education Textbooks

The quantity and quality of end of life (EOL) information in commonly used introductory health textbooks was studied. A total of 12 textbooks were identified and rated for the presence of helpful information in eight EOL domains. Content for each domain was rated as absent, minimally present, or helpful. Prior reviews of medical, nursing, pharmacy, psychology, and social work texts have revealed inadequate coverage of EOL care. EOL material contained in introductory health education textbooks seemed to modestly surpass that which has been reported in these comparable reviews. A more comprehensive and broader review of EOL in health education texts needs to be undertaken. For those employed in the health education profession, there needs to be some discussion about what role the health educator can play with respect to EOL care.
Numerical Investigation of Bone Tumor Hyperthermia Treatment Using Magnetic Scaffolds

This works claims to define, via numerical simulations, magnetic field parameters to perform an effective in situ bone tumor hyperthermia treatment using magnetic scaffolds. A Cole-Cole model to describe the frequency response of the magnetic susceptibility of nanoparticles embedded in novel magnetic biomaterials is explored. The heating phenomenon is investigated, considering both the ischemic and inflamed state of the fracture gap at the bone/implants interface. Both Osteosarcoma and Fibrosarcoma tumors are analyzed. Magnetic hydroxyapatite and poly-ϵ-caprolactone scaffolds are investigated. From the thermal analysis, it is found that the fracture behaves as a resistance to heat conduction, and therefore, strength and frequency of external magnetic field has to be tuned to perform the treatment taking the fracture status into account. Moreover, numerical experiments indicate that low perfused Fibrosarcoma can be treated using moderate-strength field, whereas more intense external fields are required to treat strongly vascularized Osteosarcoma without damaging healthy bone tissue. Magnetic hydroxyapatite stands out to be the best performing and versatile material to treat both tumors. These simulations can be regarded as a starting point to analyze possible clinical use of magnetic scaffolds for in situ bone hyperthermia.
MY Camelopardalis, a very massive merger progenitor

Context. The early-type binary MY Cam belongs to the young open cluster Alicante 1, embedded in Cam OB3. Aims. MY Cam consists of two early-O type main-sequence stars and shows a photometric modulation suggesting an orbital period slightly above one day. We intend to confirm this orbital period and derive orbital and stellar parameters. Methods. Timing analysis of a very exhaustive (4607 points) light curve indicates a period of 1.1754514 +- 0.0000015 d. High- resolution spectra and the cross-correlation technique implemented in the TODCOR program were used to derive radial velocities and obtain the corresponding radial velocity curves for MY Cam. Modelling with the stellar atmosphere code FASTWIND was used to obtain stellar parameters and create templates for cross-correlation. Stellar and orbital parameters were derived using the Wilson-Devinney code, such that a complete solution to the binary system could be described. Results. The determined masses of the primary and secondary stars in MY Cam are 37.7 +- 1.6 and 31.6 +- 1.4 Msol, respectively. The corresponding temperatures, derived from the model atmosphere fit, are 42 000 and 39 000 K, with the more massive component being hotter. Both stars are overfilling their Roche lobes, sharing a common envelope. Conclusions. MY Cam contains the most massive dwarf O-type stars found so far in an eclipsing binary. Both components are still on the main sequence, and probably not far from the zero-age main sequence. The system is a likely merger progenitor, owing to its very short period.
Source and Response of Antibody to Hepatitis B Vaccine in Hemodialysis Patients

Background and Aims: All chronic hemodialysis patients for hepatitis B infection have to be tested and vaccinated against HBV infection routinely. Methods: A descriptive study was designed in 47 hemodialysis patients. After a blood sample was taken for serologic status, three doses (0, 1, 6 month) of hepatitis B vaccine were administered. Repeated titers were obtained one month after the last vaccination and analyzed by ELISA. Results: 39 patients (83%) became immune with protective levels of HBs antibody. There was not a significant correlation between sex, age, smoking, underlying diseases, weight, duration of dialysis and positive HBs antibody after vaccination. Conclusions: Hmodialysis patients need follow-up testing.
Minimum weight norm models do not always generalize well for over-parameterized problems

Stochastic gradient descent is the de facto algorithm for training deep neural networks (DNNs). Despite its popularity, it still requires fine tuning in order to achieve its best performance. This has led to the development of adaptive methods, that claim automatic hyper-parameter optimization. Recently, researchers have studied both algorithmic classes via toy examples: e.g., for over-parameterized linear regression, Wilson et. al. (2017) shows that, while SGD always converges to the minimum-norm solution, adaptive methods show no such inclination, leading to worse generalization capabilities. Our aim is to study this conjecture further. We empirically show that the minimum weight norm is not necessarily the proper gauge of good generalization in simplified scenaria, and different models found by adaptive methods could outperform plain gradient methods. In practical DNN settings, we observe that adaptive methods can outperform SGD, with larger weight norm output models, but without necessarily reducing the amount of tuning required.