Miracle-dz/UniFAR-FTUs huggingface dataset:
Educated Cities and Regional Centralization: Spatial Trends in Students' Location in Denmark, 1982-2013

This paper provides an overview of Danish student to population ratios in post-primary education from 1982 to 2013. Using administrative register data I document a nationally increased share of enrolled students to population over the 32 years period. The increase followed a pattern of regional centralization where the shares of students rose significantly more in urban municipalities than non-urban municipalities. The highest shares of students as well as fastest increases were seen in the municipalities of the four largest cities, Copenhagen, Århus, Odense, and Aalborg. At the national level, the increases in shares of students to population was driven by medium length and long tertiary as well as high school enrollment. The tertiary enrolled students, however, were unproportionally centred in the urban municipalities. Non-urban municipalities had relatively higher levels of high school and vocational education students to population both in 1982 and 2013. The paper is concluded with suggestions for future research linking these patterns of regional centralization to challenges such as technological skill-bias and an increasing importance of continuous learning, as well as inequality and social mobility. ∗The following paper has been prepared for the Center for Research on Regional Dynamics and Disparities (ReDy) at Aalborg University. Ina Drejer, Jacob Rubæk Holm, Linh T. Tô, Katherine Stolerman, Søren Etzerodt, Jørgen Goul Andersen, Anders Kamp Høst, and Mogens Lassen have provided helpful comments and suggestions.
Minimizing liver, bowel, and gastric activity in myocardial perfusion SPECT.

UNLABELLED When using 99mTc-tetrofosmin for myocardial perfusion SPECT, increased liver, intestinal, or gastric activity may create a major problem in the visual and quantitative interpretation Of the inferoposteroseptal walls, particularly at rest. The aim of this study was to determine what measures were required to minimize this extracardial activity. METHODS Ninety-seven patients had a SPECT scan at rest without attenuation correction. They were divided into 3 groups. Preparation consisted of no action taken (group 1), 150 mL whole milk 10 min after administration of tetrofosmin (group 2), or 450 mL water 10 min before acquisition (group 3). A further 55 patients had a SPECT scan at rest with attenuation correction. They were also divided into 3 groups, and preparation consisted of 150 mL whole milk 10 min after administration of tetrofosmin (group 4), 450 mL water 10 min before acquisition (group 5), or both whole milk and water (group 6). The presence of activity in liver, bowel, and stomach was determined visually on reconstructed images. Activity was defined as interfering when it might result in either an underestimation or an overestimation of the uptake in the myocardial wall. RESULTS Interfering activity was seen in 83% of the patients in group 1, in 74% in group 2, in 33% in group 3, in 61% in group 4, in 67% in group 5, and in 20% of group 6. CONCLUSION The interpretation of inferoposteroseptal wall activity on myocardial rest SPECT images is facilitated by having the patient drink both whole milk and water at specified times before data acquisition.
Experimental study of effect of low-dose tacrolimus on acute spinal cord injury in rats

Objective:To explore the effect of low-dose tacrolimus on acute spinal cord injury(SCI)in rats.Method:A total of 72 male rats were divided randomly into three groups:the sham-operative group(n=12),the injury group(n=30)and the test group(n=30)treated with tacrolimus,while the latter two groups were subjected to SCI at the T10 level with a weight-drop impactor(10g weight was dropped from a 4.0 cm height). The rats in tacrolimus group were injected with tacrolimus 0.3mg/kg 5 minutes after SCI,while the other groups received equivalent amount of 0.9% normal saline likewise.Neurological function,histopathological examination of injured spinal cord and detection of the apoptosis of neural cells by the terminal deoxynucleotidyl transferase-mediated deoxyuredine triphosphate-digoxin nick end labeling(TUNEL)method were assessed at certain time point after SCI.Result:The inclined plate test scores and BBB scales in the tacrolimus group were significantly higher than those in the injured group at 3? 7? 14? 21d after SCI respectively(P0.05). Hemorrhage and necrosis in injured epicenter of the tacrolimus group were less serious than those of the injury group all time after SCI.The amount of TUNEL-positive cells were significantly less in the tacrolimus group than in the injury groupat 6? 24? 48? 72h after SCI(P0.05). Conclusion:Low-dose tacrolimus possesses neuroprotective effect on neuron after acute spinal cord injury in rats,which can reduce apoptosis of neural cells,attenuate secondary spinal cord injury and thus improve neurological function recovery.
METHADONE DOSAGE INTRODUCTION AND REGULATION FOR PATIENTS ON METHADONE MAINTENANCE TREATMENT

Objective:To summary methadone dosage introduction and regulation for patients on methadone maintenance treatment(MMT). Methods:We analyzed 566 medical records of patients on MMT from June 20,2005 to December 31,2006 at the MMT clinic of Liuzhou Disease Prevention and Control Center(CDC). Results:Initial dosage and superaddition on the first day, dosage and superaddition on the second day were established according to the quantity of heroin use by the patients. However the initial dosage for all patients was less than 50 mg and the dose added for the following day less than 30 mg. The lowest dosage for maintenance was 10-35 mg.Conclusion:Adoption of this method for methadone dosage introduction and regulation for patients on MMT is safe and suitable at MMT clinics, which is worth recommendation.
PACLP: a fine-grained partition-based access control policy language for provenance

Even though the idea of partitioning provenance graphs for access control was previously proposed, employing segments of the provenance DAG for fine-grained access control to provenance data has not been thoroughly explored. Hence, we take segments of a provenance graph, based on the extended OPM, and defined use a variant of regular expressions, and utilize them in our fine-grained access control language. It can not only return partial graphs to answer access requests but also introduce segments as restrictions in order to screen targeted data.
The Polycyclic Aromatic Hydrocarbon (PAH) degradation activities and genome analysis of a novel strain Stenotrophomonas sp. Pemsol isolated from Mexico

Background Stenotrophomonas are ubiquitous gram-negative bacteria, which can survive in a wide range of environments. They can use many substances for their growth and are known to be intrinsically resistant to many antimicrobial agents. They have been tested for biotechnological applications, bioremediation, and production of antimicrobial agents. Method Stenotrophomonas sp. Pemsol was isolated from a crude oil contaminated soil. The capability of this isolate to tolerate and degrade polycyclic aromatic hydrocarbons (PAH) such as anthraquinone, biphenyl, naphthalene, phenanthrene, phenanthridine, and xylene was evaluated in Bushnell Hass medium containing PAHs as the sole carbon sources. The metabolites formed after 30-day degradation of naphthalene by Pemsol were analyzed using Fourier Transform Infra-red Spectroscopic (FTIR), Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and Gas Chromatography-Mass Spectrometry (GC-MS). The genome of Pemsol was also sequenced and analyzed. Results Anthraquinone, biphenyl, naphthalene, phenanthrene, and phenanthridine except xylene can be used as sole carbon sources for Pemsol’s growth in Bushnell Hass medium. The degradation of naphthalene at a concentration of 1 mg/mL within 30 days was tested. A newly formed catechol peak and the disappearance of naphthalene peak detected on the UPLC-MS, and GC-MS analyses spectra respectively confirmed the complete degradation of naphthalene. Pemsol does not produce biosurfactant and neither bio-emulsify PAHs. The whole genome was sequenced and assembled into one scaffold with a length of 4,373,402 bp. A total of 145 genes involved in the degradation of PAHs were found in its genome, some of which are Pemsol-specific as compared with other 11 Stenotrophomonas genomes. Most specific genes are located on the genomic islands. Stenotrophomonas sp. Pemsol’s possession of few genes that are associated with bio-emulsification gives the genetic basis for its inability to bio-emulsify PAH. A possible degradation pathway for naphthalene in Pemsol was proposed following the analysis of Pemsol’s genome. ANI and GGDH analysis indicated that Pemsol is likely a new species of Stenotrophomonas. It is the first report on a complete genome sequence analysis of a PAH-degrading Stenotrophomonas. Stenotrophomonas sp. Pemsol possesses features that make it a good bacterium for genetic engineering and will be an excellent tool for the remediation of crude oil or PAH-contaminated soil.
Classification of Twitter Data Set using SVM and KSVM

Social media is used by every individual people to express, communicate and convey their feelings, opinion, experiences, sentiments and emotions. Data mining is a new technology applied in these matters. Twitter is such a social media used for processing. The categorization of emotions or sentiments was carried out using SVM and KSVM. Linear and quantitative inner product of two points were defined as kernel function. The twitter data set is divided into training data set and test data set using random normal distribution and probability normal distribution. In rnorm of KSVM, number of support vectors is minimum where asit is maximum in normal svm. The linear separability features are visualized by R software programming. Keywords— Social Media; Twitter; SVM; KSVM; Classification;
THE EFFECTS OF INTELLECTUAL CAPITAL ON E-SERVICE INNOVATION

With the emergence of knowledge-based economy, intellectual capital has been a critical factor to assist companies to obtain competitive advantage in this fierce environment. In addition, how to enhance the organizational capability to create service innovation has also been a top priority for most contemporary firms. This study adopted the knowledge-based theory to explore and propose the influences of intellectual capital on e-service innovation and further examines the mediating effects of internal cross-functional integration and external collaborative competency on intellectual capital and e-service innovation, as well as the moderating effects of technology orientation.
Prevalence of pressure ulcer in Iran's intensive care units: A systematic review and meta-analysis

1 Student Research Committee, Kurdistan University of Medical Sciences, Sanandaj, Iran 2 Department of Nursing, Faculty of Nursing and Midwifery, Kurdistan University of Medical Sciences, Sanandaj, Iran 3 Behavioral Sciences Research Center, Life Style Institute, Faculty of Nursing, Baqiyatallah University of Medical Sciences, Teheran, Iran 4 Social Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
Semantic Segmentation for Producing Nuclei Stained Images Using Conditional Generative Adversarial Networks

In order to discover nuclei of cells, biological scientist depend on various types of dyes, and coupled with the overall time involved in using these, it makes this a very inefficient process. Identifying nuclei with Deep Learning techniques can save a lot of time and can yield better accuracy. Recent developments in Generative Adversarial Networks[1](GANs) have been shown to produce text, video and realistically looking synthetic images. We use the Conditional Generative Adversarial Networks[2] to produce Nuclei Stained images from label maps using two different Generator Architectures(U-Net and EncoderDecoder with ResNet) and evaluate the performance of these networks. We also evaluate the classical Segmentation Network as a Generator and further improve it by adding Residual Blocks. Different evaluation measures like Pearson Correlation Coefficient, Mean Squared Error and Structural Similarity have been used along with software Cell Profiler to count the number of cells in the generated images and the corresponding real labels. This Thesis makes several contributions to the field of Deep Learning and using it for the generation of nuclei stained images which makes it useful to detect various cell lines including cancerous cell lines.
Patterns of corporate social and environmental disclosure in Nigeria

Article Type: Full Length Research Article The report is an exploratory study designed to identify evidence and patterns of corporate social and environmental disclosure (CSED) through annual reporting by firms in Nigeria. A total of 154 annual reports of 40 Nigerian Stock Exchange (NSE) listed firms were analyzed; consisting of four major industries, in the period starting 2009 to 2013. The study found a positive relationship between company size, industry, and a company’s CSED. The banking industry was found to disclose more information than all other industries, whereas the insurance industry disclosed the least. The oil and gas companies disclosed more than those in the food producing and processing industry.
Eco-epidemiological study on sandflies and environmental aspects related to the transmission of leishmaniasis in a municipality of Minas Gerais, Brazil, 2015–2016

The aim of this study was to evaluate Leishmania vectors and investigate the environmental and climatic characteristics related to their transmission. This was a prospective eco-epidemiological study involving the systematic collection of sandflies and a canine serological survey in areas of municipality in Brazil. Blood samples from 1,752 dogs were examined to test for canine visceral leishmaniasis (VL). An entomological evaluation was carried out using 24 light traps in the peridomicile and intradomicile areas of 12 households for 12 months. Climate variables were analyzed using a simple Spearman correlation and a spatial analysis via the fuzzy logic method and K function. The prevalence rate of canine VL was 4.1% and 7.1% in the two areas that were studied, respectively. The entomological study resulted in the capture of 431 sandflies. Most (74%) of the specimens were captured in the peridomiciliary area, and 5.6% of the samples that were analyzed using molecular biology were positive for Leishmania spp. In particular, Leishmania infantum was found in 100% of the positive samples. The spatial analysis showed that one particular area presented a higher concentration of high-density overlapping points of Lutzomyia longipalpis and seropositive dog populations, indicating a higher risk of the concomitant occurrence of both events. The results show that a parasite-reservoir-vector interface is active in the studied areas.
Towards Development of a Robust Asynchronous EEG-BCI using Error-Related Potentials

Towards Development of a Robust Asynchronous EEG-BCI using Error-Related Potentials Rozhin Yousefi Doctor of Philosophy Graduate Department of Biomedival Engineering University of Toronto 2019 The primary goal of brain-computer interface (BCI) research is to provide a means of communication for individuals with severe motor impairments. For BCIs to be widely adopted by patients, they need to have a reliable accuracy. One method to achieve this goal is to automatically correct erroneous classifications by exploiting error-related potentials (ErrPs). The first objective of this research is to explore how does the introduction of error-based autocorrection impact the accuracy of a multi-class active BCI based on non-motor imagery (MI) cognitive tasks. Another unavoidable step toward making BCIs clinically viable is to develop self-paced BCIs that users can control whenever they intend to. The second objective of this research is to investigate the impact of ErrP-based autocorrection on the accuracy of self-paced BCIs based on non-MI cognitive tasks. The first two studies were designed to answer the first research question. In the first study, participants performed multiple iterations of five different cognitive tasks. To simulate errors, a random subset of 20% of the trials were followed by incorrect feedback. An average area under curve of 0.83 was reached for the detection of ErrPs which confirmed the presence of ErrPs in such BCIs. The second study explored the effect of ErrP-guided error correction in an online three-class active BCI (idle state and two personally selected cognitive tasks). ErrP-based error correction modestly but significantly improved the average online task classification accuracy (+7%) and the information transfer rate (+0.9 bits/min) of the BCI across participants. The third study was designed to answer the second research question. Using a self-paced EEG-BCI based on cognitive tasks, the possibility of improving the BCI performance using ErrPs was investigated. The BCI continuously analyzed the EEG data and displayed real-time feedback as soon as it detected a cognitive task. Then, the BCI analyzed the EEG data after the feedback onset to detect ErrPs. The average of post-error correction success rate across participants improved significantly compared to the pre-error correction value (+7%). The findings of these studies support the addition of ErrP-informed correction to maximize the accuracy of cue-based and self-paced BCIs based on non-MI cognitive tasks.
Lightweight U-Net Based Monaural Speech Source Separation for Edge Computing Device

In this paper, a lightweight U-Net based monaural speech source separation method to implement high-quality speech source separation functionality in an edge computing device having a monaural microphone is proposed. The proposed method utilizes U-shaped neural networks to segregate speech and interfering noises from input mixtures in the time-frequency domain. To reduce the sizes of the networks suitable for real-time operation at the resource-constrained edge-computing device, the proposed method employs the inception-like multi-lane dimensionality reduction module for each convolutional layer of the U-Net. The performance of the proposed method is evaluated in terms of separation quality and number of parameters. Compared with the conventional U-Net based speech separation model, the proposed lightweight U-Net based method achieved a performance almost on-par with those of the conventional one while using a model footprint of 1.39 MB, which is only 3.72% of the size of the conventional U-Net. Moreover, the proposed method is successfully implemented in an off-the-shelf edge computing device having a tensor processing unit.
A Geostatistical Approach to Real-Time Reconciliation of the Grade Control Model – A Study regarding the Influence of Measurement Volume, Update Interval, Sensor Precision and Blending Ratios

One of the main challenges of the mining industry is to ensure that produced tonnages and grades are aligned with targets derived from model-based expectations. Unexpected deviations, resulting from large uncertainties in the grade control model, often occur and strongly impact resource recovery and process efficiency. During operation, local predictions can be significantly improved when deviations are monitored and integrated back into the grade control model. This contribution introduces a novel realization based approach to real-time updating of the grade control model by utilizing online data from a production monitoring network. A new algorithm is presented that specifically deals with the problems of an operational mining environment. Due to the complexity of the material handling process, it is very challenging to formulate an analytical approximation linking each sensor observation to the grade control model. Instead an application specific forward simulator is build translating resource realizations into observation realizations. The updating algorithm utilizes a Kalman-Filter based approach to link forward propagated realizations with real process observations to locally improve the grade control model. Differences in scale of support are automatically dealt with. This contribution further analyses the impact of the characteristics of production data on the overall performance of the updating algorithm. A series of experiments is conducted to investigate the influence of sensor precision, measurement volume,
WAREHOUSE LOCATION PROBLEM WITH GENETIC ALGORITHM

Locating an economic facility (e.g. plant, warehouse or retail store) is one of the most strategic and important issue that a business company faces. This planning question is in the operations research literature referred as a facility location problem. It focuses on defining number and location of economic facilities. The problem is to determine how many warehouses to set up, where to locate those warehouses. A Genetic Algorithm (GA) is shown to be an effective and efficient heuristic optimization method on problems of varying size. This paper presents a GA approach for the Warehouse Location Problem (WLP). According to the WLP, all cities in Turkey are considered where to the warehouses construct for minimizing the distribution costs. In the end, the results of various problems are reported.
Neutron irradiation of HF BJT and 0-T hybrids

We have irradiated with fast neutrons at the SARA facility (Grenoble) a 25 /10mA and a 50 /1mA 0-T preampli er, realized in thicklm hybrid technology as well as single bipolar devices biased at the conditions expected in the complete circuit. After 24 hours of irradiation test the maximum uence was about 1 10n=cm (1 MeV equivalent in Si). Variation of signal waveform in preampli ers was measured as a function of uence, but no noise degradation has been observed after irradiation. We have measured the dependence of the forward-gain of bipolar transistors with uence and found that it is described quite well by Messenger-Spratt model and we have extracted the values of damage constants for each transistor.
SSIM Assisted Pseudo-sequence-based Prediction Structure for Light Field Video Compression

This paper proposes a novel Structural Similarity Index (SSIM) assisted pseudo-sequence-based (PSB) coding order and prediction structure for improved compression and random-access efficiency for light field videos (LFV). The experimental analysis compares the performance of the proposed method against two recent PSB LFV compression methods in terms of PSNR gain. The results demonstrate the proposed technique yields improved bitrate and better random-access to views compared to existing methods.
High-Accuracy Mapping Design Based on Multi-view Images and 3D LiDAR Point Clouds

In recent years, the Internet of things (IOT), big data and artificial intelligence are evolving rapidly. The Self-driving vehicle is an important issue. One of the biggest advantages of self-driving vehicles is to reduce traffic accidents. The goal of our efforts is to provide more convenient and safe transportation. Therefore, we present a “high-accuracy mapping design based on multi-view images and three-dimensional (3D) LiDAR point clouds” in this paper. The proposed system for 3D LiDAR combines color camera and three dimensional space coordinate corresponding to the two-dimensional space coordinates technology.