Miracle-dz/UniFAR-FTUs huggingface dataset:
PATTERNS OF ANNUAL FLUCTUATION OF DUST CONCENTRATIONS ALONG WITH METEOROLOGICAL PARAMETERS: A CASE STUDY IN QOM PROVINCE, CENTRAL IRAN

Introduction: Concentration of Particulate Matters were measured for a one-year monitoring period from July 2011 through June 2012 in Qom, a city located in western part of Dasht-e Kavir, central Iran. Materials and Methods: Some related meteorological parameters comprising wind speed, wind direction, rainfall, relative humidity (RH), temperature and sunshine hours were evaluated. Results: PM10, PM2.5, and PM1 maximum values were recorded as 1160.67, 242.92, 90.82 μg/m3, respectively. The maximum number of days with peak concentration of PM was reported from July through November 2012. Obtained results represented that the winds are prevailed from southern and south-eastern sides of Qom with 24.5% and 24% of consequences, respectively. The correlation between PM10 concentration and relative humidity was moderate and indirect (r = - 0.340). Conclusions: The coordination between governmental administrations of central provinces engaged with dust events is suggested to mitigate the health-related impacts using a long term control program.
Defect Detection using Nonparametric Regression

To compare signals, we first model them as nonparametric regression setup, we then wish to test either those signals are significantly the same against they are significantly different. To perform a test, first we need to measure the distance between two nonparametric regression and use this distance as test statistic for testing the null hypothesis. Typically, the distribution of test statistic under the hypothesis null is not known. This problem can be handled by deriving the asymptotic approximation for unknown distribution that holds for sample size infinitely. However, this approach practically cannot be applied in signal, since the structure of the data is frequently too complicated. We then used bootstrap tests, we move from our original data to the bootstrap world of pseudo data vector or resample. We apply this method to image processing for detecting defect on the texture. We model the images as 2D Gasser-Mueller Kernel Density with rotational-ellipsoidal support function, to estimate the regression function. Moreover, we let the errors correlated in their neighborhoods. We use standardized the modification of the Mallows distance between these two estimates, to test the hypothesis and construct spatial bootstrap to get the distribution of the test statistic. The spatial bootstrap is needed to preserve the bound of a pixel to its neighborhood.
Toward a Regional Classification to Provide a More Inclusive Examination of the Ocean Biogeochemistry of Iron-Binding Ligands

Iron-binding ligands are paramount to understanding iron biogeochemistry and its potential to set the productivity and the magnitude of the biological pump in >30% of the ocean. However, the nature of these ligands is largely uncharacterized and little is known about their sources, sensitivity to photochemistry and biological transformation, or scavenging behavior. Despite many uncertainties, there is no doubt that ligands are produced by a wide range of biotic and abiotic processes, and that the bulk ligand pool encompasses a diverse range of molecules. Despite widespread recognition of the likelihood of a continuum of ligand classes making up the bulk ligand pool, studies to date largely focused on the dominant ligand. Thus, most studies have overlooked the need to assess where these targeted molecules fit across the spectrum of ligands that comprise the bulk ligand pool. Here we summarize present knowledge to critically assess the source(s), function(s), production pathways, and loss mechanisms of three important iron-binding organic ligand groups in order to assess their distinctive characteristics and how they link with observed ligand distributions. We considered that ligands are contained in broad groupings of exopolymer substances (EPS), humic substances (HS), and siderophores; using literature data for speciation modeling suggested that this adequately described the iron speciation reported in the ocean. We hypothesize that a holistic viewpoint of the multi-faceted controls on ligands dynamics is essential to begin to understand why some ligands can be expected to dominate in particular oceanic regions, depth strata, or exhibit seasonality and/or lateral gradients. We advocate that the development of a regional classification will enhance our understanding of the changing composition of the bulk ligand pool across the global ocean and to help address to what extent seasonality influences the makeup of this pool. This classification, based on selected functional ligand classes, can act as a bridge to use future ligand datasets to fill in the gaps in the continuum.
Phosphorus and emerging micro-pollutants in surface waters: challenges and prospects for water quality improvement

An oversupply of Phosphorus in water bodies accelerates growth of algae and higher forms of plant life to produce undesirable impacts on overall water quality. Phosphorus inputs to surface waters arise from a variety of point and nonpoint sources. However much of the P is contributed by agricultural runoff and outfall of treated (or untreated) wastewater in receiving water-bodies. Point sourced-P inputs to waters have considerably decreased in recent years, at least partly driven by regulatory requirements, e.g. the EU Water Framework Directive. This has largely been achieved by removing P from treated wastewaters at sewage treatment works (STWs). Studies have shown that introducing an additional treatment step (“P-stripping”) can significantly reduce P in STW outfalls. Given P deposits are depleting, there is much interest in phosphorus recovery from wastewaters. A few STWs have already started to recover P as struvite (NH4MgPO4.6H2O) mineral – a substitute for commercially produced P-fertilizers. This requires major investment and is not economically viable at small STWs. Nonetheless it is a major breakthrough in terms of P recovery and its use. Effluents from sewage treatment works (STW) can often contain a complex mixture of residual microcontaminants, not removed during wastewater treatment. Organic micro-pollutants have been found in rivers receiving STW effluents. Such residual contaminants have become the focus of an emerging field of water quality study and are collectively referred to as pharmaceuticals and other personal healthcare products, PPHCPs. Many of these chemicals have the ability to effect the hormonal signaling of organisms and are called endocrine disrupting compounds (EDC). Such chemicals have shown some of the most damaging biological effects in aquatic organisms. Biological effects in the aquatic environment are typically related to the development of intersex in fish. Recent research shows the use of STW practices such as upgrading from using a combined trickling filter contact process to activated sludge treatment, ozonation, membrane filtration and use of suspended biofilm reactors reduces the amount of EDCs in waste effluent. It is thus possible to remove contaminants from STW effluents, but it will not be possible without major infrastructure improvements. This paper presents the challenges and prospects of P and micro-organic pollutants in surface waters.
Traditional Medicine and Modern Medicine: Knowledge, Attitude and Practice of Medical Students and Their Mothers in Tabuk City, Saudi Arabia

Background: Traditional remedies are mostly used as auto-medications for the treatment of physical diseases not only in Saudi Arabia but also worldwide. The traditional preparations are also prescribed by practitioners to patients who seek their consultation. Objective: The objective of this descriptive, cross-sectional study was to assess knowledge, attitude and practice (KAP) of medical students and their mothers towards traditional medicine (TM) and modern medicine (MM) in Tabuk city. Methods: A cross-sectional survey of purposefully selected University Preparatory Program (UPP) Original Research Article Al-Ghamdi et al.; BJMMR, 16(8): 1-12, 2016; Article no.BJMMR. 26915 2 students (n=147) for health specialties and their mothers (n=61) was conducted to examine their KAP of TM and MM at the University of Tabuk and mothers' homes. A self-designed, selfadministered questionnaire with 10-item to be answered mostly by "yes" or "no" was used in this research. Results: There were no significant differences in knowledge between students and their mothers concerning TM safety, efficacy, rapid cure, cost, and use in various mild diseases and cosmetic conditions. However, mothers' practice of TM differed significantly in regards to self-use of herbal medicines for skin diseases. Mother's attitude that TM is a primitive mode of treatment significantly differed from the views of medical students. Conclusion: The preliminary findings of this survey suggest that the participants differentially preferred the use of both TM and MM in the treatment of various physical conditions as well as for cosmetic purposes. Further research is needed to comparatively explore medical student and mother KAP of TM and MM in Saudi Arabia.
Adapted Anomaly Detection for RAN Performance

Complexity of mobile radio access networks is increasing rapidly. At the same time, customers’ expectations for the service quality are keeping the pressure on operators. It requires huge human efforts to maintain a sustainable and high- performance radio access network. To meet the highest quality and service level requirements, more and more network management and maintenance functions are required to be passed to automated solutions. There are many already - like SON, MLB, automatic antenna tilting which helps to scale operations. Those are dedicated to improving specific functions, but they do not pay much attention to service KPIs, which are a direct reflection of customers’ experience. Most often, changes in network performance KPIs indicate some interruption or deterioration of service quality, which needs to be restored as soon as possible. Automated solutions based on machine learning process enables engineers to notice those network issues much faster. There are many algorithms that have been created for this purpose, but most of them are specialized and tuned to detect an anomaly in the special datasets, like fraud, abnormal CPU usage, earthquake, cyber-attack. Consequently, it is either not applicable or not performing well while identifying anomalies on telecommunication network performance data. The research on this paper proofs anomaly detection accuracy problem, lack of functions for telecommunication data in existing R libraries. The only R “changepoint” package has a functionality to detect not a single local anomaly, but also anomalous time series, which is the most relevant in RAN (radio access network) performance monitoring. Default function meanvar() of method – PELT, penalty - BIC returns up to 30 false positive anomalies in retainability and integrity KPI and up to 10 in mobility KPI group on one month time series data. To extract true positive anomalies additional algorithm is applied with a cost of false negative detection increase up to 10% in a single time series data and occurs not more than in 5% of used datasets. These results are compared against other popular R libraries, like “Anomalize”, “AnomalyDetection”, “bcp”, “changepoint” and proofed to be the most accurate on radio network performance data. This adapted anomaly detection algorithm can be treated as a scalable generic algorithm to any kind of high-dimensionality data as it does not require additional tuning for different KPI group or technology. It is the solution for automated network performance monitoring that can take off a lot of workload from daily network engineer routine and improve the quality while tackling network performance issues.
Recognizing Conscientious Degree in Instrumental Activity of Daily Living from Brightness Distribution

Because of the rapid increase of the elderly, the lack of helpers to take care of the elderly has become a serious problem in Japan. A way should be found to enable the elderly to be independent as long as possible. The paper refers to the motivation to keep the quality of life high as living willingness. The elderly with living willingness would keep their living environments comfortable. On the contrary, the elderly losing their living willingness are likely to make disorder in their house keeping, such as lazy cleaning and skipping of dish washing. The detection of the disorder of their daily activities makes it possible to find the decline of their living willingness early, because the disorder implies their physical and mental health get worse. Instrumental Activities of Daily Living (IADL) plays an important role to find the disorder. The activities are conducted to improve the quality of life. The laziness of the elderly in IADL implies they are losing their motivation to improve the quality of life. The paper proposes a method to recognize IADL, preserving the privacy of the elderly. It also figures out conscientious degree the elderly take IADL. The method uses the brightness distribution sensor. It provides a classifier of IADL from the brightness distribution. In an experiment for the elderly, the f-measure with which the method has recognized activities of cleaning, cooking, and washing are 0.975, 0.912 and 0.927, respectively. The experiment shows 0.599 in Nagelkerke R2, which indicates how well the method figures out conscientious degree in the activities. It reveals the method is precise enough to measure the decline of the elderly in the living willingness. Copyright © 2015 IFSA Publishing, S. L.
Introduction to the Taxometric Method: A Practical Guide

Preface. Part 1. Introduction and Background. Introduction. Why Latent Structure Matters. The Classification Problem. Part 2. Taxometric Method. Data Requirements for Taxometrics. Taxometric Procedures I: MAXSLOPE, MAMBAC, and L-Mode. Taxometric Procedures II: MAXCOV and MAXEIG. Consistency Tests. Interpretational Issues. A Taxometric Checklist. Part 3. Applications and Future Directions. Applications of the Taxometric Method. The Future of Taxometrics. Appendix A: Simulating Taxonic and Dimensional Comparison Data. Appendix B: Estimating Latent Parameters and Classifying Cases Using MAXCOV. Appendix C: Estimating the Taxon Base Rate Using MAXEIG.
Animal disease surveillance and survey systems: methods and applications.

Preface.Contributors. Chapter 1. Surveillance and Monitoring Systems for Animal Health Program and Disease Suveys (M.D. Salman). Chapter 2. Application of Surveillance and Monitoring Systems in Disease Control Programs (J. Christensen). Chapter 3. Planning Survey, Surveillance, and Monitoring Systems-Roles and Requirements (C. Zepeda and M.D. Salman). Chapter 4. Sampling Considerations in Surveys and Monitoring and Surveillance Systems (A. Cameron, I. Gardner, M.G. Doherr, and B. Wagner). Chapter 5. Statistical Analysis of Data from Surveys, Monitoring, and Surveillance Systems (B. Wagner, I. Gardner, A. Cameron, and M.G. Doherr). Chapter 6. Methods for Determining Temporal Clusters in Surveillance and Survey Programs (T.E. Carpenter and M.P. Ward). Chapter 7. Methods for Determining Spartial Clusters in Surveillance and Survey Programs (T.E. Carpenter and M.P. Ward). Chapter 8. Use of Sentinel Herds in Monitoring and Surveillance Systems (B.J. McCluskey). Chapter 9. Use of Animal Monitoring and Surveillance Systems When the Frequency of Health-Related Events is Near Zero (M.G. Doherr, L. Audige, M.D. Salman, and I.A. Gardner). Chapter 10. Use of Simulation Models in Surveillance and Monitoring Systems (L. Audige, M.G. Doherr, and B. Wagner). Chapter 11. Quality Assessment of Animal Disease Surveillance and Survey Systems (K.D.C. Stark). Chapter 12. Dissemination of Surveillance Findings (N.E. Wineland and D.A. Dargatz). Chapter 13. Danish Swine Salmonellosis Control Program: 1993 to 2001 (J. Christensen). Index.
Production of DAISY standard accessible reading materials for the students with print disability of grade 1-10 of Bangladesh

According to the findings of WHO and Bangladesh Bureau of Statistics (BBS, 2011), approximately four million people are visually impaired in Bangladesh. Furthermore, approximately 27% (UNESCO UIS, 2017) of people in Bangladesh are illiterate or low literate who are considered as print disable. Accessible information and reading materials have not been available to this group. However, the government and non-government/private organizations provide a range of school services and inclusive education programs for blind and partially sighted students. Although some of the organizations are using audio-books as a supplementary education materials, but there were no accessible reading materials for the students with visual impairments. Considering the situation, YPSA, along with Access to Information program (a2i), Prime Minister’s Office by the technical support of WIPO, Accessible Books Consortium, DAISY consortium and GAATES has produced DAISY digital multimedia books, Accessible E-books, Digital Braille Books for the student of grade 1 to 10 which are much accessible and cost effective than the regular paper books for the students with visual disabilities, print disabilities and learning disabilities. The project converted all the text books into DAISY multimedia format, which can be converted further into DAISY full text full audio text books, Braille and accessible e-books from the source DAISY files. The digital text books are accessible for all including the students with visual disabilities, print disabilities and learning disabilities. The Honorable Prime Minister of Bangladesh formally launched the initiative and distributed the books among the students with visual impairments. Now all learners can get free, equitable and quality primary and secondary education leading to relevant and effective learning outcomes (SDG Target 4.1). Also, education facilities became child, disability and gender sensitive and provide safe, inclusive and effective learning environments for all (SDG Target 4.a) towards quality education. The DAISY multimedia books have opened new avenues for the students to harness the accessible educational resources for learning. It can certainly improve the level of competency of the students with visual impairments, remove them from being information dark, and make them ready to work as human resources.
Palliative Care and COPD

A 72-year-old male smoker with CAD and COPD was admitted to the ICU with an exacerbation of his COPD severe enough to require intubation. This was his second hospitalization in three months. On the fourth day he showed signs of improvement and tolerated CPAP more than the prior day. Despite this improvement his wife thought he would not want to be kept on the ventilator for this length of time. At her request, the nursing staff asked the resident if a palliative care consult could be made. The palliative care team met with the wife and discussed her concerns about her husband’s being on the ventilator. She stated, “After the last time we were here he told me, ‘Don’t let them keep me on that machine again. ’” The palliative care team asked about other family members who would want to discuss this decision, and she indicated a son. At a meeting later that day the senior resident from the team explained the treatment plans and why they were hopeful that within another day or two extubation would be successful. With the son’s encouragement, the patient’s wife agreed with the medical team’s treatment plan.
A Hybrid Kinematic-Acoustic System for Automated Activity Detection of Construction Equipment

Automatically recognizing and tracking construction equipment activities is the first step towards performance monitoring of a job site. Recognizing equipment activities helps construction managers to detect the equipment downtime/idle time in a real-time framework, estimate the productivity rate of each equipment based on its progress, and efficiently evaluate the cycle time of each activity. Thus, it leads to project cost reduction and time schedule improvement. Previous studies on this topic have been based on single sources of data (e.g., kinematic, audio, video signals) for automated activity-detection purposes. However, relying on only one source of data is not appropriate, as the selected data source may not be applicable under certain conditions and fails to provide accurate results. To tackle this issue, the authors propose a hybrid system for recognizing multiple activities of construction equipment. The system integrates two major sources of data—audio and kinematic—through implementing a robust data fusion procedure. The presented system includes recording audio and kinematic signals, preprocessing data, extracting several features, as well as dimension reduction, feature fusion, equipment activity classification using Support Vector Machines (SVM), and smoothing labels. The proposed system was implemented in several case studies (i.e., ten different types and equipment models operating at various construction job sites) and the results indicate that a hybrid system is capable of providing up to 20% more accurate results, compared to cases using individual sources of data.
Repurposing rotavirus vaccines for intratumoral immunotherapy can overcome resistance to immune checkpoint blockade

Rotavirus vaccines have oncolytic properties and can overcome resistance to anti–PD-(L)1/CTLA-4 via RIG-I activation upon intratumoral administration. Repurposing a pediatric vaccine Attenuated virus vaccines such as those used to protect against influenza or chickenpox have already passed manufacturing and regulatory hurdles. Given that many viruses have anticancer properties, Shekarian et al. reasoned that existing vaccines for infectious disease may be useful for treating cancer. They tested several vaccines in vitro and saw that rotavirus vaccines activated NF-κB in a human cell line and were protective against a tumor model resistant to immune checkpoint blockade. Further study of live or inactivated rotavirus strains in multiple tumor models showed RIG-I activation and durable immunity, especially when combined with other immunotherapies. These studies indicate that rotavirus vaccines already in production and circulation could be considered as anticancer agents. Although immune checkpoint–targeted therapies are currently revolutionizing cancer care, only a minority of patients develop durable objective responses to anti–PD-1, PD-L1, and CTLA-4 therapy. Therefore, new therapeutic interventions are needed to increase the immunogenicity of tumors and overcome the resistance to these immunotherapies. Oncolytic properties of common viruses can be exploited for the priming of antitumor immunity, and such oncolytic viruses are currently in active clinical development in combination with immune checkpoint–targeted therapies. However, the routine implementation of these therapies is limited by their manufacturing constraints, the risk of exposure of clinical staff, and the ongoing regulations on genetically modified organisms. We sought to determine whether anti-infectious disease vaccines could be used as a commercially available source of immunostimulatory agents for cancer immunotherapy. We found that rotavirus vaccines have both immunostimulatory and oncolytic properties. In vitro, they can directly kill cancer cells with features of immunogenic cell death. In vivo, intratumoral rotavirus therapy has antitumor effects that are dependent on the immune system. In several immunocompetent murine tumor models, intratumoral rotavirus overcomes resistance to and synergizes with immune checkpoint–targeted therapy. Heat- and UV-inactivated rotavirus lost their oncolytic activity but kept their synergy with immune checkpoint–targeted antibodies through the up-regulation of the double-stranded RNA receptor retinoic acid–induced gene 1 (RIG-I). Rotavirus vaccines are clinical-grade products used in pediatric and adult populations. Therefore, in situ immunization strategies with intratumoral-attenuated rotavirus could be implemented quickly in the clinic.