Miracle-dz/UniFAR-FTUs huggingface dataset:
Hospital Management Based On Semantic Process Mining: A Systematic Review

Introduction: Semantic Process Mining is the extension field of process mining that is based on getting knowledge of conceptual event logs (based on ontologies) for analyzing frequent and rare processes. In the healthcare studies, semantic process mining has been used in different hospitals in order to improve processes.Material and Methods: A review of the usages of semantic process mining in hospitals is done. This review contains 65 articles from PubMed, dblp and Google scholar. It is searched from 2000 to 2017. One of them was duplicated and finally, we received 64 articles. Data were extracted according to PRISMA guidelines.Results: Out of 64 articles, 6 of them were related with inclusion and exclusion criteria. Most of them detect business process mining. In 80% of studies, the semantic process mining was useful and effective to improve hospital processes and improve its management.Conclusion: This review can show an overview the application of process mining in hospitals. It can help researchers to compare semantic process mining with other methods for improving processes in hospitals and finally, it shows the use of semantic process mining to enhance hospitals processes.
Galantamine bioactivity improvement in rat brain using two novel nanodrug delivery systems as therapy for Alzheimer's disease

Reminyl is one of the most common drugs presently used for treatment of mild to moderate Alzheimer. The present study is an attempt to investigate the influence of presenting two innovative nano-engineered drug carriers (Ce/Ca-HAp& CMCS/Ce/Ca-HAp) as carriers for Rem in Alz therapy. A total of 86 adult female albino Wistar rats were randomly assigned to the following groups: Control group (C) of 8 rats given saline; Reminyl group (Rem) of 8 rats treated with Rem; Alzheimer’s group (Alz) of 16 ovariectomized animals inoculated orally with AlCl3 (17mg/Kg b.wt/day) for 2 months after 6 weeks of surgical operation; Alzheimer’s disease-induced rats treated (i.p) with Rem (2.5mg/Kg b.wt/day); Alzheimer’s disease-induced rats treated (i.p) with Rem coated by Ce/Ca-HAp (2.5mg/Kg b.wt/day) and Alzheimer’s disease-induced rats treated (i.p) with Rem coated by CMCS/Ce/Ca-HAp (2.5mg/Kg b.wt/day). After 2 and 4 weeks animals were sacrificed by ether inhalation anesthesia where brains were removed and processed for histological analysis by Hx&E and biochemical analysis for measuring GSH, SOD, CAT and CytoP450reductase levels. Histological and biochemical alterations designated in Rem treated rat brains were ameliorated following the use of Rem coated by Ce/Ca-HAp and not with Rem coated by CMCS/Ce/Ca-HAp. Initiation of new nano drug delivery systems may attribute in delivery of therapeutic drug to the site of action and overcome drawbacks of the drug alone.
Exponentially convergence for the regressor-free adaptive fuzzy impedance control of robots by gradient descent algorithm

Having the capability to estimate parametric and non-parametric uncertainties, this paper investigates a regressor-free adaptive model-reference scheme for impedance control of robotic systems interacting with an environment. Using the gradient descent algorithm for designing a fuzzy estimator makes the tune of controller’s parameters possible in different physical situations and uncertainties. Thanks to the voltage control strategy and fuzzy systems, there is no need for designers to have the knowledge of robots and actuators’ dynamics. In addition, the force feedback is not employed in the structure of control law. Using the Lyapunov-like stability analysis, not only the exponential convergence of error signal and its time derivative to zero are guaranteed in the decentralised form but also the boundedness of all signals is ensured. To confirm the efficiency of proposed control algorithm, several simulations as well as a comparison with a positioned-based impedance controller and a regressor-based adaptive impedance controller are conducted on a two-link planar robot manipulator considering a tunable desired trajectory and different stiffness of environment. Additionally, the proposed adaptive impedance controller is applied to a six degree of freedom revolute-joint manipulator to provide better evaluation.
Characterization of chlorophyll fluorescence, absorbed photosynthetically active radiation, and reflectance-based vegetation index spectroradiometer measurements

ABSTRACT Spectroscopy plays a key role in Earth observations, especially for studies involving vegetation function and structure. These measurements are critical in the context of carbon cycle monitoring from leaf to global scales. Reflectance-based vegetation indices (RIs) have been used extensively in remote sensing studies from the unpiloted aerial vehicle, aerial, and space-based platforms to model quantities related to productivity, such as gross primary production (GPP), while more recently chlorophyll fluorescence (CF) measurements are increasingly exploited to track GPP. CF and RI measurements vary in magnitude, depend on different portions of the spectrum, and are derived from unique equations; thus, instrument uncertainty manifests distinctly for these measurements. Although this is well known, it is often unexamined in experiments and analyses. We use a portable spectroradiometer to make measurements of reflectance-based vegetation indices (RIs) and chlorophyll fluorescence (CF) in order to characterize how measurements of RIs and CF compare to one another. In particular, we examine fluorescence (F) and fluorescence yield (F Yield) under a light-emitting diode grow light (LED), solar-induced fluorescence (SIF), solar-induced fluorescence yield (SIFYield), absorbed photosynthetically active radiation (APAR), and reflectance-based vegetation indices (the normalized difference vegetation index (NDVI), the chlorophyll/carotenoid index (CCI), and the photochemical reflectance index (PRI)) and include maximized propagated uncertainty of the spectroradiometer for each measurement. We show that RIs have a significantly lower propagated error relative to the mean (0.01% to 0.28%) than CF measurements (0.01% to 1.28%) and that while fine resolution spectrometer CF measurements are outside the noise of the instrument and have potential to provide relative measurements of productivity, show why this instrument having fine spectral resolution and sampling is more effective for measurements of APAR and RIs. We also demonstrate that F and F Yield measurements have low propagated uncertainty and propose that future studies of plant function using this spectrometer/LED technique and the full range of spectra be undertaken. Finally, measurements of SIF, F, and APAR can provide estimates of SIFYieldand F Yield in the same order of magnitude, but further examination is required to determine how these measurements compare under a range of illumination and environmental conditions and how they might compare to PRI.
Henri Lefebvre’s Urban Critical Theory: Rethinking the City against Capitalism

ABSTRACT In the article the author highlights the main ways of the Lefebvrian sociological analysis conceived starting from the transformations of the city in the Fordist era: From the production of urban marginality, through the proliferation of precarious living in the France of the Sixties and Seventies, to recording the gradual disappearance of the urban–rural dichotomy, that goes into an authentic spatial hegemony of urbanization processes. The goal is therefore to highlight the “urban critical theory” of Henri Lefebvre, coming to discuss the famous meaning of “right to the city,” strongly interconnected with the concept of “city as an artwork,” that is the idea of an urban space intended as horizontal and common design by those who live and inhabit in it.
Ordination

gained to-day a new ideal of saintliness. Every one knows the traditional saint of the Middle Ages’ the thin pale face, the eyes red with tears or weary with watching, the transparent hands, the wasted form. ’ This is not our ideal ; in our protest against it we may even miss the truth that it was vainly seeking to express ; but it is something more than Pharisaic self-complacency which thanks God that He has laid upon us to-day a higher and a nobler law of Christian service.
Formal analysis and control of timed automata with guards using (max, +) and (min, +) algebras

This paper has introduced new formal approaches to model behaviours and control of a class of uncertain timed discrete event systems represented by Timed Automata with Guards (TAGs). We propose alternative representations for Timed Automata with Guards which approximate their dynamics, since only extremal behaviours are considered. More precisely, recursive equations are proposed in and algebras to describe the worst and the optimistic behaviours. Thereafter, these developed linear models are used to treat a control problem of TAGs. Finally, the proposed methodologies are illustrated by a realistic study case that corresponds to a job-shop system.
VoicePop: A Pop Noise based Anti-spoofing System for Voice Authentication on Smartphones

Voice biometrics is widely adopted for identity authentication in mobile devices. However, voice authentication is vulnerable to spoofing attacks, where an adversary may deceive the voice authentication system with pre-recorded or synthesized samples from the legitimate user or by impersonating the speaking style of the targeted user. In this paper, we design and implement VoicePop, a robust software-only anti-spoofing system on smartphones. VoicePop leverages the pop noise, which is produced by the user breathing while speaking close to the microphone. The pop noise is delicate and subject to user diversity, making it hard to record by replay attacks beyond a certain distance and to imitate precisely by impersonators. We design a novel pop noise detection scheme to pinpoint pop noises at the phonemic level, based on which we establish individually unique relationship between phonemes and pop noises to identify legitimate users and defend against spoofing attacks. Our experimental results with 18 participants and three types of smartphones show that VoicePop achieves over 93.5% detection accuracy at around 5.4% equal error rate. VoicePop requires no additional hardware but only the built-in microphones in virtually all smartphones, which can be readily integrated in existing voice authentication systems for mobile devices.
Embodied Narratives of Candomblé’s Afro-Bahian Caboclos

At a ritual compound in Salvador, Bahia's capital city in Northeastern Brazil, the Caboclo Sete Flechas dances a sinuous samba, his bare feet marking time on the leaf-covered floor. With a serpentine spine and syncopated steps that turn on a polymetric beat, Sete Flechas rides out on the horse that is Mãe Oba's body. A priestess in the Afro-Brazilian religio-cultural matrix of Candomblé, Mãe Oba, cultivates Yoruban-oriented divinities, the Orixá, as well as Caboclo, hybrid Brazilian gods identified with indigenous histories and healing traditions. At ceremonial sessions like the one described above, Caboclos use locally harvested leaves to remove ailments and dispel negative energy. Rowdy, masculine entities that embody female, male and trans-identified practitioners, Caboclos also dance circular sambas that narrate and revel in living histories of emancipation, nationalism, eroticization and racial contact. This paper places critical ethnographic fieldwork and choreographic analysis in dialogue with Timothy Morton's dark ecologies to develop what I call dark horse kinetics: a counter-hegemonic praxis activated through Caboclo performance. I suggest that Caboclos use dark horse kinetics to unfix, critique and revise dominant constructions of race, nation, gender and sex. Thinking about dark ecologies through performance, I ask if dark horse kinetics can move dark ecology towards a performance praxis, or a praxis that performs, in an efficacious and theatrical manner.
Recent advances in layered double hydroxides applied to photoprotection

ABSTRACT Layered double hydroxides have received more attention from researchers due to their range of applications, ease of synthesis and low cost of production. With broader knowledge about solar radiation effects on the body, the use of sunscreens has become even more important. The ability of some nanostructures, such as layered double hydroxides, to act as matrices has made it possible to obtain improvements in photoprotective formulations, with solutions to problems caused by radiation and sunscreens. This review article brings together the most recent advances of these clays, the layered double hydroxides, applied to photoprotection.
Deep Learning based Segmentation of Lumbar Vertebrae from CT Images

We present a method to address the challenging problem of automatic segmentation of lumbar vertebrae from CT images acquired with varying fields of view. Our method is based on cascaded 3D Fully Convolutional Networks (FCNs) consisting of a localization FCN and a segmentation FCN. More specifically, in the first step we train a regression 3D FCN (we call it “LocalizationNet”) to find the bounding box of the lumbar region. After that, a 3D U-net like FCN (we call it “SegmentationNet”) is then developed, which after training, can perform a pixel-wise multi-class segmentation to map a cropped lumber region volumetric data to its volume-wise labels. Evaluated on publicly available datasets, our method achieved an average Dice coefficient of 95.77 ± 0.81% and an average symmetric surface distance of 0.37 ± 0.06 mm.
Institutional uncertainty and supply chain quality management: A conceptual framework

Abstract To cope with external uncertainty, managers adjust supply chain quality management (SCQM) practices to ensure that quality-related aspects of interorganizational resource flows remain stable. This paper considers the nature of those adjustments when uncertainty presides at the institutional level—the political and legal realm where rules governing supply chain exchange are established and enforced. As institutional uncertainty increases, SCQM practices are proposed to shift from postures that abide by the existing institutional order to those that evade or alter unstable institutional settings. Examples of SCQM activities associated with evading and altering postures are likewise offered. An important, and somewhat novel, implication of this work is that effective interorganizational quality management requires capability for navigating and, in some cases, altering institutional environments—jurisdictions sometimes considered beyond the customary scope of quality management.
Forecasting Country Conflict within Modified Combatant Command Regions using Statistical Learning Methods

Conflict forecasts are crucial to Combatant Commanders’ understanding of the dynamic environment encompassing countries within their area of responsibility. The current structure of the Combatant Commands (COCOMs) is rooted in geography by grouping nations in geographic proximity to the same regional command. However, leaders today question the e↵ectiveness of the current structure. A novel modified k-means clustering algorithm is developed and implemented that groups countries based on data similarities and geographic proximity resulting in new COCOM groupings that improve conflict forecasts. The data spans various political, military, economic, and social characteristics of countries, and is used to develop conditional logistic regression models that predict the likelihood of a country to transition into or out of conflict. Predictions from models using the original COCOM regions are compared to predictions from models using the new, data and geography based, regions. Reorganizing the COCOMs based on data similarity and geography improves conflict forecasting models and prediction capabilities significantly. The new models achieved training data classification accuracies exceeding 89% for each new COCOM and improved predicting the validation data with classification accuracies increasing up to 2% as compared to the current COCOM models and up to 2.5% in comparison to previous conflict studies. This methodology of grouping countries based on data similarities and geographic proximity leads to newly defined COCOMs which improve overall forecasting ability of conflict transitions, the best found in the literature to date. These results can help Combatant Commanders better understand the dynamic conflict environment of their area of responsibility and lead to the development of more e↵ective operational and strategic plans.
Comparative Analysis of Cold Events Over Central and Eastern China Associated with Arctic Warming in Early 2008 and 2016

ABSTRACT This study investigates the possible reasons for the cold events over central and eastern China (CEC) in early 2008 and 2016. The Arctic is dramatically warming, in particular over the Barents–Kara Seas region and notable cold events were observed over CEC although La Niña and El Niño events occurred in early 2008 and 2016, respectively. At the same time, the westerlies decelerated at middle latitudes and the Ural Mountains Blocking High and the Siberian High strengthened. Subsequent analyses indicate that the cold events and the related atmospheric circulation anomalies are closely associated with Arctic warming. Additionally, the cold (warm) phase of the El Niño–Southern Oscillation causes the East Asian winter monsoon (EAWM) to strengthen (weaken) and correspondingly intensify (mitigate) the cold events over CEC. In brief, the Arctic warming is superimposed on La Niña or El Niño events by thermal and dynamic processes, which impact the relevant atmospheric circulation and EAWM and then induce the cold events over CEC in early 2008 and 2016 although their intensity and coverage are also different to some extent.
The impact of horizontal errors on the accuracy of freely available Digital Elevation Models (DEMs)

ABSTRACT Many freely available global or quasi-global digital elevation model (DEM) datasets, including Advanced Land Observing Satellite (ALOS) World 3 Dimensions (3D) 30 m DEM (AW3D30 DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer DEM (ASTER DEM), Shuttle Radar Topography Mission DEM (SRTM DEM), Multiple-Error-Removed-Improved-Terrain DEM (MERIT DEM), and TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) DEM (TanDEM-X DEM), are extremely useful products for many applications, so it is necessary to make a reasonable analysis of the quality of these DEMs. The quality of these DEMs is affected by both horizontal and vertical errors. However, most related researches have paid little attention to the effects of horizontal errors on the vertical accuracy of DEMs. Herein, after analysing the horizontal errors caused in the data acquisition process from optical stereo pairs and interferometry, experiments were proposed to assess the horizontal errors in DEMs. Then, we used the high accuracy digital surface model (DSM) of the Changsha area generated from the ZiYuan-3 triplet stereos to investigate the impact of horizontal errors on the accuracy of the five freely available DEMs. The subpixel level horizontal errors of the five DEMs were calculated, showing that the TanDEM-X DEM has systematic offsets and the other four DEMs have strip-like geometric errors. All the DEMs, except ASTER DEM, attained an accuracy increase of approximately 10% after the horizontal errors were removed. In mountainous areas, correcting the horizontal errors could eliminate the elevation errors caused by the imaging geometry of the optical camera and radar system. Generally, AW3D30 DEM has the best performance in terms of overall elevation accuracy and geometric accuracy after eliminating horizontal errors, and so it can have wide-ranging applications. These findings demonstrate the importance of removing horizontal errors to improve the elevation accuracy in practical applications using these global freely available DEMs.
Appendicular Stump Disinfection Using Povidone- iodine Swab Compared with Electrocautery; which one is more effective?

Objective: To evaluate the effectiveness of povidine-iodine swab versus electrocautery to disinfect appendicular stump. Methods: A randomized controlled trial was conducted in Services Institute of Medical Sciences, Lahore, with a sample size of 40 patients from 1st Dec 2012 to 31th August 2013. Random allocation was done into two equal groups. After cutting appendix, a culture swab was taken from the appendix stump. Electrocautery was used to disinfect appendicular stump in group A while, 10% povidone-iodine was used in group B. A second culture swab was taken from stump after five minutes. Absence of growth on the second culture was considered as effective therapy. Results: Out of total 40 patients, 27 (67%) were males and 13 (33%) were females. Mean age of the patients was 25.6 years. Electrocautery was effective in 100% while Povidone-Iodine was effective in 60% cases (p<0.05). Wound infections were reported in 15% of the cases in electrocautery group and 20% in povidone-iodine group. While assessing possible relationship between wound infection and effective appendix stump disinfection. Out of 32 (20 in Group A and 12 in Group B) cases who were “effectively treated” as shown by negative culture reports after application of either intervention (cautery/ povidone-iodine), 4 (12%) cases developed wound infection. Whereas 3 out of 8 (All in Group B) (37%) patients in ‘In effectively treated’ group developed wound infection. Relationship between effectiveness of the treatment and wound infection could not reach to a statistically significance level. (p = 0.096) Conclusion: Electrocautery is better option in disinfecting appendix stump as compared to Povidone-Iodine swab.
Predicting AI News Credibility: Communicative or Social Capital or Both?

ABSTRACT News credibility as an essential democratic value has been at the forefront of scholarly endeavors over the last several decades. Despite prolific research in this area, scholarship on the credibility of algorithm-based and automated news has yet to offer empirical findings in regards to the causes and their impacts. In line with prior studies concerning news credibility, this study examines the driving forces in predicting the level of credibility on artificial intelligence (AI) news. Specially, this study unveils the effects of communicative capital, such as media use and public discussion, among audiences, as well as social capital, such as social trust, on AI news credibility. Data collected through a nationwide online survey reveals that media use through television, social network sites, and online news sites, as well as public discussion yielded a positive association with AI news credibility. Of particular interest is that social trust moderated the effect of public discussion on credibility, indicating that the relationship between discussion and credibility was even stronger for those who have a higher level of trust in others. Implications are further discussed.