Miracle-dz/UniFAR-FTUs huggingface dataset:
The relationship between moral distress in nurses and ethical climate in selected hospitals of the Iranian social security organization

The present study was conducted to determine the relation between nurses’ moral distress and the ethical climate in selected hospitals of the Iranian Social Security Organization (ISSO). This descriptive-analytical correlational study was conducted in 6 hospitals under the coverage of the Iranian Social Security Organization in 2016. Three hundred nurses were selected by convenience sampling method. Data were gathered using Corley’s Standard Moral Distress and Olson’s Hospital Ethical Climate Scales. Data were analyzed using SPSS software version 19. The mean score of the nurses’ moral distress was 1.94 ± 0.66, which is considered moderate. The mean score of ethical climate was 88.97, indicating desirable ethical climate in these hospitals. The frequency score of moral distress had a unilateral reverse correlation with the total score of ethical climate as well as its dimensions, including colleagues, patients, hospitals and physicians. The score of the intensity of nurses’ moral distress also had a unilateral reverse correlation with the total score of ethical climate and the scores of the hospital and physicians dimensions. These results emphasized the importance of creating a positive ethical climate to decrease moral distress as well as the need for professional interventions to increase support in moral issues.
ntegration of the state observer RAPTOR in the real-time MARTe ramework at RFX-mod

The RAPTOR – RApid Plasma Transport simulatOR code is a model-based control-oriented code that predicts Tokamak plasma profile evolution in real-time. One of its key applications is in a state observer, where the real-time predictions are combined with the measurements of the available diagnostics, yielding a complete estimate of the plasma profiles. The state observer RAPTOR is currently installed in the
Does Moral Awareness Increase Polarization ? ∗

Many companies invest heavily in the moral awareness of their employees. This paper investigates whether that practice may have unintended side-effects. Using a self-image framework, I predict that – if home-grown conceptions of morality differ – raising moral awareness may not only make people’s behavior less selfish but also more polarized. In a laboratory experiment, I test these predictions by means of a modified dictator game in which participants may plausibly pursue different moral ideals. I exogenously vary the degree of moral awareness across treatments by requiring randomly selected participants to make pre-choice moral judgments. My experimental results support the theoretical predictions: increased moral awareness makes choices less selfish and more polarized, reflecting even more divergent moral judgments. All results are robust to participants being informed about the (descriptive) social norm. These findings have important implications for the design of ethics programs within organizations.
Strategic technology allianceS , technology tranSfer and the Performance of malaySian manufacturerS

Organizations are realizing the strategic importance of technology alliances to enhance and maintain their competitive advantage. The turbulent business environment compels firms to adopt appropriate technologies for effective and efficient operations. While many firms are inclined to source external technology or form alliances, there are various considerations that can affect the success of such initiatives. This study examines the relationship between factors enabling strategic technology alliances (STAs), technology transfer and organizational performance. Based on three theories namely: Resource-based View (RBV); Organizational Learning Theory (OLT); and Technology Acceptance Model (TAM), this paper presents a model on the antecedent and outcomes of STA that is analyzed using structural equation modeling (SEM). The findings depict that absorptive capacity, type of alliances; relative advantage and perceived ease of technology implementation affect the alliance, which in turn determine organizational performance. Further tests show that technology transfer only partially mediates the relationship between STA and organizational performance. This research provides platforms and consideration for the implementation of new technologies and capabilities in manufacturing firms in a developing nation.
Modeling salt intrusion in the San Francisco Estuary prior to anthropogenic in fl uence

Anthropogenic changes have dramatically transformed the upper San Francisco Estuary over the past two centuries. Key changes influencing the region’s hydrology and hydrodynamics include land use changes, levee construction and channel modifications, upstream reservoir construction, and out-of-basin water exports. In order to examine how these changes have altered the physical characteristics of the estuary, 3-D hydrodynamic models were constructed to study the system in its “pre-development” condition, prior to significant modern anthropogenic influence, and in its contemporary condition. The pre-development system model was calibrated by varying marsh plain elevations in order to match sparse observations of tidal characteristics; the contemporary system model was calibrated to observed flow, stage, and salinity data. A recent three-year period covering a wide range of flow conditions was used to compare and contrast the hydrodynamic behavior of the two systems. While the contemporary model simulation assumed historical observed boundary conditions, the pre-development model simulation assumed conditions thought to exist prior to the alterations of the past two centuries. The relationship between estuary outflow and the longitudinal distance from the estuary mouth to the 2 psu bottom salinity isohaline (X2) was analyzed. Salt intrusion in the pre-development system was found to be slightly more sensitive to outflow and responded faster to changes in outflow than in the contemporary system. Changes in estuary outflows were responsible for more of the salt intrusion differences between the two systems than were changes in estuary geometry and bathymetry. An analysis of the physical mechanisms contributing to salt intrusion found tidal trapping and other unsteady processes to be more important in the pre-development estuary than in the contemporary one. In both systems, steady processes such as estuarine circulation were strongest during neap tides and unsteady salt intrusion processes were strongest during spring tides, resulting in limited spring-neap variability in salt intrusion.
DETECT BLAD AND DUMPS IN URUGUAYAN HOLSTEIN BREED ( Análise da curva de alta resolucao ( HRM ) : nova abordagem usada para detectar BLAD

The widespread use of artificial insemination has allowed the expansion of genetic progress. However, it also brought consequences such as the expansion of lethal hereditary diseases and the increase in inbreeding. The object of this study was to establish a fast and sensitive molecular assay to detect bovine leukocyte adhesion deficiency (BLAD) and deficiency of uridine monophosphate synthase (DUMPS) carriers in Uruguayan Holstein cattle by means of high resolution melting (HRM) curve analysis. By testing previously confirmed carrier and non-carrier animals, we set up a rapid, simple, and inexpensive diagnostic test using PCR followed by HRM curve analysis. The PCR-HRM genotyping method was effective for the discrimination of BLAD and DUMPS homozygous genotypes, and the BLAD heterozygous genotype. We conclude that the PCR-HRM assay is a robust, reliable, and economical tool for the detection of these mutations in the Holstein breed, which may be implemented in genetic selection programs.
Large Margin Random Forests On Mixed Type Data

Incorporating various sources of biological information is important for biological discovery. For example, genes have a multi-view representation. They can be represented by features such as sequence length and physical-chemical properties. They can also be represented by pairwise similarities, gene expression levels, and phylogenetics position. Hence, the types vary from numerical features to categorical features. An efficient way of learning from observations with a multi-view representation of mixed type of data is thus important. We propose a large margin random forests classification approach based on random forests proximity. Random forests accommodate mixed data types naturally. Large margin classifiers are obtained from the random forests proximity kernel or its derivative kernels. We test the approach on four biological datasets. The performance is promising compared with other state of the art methods including support vector machines (SVMs) and Random Forests classifiers. It demonstrates high potential in the discovery of functional roles of genes and proteins. We also examine the effects of mixed type of data on the algorithms used.
Title Low-Voltage Ride-Through Capability of Cascaded H-Bridge Multilevel Converters for Large-Scale Photovoltaic Power Plants

Multilevel cascade H-bridge (CHB) converters are increasingly applied for large-scale grid-connected photovoltaic power plants (GCPVPPs) because of their improved quality of output voltage waveforms, high efficiency due to the elimination of the line frequency transformer and modular structure. On the other hand, due to the high penetration of the installed distributed generation units in the power system, low-voltage ride-through (LVRT) capability and injection of reactive power during voltage sags are becoming necessary for large-scale GCPVPPs. This paper studies the LVRT capability of the gridconnected CHB inverter of a GCPVPP during various voltage sag conditions. Active/reactive power injection to the grid is also considered according to grid codes. The performance of the gridconnected seven-level CHB with LVRT capability is investigated on a 10-MVA GCPVPP, connected to the 6.6 kV medium-voltage grid simulation model during various voltage sag conditions.
Role and application of Ontology Design Patterns in bio-ontologies

Knowledge Representation (KR) languages such as OWL (Web Ontology Language), offer the possibility of computationally exploiting biological knowledge, by codifying it in the axioms of bio-ontologies. Bio-ontologies are widely used in life sciences for knowledge management. Knowledge is, however, often represented in bio-ontologies without following rigorous principles of modelling and the resulting bio-ontologies are axiomatically lean. Therefore knowledge cannot be fully computationally exploited. A solution is provided by the use of Ontology Design Patterns (ODPs). ODPs are thoroughly documented and efficient solutions for recurrent problems encountered when building ontologies. In order for ODPs to be efficiently accessed by bio-ontologists, an online catalogue of ODPs has been created. Such ODPs can be applied automatically with the Ontology PreProcessor Language (OPPL). The infrastructure for applying ODPs formed by the catalogue and OPPL has been used for applying ODPs in bio-ontologies like the Cell Type Ontology. The results of such application have been evaluated to assess the applied ODPs and the change on ontology quality.
Experiment-based Performance Improvement of State Feedback Control Systems for Single Input Processes

This paper gives an extension to the Iterative Feedback Tuning (IFT) approach that ensures the performance improvement of state feedback control systems for single input processes. IFT employs sensitivity functions and the experiments conducted on the real-world control system in order to provide an efficient way to deal with the nonlinear or ill-defined processes when the model-dependent Linear-Quadratic Regulator (LQR) is not successful. An experimental setup is suggested to implement the real-time iterative calculation of the gradients in the minimization of the LQR’s objective function. The experimental results validate the performance of the proposed IFT algorithm in a mechatronics application which deals with the angular position controller for a DC servo system with actuator dead zone and control signal saturation. The results show the reduction of the LQR’s objective function for a single input process application.
Marine Derived Fungi of Peninsular Malaysia – a Biochemical Perspective

In an effort to tap into natural products harboured by marine derived fungi in Malaysia, selected marine derived endophytic and manglicolous fungi from the coastlines of Peninsular Malaysia were investigated for their antibacterial potential. Forty-one strains were isolated from marine associated plants, comprised and comprised 12 and 19 endophytic strains from Vitex rotundifolia and Ipomoea pes-caprae respectively, while 10 manglicolous strains were from decaying mangrove wood collected in Peninsular Malaysia. In preliminary experiments, a plug assay was employed to study the antibacterial activities of all 41 fungi isolates. Fifteen of the endophytic isolates and nine of the manglicolous isolates displayed antibacterial activities against at least one of the test bacteria. Based on the plug assay, the endophytic fungi from Ipomoea pes-caprae were shown to display higher antibacterial potential in comparison to the endophytic fungi from Vitex rotundifolia. In particular, Minimidochium sp. and Bipolaris sp. (ISB0014) displayed antibacterial activities against 5 or more test bacteria. Potential fungi isolates with good antibacterial activities were further analysed through a broth microdilution assay. Minimidochium sp. and Dyfrolomyces rhizophorae exhibited promising antibacterial activities with minimum inhibitory concentrations not higher than 0.5 mg/ml. Bioactivityguided fractionation of D. rhizophorae extracts resulted in the isolation of fatty acids, palmitic and linoleic acid. Though ubiquitous in nature, linoleic acid is known as an essential health supplement and both fatty acids are used as biodiesel replacing conventional fuels.
An Adaptive Multi-Sensor Positioning System for Personal Navigation

MEMS sensors, such as accelerometers, gyros and barometers are being widely suggested for augmentation to Global Navigation Satellite Systems (GNSS). Combining such sensor provided information loosely to GNSS positioning is, nevertheless, very demanding and plenty of adaptability is needed in order to obtain sufficient positioning accuracy and acceptable service availability. This paper presents a low-cost multi-sensor positioning system that includes a high-degree of adaptability; environment detection for adaptive filter coefficient steering and measurement rejection. The system analyzed includes a commercial GPS receiver, a 3-axis accelerometer, and a 2-axis digital compass; and the measurements from the different sources are combined in a central Kalman filter. Test results are presented of the adaptive system and the shown performance demonstrates the usefulness of the adaptive low-cost multi-sensor usage with respect to a standalone high-sensitivity GPS solution.
SensePlace3: a geovisual framework to analyze place–time–attribute information in social media

ABSTRACT SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources.
Urban structure degradation caused by growth of plants and microbial activity

The purpose of this study was to isolate microorganisms associated to surface-affected concrete structures and to measure the in vitro dissolution of concrete based on the release of elements such as calcium and silicon. Although many microorganisms were detected only a fungus was capable of significantly decreasing the culture medium pH and releasing both elements. The molecular characterization allowed to identify the microorganism as Aspergillus carbonaurius, a citric-acid producing fungus that dissolved concrete in the in vitro test. After seven days of incubation, the soluble calcium concentration in the uninoculated culture medium containing concrete was 172.3 mg/L, while in the inoculated medium it was 525.0 mg/L. The soluble silicon concentration in the uninoculated medium was 10.3 mg/L, while in the inoculated medium it was 50.1 mg/L. These findings showed that plants and microorganisms rendered a synergistic effect accelerating the biodeterioration
Empathy and Feminist Attitudes

Empathy has been a topic of interest in the communities of psychology and popular media, especially in its potential connections to violent crimes. As the discussion surrounding empathy has grown, society has seen the rise of numerous problems in the progress of feminism, including the widespread recognition of the sexual assault epidemic on college campuses. In society’s continued struggle to mitigate this issue, I am proposing a research study to examine the correlation between empathy and feminist attitudes in undergraduate college students. This project will speak to the relevance of empathy in addressing feminist issues, warrant further research into its relation to such issues, and identify a growing need to teach American youth the importance of empathy. This is a simple, low budget project with most costs concentrated in brief housing expenses and printing materials.
Dynamic Capabilities in the German financial services industry

Purpose. The purpose of this work is to investigate processes constituting to Dynamic Capabilities in companies of the German financial services industry. Design/Method/Approach. Exploratory with a qualitative approach and a multiple case study method. Findings. The results indicate a connection of Dynamic Capabilities and the dynamism of the environment. The actual Dynamic Capabilities seem to operate in business model related activities, such as distribution channels, but not in product development. Theoretical implications. Suggestions are given for the development of a comparative measurement concept for Dynamic Capabilities. furthermore, the inclusion of environmental dynamism in the research is emphasized. Practical implications. Firms can use the structure of sensing, seizing and reconfiguration and apply the dimensions for the relational measurement to evaluate their innovation activities. Originality/Value. Connections of Dynamic Capabilities to the environmental dynamism were found. Furthermore, the process lens of this research makes the theoretical concept of dynamic capabilities more graspable and gives suggestions for an operationalization.
Finding Wally Parallel Object Recognition

A report on the potential of parallel computer vision for everyday use. Discussed within are algorithms and libraries that could make this a possibility. Special focus is put on the computer vision library OpenCV. Where’s Wally? puzzles are used as a test case for parallel object recognition, with OpenMP used for parallelism. The program experiences moderate speedup up to 16 cores. The reliability of the program’s solutions was not generic, requiring tweaking to become correct.
ON PUTATIVE PATHOGEN REDUCTION FROM SWINE WASTEWATER TREATMENT PROCESSES THROUGH 16 S rDNA PYROSEQUENCING ANALYSES

Pyrosequencing analyses of bacterial and archaeal 16S rDNA fragments were performed in effluent samples from two distinct field scale swine wastewater treatment plants (WWTP). A total of 83,333 and 63,636 sequence reads were obtained from Bacterial and Archaeal 16S rDNA, respectively. Bacterial communities were mostly associated with phylum Firmicutes, Bacteroidetes, Proteobacteria or Actinobacteria. Archaeal members of the phylum Eurychaeota were dominant in all samples evaluated. Different from Escherichia, and/ or Atopostipes, that are microorganisms conventionally utilized as indicators of fecal contamination, Bacteroidetes and/ or Prevotella were detected in most samples from the WWTP validating at some extent their usefulness as biomarker to predict environmental contamination by swine wastewaters. Satisfactory putative pathogen reduction was observed after the open pond natural attenuation lagoon but not after the air sparged nitrification/ denitrification followed by alkaline phosphorus precipitation treatment processes. Treated effluents from WWTPs could still contain pathogenic bacteria, thus presenting a potential threat to public health.
MULTI-LABEL CLASSIFICATION FOR PHYSICAL ACTIVITY RECOGNITION FROM VARIOUS ACCELEROMETER SENSOR POSITIONS 1

In recent years, the use of accelerometers embedded in smartphones for Human Activity Recognition (HAR) has been well considered. Nevertheless, the role of the sensor placement is yet to be explored and needs to be further investigated. In this study, we investigated the role of sensor placements for recognizing various types of physical activities using the accelerometer sensor embedded in the smartphone. In fact, most of the reported work in HAR utilized traditional multi-class classification approaches to determine the types of activities. Hence, this study was to recognize the activity based on the best sensor placements that are appropriate to the activity performed. The traditional multi-class classification approach required more manual work and was time consuming to run the experiment separately. Thus, this study proposed the multilabel classification technique with the Label Combination (LC) approach in order to tackle this issue. The result was compared Journal of ICT, 17, No. 2 (April) 2018, pp: 209–231 210 with several state-of-the-art traditional multi-class classification approaches. The multi-label classification result significantly outperformed the traditional multi-class classification methods as well as minimized the model build time.
Learning to Paraphrase for Question Answering

Question answering (QA) systems are sensitive to the many different ways natural language expresses the same information need. In this paper we turn to paraphrases as a means of capturing this knowledge and present a general framework which learns felicitous paraphrases for various QA tasks. Our method is trained end-toend using question-answer pairs as a supervision signal. A question and its paraphrases serve as input to a neural scoring model which assigns higher weights to linguistic expressions most likely to yield correct answers. We evaluate our approach on QA over Freebase and answer sentence selection. Experimental results on three datasets show that our framework consistently improves performance, achieving competitive results despite the use of simple QA models.