Miracle-dz/UniFAR-FTUs huggingface dataset:
Perbandingan Regresi Linier Berganda dan Regresi Buckley-James Pada Analisis Survival Data Tersensor Kanan

Abstract. Analisis survival atau analisis uji hidup adalah teknik statistik yang digunakan untuk menganalisis data yang bertujuan untuk mengetahui hasil dari variabel yang mempengaruhi suatu awal kejadian sampai akhir kejadian. Analisis regresi linear merupakan analisis yang bertujuan untuk mengetahui pengaruh dan hubungan linear variabel independen terhadap variabel dependen. Model regresi linear biasa tidak dapat digunakan untuk memodelkan data survival karena adanya data yang tersensor kanan. Jika dipaksakan untuk digunakan, regresi linear biasa akan memberikan hasil yang kurang akurat, karena data tersensor merupakan data yang diperoleh dari observasi yang tidak lengkap. Analisis Regresi Linear Berganda dapat digunakan apabila terdapat outlier namun kurang mampu memberikan hasil yang tepat. Data outlier tersebut yang akan dijadikan sebagai data tersensor. Untuk menganalisis data tersensor tersebut digunakan analisis Regresi Buckley-James. Pada penelitian ini, dilakukan studi kasus tentang faktor-faktor yang mempengaruhi lama waktu sembuh pasien Tuberculosis. Faktor-faktor yang diduga mempengaruhi lama waktu sembuh pasien Tuberculosis yaitu jenis kelamin, usia pasien, komplikasi, penyakit lain, pendidikan, pekerjaan, kasus, dan diagnosa. Dari hasil analisis memberikan kesimpulan bahwa metode Regresi Buckley-James memiliki nilai MAPE lebih kecil dibanding dengan metode Regresi Linier Berganda. Sehingga Regresi Buckley-James dapat lebih akurat digunakan pada data survival yang mengandung data tersensor. Kata kunci : Survival, Regresi Linear Berganda, Regresi Buckley-James, Outlier , Data Tersensor, Tuberculosis
DNA Barcoding for mangrove identification

Mangroves are distributed in the transition zone between sea and land, mostly in tropical and subtropical areas. They provide important ecosystem services and are therefore economically valuable. Mangrove species identification using traditional taxonomical methods is often burdened with taxonomic controversies. DNA barcoding provides a useful tool for species identification and phylogenetic reconstruction. rbcL and matK are short and unique DNA sequences, and also provide good identification for magrove. This critical review highlights the development of the use of molecular applications that is DNA Barcoding. We focus on observing the development of the use of DNA barcoding in the world, especially on mangroves. Our observations are limited to the use of rbcl and matk markers in some mangrove species in the world. In conjugation with newer and faster techniques such as high-throughout sequencing, rbcL and matK marker can serve as an effective modern tool in mangrove identification.
Teenage mothers’ language use during shared reading: An examination of quantity and quality

This study investigated the impact of an emergent literacy intervention on the language quality and quantity used during shared reading interactions of 14 teenage mothers (M = 19;9, SD = 1;3) and their young children (M = 2;1, SD = 0;8). Mothers participated in a seven-week emergent literacy intervention focused on a range of behaviours they could use to enhance shared reading interactions with their children. A pre-post single group (no control/comparison group) research design was used to evaluate intervention effects on language use. Results demonstrated a significant intervention effect on most aspects of language quality and quantity measured. Number of total words, total utterances and number of different words demonstrated a statistically significant increase for both mothers and children; mothers used more rare-sophisticated words; and children used more different types of word classes. Context of talk for mothers also showed significant growth in areas of description and prediction/explanation. Results provide considerations for designing parent-focused interventions to effectively target both literacy and language development in children from at-risk populations.
Conductometric determination of Betahistine dihydrochloride and Heptaminol hydrochloride using silver nitrate

A simple, precise and cost effective conductometric method was developed for determination of betahistine dihydrochloride and heptaminol hydrochloride in pure form and pharmaceutical formulations. The method is based on the precipitation of chloride ions present in cited drugs with silver ions, yielding silver chloride, the conductance of the solution is measured as a function of the volume of titrant. Effect of solvent, reagent concentration, temperature were studied and evaluated. The suggested method was applied for determination of betahistine dihydrochloride and heptaminol hydrochloride in pure forms and pharmaceutical preparations. The described procedure allowed the determination of betahistine dihydrochloride and heptaminol hydrochloride in the range of 2-10mg/ml and 2-13mg /ml respectively.The molar ratio was (2:1),(1:1) (drug:reagent) between betahistine dihydrochloride and heptaminol hydrochloride with silver nitrate respectively. The suggested procedure was applied successfully to the analysis of these drugs in their pharmaceutical formulations, and the results obtained were in agreement with those given by the official methods
Investigating Attentional Demands of a Continuous Motor Task Using Probe Reaction Time and Measures of Corticospinal Excitability

The performance of a secondary motor task during an ongoing motor task can require attention; however, it is unclear how the attentional demands of the ongoing task may affect the preparation and execution of the secondary task. Previously, probe reaction time (RT) tasks have been used as secondary tasks to investigate the attentional demands of various primary tasks. The purpose of the present experiment was to investigate whether the attentional demands of a cyclical primary motor task vary with location within a movement cycle, and whether these variations are reflected as differences in probe RT and/or measures of corticospinal excitability. Participants performed a continuous tracking task involving cycles of wrist flexion and extension with their left hand. A probe RT task involving isometric force production was performed with the right hand in response to auditory stimuli (80 dB and 120 dB) that occurred as the left hand cycled through one of five locations. Additionally, on separate trials, transcranial magnetic stimulation was applied over the left primary motor cortex to assess corticospinal excitability associated with the probe RT task. Generally, probe RT latencies were shorter following a reversal in direction of the left hand (i.e., after the left wrist cycled from flexion to extension) and there were no differences in corticospinal excitability. These results suggest that the attentional requirements for a continuous motor task vary across locations within a movement cycle, and these variations are reflected behaviourally as differences in probe RT.Acknowledgments: Supported by NSERC and the Ontario Ministry of Research, Innovation and Science
The impact of online death literacy education on psychology students to have better end‐of‐life conversations

Abstract Objective The role of psychologists is relatively invisible at end‐of‐life (EOL) and lack of training has been cited as one important reason for this. Contrasting the medicalisation of death, a new term Death Literacy references communities regaining knowledge and familiarity with the dying process. The aim of this study is to assess the impact on postgraduate students participating in a voluntary Online Death Literacy Education Module (ODELM). Methods Using a mixed methods, quasi‐experimental, repeated measure design, the current research paper measures the self‐reported Death Literacy of 86 post‐graduate psychology students. Results The results found that psychology students' overall Death Literacy increased significantly, in addition, to the specific dimensions of knowledge and comfort in having EOL conversations. Further, exposure to Death Literacy training significantly increased participants' interest in EOL concerns and enhanced their perceptions of its relevance to the role of psychologists. Qualitative findings support a high level of engagement and interest in this sensitive and emotionally challenging topic for students, particularly in having EOL conversations with children. Discussion This study shows that online delivery is an effective way to deliver Death Literacy content, particularly for fifth‐year psychology students, who benefited most from gaining professional development hours towards provisional psychologist registration. Case studies and videos stimulated reflections on both the personal and professional dimensions of EOL supporting increased Death Literacy of participants. Conclusion The strong interest and positive engagement in EOL expressed by emerging psychologists augurs well for their increased involvement in EOL care across the lifespan.
TURBIDITY PATTERNS IN THE ALBUFERA LAKE, SPAIN, AND THEIR RELATION TO IRRIGATION CYCLES

The Albufera Natural Park (Valencia, Spain) is one of the most representative coastal wetlands in the Mediterranean basin. It holds several protection designations at national and international level, such as Spanish Natural Park, Special Protection Areas (SPAs) for birds, Sites of Community Importance (SCIs) and Ramsar Site. Both the park and its main lake, Albufera’s lake, face several environmental problems. One of them is reduced transparency and lake clogging. The lake is highly dependent on the rice cycle and on irrigation returns, mainly from the Acequia Real. In this study, we analyse the monthly transparency and turbidity patterns during year 2018, and we relate them to irrigation cycles. We used Sentinel 2A satellite images from the European Space Agency, which have an atmospheric correction. Remote sensing results were compared with in situ data from the monitoring program of the Environment General Subdivision of the regional government. This monitoring program samples five points on a monthly basis, and analyses Secchi disk depth, suspended solids and chlorophyll a. Our results show the temporal and spatial pattern of turbidity in the Albufera lake which offers relevant information for water resources management.
Green Compressed Fluid Technologies To Extract Antioxidants and Lipids from Galdieria phlegrea in a Biorefinery Approach

A green cascade approach was used to recover phycocyanins, carotenoids and lipids from Galdiera phlegrea. Phycocyanin extraction was performed by high pressure homogenization and purified by ultrafiltration, whereas carotenoids were obtained by a pressurized liquid extraction and lipids by supercritical fluid extraction. The second step of this innovative, green, and cost-effective procedure is able to improve the recovery of zeaxanthin and β-carotene up to 40%, without affecting the quality of compounds and avoiding the use of organic solvents and the drying processes. The isolated carotenoids were active as antioxidants, as clearly shown by their protective activity on a cell-based model. The lipid yield was increased by 12% with respect to conventional methods.
Statistical inference of mechanistic models from qualitative data using an efficient optimal scaling approach

Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. These models usually comprise unknown parameters, which have to be inferred from experimental data. For quantitative experimental data, there are several methods and software tools available. However, for qualitative data the available approaches are limited and computationally demanding. Here, we consider the optimal scaling method which has been developed in statistics for categorical data and has been applied to dynamical systems. This approach turns qualitative variables into quantitative ones, accounting for constraints on their relation. We derive a reduced formulation for the optimization problem defining the optimal scaling. The reduced formulation possesses the same optimal points as the established formulation but requires less degrees of freedom. Parameter estimation for dynamical models of cellular pathways revealed that the reduced formulation improves the robustness and convergence of optimizers. This resulted in substantially reduced computation times. We implemented the proposed approach in the open-source Python Parameter EStimation TOolbox (pyPESTO) to facilitate reuse and extension. The proposed approach enables efficient parameterization of quantitative dynamical models using qualitative data.
The Antioxidant Activity and Phytochemical Analysis of Medicinal Plant Veronica Biloba

A medicinal plant veronica genus has 450 well known species and found across both temperate and hemisphere region their 26 species are endemic and known in a total of 79 popular species and are widely utilized throughout the world due to important biological activities. In this study fully powdered uniform size specie veronica biloba plant taken in porous bag were manually subjected to soxhlet hot continuous process for cyclization of extraction using ethanol (300 mL) a concentrated dried extract obtained after solvent evaporation. Furthermore, liquid-liquid extracted fractions as water, dichloromethane, n-hexane, and ethyl acetate yields results founds polar fraction with highest percentage (water 47.51 %). The phytochemical screening of veronica biloba has shown all major compounds entirely present in extracts. One of the primitive phenolic compound flavonoid is present in plant and show potency towards antioxidants. All the extracted fractions of plant showed excellent antioxidant activity using a stable DPPH (1,1-diphenyl-2-picryl-hydrazyl) method at concentration (range from 31.25 to 500µg/mL). Primary our ethyl acetate extract fraction showed highest inhibition potential at IC50 = 1.70±0. 05µg/mL which is much closer to a standard positive control Propyl gallate showed IC50 = 1.6±0. 05µg/mL percent potential. The purification and isolation of these extract is important which can provide us help in novel antioxidants discovery also natural antioxidants currently in cosmetics products, food and therapeutics health related products significantly demanded because they are very effective, efficient and harmless as compared to synthetic one.
Learning to fight in UN peacekeeping

ABSTRACT Peace operations of the United Nations (UN) have changed significantly since the 1990s. The turn towards “stabilisation” operations increasingly allows the use of military force against armed groups. For some troop contributing armies, this means that peacekeeping has become the first occasion on which soldiers gain combat experience. Yet, what are the consequences of this development for eventual internal public security roles of armed forces? Contributing to discussions on conditions for organisational change, this article develops a model for blending the analysis of bottom-up adaptation and top-down military innovation with studies on civil-military relations. This model is used for examining military learning that resulted from the reciprocal relationship between the Brazilian military’s internal “Guaranteeing Law and Order” (GLO) operations and coercive operations against urban crime groups during the UN Stabilisation Mission in Haiti (MINUSTAH). The article finds that a complex interplay between bottom-up adaptation and top-down innovation – enabled by politicians who supported the transfer of lessons – led to a process in which internal missions and peacekeeping deployments mutually informed military change. Soldiers’ adaptation to coercive operations, changes in the legal framework for internal missions, and the development of appropriate doctrine for urban operations resulted in the institutionalisation of military learning.
Multimorbidity and Polypharmacy in Family Medicine Residency Practices

Background: Prescription-related problems among older adults have been of great interest. However, few data are available regarding the prevalence of these problems in US family medicine residency practices (FMRPs). Objective: The aim of this research was to examine the prevalence of multimorbidity, polypharmacy, and potentially inappropriate medications (PIMs) use among older adults who visited 5 FMRPs more than once a year. Methods: A cross-sectional hospital record review for patients 65 years or older who visited 1 of the 5 university-affiliated FMRPs at least twice during January 1 to December 31, 2014, was conducted. The prevalence of multimorbidity (24 chronic index conditions), polypharmacy, and PIMs use was examined. Results: A total of 1084 patients were included in the analyses. The most common chronic conditions were hypertension (87.8%), hyperlipidemia (69.7%), and osteoarthritis (56.1%). The mean number of chronic conditions was 5.3 (SD 2.6). The prevalence of multimorbidity (≥2 chronic conditions) was 95.6%. Among these multimorbid older adults (N = 1036), the mean number of medication orders was 9.04 (SD 4.36) and 1.57 (SD 0.92) for PIMs, 86.1% met polypharmacy standards (≥5 medications), and 33.4% were prescribed one or more PIMs. The proportion of patients with fewer prescriptions at the last visit was 45.4% in the polypharmacy group and 38.0% in the PIMs group. Conclusion: Our results suggest a high level of morbidity and complexity among older adults receiving care in FMRPs. Improving the continuity of care as well as promoting interdisciplinary collaboration would have potential to reduce these prescription-related problems. Further research and education to address polypharmacy and PIMs among this population at FMRPs are required.
An investigation into the relationships between bullying, discrimination, burnout and patient safety in nurses and midwives: is burnout a mediator?

Background Bullying and discrimination may be indirectly associated with patient safety via their contribution to burnout, but research has yet to establish this. Aims The aims of this study were to investigate the relationships between workplace bullying, perceived discrimination, levels of burnout and patient safety perceptions in nurses and midwives and to assess whether bullying and discrimination were more frequently experienced by Black, Asian and minority ethnic than White nurses and midwives. Methods In total, 528 nurses and midwives were recruited from four hospitals in the United Kingdom to complete a cross-sectional survey between February and March 2017. The survey included items on bullying, discrimination, burnout and individual level and ward level patient safety perceptions. Data were analysed using path analysis. Results The results were reported according to the STROBE checklist. Bullying and discrimination were significantly associated with higher burnout. Higher burnout was in turn associated with poorer individual- and ward-level patient safety perceptions. Experiences of discrimination were three times more common among Black, Asian and minority ethnic than White nurses and midwives, but there was no significant difference in experiences of bullying. Conclusions Bullying and discrimination are indirectly associated with patient safety perceptions via their influence on burnout. Healthcare organisations seeking to improve patient care should implement strategies to reduce workplace bullying and discrimination.
EFFICIENT MACHINE LEARNING INFERENCE FOR EMBEDDED SYSTEMS WITH INTEGER BASED RESTRICTED BOLTZMANN MACHINES CLASSIFIERS

Nowadays, there exist many emerging applications for embedded systems, such as computer vision and speech recognition, which heavily rely on machine learning classification. The typical approach to carry out machine learning related tasks in embedded systems is to use the embedded device as a sensor which collects data, and then carry out the classification computations in the cloud. However, this approach presents issues in several aspects such as latency, power consumption, network bandwidth, privacy, and security. Thus, it would be ideal to perform the machine learning computations in the actual embedded device. Nonetheless, this is not a trivial task as machine learning algorithms are characterized to be too computationally intensive for the constrained specifications of embedded systems. In this work, we present an efficient machine learning classification approach based on Restricted Boltzmann Machines (RBMs) and integer arithmetic, which is suitable for embedded devices and classification problems over data containing a small to medium amount of features. Experiment results over the MNIST dataset show that approach proposed in this work outperforms the current state-of-the-art solution by a factor of 42 in terms of speed, and a factor of 62 in terms of energy efficiency. Furthermore, we propose a novel quantization method based on finite p-adic numbers which improves the efficiency of RBMs and yields higher accurate classification results than other integer quantization methods such as fixed-point quantization.
Novel seed selection techniques for MR brain image segmentation using graph cut

ABSTRACT Brain tumour segmentation is a challenging task because of high diversity of the tumour for different patients and the ambiguity in its location. The high accuracy of extracting the tumour region from the normal brain solely depends on the seed selection. This prior knowledge of the seed points is also required for the initialisation of the graph cut segmentation. In this paper, two techniques (Centroid-Based Seed Selection [CBSS] and k-Mean Seed Selection [KMSS]) for the seed selection and segmentation of the tumour region using the graph-cut technique are proposed. The intensity distribution in the MRI brain images is utilised for the calculation of these points. In (CBSS), the symmetrical intensity distribution on both half of the brain is exploited. While in (KMSS) different groups of the similar intensity distribution are formed. The seed values obtained initialise the Graph-cut method to perform the segmentation. The performance parameters for the proposed methods are evaluated using MR brain images from standard and real time dataset. The mean Dice Sensitivity Coefficient (DSC) and mean Jaccard Index (JI) values are evaluated for indicating effectiveness and accuracy of the proposed work.
A methodology to quantify risk of failure for dynamic robots

Humans possess an innate sense of danger that guides the execution of extraordinary dynamic maneuvers. They can also use this sense to generate creative recovery strategies to eventually come to a safe stop. This capability is not yet available to robots, fundamentally because there is no clear metric that represents the quantified risk of failing. Possessing such a metric would allow robots to explore their dynamic capability up to their physical limitations. This thesis attempts to address this problem by introducing a methodology to quantify the risk of failure for dynamic robots. It employs a sampling-based network constructed using the principles of viability theory, which focuses on the avoidance of failure instead of the regulation to specific movements. Simplifications that specifically target complex hybrid systems are explored to extend the usage of viability theory for practical application to legged robots. The results of this methodology are the Viable State Network, a network showing the non-failing and failing states, and the Risk Map, the quantified risk of failure. These concepts are demonstrated for a planar hopping robot model. Thesis Supervisor: Sangbae Kim Title: Associate Professor