Miracle-dz/UniFAR-FTUs huggingface dataset:
II ) : a randomized trial to determine whether HLA class II matching reduces the risk of allograft rejection in penetrating keratoplasty

Armitage WJ, Winton HL, Jones MNA, Downward L, Crewe JM,Rogers CA, Tole DM, Dick AD Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK NHS Blood & Transplant, Bristol, UK Bristol Trials Centre, Bristol Medical School, University of Bristol, Bristol, UK Bristol Eye Hospital, Bristol, UK School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK Corresponding author: Professor W John Armitage Translational Health Sciences, Bristol Medical School University of Bristol Bristol Eye Hospital Lower Maudlin Street Bristol BS1 2LX United Kingdom Email: w.j.armitage@bristol.ac. uk
SYSTEMATICKÝ LITERÁRNY PREHĽAD FEAR OF FALLING AND QUALITY OF LIFE IN OLDER ADULTS: SYSTEMATIC LITERATURE REVIEW BOBKOWSKA Michaela, MATIŠÁKOVÁ Iveta Fakulta zdravotníctva, Trenčianska univerzita Alexandra Dubčeka v Trenčíne, Trenčín

Background: Maintaining and improving the quality of life is the subject and at the same time the objective of nursing not only in the practise, but also in the field of research. Fear of falling, which is a common phenomenon in the elderly population, can lead to limited activity and social participation, with a negative impact on the quality of life. Aim: The objective of the systematic review was to find out the impact of experiencing the fear of falling on the quality of life; to identify the areas of quality of life that are most affected by fear of falling; to analyse conceptual approaches and tools for objectifying the fear of falling used in the assessment of the quality of life of the elderly. Design and Method: A systematic literature review of relevant studies published from 2009 to 2020 in the Medline/PubMed database was conducted. Sample and Results: By analysing fifteen mostly cross-sectional studies, we found out in a sample of 25 947 participants with an average age of 73.98 and a predominance of women (72 %) that the rate of fear of falling statistically significantly changes the quality of life. The most significant effect of fear of falling was identified in the field of physical functioning. Less, but statistically significantly, the quality of life was reduced due to the fear of falling in the field of pain experience, subjectively perceived health, and role-playing. Fear of falling was most often assessed on a single item or on the scale of The Fall Efficacy Scale – International (FES-I). Conclusion: The extent of experienced fear of falling is statistically significantly associated with the quality of life related to health, especially at the level of physical health and functioning of the elderly. In terms of the research of the quality of life and fear of falling, FES-I is a sufficiently sensitive, valid and reliable tool for objectification of the fear of falling in older adults.
Parameters Estimation for Condition Based Maintenance with Uncorrelated and Correlated Observations

ABSTRACT Condition Based Maintenance (CBM) is based on the assessment of equipment state which is obtained by measuring some indicators. When there is uncertainty concerning the state of the equipment, the measurements gathered are called imperfect. In this case the equipment aging and degradation process is assumed to follow a Markov process and is modeled by a Hidden Markov Model (HMM). This article describes a general procedure that can be used to estimate the parameters of the HMM. It is based on the Expectation-Maximization (EM) algorithm. The procedure deals with independent as well as correlated maintenance observations. The latter are most common in CBM applications. Simulated examples are presented.
Scanning Electron Microscopy (SEM) of Monitor Lizards’ Scale Ultrastructure: Systematic Implications

Because monitor lizards, in contrast to most other squamate lizards, lack differentiated head and body scales (fuchs & fuchs, 2002), except for the enlarged supraoculars and enlarged to spinose neck scales in some species, the use of scalation features for systematic questions is generally confined to quantitative analyses, which help to distinguish between species with larger, and thus fewer scales, or those with smaller, and consequently more body scales (e.g., mertens, 1942; Brandenburg, 1983; Böhme et al., 1994; koch et al., 2010b). While the microstructure of body scales has been used in various other squamate reptiles to differentiate between distinct species and even higher taxonomic categories (e.g. stewart et al., 1973; arnold, 2002), this methodological approach is now applied for the first time to lizards of the family Varanidae. across all nine recognized subgenera of the genus Varanus scale shape and structure were analyzed using scanning electron microscopy (sem). in a preliminary approach, we investigated the dorsal scales of 37 species (i.e. >50% of the species currently recognized) in order to answer the question if qualitative scalation features are useful for systematic issues. our results show that a microornamentation (ultradermatoglyphics) as seen in various squamate groups is also partly present in monitor lizards. However, only in a few, albeit unrelated, monitor species examined do the dorsal scales exhibit a specific honeycomb microstructure (fig. 1). the ecological meaning of this microstructure, if any, remains unknown. Nevertheless, scale shape as well as the extent and size of granula rows around the main scales allow differentiation between single species, even among close relatives, such as the members of the V. indicus species group (Ziegler et al., 2007). special attention was paid to V. spinulosus mertens, 1941, a rare endemic
Mindfulness and ethical decision making : A short mindfulness exercise affects the cheating behavior among students

The views stated in this thesis are those of the author and not necessarily those of the supervisor, second assessor, Erasmus School of Economics or Erasmus University Rotterdam. This paper investigates the effect of a short mindfulness exercise on the cheating behavior among students between the age of 16 and 26. I conducted an online randomized experiment. Participants in the treatment watched a short mindfulness video focusing on the body, mind and environment, whereas participants in the control group watched a funny video of similar length. As measured by the MAAS-scale, the mindfulness exercise increased people’s mindfulness level. However, the higher mindfulness level did not affect people’s cheating behavior.
COMPUTER GENERATIVE METHOD ON BRAIN TUMOR SEGMENTATION IN MRI IMAGES

Computer generative method has been used for long time in brain tumor segmentation tasks on magnetic resonance images. The popularity of machine learning also prompts people to explore the use of generative methods to better train their segmentation models. At the early stage, brain tumor segmentation competitions like BraTS 2012 used computer synthetic MR images with tumor to solve the lack of enough data in the training set, and now, with the rise of computer generative models in deep learning, more researchers have started to work on this track to find a better solution for the task. This thesis addresses the implementation and analysis of some existing methods, specifically a tumor synthetic tool called TumorSim and a competition winning deep learning model that incorporates variational auto-encoder as a generative model. This thesis also reports on an experiment that uses imperfect segmented tumors from simple models as the input to a generative adversarial network to generate a better result.
MAIN ASPECTS OF SYSTEMS AND NETWORK THINKING IN MANAGEMENT

System development methodology has become a prerequisite for understanding the logic of the evolution of the economic crisis and for creating strategies for sustainable development. Systems thinking can penetrate beyond the limits of what appears to be isolated and independent events, and see the underlying structure. This allows managers to recognize the relationship between events, and thus improve their ability to understand and influence the future. The lack of a systems approach, and the lack of analytical capacity, can result not only in the inability to achieve expected results, but above all in the loss of the ability to generate value for the company. This article presents some aspects of the use of systems and network thinking in management.
Optimization Model for Groundwater Management in Multi‐Aquifer Systems

The use of embedding technique as a mechanism for coupling the simulation model of a particular groundwater system with an optimization model has been extended herein to multi-aquifer systems. The combined management model is used to determine the optimal groundwater management schemes in a hypothetical multi-aquifer system under transient and steady state conditions. The model enables the determination of optimal allocation of wells in different aquifers and their pumping rates to achieve a system-wide maximum head distribution while satisfying the water production targets, well capacity restrictions and lower bounds on hydraulic heads at critical points. Constraint and weighting methods of the multi-objective programming techniques are used to develop trade-off curves relating the sum of hydraulic heads in the whole system as well as in individual aquifers at various water production targets. The generated trade-off curves may enhance the decision maker’s ability to select the best development policy from a set of alternative policies by considering other technological, financial and legal constraints.
On Interbeing and Learning to Respect Everything Beyond the Self

to Respect Everything Beyond the Self by Hiroshi Munehiro Niwano 3 Th e Buddhahood of Plants and the Japanese View of Nature by Fumihiko Sueki 6 Does a Dewdrop Teach Dharma? Zen Perspectives on the Teachings of the Insentient by Kenneth Kraft 10 Th e Buddhahood of All Insentient Beings by Brook Ziporyn 13 A Prayer for “Plants and Trees, Countries and Lands, All Become Buddhas” by Shinsui Okada 16 How Do We Respect the Buddha-Nature of Nature? by David R. Loy 20 Flowers of Sentience, Roots of Consciousness: Th e Buddhahood of Plants in the Nō Th eater by M. Cody Poulton
A Study of Promoting and Developing Model for Leisure Farm

Taiwan enters the leisure society, and optimistically, many traditional farms are transformed into a leisure farm. However, a number of farms lack business philosophy and therefore, struggle in the severe competition in the industry. In this study, since the researchers have been involved in the leisure farm management counseling practical experience, they make an effort to sum leisure farm development model, with reference to tourism planning concepts and theories (tourist area cycle of evolution, tourism impact, social exchange theory, and resource based and key success factors). According to the model of operation process works, leisure farms can participate in tourism development together with local residents, integrate other local sightseeing source on the basis of its own resources, and develop each product positioning. Finally, the process of various leisure farm competition and cooperation is able to promote the development of the local economy.
Reinforcement Learning Robot Control with Progressive State Aggregation

Abstract While reinforcement learning algorithms based on parametric models can deal with the curse of dimensionality, convergence properties can be difﬁcult to establish and their performance in practice heavily depends on the choice of the basis functions. We propose a reinforcement learning algorithm based on an adaptive aggregation scheme deﬁned by a progressively growing set of codevectors placed in the joint state-action space according to a maximum-entropy vector quantization scheme. The proposed algorithm can be used for robot control and constitutes a two-timescale stochastic approximation algorithm with: (a) a fast component that executes a temporal-difference learning algorithm, and (b) a slow component, based on an online deterministic annealing algorithm, that adaptively partitions the state-action space according to a dissimilarity measure that belongs to the family of Bregman divergences. The proposed online deterministic annealing algorithm constitutes a competitive-learning neural network that shows robustness with respect to the initial conditions, requires minimal hyper-parameter tuning, and provides online control over the performance-complexity trade-off.
Proposed design of a DSS for the justification of advanced manufacturing technologies

The design of a decision support system (DSS) that helps the strategic planner evaluate the effect of advanced manufacturing technology (AMT) on the performance of an organization and determine the parameters which affect the costs and benefits of such a system is introduced. The DSS involves analysis and quantification of costs and benefits through the use of interacting accounting, simulation, and optimization modules. It enables the decision maker to perform sensitivity analyses by allowing consideration of various scenarios and different levels of various inputs. In this DSS, the decision maker is able to combine either traditional accounting techniques or activity-based costing with simulation and optimization in order to arrive at a decision as to the level of investment to make in an AMT system. >
Failure to Learn: The BP Texas City Refinery Disaster

Disastrous DecisionsSleep Disorders and Sleep DeprivationFrom Hypertension to Heart FailureMacondo Well Deepwater Horizon BlowoutFailure to LearnChecklist Manifesto, The (HB)Deep Learning with PythonBlack Box ThinkingDrift into Failure12 Rules for LifeFailure to Learn Mandarin VersionThe Merchant of VeniceCollective CourageRenal Vascular DiseaseMindsetHeart MafiaYour Guide to Lowering Your Blood Pressure with DashBlowout in the GulfFailure to Learn The BP Texas City Refinery disasterAdaptMiseducatedNormal AccidentsCommunities in ActionAll We Can SaveChronic Kidney Disease and HypertensionLearning from FailuresMayo Clinic 5 Steps to Controlling High Blood PressureFailure to LearnSpills and SpinParenting MattersPattern Recognition and Machine LearningThe Subtle Art of Not Giving a F*ckDisastrous DecisionsEvolution of a Corporate IdealistCardiovascular HemodynamicsRun to Failure: BP and the Making of the Deepwater Horizon DisasterThe Night the Lights Went OutA Hole at the Bottom of the SeaUnsettledControlling High Blood Pressure through Nutrition, Supplements, Lifestyle and Drugs
Amplification of spontaneous emission in erbium-doped single-mode fibers

Amplification of spontaneous emission (ASE) in erbium-doped single-mode fiber amplifiers operating at lambda =1.53 mu m is studied theoretically and experimentally. The ASE noise spectra obtained from the theory are found to be in excellent quantitative agreement with the experimental data. The observed changes in ASE spectral shapes under different population inversion conditions are also explained. The model may be used to evaluate the performance of erbium-doped fiber lasers as well as to assess the noise characteristics of erbium-doped fiber amplifiers as applied to wavelength-division multiplexing optical communications. >
Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia

MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare for the inverse problem the standard dipole scanning method with two beamformer approaches and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG and combined EEG and MEG. For forward modeling, we investigate the difference between calibrated six-compartment and standard three-compartment head modeling. In a retrospective study of two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure-freedom following lesionectomy or radiofrequency-guided thermocoagulation, we used the distance of the localization of interictal epileptic spikes to the resection cavity resp. rediofrequency lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modeling was smaller, due to similar skull conductivity modeling and the fixed source space without orientation constraint.
Effect of Post Deposition Annealing Process on the pH Sensitivity of Spin-Coated Titanium Dioxide Thin Film

This paper presents an investigation on titanium dioxide (TiO2) thin film, which is used as sensing membrane for Extended-Gate Field Effect Transistor (EGFET) for pH sensing application. TiO2 thin films were deposited using sol-gel spin coating method on indium tin oxide (ITO) substrates. After the deposition, the thin films were annealed at 300 °C for 10 and 15 min, while another sample was annealed at 400 °C for 15 min. The sensitivity measurement was taken using the EGFET setup equipment with constant-current (100 μA) and constant-voltage (0.5 V) biasing interfacing circuit. TiO2 thin film as the pH-sensitive membrane and the working electrode was connected to a commercial metal-oxide semiconductor FET (MOSFET). The MOSFET then was connected to the interfacing circuit. The sensitivity of the TiO2 thin film towards pH buffer solution was measured by dipping the sensing membrane in pH4, pH7 and pH10 buffer solution. For comparison, a sample of bare-ITO was also tested to see its sensitivity. We found that the TiO2 thin film annealed at 400 °C for 15 min gave the highest sensitivity compared to other annealing conditions and also compared to the bare ITO substrate with the value of 44.30 mV/pH. This showed that TiO2 thin film can be used for pH sensing and the post-deposition treatment of the thin film can influence the sensing ability. We also measured the TiO2 thin films’ current – voltage (I-V) characteristics. Relating the I-V characteristic of the thin films and sensitivity, the sensing membrane with higher conductivity gave better sensitivity.
Datensouveränität für Verbraucher: innen: Technische Ansätze durch KI-basierte Transparenz und Auskunft im Kontext der DSGVO

Hinreichende Datensouveränität gestaltet sich für Verbraucher:innen in der Praxis als äußerst schwierig. Die Europäische Datenschutzgrundverordnung garantiert umfassende Betroffenenrechte, die von verwantwortlichen Stellen durch technischorganisatorische Maßnahmen umzusetzen sind. Traditionelle Vorgehensweisen wie die Bereitstellung länglicher Datenschutzerklärungen oder der ohne weitere Hilfestellungen angebotene Download von personenbezogenen Rohdaten werden dem Anspruch der informationellen Selbstbestimmung nicht gerecht. Die im Folgenden aufgezeigten neuen technischen Ansätze insbesondere KI-basierter Transparenzund Auskunftsmodalitäten zeigen die Praktikabilität wirksamer und vielseitiger Mechanismen. Hierzu werden die relevanten Transparenzangaben teilautomatisiert extrahiert, maschinenlesbar repräsentiert und anschließend über diverse Kanäle wie virtuelle Assistenten oder die Anreicherung von Suchergebnissen ausgespielt. Ergänzt werden außerdem automatisierte und leicht zugängliche Methoden für Auskunftsersuchen und deren Aufbereitung nach Art. 15 DSGVO. Abschließend werden konkrete Regulierungsimplikationen diskutiert.
A hybrid projection algorithm for stochastic differential equations on manifolds

Stochastic differential equations projected onto manifolds occur widely in physics, chemistry, biology, engineering, nanotechnology and optimization theory. In some problems one can use an intrinsic coordinate system on the manifold, but this is often computationally impractical. Numerical projections are preferable in many cases. We derive an algorithm to solve these, using adiabatic elimination and a constraining potential. We also review earlier proposed algorithms. Our hybrid midpoint projection algorithm uses a midpoint projection on a tangent manifold, combined with a normal projection to satisfy the constraints. We show from numerical examples on spheroidal and hyperboloidal surfaces that this has greatly reduced errors compared to earlier methods using either a hybrid Euler with tangential and normal projections or purely tangential derivative methods. Our technique can handle multiple constraints. This allows, for example, the treatment of manifolds that embody several conserved quantities. The resulting algorithm is accurate, relatively simple to implement and efficient.
Cadence: A Practical Time-series Partitioning Algorithm for Unlabeled IoT Sensor Streams

Timeseries partitioning is an essential step in most machine-learning driven, sensor-based IoT applications. This paper introduces a sample-efficient, robust, time-series segmentation model and algorithm. We show that by learning a representation specifically with the segmentation objective based on maximum mean discrepancy (MMD), our algorithm can robustly detect time-series events across different applications. Our loss function allows us to infer whether consecutive sequences of samples are drawn from the same distribution (null hypothesis) and determines the change-point between pairs that reject the null hypothesis (i.e., come from different distributions). We demonstrate its applicability in a real-world IoT deployment for ambient-sensing based activity recognition. Moreover, while many works on change-point detection exist in the literature, our model is significantly simpler and can be fully trained in 9-93 seconds on average with little variation in hyperparameters for data across different applications. We empirically evaluate Cadence on four popular change point detection (CPD) datasets where Cadence matches or outperforms existing CPD techniques.