Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of the STOPP and START criteria to address polypharmacy for elderly patients in University Hospital Lewisham Clinical Decisions Unit

Background: Polypharmacy and inappropriate prescribing are risk factors for adverse drug reactions, which commonly cause complications in older people. The STOPP (Screening Tool of Older Persons’ Prescriptions)/START (Screening Tool to Alert Doctors to Right Treatment) criteria are screening tools, which aim to improve prescribing in the elderly. Objectives: The aim was to improve prescribing, using the STOPP/START criteria, for patients aged 65 and above, who were admitted to the Clinical Decisions Unit at University Hospital Lewisham. We focused on the most common prescribing errors in clinical decision unit, an emergency medicine department. Methods: We reviewed all patients aged 65 and above admitted to the Clinical Decisions Unit in September. Data was collected from clinical documentation and archived drug charts. This pilot study of 114 patients revealed the most common prescribing errors, of which 8 were STOPP and 11 were START criteria. A plan–do–study–act methodology was implemented over 1 month, involving presentations, emails and posters. Prescribing patterns were then reviewed over 4 weeks in December in 111 patients. Results: Focusing on the 8 STOPP and 11 START criteria, there was a significant reduction in the proportion of patients with at least one STOPP error (17.5% to 9%, p = 0.04). However, the decrease in the percentage of patients with at least one START error was insignificant (24.6% to 20.7%, p = 0.24). Conclusion: By identifying problematic areas of prescribing and using targeted interventions, the proportion of STOPP errors made in clinical decision unit reduced significantly. This study highlights the prevalence of prescription errors in the clinical decision unit and the impact of using screening tools to reduce incorrect prescribing.
An Object-Oriented L-System for Simulating Tree Growth

In practice, when man develops a game or an animation, one problem encountered is that application programmers usually derive a new code from scratch for each application . In order to simplify the programming, this paper presents an object-oriented L-system model which can simulate a variety of trees growth. For real-time rendering,this paper also introduces some efficient and concise algorithms for animation control and interactions between trees and their environments based on the simplification of tree’s biological properties . Based on this object-oriented L system, the growth of different kinds of trees can be visualized and simulated by inputing different production rules and environmental data. As a result the development time can be shortened with the reuse of the code.
Reconfigurable tesh connected parallel computers

Computing structures for the twenty-first century will require sub-micron technologies, highly parallel architectures capable of performing at teraflops level, and software paradigms that have not been invented yet. One of the major obstacles in the design and construction of such parallel computers is the binding ether for the processing modules. This dissertation develops efficient and cost effective connectivity for highly scalable, expandable, and manufacturable parallel computing structures. Specifically, a new class of modular interconnection networks--Tori Connected Meshes (TESH)--is investigated. Important characteristics of the network, that are critical to microchip implementation on the one hand and efficient embedding of applications on the other, are studied in depth. It is shown that the wiring complexity of the TESH is up to four times smaller than that of a comparable mesh network, and an order of magnitude smaller than that of the hypercube. Also, recognizing that the brain of a network is the set of its distributed routers, this critical sub-system is designed for the TESH network. From the perspective of the semiconductor industry, defect tolerance is exceedingly important for economical manufacturing of large-scale computing structures. To automate this process, an efficient methodology and corresponding software for reconfiguration and defect circumvention are developed. It includes placement, that assigns logical nodes to healthy physical nodes, and routing, that reconfigures switches to bypass the defective components--cells, switches and links. Theoretical predictions as well as simulations indicate that yields approaching 100% can be attained for 256- to 4096-node computing structures. This creates the potential for manufacturing TESH based parallel machines with tens to hundreds of tera-ops performance. Advanced algorithms such as real-time solution of partial differential equations, 2-D wavelet transforms, and multi-layer artificial neural networks are mapped using the parallelism of a TESH connected array of processors. The partial differential equation models are relevant in modeling various physical phenomena such as fluid flow, and dynamic electromagnetic fields. It is also well known that their real-time solution (which would make them attractive to the industry as well as the scientific community) requires tens to hundreds of tera-ops per second. The 2-D wavelet transform, on the other hand, finds application in digital video and image processing such as a fingerprint or retina scan identification. Both of these algorithms are implemented in such a way so as to completely hide the communication overhead. Even more important, it is shown that the performance of a TESH implemented algorithm is comparable to the MESH based algorithm. This is significant because TESH networks are easier to implement due to the much reduced wiring than MESH networks. We believe that this dissertation has taken a significant step toward providing the ether for highly scalable, expandable, and manufacturable parallel computing structures of the future.
A Broadband Differential Antenna Based on Common-Gate/Common-Source Active Balun Feed

Abstract In this paper, a novel broadband differential antenna is designed. An active balun is utilized to realize the wideband differential feed to achieve low cross- polarization antenna radiation within the working frequency of 1.0–1.6 GHz. The active balun uses a common-gate/common-source structure to achieve two equal-amplitude signals with 180° phase difference. The differential antenna is composed of rectangular slot floor and symmetrical radiation patch. The antenna is fed by the out-of-phase output of the active balun. The tested results in 1.0–1.6 GHz show the cross-polarization of E and H plane of the proposed differential antenna are lower than −22 dB, with maximum radiation direction gain is 2.3 dBi. The measured reflection coefficient of the proposed differential antenna based on the active balun feed is in good agreement with the simulation data.
EDCrammer: An Efficient Caching Rate-Control Algorithm for Streaming Data on Resource-Limited Edge Nodes

This paper explores data caching as a key factor of edge computing. State-of-the-art research of data caching on edge nodes mainly considers reactive and proactive caching, and machine learning based caching, which could be a heavy task for edge nodes. However, edge nodes usually have relatively lower computing resources than cloud datacenters as those are geo-distributed from the administrator. Therefore, a caching algorithm should be lightweight for saving computing resources on edge nodes. In addition, the data caching should be agile because it has to support high-quality services on edge nodes. Accordingly, this paper proposes a lightweight, agile caching algorithm, EDCrammer (Efficient Data Crammer), which performs agile operations to control caching rate for streaming data by using the enhanced PID (Proportional-Integral-Differential) controller. Experimental results using this lightweight, agile caching algorithm show its significant value in each scenario. In four common scenarios, the desired cache utilization was reached in 1.1 s on average and then maintained within a 4–7% deviation. The cache hit ratio is about 96%, and the optimal cache capacity is around 1.5 MB. Thus, EDCrammer can help distribute the streaming data traffic to the edge nodes, mitigate the uplink load on the central cloud, and ultimately provide users with high-quality video services. We also hope that EDCrammer can improve overall service quality in 5G environment, Augmented Reality/Virtual Reality (AR/VR), Intelligent Transportation System (ITS), Internet of Things (IoT), etc.
Multi-Source Traffic Data Reconstruction Using Joint Low-Rank and Fundamental Diagram Constraints

Accurate and complete traffic information plays an important role in traffic monitoring, traffic state estimation and prediction in all intelligent transportation systems. However, in practice, data provided from various types of traffic sensors may suffer from many issues, such as heterogeneity, missing data and bias. Therefore, extracting unbiased, accurate and complete data from multiple traffic data sources, referred to as multi-source traffic data reconstruction, is critical before data can be utilized. There are many existing methods for multi-source traffic data reconstruction, but two issues remain challenging and unaddressed: the effectiveness of reconstruction is fairly limited to attributes of available data, especially data loss ratio and reliability; the probability distribution of data assumed, which brings in bias prior to data analytics. This paper proposes a novel framework that integrates low-rank representation and fundamental traffic flow models into multi-source traffic data reconstruction. It makes full use of multi-source data, and can simultaneously impute missing data and eliminate outliers/errors. Multiple parameters in the traffic flow models are learned from large-scale spatio-temporal data, which ensures the extracted and imputed data are consistent with traffic flow physics. Experimental results on real-world traffic data demonstrate the superiority of this method over existing methods.
Solution Techniques for Transient Stability Constrained Optimal Power Flow - Part II

This series of studies present the state-of-the-art for the solution of the transient stability constrained optimal power flow problem (TSC-OPF). Three different classes of solution techniques: dynamic optimisation-based, SIME method, and computational intelligence, are discussed in detail. Moreover, discussed are issues to consider while solving such problems, various application areas, and future directions in this research area. A comprehensive resource of the available literature, publicly available test systems, and relevant numerical libraries is also provided. This study presents the TSC-OPF formulation and discusses various dynamic optimisation-based approaches. Two optimisation techniques, full-space and reduced-space method, are presented for solving the resulting non-linear optimisation problem.
Corrosion Initiation and Service Life of Concrete Structures

The Corrosion of steel reinforcements in concrete is of great concern in the view of safety and durability of reinforced concrete structures. The reinforced concrete structures exposed to sea environments suffer from corrosion of steel bars due to chloride ingress. The chloride penetration into concrete is influenced by many parameters such as type of cement, mixture proportions and existence of rebars. The conventional diffusion analyses have neglected the existence of steel bar in concrete. The purpose of the present paper is, therefore, to explore the effects of reinforcement on the chloride diffusion in concrete structures by incorporating realistic diffusion models. To this end, the nonlinear binding isotherm which includes the effects of cement types and mixture proportion has been introduced in the chloride diffusion analysis. The effects of reinforcements on the chloride penetration have been analyzed through finite element analysis. The present study indicates that the chlorides are accumulated in front of a reinforcing bar and the accumulation of chlorides is much more pronounced for the case of larger-size bars. The higher accumulation of chlorides at bar location causes faster corrosion of reinforcing bars. The corrosion initiation time reduces by about 30-40 percent when the existence of rebar is considered in the chloride diffusion analysis.
Advising matters:: engineering transfer students’transition experiences at five institutions

This study identifies challenges that engineering transfer students may face as they transition from one institution toanother while pursuing their undergraduate degrees and explores ways institutions can address and potentially mitigatethese challenges. We interviewed 86 engineering transfer students at five institutions in the US to identify policies andpractices that can be employed to improve the transfer process. The results reveal two themes within the control ofuniversities and engineering colleges that contribute to the ease or difficulty of transferring to these institutions. The firsttheme,transmitting information, includes advising, orientation, mentoring, and websites for engineering transfer students.The second theme,policies and processes, includes formal transfer programs (e.g., 3+2 programs), relationships with keyfeeder schools, admissions, and accepting transfer credits. We conclude that online and in-person advising that takes placeduring the pre-transfer, pre-enrollment, and first term of the student’s transition is critically important to a successfuloverall experience in the new institution. Students experienced challenges with the unexpected delays associated withformal transfer programs, such as 3+2 programs; administrators should ensure that students enrolled in these programsgraduate in a timely fashion.
Individualized Interaural Feature Learning and Personalized Binaural Localization Model

The increasing importance of spatial audio technologies has demonstrated the need and importance of correctly adapting to the individual characteristics of the human auditory system, and illustrates the crucial need for humanoid localization systems for testing these technologies. To this end, this paper introduces a novel feature analysis and selection approach for binaural localization and builds a probabilistic localization mapping model, especially useful for the vertical dimension localization. The approach uses the mutual information as a metric to evaluate the most significant frequencies of the interaural phase difference and interaural level difference. Then, by using the random forest algorithm and embedding the mutual information as a feature selection criteria, the feature selection procedures are encoded with the training of the localization mapping. The trained mapping model is capable of using interaural features more efficiently, and, because of the multiple-tree-based model structure, the localization model shows robust performance to noise and interference. By integrating the direct path relative transfer function estimation, we propose to devise a novel localization approach that has improved performance in the presence of noise and reverberation. The proposed mapping model is compared with the state-of-the-art manifold learning procedure in different acoustical configurations, and a more accurate and robust output can be observed.
Strategy for Modelling Nonrandom Missing Data Mechanisms in Observational Studies Using Bayesian Methods

Observational studies are notoriously full of non-responses and missing values. Bayesian full probability modelling provides a °exible approach for analysing such data, allowing a plausible model to be built which can then be adapted to carry out a range of sensitivity analyses. In this context, we propose a strategy for using Bayesian methods for a `statistically principled' investigation of data which contains missing covariates and missing responses, likely to be non- random. The ¯rst part of this strategy entails constructing a `base model' by selecting a model of interest, then adding a sub-model to impute the missing covariates followed by a sub-model to allow informative missingness in the response. The second part involves running a series of sensitivity analyses to check the robustness of the conclusions. We implement our strategy to investigate some typical research questions relating to the prediction of income, using data from the Millennium Cohort Study.
Marketing sonic thinking with creative visualization: getting decision-makers to listen

ABSTRACT Sound artists and musicians understand sound’s impact on health and well-being; their knowledge can make a difference in the planning and construction of healthy cities. As immersive sound experience designers at Charles Morrow Productions LLC, the authors have created numerous installations for health and well-being throughout the world. In our professional experience, however, communicating our knowledge about the importance of sound to visually-oriented professionals who design and manage urban spaces can be a challenge. In this article, we outline our learnings in order to develop principles for visualizing sonic environments that can help decision-makers to listen to and with us. We speculate that such visualizations may aid other sound artists and designers to generate interest for sound among diverse stakeholders.
Experimental Study of Defect Localization in a Cross-Ply Fiber Reinforced Composite with Diffuse Ultrasonic Waves

Diffuse wave inspection benefits from multiple scattering and is suitable for the nondestructive testing of complex structures with high sensitivity. This paper aims to localize the defect in a cross-ply carbon fiber reinforced polymer composite with the diffuse wave field experimentally based on the Locadiff technique. Firstly, the wave diffusivity and dissipation parameters are determined from the diffuse waveforms. Great dissipation is found for this composite plate due to its strong viscoelasticity, which makes the amplitude attenuate fast in a short propagation distance. The signal-to-noise ratios degrade significantly at off-axis directions so that only measurements along the X and Y axes are chosen. Secondly, the decorrelation coefficients are determined using the stretching technique. The decorrelation coefficients decrease initially due to the interaction between the wave fields and the defect and subsequently increase due to the low signal-to-noise ratio at the later time. Based on these data, a sensitivity time domain is chosen to center at t = 50 μs. Together with the defect sensitivity kernel calculated under constant diffusion property assumption, the defect is localized at [270 mm, 265 mm] compared to [300 mm, 280 mm] in the final reference state. This method is promising for early damage detection in fiber reinforced composite structures.
A Survey of Semantic Web Based Architectures for Adaptive Intelligent Tutoring System

Most recently, IT-enabled education has become a very important branch of educational technology. Education is becoming more dynamic, networked, and increasingly electronic. Today’s is a world of Internet social networks, blogs, digital audio and video content, et cetera. A few clear advantages of Web-based education are classroom independence and availability of authoring tools for developing Web-based courseware, cheap and efficient storage and distribution of course materials, hyperlinks to suggested readings, and digital libraries. However, there are several challenges in improving Webbased education, such as providing for more adaptivity and intelligence. The main idea is to incorporate Semantic Web technologies and resources to the design of artificial intelligence in education (AIED) systems aiming to update their architectures to provide more adaptability, robustness, and richer learning environments. The construction of such systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This chapter addresses state of the art Semantic Web methods and tools used for modeling and designing intelligent tutoring systems (ITS). Also it draws attention of Semantic Web users towards e-learning systems with a hope that the use of Semantic Web technologies in educational systems can help the accomplishment of anytime, anywhere, anybody learning, where most of the web resources are reusable learning objects supported by standard technologies and learning is facilitated by intelligent pedagogical agents, that may be adding the essential instructional ingredients implicitly.
Superkilen: exploring the human–nonhuman relations of intercultural encounter

ABSTRACT Superkilen is a much-lauded contemporary urban public space that has been widely photographed and the subject of public talks, articles, interviews, short films, books and awards, including the prestigious Aga Khan Award for Architecture in 2016. Although it was designed to improve social cohesion in the multi-ethnic neighbourhood of Nørrebro, it remains largely unresearched in how well its built form contributes to this goal. This paper provides an empirical examination of how the built form of Superkilen enables and constrains intercultural encounter. The paper begins with an exploration of literature on encounter in public spaces, and the agency of built form in mediating such interactions. The paper then presents three key findings based on ethnographic fieldwork using actor-network theory. This paper is critical of the design concept behind Superkilen, claiming that it privileged spatial representation above spatial practice. However, the findings also show how such encounters can be triangulated, shaped and programmed. It is hoped these findings will better inform urban designers in shaping public space for intercultural encounters in Western cities.
Reduction of Posttraumatic Stress Disorder (PTSD) Symptoms in PTSD and Major Depressive Disorder Comorbidity After Acute Hypoglycemia—A Case Report

Background: Approximately half of all patients with posttraumatic stress disorder (PTSD) also suffer from major depressive disorder (MDD). This co-occurrence might lead to an impairment of cognitive functions, worse response to antidepressant medications, and an increased risk of suicide in comparison to patients with PTSD alone. Prognosis for people with PTSD and MDD co-occurrence is poorer than for either one alone; therefore, researchers look for novel, effective treatments. Case Presentation: A patient with MDD with the co-occurrence of PTSD was admitted to the Department of Endocrinology with suspicion of adrenal insufficiency. In order to assess the adrenocorticotropin/cortisol axis, a standard insulin tolerance test was performed. After inducing a hypoglycemic episode with intravenous short-acting insulin, PTSD symptoms were reduced. To the best of our knowledge, this is the first report on the reduction of PTSD symptoms after performing an insulin tolerance test. Conclusion: Reduction of PTSD symptoms in PTSD and MDD comorbidity has been noticed after a hypoglycemic episode. This demonstrates the mutual dependencies between the endocrine and nervous systems, covered extensively by psychoneuroendocrinology.