WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/256

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17th International Conference on Mechatronics Technology, October 15-18, 2013, Jeju Island, Korea
(Elsevier, 2015) Hwang, Sung Ho; Kim, Joon-wan; Dorantes-Gonzalez, Dante Jorge
In recent years, Mechatronics has gained a lot of interest as more applications have been introduced to industry and society. The need for new mechatronic technologies in the form of advanced production systems, mechatronic devices, control systems, robotics, biomedical applications, MEMS, and measurement systems, among others, is very much required in improving productivity and competitiveness in many industries. Thus, this conference was organized to address the state-of-the-art technology for the benefit of researchers and users, and this time the conference made a special focus on the topic: Sustainable Mechatronics Technology.
A Bayesian Allocation Model Based Approach To Mixed Membership Stochastic Blockmodels
(Taylor and Francis Ltd., 2022) Kırbız, Serap; Hızlı, Çağlar
Although detecting communities in networks has attracted considerable recent attention, estimating the number of communities is still an open problem. In this paper, we propose a model, which replicates the generative process of the mixed-membership stochastic block model (MMSB) within the generic allocation framework of Bayesian allocation model (BAM) and BAM-MMSB. In contrast to traditional blockmodels, BAM-MMSB considers the observations as Poisson counts generated by a base Poisson process and marks according to the generative process of MMSB. Moreover, the optimal number of communities for BAM-MMSB is estimated by computing the variational approximations of the marginal likelihood for each model order. Experiments on synthetic and real data sets show that the proposed approach promises a generalized model selection solution that can choose not only the model size but also the most appropriate decomposition.
Citation - WoS: 111
Citation - Scopus: 142
A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making
(MDPI, 2023) Abacıoğlu, Seda; Ayan, Büşra; Basilio, Marcio Pereira
In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.
Citation - WoS: 3
Citation - Scopus: 1
A Configurational Analysis of the Impact of Entrepreneurial Orientation and Global Mindset on Export Performance of Smes
(SAGE Publications Inc., 2024) Matemane, R.; Mintah, R.; Şahin, F.; Karadağ, H.
Although contemporary literature provides several important insights into the role of attributes of SMEs, there is much less evidence on what configuration of entrepreneurial orientation and global mindset makes this process successful, that is, contributing to the export performance of SMEs. This study uses a fuzzy set qualitative comparative analysis on a sample of 97 SMEs in Ghana to explore the potential complementary role between the entrepreneurial orientation dimensions and global mindset for superior export performance. The results indicate two different yet equifinal configurations of these factors that lead to a high level of export performance of SMEs. One of the configurations shows that proactive and innovative SMEs with managers high on global mindset achieve superior export performance regardless of their willingness to take risks. Another configuration indicates that regardless of the global mindset of managers, SMEs can achieve higher export performance by being proactive, innovative, and willing to take high risks. Several implications for theory and practice are discussed based on the findings. © The Author(s) 2024.
Citation - WoS: 1
Citation - Scopus: 1
A Decomposition Algorithm for Single and Multiobjective Integrated Market Selection and Production Planning
(Informs, 2023) van den Heuvel, Wilco; Ağralı, Semra; Taşkın, Z. Caner
We study an integrated market selection and production planning problem. There is a set of markets with deterministic demand, and each market has a certain revenue that is obtained if the market's demand is satisfied throughout a planning horizon. The demand is satisfied with a production scheme that has a lot-sizing structure. The problem is to decide on which markets' demand to satisfy and plan the production simultaneously. We consider both single and multiobjective settings. The single objective problem maximizes the profit, whereas the multiobjective problem includes the maximization of the revenue and the minimization of the production cost objectives. We develop a decomposition-based exact solution algorithm for the single objective setting and show how it can be used in a proposed three-phase algorithm for the multiobjective setting. The master problem chooses a subset of markets, and the subproblem calculates an optimal production plan to satisfy the selected markets' demand. We investigate the subproblem from a cooperative game theory perspective to devise cuts and strengthen them based on lifting. We also propose a set of valid inequalities and preprocessing rules to improve the proposed algorithm. We test the efficacy of our solution method over a suite of problem instances and show that our algorithm substantially decreases solution times for all problem instances.
Citation - WoS: 9
Citation - Scopus: 8
A Longitudinal Assessment of Variability in Covid-19 Vaccine Hesitancy and Psychosocial Correlates in a National United States Sample
(Elsevier Sci Ltd, 2023) Shook, Natalie J.; Oosterhoff, Benjamin; Sevi, Barış
Recent evidence suggests that COVID-19 vaccine hesitancy is not static. In order to develop effective vaccine uptake interventions, we need to understand the extent to which vaccine hesitancy fluctuates and identify factors associated with both between- and within-person differences in vaccine hesitancy. The goals of the current study were to assess the extent to which COVID-19 vaccine hesitancy varied at an individual level across time and to determine whether disgust sensitivity and germ aversion were associated with between- and within-person differences in COVID-19 vaccine hesitancy. A national sample of U.S. adults (N = 1025; 516 woman; M-age = 46.34 years, SDage = 16.56, range: 18 to 85 years; 72.6 % White) completed six weekly online surveys (March 20 - May 3, 2020). Between-person mean COVID-19 vaccine hesitancy rates were relatively stable across the six-week period (range: 38-42 %). However, there was considerable within-person variability in COVID-19 vaccine hesitancy. Approximately, 40 % of the sample changed their vaccine hesitancy at least once during the six weeks. There was a significant between-person effect for disgust sensitivity, such that greater disgust sensitivity was associated with a lower likelihood of COVID-19 vaccine hesitance. There was also a significant within-person effect for germ aversion. Participants who experienced greater germ aversion for a given week relative to their own six week average were less likely to be COVID-19 vaccine hesitant that week relative to their own six-week average. This study provides important information on rapidly changing individual variability in COVID-19 vaccine hesitancy on a weekly basis, which should be taken into consideration with any efforts to decrease vaccine hesitancy and increase vaccine uptake. Further, these findings identify-two psychological factors (disgust sensitivity and germ aversion) with malleable components that could be leveraged in developing vaccine uptake interventions.
A Lot-Sizing Problem in Deliberated and Controlled Co-Production Systems
(Taylor and Francis, 2021) Kabakulak, Banu; Ağralı, Semra; Taşkın, Z. Caner; Pamuk, Bahadır
We consider an uncapacitated lot sizing problem in co-production systems, in which it is possible to produce multiple items simultaneously in a single production run. Each product has a deterministic demand to be satisfied on time. The decision is to choose which items to co-produce and the amount of production throughout a predetermined planning horizon. We show that the lot sizing problem with co-production is strongly NP-Hard. Then, we develop various mixed-integer linear programming (MILP) formulation of the problem and show that LP relaxations of all MILPs are equal. We develop a separation algorithm based on a set of valid inequalities, lower bounds based on a dynamic lot-sizing relaxation of our problem and a constructive heuristic that is used to obtain an initial solution for the solver, which form the basis of our proposed Branch & Cut algorithm for the problem. We test our models and algorithms on different data sets and provide the results.
Citation - WoS: 1
Citation - Scopus: 2
A Machine Learning Approach To Resolving Conflicts in Physical Human-Robot Interaction
(Association for Computing Machinery, 2025) Ulas Dincer, Enes; Al-Saadi, Zaid; Hamad, Y.M.; Aydın, Yusuf; Kucukyilmaz, A.; Basdogan, C.
As artificial intelligence techniques become more sophisticated, we anticipate that robots collaborating with humans will develop their own intentions, leading to potential conflicts in interaction. This development calls for advanced conflict resolution strategies in physical human-robot interaction (pHRI), a key focus of our research. We use a machine learning (ML) classifier to detect conflicts during co-manipulation tasks to adapt the robot's behavior accordingly using an admittance controller. In our approach, we focus on two groups of interactions, namely "harmonious"and "conflicting,"corresponding respectively to the cases of the human and the robot working in harmony to transport an object when they aim for the same target, and human and robot are in conflict when human changes the manipulation plan, e.g. due to a change in the direction of movement or parking location of the object.Co-manipulation scenarios were designed to investigate the efficacy of the proposed ML approach, involving 20 participants. Task performance achieved by the ML approach was compared against three alternative approaches: (a) a rule-based (RB) Approach, where interaction behaviors were rule-derived from statistical distributions of haptic features; (b) an unyielding robot that is proactive during harmonious interactions but does not resolve conflicts otherwise, and (c) a passive robot which always follows the human partner. This mode of cooperation is known as "hand guidance"in pHRI literature and is frequently used in industrial settings for so-called "teaching"a trajectory to a collaborative robot.The results show that the proposed ML approach is superior to the others in task performance. However, a detailed questionnaire administered after the experiments, which contains several metrics, covering a spectrum of dimensions to measure the subjective opinion of the participants, reveals that the most preferred mode of interaction with the robot is surprisingly passive. This preference indicates a strong inclination toward an interaction mode that gives more control to humans and offers less demanding interaction, even if it is not the most efficient in task performance. Hence, there is a clear trade-off between task performance and the preferred mode of interaction of humans with a robot, and a well-balanced approach is necessary for designing effective pHRI systems in the future. © 2025 Copyright held by the owner/author(s).
Citation - WoS: 5
Citation - Scopus: 6
A New Approach for Measuring Viscoelastic Properties of Soft Materials Using the Dynamic Response of a Spherical Object Placed at the Sample Interface
(Springer, 2023) Besli, Ayça; Koç,Ömer Hayati; Körük,Hasan; Yurdaer, Berk Salih
Background: There are several techniques to characterize the mechanical properties of soft materials, such as the indentation method and the method based on the application of a spherical object placed inside the sample. The indentation systems usually yield the elastic properties of materials and their mathematical models do not consider the inertia of the sample involved in motion and radiation damping, while placing an object inside the sample is not practical and this procedure can alter the mechanical properties of the sample for the method based on the application of a bubble/sphere placed inside the sample. Objective: A new approach for the identification of the viscoelastic properties of soft materials using the dynamic response of a spherical object placed at the sample interface was proposed. Methods: The spherical object placed at the sample interface was pressed using an electromagnet and the dynamic response of the spherical object was tracked using a high-speed camera, while the dynamic response of the spherical object placed at the sample interface was estimated using a comprehensive analytical model. The effects of the shear modulus, viscosity, Poisson’s ratio and density of the soft sample, the radius and density of the spherical object and the damping due to radiation were considered in this mathematical model. The shear modulus and viscosity of the soft sample were determined by matching the experimentally identified and theoretically estimated responses of the spherical object. Results: The shear moduli and viscosities of the three phantoms with the gelatin mass ratios of 0.20, 0.25 and 0.29 were measured to be 3450, 4300 and 4950 Pa and 12.5, 14.0 and 15.0 Pa⋅s, respectively. The shear modulus and viscosity of the phantom increases as the gelatin mass ratio increases. The frequency of oscillations of the hemisphere placed at the phantom interface increases as the gelatin mass ratio increases due to stiffness increase. Conclusions: After matching the experimental and theoretical steady-state displacements and amplitudes of oscillations of the hemisphere at the sample interface, the comparison of the experimentally identified and theoretically predicted frequency of oscillations further confirmed the identified material properties of the samples. The approach presented here is expected to provide valuable information on material properties in biomedical and industrial applications.
A New Benchmark Dataset for P300 Erp-Based Bci Applications
(Academic Press Inc Elsevier Science, 2023) Çakar, Tuna; Özkan, Hüseyin; Musellim, Serkan; Arslan, Suayb S.; Yağan, Mehmet; Çakar, Tuna; Alp, Nihan
Because of its non-invasive nature, one of the most commonly used event-related potentials in brain -computer interface (BCI) system designs is the P300 electroencephalogram (EEG) signal. The fact that the P300 response can easily be stimulated and measured is particularly important for participants with severe motor disabilities. In order to train and test P300-based BCI speller systems in more realistic high-speed settings, there is a pressing need for a large and challenging benchmark dataset. Various datasets already exist in the literature but most of them are not publicly available, and they either have a limited number of participants or utilize relatively long stimulus duration (SD) and inter-stimulus intervals (ISI). They are also typically based on a 36 target (6 x 6) character matrix. The use of long ISI, in particular, not only reduces the speed and the information transfer rates (ITRs) but also oversimplifies the P300 detection. This leaves a limited challenge to state-of-the-art machine learning and signal processing algorithms. In fact, near-perfect P300 classification accuracies are reported with the existing datasets. Therefore, one certainly needs a large-scale dataset with challenging settings to fully exploit the recent advancements in algorithm design (machine learning and signal processing) and achieve high-performance speller results. To this end, in this article we introduce a new freely-and publicly-accessible P300 dataset obtained using 32-channel EEG, in the hope that it will lead to new research findings and eventually more efficient BCI designs. The introduced dataset comprises 18 participants performing a 40 -target (5 x 8) cued-spelling task, with reduced SD (66.6 ms) and ISI (33.3 ms) for fast spelling. We have also processed, analyzed, and character-classified the introduced dataset and we presented the accuracy and ITR results as a benchmark. The introduced dataset and the codes of our experiments are publicly accessible at https://data .mendeley.com /datasets /vyczny2r4w.(c) 2023 Elsevier Inc. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 2
A New Learning Community for Educating Future Teachers: Online Baboratory School
(Taylor and Francis Ltd., 2022) Pekkan, Tunç Zelha; Taylan, Didem Rukiye
To provide quality mathematics education for disadvantaged groups of middle school students and continue to offer quality practicum experience to future teachers during the Covid 19 outbreak, we founded the Online Laboratory School. This school was free and open to public school students: 130 middle school students throughout Turkey attended for a 5-week period. There were 25 pre-service teachers actively involved in teaching, under the close supervision of 7 university supervisors. The entire gamut of planning, teaching and reflection sessions for each virtual class were recorded via an e-learning platform. Additionally, survey data was collected from the participating students, parents, pre-service teachers and supervisors. Our findings indicate that we were able to build a unique and virtual learning community. While pre-service teachers and middle school students benefited the most, university supervisors also reported improving their skills on when and how to give feedback. We describe how the school functioned and the range of opportunities it provided to all participants considering situated-learning perspectives and building online-learning communities. We also discuss how this model can be used in the future as a strong asset for teacher education programs and adaptation of fieldwork practices.
Citation - WoS: 3
Citation - Scopus: 4
A Novel Graph Transformation Strategy for Optimizing Sptrsv on Cpus
(Wiley, 2023) Yılmaz, Buse
Sparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present a novel graph transformation strategy to increase the parallelism degree of a sparse matrix and compare it to our previous strategy. It is seen that our transformation strategy can provide a speedup as high as 1.42x$$ 1.42x $$.
A Novel Plasma-Facing Ndb6 Particulate Reinforced W1ni Matrix Composite: Powder Metallurgical Fabrication, Microstructural and Mechanical Characterization
(Elsevier Sci Ltd, 2024) Boztemur, Burçak; Öveçoğlu, Mustafa Lutfi; Luo, Laima; Ağaoğulları, Duygu; Xu, Yue; Alkraidi, Ammar
Tungsten (W) is one of best candidate metal for plasma-facing materials (PFM), especially due to its high melting temperature and neutron absorption capability. However, converting W into bulk PFM is hard because of its high melting point. This problem can be solved by adding metallic sintering aids with low melting points. In this study, W matrix with 1 wt% Ni aid was reinforced by adding NdB6 particles (1, 5, and 10 wt%). It can be introduced as a novel potential PFM, thanks to its low volatility and high neutron absorbability. The ceramic and composite powders produced via mechanochemical synthesis and mechanical alloying were examined in terms of composition, particle size, crystallite size, and lattice strain. Samples sintered via pressureless sintering (PS) and spark plasma sintering (SPS) were microstructurally analyzed by using an X-ray diffractometer (XRD), a scanning electron microscope (SEM) attached with an energy dispersive spectroscope (EDS), and mechanically analyzed in terms of microhardness and wear behavior. Based on the results, W2B and WB phases emerged in the SPS'ed W1Ni-5NdB6 and PS'ed./SPS'ed W1Ni-10NdB6 composites. SPS'ed W1Ni-10NdB6 composite had the highest hardness value and the lowest specific wear rate. The SPS'ed W1Ni-5NdB6 composite showed fewer surface damages and higher irradiation resistance as compared with other samples after exposure of He+ irradiation.
A Strategy to Engage Students in Inquiry-Based Learning of Mathematics: Predict, Observe and Explain
(Springer, 2025) Karakoc, Gokhan; Alacaci, Cengiz; Ayas, Alipasa
The current research implemented the Predict Observe and Explain (POE) instructional approach in mathematics and examined its efficacy in enhancing students' understanding of functions in terms of their ability to connect algebraic and graphical representations in optimization problems. Two grade 11 classes (40 students in total) and two grade 10 classes (42 students in total) participated in this study, for a combined total of 82 students. Following a quasi-experimental design, students in the experimental group solved six open mathematical tasks in a small group setting. They were explicitly asked to predict the outcome before attempting to solve the tasks, make observations using concrete materials and finally attempt a solution. They were then expected to reflect on their observation and initial predictions to interpret their findings. The control group students were given the same tasks without an explicit heuristic. They directly attempted to solve the same problems without prediction and observation. The data were collected using students' written responses to each task. Students' responses to the tasks were assessed based on the following criteria: understanding, constructing, using a mathematical model, communicating and interpreting results. An independent samples t-test showed that the POE strategy improved students' learning in cognitive domains. The POE strategy helped students better understand the problem, select and apply appropriate mathematical methods and interpret their findings. Students in the control group spent more time discussing and integrating clues into possible solutions to the given tasks. The results were interpreted within the framework of inquiry-based education, informed by semiotic representation theory.
Citation - WoS: 8
Citation - Scopus: 9
A Value-Adding Approach To Reliability Under Preventive Maintenance Costs and Its Applications
(2014) Dubey, Rameshwar; Kılıç, Erdem; Ali, Sadia Samar; Weber, Gerhard Wilhelm
No equipment (system) can be perfectly reliable in spite of the utmost care and best efforts on the part of the designer, decision-maker and manufacturer. The two sides of maintenance are corrective and preventive maintenance. It is generally assumed that a preventive maintenance action is less costly than a repair maintenance action. We examine this proposition in detail on the basis of a failure-time model that relates conformance quality to reliability. Illustratively, we present reliability in the context of contracts with asymmetric information. The model shows how to overcome information rents through price distortions and quantity rationing. The paper ends with a conclusion and an outlook to future studies.
Citation - WoS: 1
Citation - Scopus: 1
Acoustic Cavitation Model Based on a Novel Reduced Order Gas Pressure Law
(2021) Pasinlioğlu, Şenay; Delale, Can Fuad
The thermal behavior of a spherical gas bubble in a liquid excited by an acoustic pressure signal is investigated by constructing an iterative solution of the energy balance equations between the gas bubble and the surrounding liquid in the uniform pressure approximation. This iterative solution leads to hierarchy equations for the radial partial derivatives of the temperature at the bubble wall, which control the temporal rate of change of the gas pressure and gas temperature within the bubble. In particular, a closure relation for the hierarchy equations is introduced based on the ansatz that approximates the rapid change of state during the collapse of the bubble from almost isothermal to almost adiabatic behavior by time averaging the complex dynamics of change of state over a relatively short characteristic time. This, in turn, leads to the desired reduced order gas pressure law exhibiting power law dependence on the bubble wall temperature and on the bubble radius, with the polytropic index depending on the isentropic exponent of the gas and on a parameter that is a function of the Péclet number and a characteristic time scale. Results of the linear theory for gas bubbles are recovered by identifying this parameter as a function of the Péclet number based on the Minnaert frequency. The novel gas pressure law is then validated against the near-isothermal solution and against the results of the numerical simulations of the original energy balance equations for large amplitude oscillations using spectral methods. Consequently, an acoustic cavitation model that accounts for phase change but that neglects mass diffusion is constructed by employing the reduced order gas pressure law together with the Plesset–Zwick solution for the bubble wall temperature and the Keller–Miksis equation for spherical bubble dynamics. Results obtained using variable interface properties for acoustically driven cavitation bubbles in water show that the time variations of the bubble radius and the bubble wall temperature lie between those obtained by the isothermal and adiabatic laws depending on the value of the Péclet number and the characteristic time scale.
Citation - WoS: 12
Citation - Scopus: 15
Acoustic Streaming in a Soft Tissue Microenvironment
(Elsevier, 2019) El Ghamrawy, Ahmed; Mohammed, Ali; Jones, Julian R; Körük, Hasan; Choi, James J; de Comtes, Florentina
We demonstrated that sound can push fluid through a tissue-mimicking material. Although acousticstreaming in tissue has been proposed as a mechanism for biomedical ultrasound applications, such as neuromodu-lation and enhanced drug penetration, streaming in tissue or acoustic phantoms has not been directly observed. Wedeveloped a material that mimics the porous structure of tissue and used a dye and a video camera to track fluidmovement. When applied above an acoustic intensity threshold, a continuous focused ultrasound beam (spatialpeak time average intensity: 238 W/cm2, centre frequency: 5 MHz) was found to push the dye axially, that is, in thedirection of wave propagation and in the radial direction. Dye clearance increased with ultrasound intensity andwas modelled using an adapted version of Eckart’s acoustic streaming velocity equation. No microstructuralchanges were observed in the sonicated region when assessed using scanning electron microscopy. Our study indi-cates that acoustic streaming can occur in soft porous materials and provides a mechanistic basis for future use ofstreaming for therapeutic or diagnostic purposes.
Citation - WoS: 37
Citation - Scopus: 44
Adaptive Human Force Scaling Via Admittance Control for Physical Human-Robot Interaction
(IEEE, 2021) Başdoğan, Çağatay; Aydın, Yusuf; Hamad, Yahya M.
The goal of this article is to design an admittance controller for a robot to adaptively change its contribution to a collaborative manipulation task executed with a human partner to improve the task performance. This has been achieved by adaptive scaling of human force based on her/his movement intention while paying attention to the requirements of different task phases. In our approach, movement intentions of human are estimated from measured human force and velocity of manipulated object, and converted to a quantitative value using a fuzzy logic scheme. This value is then utilized as a variable gain in an admittance controller to adaptively adjust the contribution of robot to the task without changing the admittance time constant. We demonstrate the benefits of the proposed approach by a pHRI experiment utilizing Fitts’ reaching movement task. The results of the experiment show that there is a) an optimum admittance time constant maximizing the human force amplification and b) a desirable admittance gain profile which leads to a more effective co-manipulation in terms of overall task performance.
Citation - WoS: 2
Citation - Scopus: 3
Adaptive Reuse of High-Rise Buildings for Housing: a Study of Istanbul Central Business District
(Cogitatio Press, 2024) Aydemir, Ayşe Zeynep; Akın, Tomris
The abrupt shift to remote work due to the Covid-19 pandemic increased vacant office spaces globally, especially in high -rent central business districts (CBDs). These vacant office spaces offer the potential for conversion into housing, addressing the shortage of affordable housing in central areas. Additionally, this topic presents a unique experimental ground for architecture students. This study focuses on the Istanbul CBD as a case study, examining the historical developments that led to a rise in office vacancy rates and housing inequality, and exploring the potential for adaptive reuse of these vacant office buildings. A key focus of this study is to underline the pedagogical value of adaptive reuse, highlighting how such projects can inspire more diverse and equitable housing models, fostering experimental and sustainable design approaches. It systematically evaluates the outcomes of a 4th -year architectural design studio that focuses on the adaptive reuse of the Tat Towers in the Istanbul CBD, a structurally vacant high-rise office building, and asks: How does the context of adaptive reuse enable a different design approach, and, potentially, new spatial norms and standards to emerge, and how might this hold a pedagogical value for architecture education? Following these questions, the article discusses how norms and standards are not only culturally but also typologically contextual, and how the students have explored how norms and standards might change, outlining new design approaches to adaptive reuse.
Citation - WoS: 18
Citation - Scopus: 18
Adding Rapid-Acting Insulin or Glp-1 Receptor Agonist To Basal Insulin: Outcomes in a Community Setting
(2015) Dalal, Mehul R; DiGenio, Andres; Xie, Lin; Başer, Onur
To evaluate real-world outcomes in patients with type 2 diabetes mellitus (T2DM)receiving basal insulin, who initiate add-on therapy with a rapid-acting insulin (RAI) or aglucagon-like peptide 1 (GLP-1) receptor agonist.Data were extracted retrospectively from a U.S. health claims database. Adults withT2DM on basal insulin who added an RAI (basal+RAI) or GLP-1 receptor agonist (basal+GLP-1) were included. Propensity score matching (1 up to 3 ratio) was used to control for differencesin baseline demographics, clinical characteristics, and health resource utilization. Endpointsincluded prevalence of hypoglycemia, pancreatic events, all-cause and diabetes-relatedresource utilization, and costs at 1 year follow-up. Overall, 6,718 matched patients were included: 5,013 basal+RAI and 1,705basal+GLP1. Patients in both groups experienced a similar proportion of any hypoglycemicevent (P = .4079). Hypoglycemic events leading to hospitalization were higher in the basal+RAIcohort (2.7% vs. 1.8%; P = .0444). The basal+GLP-1 cohort experienced fewer all-cause(13.55% vs. 18.61%; P<.0001) and diabetes-related hospitalizations (11.79% vs. 15.68%;P<.0001). The basal+GLP-1 cohort had lower total all-cause health care costs ($18,413 vs.$20,821; P = .0002), but similar diabetes-related costs ($9,134 vs. $8,985; P<.0001) comparedwith the basal+RAI cohort. Add-on therapy with a GLP-1 receptor agonist in T2DM patients receiving basalinsulin was associated with fewer hospitalizations and lower total all-cause costs compared withadd-on therapy using a RAI, and could be considered an alternative to a RAI in certain patientswith T2DM, who do not achieve effective glycemic control with basal insulin.

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