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Uncertainty of data, the degree to which data are inaccurate, imprecise, untrusted, and undetermined, is inherent in many contemporary database applications, and numerous research endeavours have been devoted to efficiently answer skyline queries over uncertain data. The literature discussed two different methods that could be used to handle the data uncertainty in which objects having continuous range values. The first method employs a probability-based approach, while the second assumes that the uncertain values are represented by their median values. Nevertheless, neither of these methods seem to be suitable for the modern high-dimensional uncertain databases due to the following reasons. The first method requires an intensive probability calculations while the second is impractical. Therefore, this work introduces an index, non-probability framework named Constrained Skyline Query processing on Uncertain Data (CSQUiD) aiming at reducing the computational time in processing constrained skyline queries over uncertain high-dimensional data. Given a collection of objects with uncertain data, the CSQUiD framework constructs the minimum bounding rectangles (MBRs) by employing the X-tree indexing structure. Instead of scanning the whole collection of objects, only objects within the dominant MBRs are analyzed in determining the final skylines. In addition, CSQUiD makes use of the Fuzzification approach where the exact value of each continuous range value of those dominant MBRs' objects is identified. The proposed CSQUiD framework is validated using real and synthetic data sets through extensive experimentations. Based on the performance analysis conducted, by varying the sizes of the constrained query, the CSQUiD framework outperformed the most recent methods (CIS algorithm and SkyQUD-T framework) with an average improvement of 44.07% and 57.15% with regards to the number of pairwise comparisons, while the average improvement of CPU processing time over CIS and SkyQUD-T stood at 27.17% and 18.62%, respectively. [ABSTRACT FROM AUTHOR]

Abstract Background The zero-profile implant system (Zero-P) and conventional plates have been widely used in anterior cervical discectomy and fusion (ACDF) to treat cervical spondylosis. The purpose of this study was to compare the effects of the application of Zero-P and new conventional plates (ZEVO, Skyline) in ACDF on the sagittal imaging parameters of cervical spondylosis patients and to analyze their clinical efficacy. Methods We conducted a retrospective study on 119 cervical spondylosis patients from January 2018 to December 2021, comparing outcomes between those receiving the Zero-P device (n = 63) and those receiving a novel conventional plate (n = 56, including 46 ZEVO and 10 Skyline plates) through ACDF. Cervical sagittal alignment was assessed pre- and postoperatively via lateral radiographs. The Japanese Orthopedic Association (JOA), Neck Disability Index (NDI), and visual analog scale (VAS) scores were recorded at baseline, after surgery, and at the 2-year follow-up to evaluate patient recovery and intervention success. Results There were significant differences in the postoperative C0-C2 Cobb angle and postoperative sagittal segmental angle (SSA) between patients in the novel conventional plate group and those in the Zero-P group (P

Copyright of Online Journal of Art & Design is the property of Online Journal of Art & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The zero-profile implant system (Zero-P) and conventional plates have been widely used in anterior cervical discectomy and fusion (ACDF) to treat cervical spondylosis. The purpose of this study was to compare the effects of the application of Zero-P and new conventional plates (ZEVO, Skyline) in ACDF on the sagittal imaging parameters of cervical spondylosis patients and to analyze their clinical efficacy. Methods: We conducted a retrospective study on 119 cervical spondylosis patients from January 2018 to December 2021, comparing outcomes between those receiving the Zero-P device (n = 63) and those receiving a novel conventional plate (n = 56, including 46 ZEVO and 10 Skyline plates) through ACDF. Cervical sagittal alignment was assessed pre- and postoperatively via lateral radiographs. The Japanese Orthopedic Association (JOA), Neck Disability Index (NDI), and visual analog scale (VAS) scores were recorded at baseline, after surgery, and at the 2-year follow-up to evaluate patient recovery and intervention success. Results: There were significant differences in the postoperative C0-C2 Cobb angle and postoperative sagittal segmental angle (SSA) between patients in the novel conventional plate group and those in the Zero-P group (P < 0.05). Postoperatively, there were significant changes in the C2‒C7 Cobb angle, C0‒C2 Cobb angle, SSA, and average surgical disc height (ASDH) compared to the preoperative values in both patient groups (P < 0.05). Dysphagia in the immediate postoperative period was lower in the Zero-P group than in the new conventional plate group (0% in the Zero-P group, 7.14% in the novel conventional plate group, P = 0.046), and the symptoms disappeared within 2 years in both groups. There was no statistically significant difference between the two groups in terms of complications of adjacent spondylolisthesis (ASD) at 2 years postoperatively (3.17% in the Zero-P group, 8.93% in the novel conventional plate group; P = 0.252). According to the subgroup analysis, there were significant differences in the postoperative C2‒C7 Cobb angle, C0‒C2 Cobb angle, T1 slope, and ASDH between the ZEVO group and the Skyline group (P < 0.05). Compared with the preoperative scores, the JOA, NDI, and VAS scores of all groups significantly improved at the 2-year follow-up (P < 0.01). According to the subgroup analysis, the immediate postoperative NDI and VAS scores of the ZEVO group were significantly better than those of the Skyline group (P < 0.05). Conclusion: In ACDF, both novel conventional plates and Zero-P can improve sagittal parameters and related scale scores. Compared to the Zero-P plate, the novel conventional plate has a greater advantage in correcting the curvature of the surgical segment, but the Zero-P plate is less likely to produce postoperative dysphagia. [ABSTRACT FROM AUTHOR]

Uncertainty of data, the degree to which data are inaccurate, imprecise, untrusted, and undetermined, is inherent in many contemporary database applications, and numerous research endeavours have been devoted to efficiently answer skyline queries over uncertain data. The literature discussed two different methods that could be used to handle the data uncertainty in which objects having continuous range values. The first method employs a probability-based approach, while the second assumes that the uncertain values are represented by their median values. Nevertheless, neither of these methods seem to be suitable for the modern high-dimensional uncertain databases due to the following reasons. The first method requires an intensive probability calculations while the second is impractical. Therefore, this work introduces an index, non-probability framework named Constrained Skyline Query processing on Uncertain Data (CSQUiD) aiming at reducing the computational time in processing constrained skyline queries over uncertain high-dimensional data. Given a collection of objects with uncertain data, the CSQUiD framework constructs the minimum bounding rectangles (MBRs) by employing the X-tree indexing structure. Instead of scanning the whole collection of objects, only objects within the dominant MBRs are analyzed in determining the final skylines. In addition, CSQUiD makes use of the Fuzzification approach where the exact value of each continuous range value of those dominant MBRs’ objects is identified. The proposed CSQUiD framework is validated using real and synthetic data sets through extensive experimentations. Based on the performance analysis conducted, by varying the sizes of the constrained query, the CSQUiD framework outperformed the most recent methods (CIS algorithm and SkyQUD-T framework) with an average improvement of 44.07% and 57.15% with regards to the number of pairwise comparisons, while the average improvement of CPU processing time over CIS and SkyQUD-T stood at 27.17% and 18.62%, respectively.

Selecting the QoS-optimized software-as-a-service (SaaS) from a large number of services with the same functionality and different Quality of Service (QoS) is still a hot issue. Massive QoS feedback forms big QoS data, which exhibits ambiguity and randomness increasing the uncertainty of service selection. Starting from the characterization of big QoS data, the Uncertain Big QoS data-driven Efficient SaaS Decision Making Method (UBQoS_ESDM) is proposed. The method firstly utilizes cloud model to portray QoS in order to solve the problem of inaccurate description of uncertain big QoS data; then draws on the idea of Skyline query to establish uncertain service Skyline set, which reduces the search space and improves the efficiency of QoS-optimal SaaS selection; and draws on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to design two decision-making algorithms to evaluate alternative SaaSs, and to obtain the QoS-optimal SaaS that reflects user requirements. In addition, two types of backward QoS cloud generators are introduced to convert big QoS data to QoS cloud models, and the QoS cloud model adaptive adjustment mechanism is introduced too, which can adapt to the dynamic changes of QoS. Finally, theoretical proofs and experiments verify the superiority and efficiency of the method.

Protein glycosylation is an essential post-translational modification in all domains of life. Its impairment in humans can result in severe diseases named congenital disorders of glycosylation (CDGs). Most of the glycosyltransferases (GTs) responsible for proper glycosylation are polytopic membrane proteins that represent challenging targets in proteomics. We established a multiple reaction monitoring (MRM) assay to comprehensively quantify GTs involved in the processes of N-glycosylation and O- and C-mannosylation in the endoplasmic reticulum. High robustness was achieved by using an enriched membrane protein fraction of isotopically labeled HEK 293T cells as an internal protein standard. The analysis of primary skin fibroblasts from eight CDG type I patients with impaired ALG1, ALG2, and ALG11 genes, respectively, revealed a substantial reduction in the corresponding protein levels. The abundance of the other GTs, however, remained unchanged at the transcript and protein levels, indicating that there is no fail-safe mechanism for the early steps of glycosylation in the endoplasmic reticulum. The established MRM assay was shared with the scientific community via the commonly used open source Skyline software environment, including Skyline Batch for automated data analysis. We demonstrate that another research group could easily reproduce all analysis steps, even while using different LC-MS hardware. [ABSTRACT FROM AUTHOR]

Copyright of METU Journal of the Faculty of Architecture / Mimarlık Fakültesi Dergisi is the property of METU Journal of the Faculty of Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate relative quantification is critical in proteomic studies. The incorporation of stable isotope 15N to plant-expressed proteins in vivo is a powerful tool for accurate quantification with a major advantage of reducing preparative and analytical variabilities. However, 15N labeling quantification has several challenges. Less identifications are often observed in the heavy-labeled samples because of incomplete labeling, resulting in missing values in reciprocal labeling experiments. Inaccurate quantification can happen when there is contamination from co-eluting peptides or chemical noise in the MS1 survey scan. These drawbacks in quantification can be more pronounced in less abundant but biologically interesting proteins, which often have very few identified peptides. Here, we demonstrate the application of parallel reaction monitoring (PRM) to 15N labeled samples on a high resolution, high mass accuracy Orbitrap mass spectrometer to achieve reliable quantification even of low abundance proteins in samples.

Introduction. The widespread use of piezoelectric materials in various industries stimulates the study of their physical characteristics and determines the urgency of such research. In this case, modal analysis makes it possible to determine the operating frequency and the coefficient of electromechanical coupling of piezoelectric elements of various devices. These indicators are of serious theoretical and applied interest. The study was aimed at the development of numerical methods for solving the problem of determining resonance frequencies in a system of elastic bodies. To achieve this goal, we needed new approaches to the discretization of the problem based on the finite element method and the execution of the software implementation of the selected method in C# on the .net platform. Current solutions were created in the context of the ACELAN-COMPOS class library. The known methods of solving the generalized eigenvalue problem based on matrix inversion are not applicable to large-dimensional matrices. To overcome this limitation, the presented scientific work implemented the logic of constructing mass matrices and created software interfaces for exchanging data on eigenvalue problems with pre- and postprocessing modules.Materials and Methods. A platform was used to implement numerical methods .net and the C# programming language. Validation of the research results was carried out through comparing the values found with solutions obtained in well-known SAE packages (computer-aided engineering). The created routines were evaluated in terms of performance and applicability for large-scale tasks. Numerical experiments were carried out to validate new algorithms in small-dimensional problems that were solved by known methods in MATLAB. Next, the approach was tested on tasks with a large number of unknowns and taking into account the parallelization of individual operations. To avoid finding the inverse matrix, a modified Lanczos method was programmatically implemented. We examined the formats for storing matrices in RAM: triplets, CSR, СSC, Skyline. To solve a system of linear algebraic equations (SLAE), an iterative symmetric LQ method adapted to these storage formats was used.Results. New calculation modules integrated into the class library of the ACELAN-COMPOS complex were developed. Calculations were carried out to determine the applicability of various formats for storing sparse matrices in RAM and various methods for implementing operations with sparse matrices. The structure of stiffness matrices constructed for the same task, but with different renumbering of nodes of a finite element grid, was graphically visualized. In relation to the problem of the theory of electroelasticity, data on the time required to perform basic operations with stiffness matrices in various storage formats were summarized and presented in the form of a table. It has been established that the renumbering of grid nodes gives a significant increase in performance even without changing the internal structure of the matrix in memory. Taking into account the objectives of the study, the advantages and weaknesses of known matrix storage formats were named. Thus, CSR was optimal when multiplying a matrix by a vector, SKS was optimal when inverting a matrix. In problems with the number of unknowns of the order of 103, iterative methods for solving a generalized eigenvalue problem won in speed. The performance of the software implementation of the Lanczos method was evaluated. The contribution of all operations to the total solution time was measured. It has been found that the operation of solving SLAE takes up to 95% of the total time of the algorithm. When solving the SLAE by symmetric LQ method, the greatest computational costs were needed to multiply the matrix by a vector. To increase the performance of the algorithm, parallelization with shared memory was resorted to. When using eight threads, the performance gain increased by 40–50%.Discussion and Conclusion. The software modules obtained as part of the scientific work were implemented in the ACELAN-COMPOS package. Their performance for model problems with quasi-regular finite element grids was estimated. Taking into account the features of the structures of the stiffness and mass matrices obtained through solving the generalized eigenvalue problem for an electroelastic body, the preferred methods for their processing were determined.

Several total-evidence dating studies under the fossilized birth–death (FBD) model have produced very old age estimates, which are not supported by the fossil record. This phenomenon has been termed "deep root attraction (DRA)." For two specific data sets, involving divergence time estimation for the early radiations of ants, bees, and wasps (Hymenoptera) and of placental mammals (Eutheria), it has been shown that the DRA effect can be greatly reduced by accommodating the fact that extant species in these trees have been sampled to maximize diversity, so-called diversified sampling. Unfortunately, current methods to accommodate diversified sampling only consider the extreme case where it is possible to identify a cut-off time such that all splits occurring before this time are represented in the sampled tree but none of the younger splits. In reality, the sampling bias is rarely this extreme and may be difficult to model properly. Similar modeling challenges apply to the sampling of the fossil record. This raises the question of whether it is possible to find dating methods that are more robust to sampling biases. Here, we show that the skyline FBD (SFBD) process, where the diversification and fossil-sampling rates can vary over time in a piecewise fashion, provides age estimates that are more robust to inadequacies in the modeling of the sampling process and less sensitive to DRA effects. In the SFBD model we consider, rates in different time intervals are either considered to be independent and identically distributed or assumed to be autocorrelated following an Ornstein–Uhlenbeck (OU) process. Through simulations and reanalyses of Hymenoptera and Eutheria data, we show that both variants of the SFBD model unify age estimates under random and diversified sampling assumptions. The SFBD model can resolve DRA by absorbing the deviations from the sampling assumptions into the inferred dynamics of the diversification process over time. Although this means that the inferred diversification dynamics must be interpreted with caution, taking sampling biases into account, we conclude that the SFBD model represents the most robust approach currently available for addressing DRA in total-evidence dating. [ABSTRACT FROM AUTHOR]

The integration of Internet of Things (IoT) technologies, particularly the Internet of Medical Things (IoMT), with wireless sensor networks (WSNs) has revolutionized the healthcare industry. However, despite the undeniable benefits of WSNs, their limited communication capabilities and network congestion have emerged as critical challenges in the context of healthcare applications. This research addresses these challenges through a dynamic and on-demand route-finding protocol called P2P-IoMT, based on LOADng for point-to-point routing in IoMT. To reduce congestion, dynamic composite routing metrics allow nodes to select the optimal parent based on the application requirements during the routing discovery phase. Nodes running the proposed routing protocol use the multi-criteria decision-making Skyline technique for parent selection. Experimental evaluation results show that P2P-IoMT protocol outperforms its best rivals in the literature in terms of residual network energy and packet delivery ratio. The network lifetime is extended by 4% while achieving a comparable packet delivery ratio and communication delay compared to LRRE. These performances are offered on top of the dynamic path selection and configurable route metrics capabilities of P2P-IoMT. [ABSTRACT FROM AUTHOR]

In recent years, people have been buying custom-built PCs based on the performance they want and what they will use them for. However, there are many challenges for non-technical users when purchasing a custom-built PC. Not only is the terminology of computer devices unfamiliar to non-experts, but there are many specifications for different computer devices that need to be considered. Therefore, this paper proposes a method for recommending appropriate device models when purchasing custom-built PCs using a skyline. Because different computer devices have different specifications, we need a method that takes into account multiple attributes. Skyline querying is a technique that considers multiple attributes of an object and indexes them in order of user satisfaction. A grid skyline is a technique that uses a grid-based partitioning technique to reduce the number of calculations of the dominance relationship between objects in the existing skyline technique, thus reducing the index construction time. We measured the similarity between the results of the grid skyline and the leaderboard for each model of computer device. As a result of this experiment, compared to the leaderboard categorized by model of computer device, the average score was 88 out of 100, which was similar to the actual leaderboard. [ABSTRACT FROM AUTHOR]

The integration of Internet of Things (IoT) technologies, particularly the Internet of Medical Things (IoMT), with wireless sensor networks (WSNs) has revolutionized the healthcare industry. However, despite the undeniable benefits of WSNs, their limited communication capabilities and network congestion have emerged as critical challenges in the context of healthcare applications. This research addresses these challenges through a dynamic and on-demand route-finding protocol called P2P-IoMT, based on LOADng for point-to-point routing in IoMT. To reduce congestion, dynamic composite routing metrics allow nodes to select the optimal parent based on the application requirements during the routing discovery phase. Nodes running the proposed routing protocol use the multi-criteria decision-making Skyline technique for parent selection. Experimental evaluation results show that P2P-IoMT protocol outperforms its best rivals in the literature in terms of residual network energy and packet delivery ratio. The network lifetime is extended by 4% while achieving a comparable packet delivery ratio and communication delay compared to LRRE. These performances are offered on top of the dynamic path selection and configurable route metrics capabilities of P2P-IoMT.

Along with the widespread adoption of solar energy, it is fundamental to develop methods and tools that help practitioners during the design phase of photovoltaic (PV) systems. Currently, multiple commercial software can quantify a particular location’s annual energy yield while including the horizon’s shading effect (e.g., mountains, buildings, and trees). To do so, precise information about the PV system’s surroundings is necessary. This information is gathered by specialized equipment or by having access to satellite imagery. Therefore, to offer a more practical approach, we propose a method that requires only a cellphone camera, a fixed point for taking a panoramic photograph, and a compass. Once the panoramic image is taken, the obstacles’ width, height, and altitude are calculated, and the skyline is built. With this information, the method correlates the position of the sun with meteorological data to include the effect of shading on direct irradiation. The method was tested using one–year meteorological data to determine the best orientation of a PV system. The image processing method and the general method were validated by getting PV power generation data and aerial images and comparing them to the method’s predictions. Therefore, we introduce a method that, with low computational complexity, facilitates the study of shading on the performance of PV systems.

Cloud computing has experienced rapid growth in recent years and has become a critical computing paradigm. Combining multiple cloud services to satisfy complex user requirements has become a research hotspot in cloud computing. Service composition in multi-cloud environments is characterized by high energy consumption, which brings attention to the importance of energy consumption in cross-cloud service composition. Nonetheless, prior research has mainly focused on finding a service composition that maximizes the quality of service (QoS) and overlooks the energy consumption generated during service invocation. Additionally, the dynamic nature of multi-cloud environments challenges the adaptability and scalability of cloud service composition methods. Therefore, we propose the skyline-enhanced deep reinforcement learning approach (SkyDRL) to address these challenges. Our approach defines an energy consumption model for cloud service composition in multi-cloud environments. The branch and bound skyline algorithm is leveraged to reduce the search space and training time. Additionally, we enhance the basic deep Q-network (DQN) algorithm by incorporating double DQN to address the overestimation problem, incorporating Dueling Network and Prioritized Experience Replay to speed up training and improve stability. We evaluate our proposed method using comparative experiments with existing methods. Our results demonstrate that our approach effectively reduces energy consumption in cloud service composition while maintaining good adaptability and scalability in service composition problems. According to the experimental results, our approach outperforms the existing approaches by demonstrating energy savings ranging from 8% to 35%. [ABSTRACT FROM AUTHOR]

We consider the problem of computing the distance-based representative skyline in the plane, a problem introduced by Tao, Ding, Lin and Pei [Proc. 25th IEEE International Conference on Data Engineering (ICDE), 2009] and independently considered by Dupin, Nielsen and Talbi [Mathematics; Optimization and Learning - Third International Conference, OLA 2020] in the context of multi-objective optimization. Given a set P of n points in the plane and a parameter k, the task is to select k points of the skyline defined by P (also known as Pareto front for P) to minimize the maximum distance from the points of the skyline to the selected points. We show that the problem can be solved in O (n log h) time, where h is the number of points in the skyline of P. We also show that the decision problem can be solved in O (n log k) time and the optimization problem can be solved in O (n log k + n loglog n) time. This improves previous algorithms and is optimal for a large range of values of k. [ABSTRACT FROM AUTHOR]

In view of the problems of underground pipe network, such as tight spatial distribution, low security and insufficient disaster prevention capacity, GIS technology and Skyline platform are used to build a 3D city reality model which is ground and underground integration, visually reproduce the buried situation of the underground pipe network and its spatial location relationship with surface features, deeply carry out emergency application research that focus on what base on connectivity, pipe burst, valve closing and safety distance analysis. The research results show that the 3D city model was able to quickly determine the burst position and the scope of the accident. The research conclusions can provide reference for decision-making of pipeline accident emergency treatment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of the Japan Forest Engineering Society is the property of Japan Forest Engineering Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Metabolomics has been used as a powerful tool for the analysis, and drug-lead identification in medicinal plants and herbal medicines. For the coverage of a broader range of plant-based metabolites using LC-MS, one of the important parameters is the selection of analysis mode and data processing for identification. This paper describes the utility of two distinctive acquisition modes in combination, a classic data-dependent acquisition (DDA) mode and a data-independent acquisition (DIA) mode for obtaining the mass spectrometry data of plant extracts using LC-ESI-QTOF/MS. Tribulus terrestris plant was used as a case study. We have applied three-step data analysis pipeline 1-annotation and putative identification of metabolites, 2-validation, and relative quantification, and 3-multivariate analysis using open-access MS-DIAL, Skyline, and Perseus software. A total of four samples of T. terrestris (aqueous extracts), two fruits, and two whole plant samples, from two different regions, were used. By combining data analysis results of plant fruit samples from two different regions, a total of 95 and 77 metabolites were identified in positive and negative ionization modes, respectively. Similarly, in the analysis of the whole plant from two different regions, 75 and 76 metabolites were identified in positive and negative ionization modes, respectively. We suggested the use of DDA mode for annotation, identification of metabolites, and generation of transition lists in MS-DIAL, furthermore, the use of DIA acquisition mode for enhancing metabolites sensitivity in complex samples, deconvolute MS1/MS2 spectra in Skyline for the quantitative performance and analytical reliability. The developed protocol can be used for the broader coverage of plant-based metabolites.

This is a postcard performance project about the Twin Towers, language, and memory.

IntroductionVarious physical, semantic and functional factors in the role of the city as a bed to meet the needs and a container for the activities and behaviors of residents are effective, among which the structure and visual values ​​of the environment play an important role in improving the quality of urban space (Hosseini and Et al., 1390: 84). Among these, one of the urban elements that can play an important role in promoting the quality and visual values ​​of the environment and the appearance of the city is the sky line. The skyline is one of the most influential factors in arranging urban spaces and planning appropriate urban environments, etc. A factor that is rarely seen in metropolitan areas today. It seems that in order to have a diverse and at the same time harmonious urban skyline, in the first place, it is necessary to reconnect the fields of philosophy, art and daily life, which are free from the abstract and abstract view of experts. The development of interdisciplinary professions such as GIS, architecture and urban design is one of the measures in this direction that can have a different and more accurate view of the urban skyline. Therefore, the need for advanced geographical models for spatial three-dimensionalization and decision-making and forecasting goals in urban planning and design, especially in the case of vertical evaluation and development, is very clear and necessary. The advantages of using three-dimensional GIS models can be high potential in urban evaluation and analysis in various dimensions of urban aesthetics and high technology in the field of spatial analysis, the ability to test urban proposals and the power of semantic and topological storage. Mentioned above. Therefore, the use of these softwares to analyze urban issues is very important and increases the accuracy of urban planners and managers. For this purpose, the present study seeks to investigate the status of the urban skyline in the study areas and based on this, the importance of the perceptual and managerial dimension of the issue is analyzed using new methods and techniques.Data and Method The analytical approach of the research is physical and the method used in this research is three-dimensional vision analysis. Also, Arc GIS software has been used for easy preparation of the environment in 3D to perform the required analyzes. The data set used includes: digital model data of elevation, surface and floor layers of urban blocks.Results and Discussion In the present study, the concept of skyline was analyzed using three-dimensional GIS analysis in areas of urban areas 1 and 5 located in the east and northeast of Tabriz. Areas of interest include Valiasr town and Rushdieh town. So far, many different methods have been proposed to display and analyze the skyline. Some of these methods were reviewed in the research background and their strengths and weaknesses were identified. But the purpose of this article was to investigate the capabilities of 3D analysis and modeling through the development of 3D GIS in skyline display and analysis. Evaluating the results obtained in this research and comparing it with the results of studies in this field shows that three-dimensional analysis of GIS and 3D GIS development in comparison with other methods, provided there is accurate and comprehensive information, has high efficiency and capability. The research hypothesis is confirmed.ConclusionThe skyline is important both in terms of urban architecture and in terms of urban planners and designers; Although these specialties are different in terms of information extraction methods, methods and analytical contexts, but they are quite similar in terms of results. In general, it can be said that the skyline is one of the analyzes that are analyzed and evaluated in different software environments such as Arc GIS and in different fields.But the results of this study proved in another way that the three-dimensional GIS environment provides an opportunity to easily view and analyze the level of impact, effectiveness, volume, dimensions and angles of the skyline; This software also has high analytical power. While the analysis of the sky line in a two-dimensional environment gives a graphical and dimensionless result, percentage and frequency. But the most important difference and the ability to use 3D GIS analysis is that it provides a platform where even people with little knowledge of urban views can easily see the results and make decisions based on it. Also, the capabilities and capabilities of GIS in the field of various valuations and combined analyzes of vector and raster functions, as well as the presentation of three-dimensional analysis, have led its applications to urban design.

Common passive surveys for the presence of clouds in the sky are carried out using the digital processing of photographs taken using fish-eye type lenses. Another type of survey is carried out using active measuring systems, e.g. thermal imaging, active laser distance sensors, etc. A common feature of these sensors is the high cost of the measuring apparatus, which is hardly acceptable for small local short-term weather forecasting stations. The main task of these weather stations is to forecast local dynamic weather phenomena that have (or may have) an impact on the use or operation of technical facilities (e.g. photovoltaic farms, wind farms, cranes, etc.) or agricultural plant protection measures. This paper proposes a hybrid method for detecting clouds and predicting changes in cloud cover on the horizon line. The proposed method is based on an analysis of colour photographs of the cross-section of the sky using chrominance distribution by the RGB method. In the next step, the CCT colour temperature and the ALS-based ambient light intensity resulting from spectral analysis are determined for the cross-section of the sky being identified. The survey results indicate the dependence of the variability of CCT and ALS parameters for classifying objects on the horizon line. The above analysis makes it possible to distinguish the sky on the horizon, a cloud, or agglomeration elements. The data obtained from the surveys show that the proposed structure of the hybrid system for analysing the presence and movement of clouds on the horizon line can provide the basis for further development of data processing algorithms for a passive sensor of the apparatus for detecting clouds and other objects on the horizon line. [ABSTRACT FROM AUTHOR]

The evening and night silhouette of the city differs from daytime views and is recognizable by the illumination of the buildings. The text refers to the theoretical issues and research by design related to the illumination project of the Skyreach skyscraper building located at ul. Grzybowska 59. The criteria to light the building at night and the methodology of designing the illumination of buildings in terms of architecture are introduced. The research results are presented. The proposed methodology includes carrying out an analysis of the visibility of the city panorama and the illuminated building from key vantage points and key observation plans for the designed building, the role of illuminated buildings in spatial orientation, lighting colours, aspects of connecting lighting with the nature of the illuminated building, lighting intensity and light sources. All these issues were taken into account when designing the illumination of a high-rise building in an urban environment, especially, as in the case of Warsaw, in the absence of municipal guidelines regarding the illumination strategy of the city skyline. Since shortly, in connection with the rapid development of LED and OLED lighting, a large impact of building illumination on the appearance of the city should be expected, therefore the right tactics in carrying out the project of illuminating high-rise buildings, is important, which is diagnosed in the text. [ABSTRACT FROM AUTHOR]

Nowadays, big data is coming to the force in a lot of applications. Processing a skyline query on big data in more than linear time is by far too expensive and often even linear time may be too slow. It is obviously not possible to compute an exact solution to a skyline query in sublinear time, since an exact solution may itself have linear size. Fortunately, in many situations, a fast approximate solution is more useful than a slower exact solution. This paper proposes two sampling-based approximate algorithms for processing skyline queries. The first algorithm obtains a fixed size sample and computes the approximate skyline on it. The error of the algorithm is not only relatively small in most cases, but also is almost unaffected by the input size. The second algorithm returns an (, δ) -approximation for the exact skyline efficiently. The running time of the algorithm has nothing to do with the input size in practical, achieving the goal of sublinearity on big data. Experiments verify the error analysis of the first algorithm, and show that the second is much faster than the existing skyline algorithms. [ABSTRACT FROM AUTHOR]

The following paper is devoted to research on the types of forms of skyscrapers built in Warsaw from 1989 to 2022. The research focuses on defining the architectural typology of such forms as elements of the image of the city. The research was carried out in the following stages: defining the character of international examples of skyscrapers, research on types of forms of high-rise buildings realized in Warsaw and their formal classification, determination of typological features of twenty-four high-rise buildings under study, and their changes over time. The characteristic elements of the image of the city and urban composition related to the examined buildings were determined. As a result of the research, it was determined that the most common types of forms found in the study group were free forms—41.6%, polygonal forms—25%, and obelisk forms—20.8%. In individual cases, there are tapered, aerodynamic, and regional forms. The research showed a trend in the latest projects, dating back to the last five years, consisting of an increase in the number of buildings constructed, an increase their scale, a lowering of their slenderness, and a tendency to implement polygonal forms more often than free forms. High-rise buildings are landmarks in the urban composition and the image of Warsaw. Most often, they designate paths and nodes with which they are associated. The types of forms of high-rise buildings in Warsaw vary; there is no uniform type of form of high-rise building implemented in the period. For this reason, the research should be updated and carried out using the methodology presented in the paper. [ABSTRACT FROM AUTHOR]

In recent years, people have been buying custom-built PCs based on the performance they want and what they will use them for. However, there are many challenges for non-technical users when purchasing a custom-built PC. Not only is the terminology of computer devices unfamiliar to non-experts, but there are many specifications for different computer devices that need to be considered. Therefore, this paper proposes a method for recommending appropriate device models when purchasing custom-built PCs using a skyline. Because different computer devices have different specifications, we need a method that takes into account multiple attributes. Skyline querying is a technique that considers multiple attributes of an object and indexes them in order of user satisfaction. A grid skyline is a technique that uses a grid-based partitioning technique to reduce the number of calculations of the dominance relationship between objects in the existing skyline technique, thus reducing the index construction time. We measured the similarity between the results of the grid skyline and the leaderboard for each model of computer device. As a result of this experiment, compared to the leaderboard categorized by model of computer device, the average score was 88 out of 100, which was similar to the actual leaderboard.

Cloud computing has experienced rapid growth in recent years and has become a critical computing paradigm. Combining multiple cloud services to satisfy complex user requirements has become a research hotspot in cloud computing. Service composition in multi-cloud environments is characterized by high energy consumption, which brings attention to the importance of energy consumption in cross-cloud service composition. Nonetheless, prior research has mainly focused on finding a service composition that maximizes the quality of service (QoS) and overlooks the energy consumption generated during service invocation. Additionally, the dynamic nature of multi-cloud environments challenges the adaptability and scalability of cloud service composition methods. Therefore, we propose the skyline-enhanced deep reinforcement learning approach (SkyDRL) to address these challenges. Our approach defines an energy consumption model for cloud service composition in multi-cloud environments. The branch and bound skyline algorithm is leveraged to reduce the search space and training time. Additionally, we enhance the basic deep Q-network (DQN) algorithm by incorporating double DQN to address the overestimation problem, incorporating Dueling Network and Prioritized Experience Replay to speed up training and improve stability. We evaluate our proposed method using comparative experiments with existing methods. Our results demonstrate that our approach effectively reduces energy consumption in cloud service composition while maintaining good adaptability and scalability in service composition problems. According to the experimental results, our approach outperforms the existing approaches by demonstrating energy savings ranging from 8% to 35%.

Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis to facilitate the data deconvolution process. We proposed a pipeline for quantitative profiling of pharmaceutical drugs and serum metabolites in DIA mode after comparing the results obtained from full-scan, Data-dependent acquisition (DDA) and DIA modes. using open-access software. Pharmaceutical drugs (10) were pooled in healthy human serum and analysed by LC-ESI-QTOF-MS. MS1 full-scan and Data-dependent (MS2) results were used for identification using MS-DIAL software while deconvolution of MS1/MS2 spectra in DIA mode was achieved by using Skyline software. The results of acquisition methods for quantitative analysis validated the remarkable analytical performance of the constructed workflow, proving it to be a sensitive and reproducible pipeline for biological complex fluids. [ABSTRACT FROM AUTHOR]

With the increase of data volume in heterogeneous datasets that are being published following Open Data initiatives, new operators are necessary to help users to find the subset of data that best satisfies their preference criteria. Quantitative approaches such as top-k queries may not be the most appropriate approaches as they require the user to assign weights that may not be known beforehand to a scoring function. Unlike the quantitative approach, under the qualitative approach, which includes the well-known skyline, preference criteria are more intuitive in certain cases and can be expressed more naturally. In this paper, we address the problem of evaluating SPARQL qualitative preference queries over an Ontology-Based Data Access (OBDA) approach, which provides uniform access over multiple and heterogeneous data sources. Our main contribution is Morph-Skyline++, a framework for processing SPARQL qualitative preferences by directly querying relational databases. Our framework implements a technique that translates SPARQL qualitative preference queries directly into queries that can be evaluated by a relational database management system. We evaluate our approach over different scenarios, reporting the effects of data distribution, data size, and query complexity on the performance of our proposed technique in comparison with state-of-the-art techniques. Obtained results suggest that the execution time can be reduced by up to two orders of magnitude in comparison to current techniques scaling up to larger datasets while identifying precisely the result set. [ABSTRACT FROM AUTHOR]

Purpose: The LUMIPOINT™ software module was developed to aid the physician in determining the mechanism of individual atrial tachycardias (ATs). The purpose of this study was to assess the clinical utility of the SKYLINE™ histogram that is a part of LUMIPOINT™.Methods: This study included consecutive patients with iatrogenic sustained AT who underwent catheter ablation using conventional mapping (RHYTHMIA™). SKYLINE™ patterns were analyzed offline and classified into two types: (1) focal type (type-F) exhibiting a low-amplitude (relative activating surface area < 10%) plateau period and (2) reentrant type (type-R) showing no plateau period. How well the two patterns distinguished between focal and macroreentrant ATs as determined by conventional mapping was evaluated.Results: We studied 101 iatrogenic ATs in 91 patients (female: 24, mean age: 67.3 ± 9.1 years). Activation mapping revealed 79 (78.2%) macroreentrant, 6 (5.9%) localized reentrant, and 16 (15.8%) focal ATs. Among the 72 type-R ATs, the mechanism was truly a macroreentry in 70 ATs. However, one focal AT and one localized reentrant AT displayed a type-R pattern (pseudo-reentry pattern). In the 29 type-F ATs, nine macroreentrant ATs were recognized (pseudo-focal pattern). Using SKYLINE™ type-R to differentiate macroreentrant AT from AT with centrifugal activation (focal or localized reentry), the sensitivity and specificity were 88.6% and 90.9%, respectively. Even when the SKYLINE™ type did not match the mapping-based AT mechanism, all discrepancies were electrophysiologically explicable using the SKYLINE™ histograms.Conclusions: SKYLINE™ histograms are a useful tool for the intuitive diagnosis of AT mechanisms. [ABSTRACT FROM AUTHOR]

This paper presented a Computational Fluid Dynamics (CFD) study on the relationship between skyline quantitative factors and the wind environment. At present, most researches on skyline revealed the changes of skyline quantitative factors on the aesthetic degrees but neglected the influence of the factors on the outdoor wind environment. This paper addresses the gap in using the changing factors for the prediction of outdoor wind speed. It provides a standardized range for aesthetic degrees in the comfortable range of the wind environment and an exact relationship between the factors and the wind environment. To validate the effectiveness of the proposed approach, a case study is undertaken on the existing skyline of Qianjiang New City in Hangzhou and extracts the following three skyline quantitative factors in skyline contour: contour tortuosity, building undulation, and skyline rhythm index. The result shows that the proposed range and relationship are ready to provide a quantitative understanding of the skyline under outdoor wind conditions. [ABSTRACT FROM AUTHOR]

In the brain, the Homer protein family modulates excitatory signal transduction and receptor plasticity through interactions with other proteins in dendritic spines. Homer proteins are implicated in a variety of psychiatric disorders such as schizophrenia and addiction. Since long Homers serve as scaffolding proteins, identifying their interacting partners is an important first step in understanding their biological function and could help to guide the design of new therapeutic strategies. The present study set out to document Homer2-interacting proteins in the mouse brain using a co-immunoprecipitation-based mass spectrometry approach where Homer2 knockout samples were used to filter out non-specific interactors. We found that in the mouse brain, Homer2 interacts with a limited subset of its previously reported interacting partners (3 out of 31). Importantly, we detected an additional 15 novel Homer2-interacting proteins, most of which are part of the N-methyl-D-aspartate receptor signaling pathway. These results corroborate the central role Homer2 plays in glutamatergic transmission and expand the network of proteins potentially contributing to the behavioral abnormalities associated with altered Homer2 expression.SignificanceLong Homer proteins are scaffolding proteins that regulate signal transduction in neurons. Identifying their interacting partners is key to understanding their function. We used co-immunoprecipitation in combination with mass spectrometry to establish the first comprehensive list of Homer2-interacting partners in the mouse brain. The specificity of interactions was evaluated using Homer2 knockout brain tissue as a negative control. The set of proteins that we identified minimally overlaps with previously reported interacting partners of Homer2; however, we identified novel interactors that are part of a signaling cascade activated by glutamatergic transmission, which improves our mechanistic understanding of the role of Homer2 in behavior.

Liquid chromatography (LC)-selected reaction monitoring (SRM) is a powerful protein quantification technique in terms of sensitivity, reproducibility, and multiplexing capability. LC-SRM can accurately measure the concentrations of surrogate proteotypic peptides for targeted proteins in complex biological samples by using their stable heavy isotope-labeled counterparts as internal standards. Herein, we describe a step-by-step protocol of the application of LC-SRM to quantify candidate protein biomarkers in human urine.

Visibility is an important factor for decision-making regarding the visual quality of the skyline of modern cities which dominated by tall buildings. The basic method of visibility is referred to the concept of targeted isovist that represents the visible portion of the target area of tall buildings. This paper presents a reliable method of visibility analysis for tall building clusters, examining all unobstructed views of those clusters from surrounding streets and their impact on the shape of skyline, using Jakarta as a case study. The visibility algorithm was developed with Grasshopper and building models were simultaneously simulated using Rhinoceros 3D. The results are presented with a color segment that represents the percentage of visible viewpoints and the visible area of a building’s facade. The results showed that building height configurations, the location of buildings, the relation to the street, and the distances of various viewpoints have a significant effect on the rate of visibility. Moreover, the level of visibility of tall building clusters determines the shape of the skyline. The proposed visibility analysis method is expected to be an essential tool in the planning and design of tall buildings in a clustered organization for shaping the city skyline of the future.

Accurate relative quantification is critical in proteomic studies. The incorporation of stable isotope 15N to plant-expressed proteins in vivo is a powerful tool for accurate quantification with a major advantage of reducing preparative and analytical variabilities. However, 15N labeling quantification has several challenges. Less identifications are often observed in the heavy-labeled samples because of incomplete labeling, resulting in missing values in reciprocal labeling experiments. Inaccurate quantification can happen when there is contamination from co-eluting peptides or chemical noise in the MS1 survey scan. These drawbacks in quantification can be more pronounced in less abundant but biologically interesting proteins, which often have very few identified peptides. Here, we demonstrate the application of parallel reaction monitoring (PRM) to 15N labeled samples on a high resolution, high mass accuracy Orbitrap mass spectrometer to achieve reliable quantification even of low abundance proteins in samples. [ABSTRACT FROM AUTHOR]