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Purpose: Ludruk has a socio-cultural role for the people of East Java in the effort to preserve and develop the local culture. Especially as performing arts, ludruk can act as entertainment that can be enjoyed by various layers of society in East Java, the purpose of this study is: Describe the Improvement of the Management of the Organization of Performing Arts Ludruk Irama Sinar Nusantara Culture. Design/methodology/approach: This research is a qualitative sociological phenomenological study, based on the literature review. The data in this study form qualitative data consisting of three types, namely data behavior, oral data, and writing data. Instruments in this study are researchers themselves. Data analysis in this research consists of several activities that are done jointly, according to Miles and Huberman data reduction, display data and conclusion drawing / verification. Findings: The results of this study are: 1) In general in the approach of critical theorists of art and entertainment ludruk is the idea that they deserve attention for three reasons. First, the contents of art and works present a potentially revealing story of the human, social, and world way of working in the same way as the myth that offers a mimetic representation of the world of life experience. Secondly, ludruk as a means of art and entertainment produced reflects something from the way people live with real conditions is significant. Third, ludruk as an art, if not entertainment how able to entertain the fans as they start to switch to other entertainment. 2) Changes in the paradigm of technical managers in management skills so that the focus to practice the skills required to successfully manage ludruk seriously from various circles to preserve and develop it, to build maximum functional relationships with internal and external clients, it must have a management infusion by adopting the model most recently covering the organizational structure, the function of the marketing channel for the performing arts will lead to the improvement of the delivery of performing arts through more effective inter-organizational management, or certain services to predetermined consumption points, and more importantly improved performance is a change organizations in which managers and organizations that organize organizations place and manage programs that measure the current level of organizational performance and then generate ideas to modify organizational behavior and infrastructure incorporated into the temp at to achieve higher results. Originality/value: This paper is original Paper type: a Research Paper

Background The health system in South Sudan faces extreme domestic resource constraints, low capacity, and protracted humanitarian crises. Supportive supervision is believed to improve the quality of health care and service delivery by compensating for flaws in health workforce management. This study aimed to explore the current supervision practices in South Sudan and identify areas for quality improvement. Methods The study employed qualitative approaches to collect and analyse data from six purposefully selected counties. Data were collected from 194 participants using semi-structured interviews (43 health managers) and focus group discussions (151 health workers). Thematic content analysis was used to yield an in-depth understanding of the supervision practices in the health sector. Results The study found that integrated supportive supervision and monitoring visits were the main approaches used for health services supervision in South Sudan. Supportive supervision focused more on health system administration and less on clinical matters. Although fragmented, supportive supervision was carried out quarterly, while monitoring visits were either conducted monthly or ad hoc. Prioritization for supportive supervision was mainly data driven. Paper-based checklists were the most commonly used supervision tools. Many supervisors had no formal training on supportive supervision and only learned on the job. The health workers received on-site verbal feedback and, most times, on-the-job training sessions through coaching and mentorship. Action plans developed during supervision were inadequately followed up due to insufficient funding. Insecurity, poor road networks, lack of competent health managers, poor coordination, and lack of adequate means of transport were some of the challenges experienced during supervision. The presumed outcomes of supportive supervision were improvements in human resource management, drug management, health data reporting, teamwork, and staff respect for one another. Conclusion Supportive supervision remains a daunting task in the South Sudan health sector due to a combination of external and health system factors. Our study findings suggest that strengthening the processes and providing inputs for supervision should be prioritized if quality improvement is to be attained. This necessitates stronger stewardship from the Ministry of Health, integration of different supervision practices, investment in the capacity of the health workforce, and health infrastructure development.

In heterogeneous wireless networks, random packet loss and high latency lead to conventional TCP variants performing unsatisfactorily in the case of competing communications. Especially on high-latency wireless links, conventional TCP variants are unable to estimate congestion degrees accurately for fine-grained congestion control because of the effects of random packet loss and delay oscillations. This paper proposes a TCP variant at the sender side to identify congestion degrees, namely TCP-WBQ, which quickly responses to the real congestion and effectively shields against random packet loss and oscillations of latency time. The proposed algorithm of congestion control firstly constructs a backlog-queue model based on the dynamics of the congestion window, and deduces the two bounds of the model which delimit oscillations of the backlog queue for non-congestion and random packet loss respectively. TCP-WBQ detects congestion degrees more accurately and thus implements the corresponding schemes of adjusting the congestion window, maintaining a tradeoff between high throughputs and congestion avoidance. The comprehensive simulations show that TCP-WBQ works efficiently in bandwidth utilization with single and multiple bottleneck scenarios, and achieves high performance and competitive fairness in heterogeneous wireless networks.

As a result of their cell structures, elastomeric foams exhibit high compressibility and are frequently used as buffer cushions in energy absorption. Foam pads between two surfaces typically withstand uniaxial loads. In this paper, we considered the effects of porosity and cell size on the mechanical behavior of random elastomeric foams, and proposed a constitutive model based on an artificial neural network (ANN). Uniform cell size distribution was used to represent monodisperse foam. The constitutive relationship between Cauchy stress and the four input variables of axial stretch λU, lateral stretch λL, porosity φ, and cell size θ was given by con-ANN. The mechanical responses of 500 different foam structures (20% < φ < 60%, 0.1 mm < θ < 0.5 mm) under compression and tension loads (0.4 < λU < 3) were simulated, and a dataset containing 100,000 samples was constructed. We also introduced a pre-ANN to predict lateral stretch to address the issue of missing lateral strain data in practical applications. By combining physical experience, we chose appropriate input forms and activation functions to improve ANN’s extrapolation capability. The results showed that pre-ANN and con-ANN could provide reasonable predictions for λU outside the dataset. We can obtain accurate lateral stretch and axial stress predictions from two ANNs. The porosity affects the stress and λL, while the cell size only affects the stress during foam compression.

This paper aims to investigate the hysteric tendencies, inconsistent speeches and silences of woman in Jhumpa Lahiri’s two short stories “The Treatment of Bibi Haldar” and “The Real Durwan.” The paper addresses this objective through the application of subaltern perspective: subaltern cannot speak. More specifically, single, poor and helpless women’s position and their inability to speak in need are analyzed in the light of subaltern studies. These two stories expose the issue of hysteric woman and an elderly street woman with different stories, respectively. The disadvantaged women’s inability to speak – parallels the subaltern’s inability to speak. This paper analyses hysterical tendencies, inconsistent behavior of Lahiri’s protagonists as the outburst, thus, the subtle ways of resistance. Thus, the paper draws the conclusion that Lahiri’s stories demonstrate economically and socially marginalized woman who lack the act of protest as they cannot speak, tending to develop the different verbal and physical inconsistencies.

Cavernous lymphangioma often occurs in the head, neck, trunk, and extremities of infants and children, and it is rare to cause a small intestine intussusception in adults. In this case, a 32-year-old woman presented with abdominal pain, vomiting, and a 5 cm × 5 cm abdominal mass on the left side of the abdomen. Laboratory tests showed anemia and CT showed small intestinal intussusception. After conservative treatments, her symptoms disappeared. However, 18F-FDG PET/CT suggested malignancy and her symptoms reappeared after eating something. Segmental jejunal resection was performed and pathology showed submucosal cavernous lymphangioma. At the 1-year follow-up, the patient was asymptomatic. Then this paper reviewed the literature on small intestinal cavernous lymphangioma in adults and found that this is the first English case report of intussusception caused by a jejunal submucosal cavernous lymphangioma in an adult. Current problem is that adult intussusception and intestinal lymphangioma are difficult to diagnose preoperatively. Imaging techniques such as tomography and PET/CT aid in the diagnosis of these benign lesions. Surgical resection was considered to be the required treatment and seems to have had no recurrence in adults according to the literature.

Focal boost to dominant intraprostatic lesions (DILs) has recently been proposed for prostate radiation therapy. Accurate and fast delineation of the prostate and DILs is thus required during treatment planning. In this paper, we develop a learning-based method using positron emission tomography (PET)/computed tomography (CT) images to automatically segment the prostate and its DILs. To enable end-to-end segmentation, a deep learning-based method, called cascaded regional-Net, is utilized. The first network, referred to as dual attention network, is used to segment the prostate via extracting comprehensive features from both PET and CT images. A second network, referred to as mask scoring regional convolutional neural network (MSR-CNN), is used to segment the DILs from the PET and CT within the prostate region. Scoring strategy is used to diminish the misclassification of the DILs. For DIL segmentation, the proposed cascaded regional-Net uses two steps to remove normal tissue regions, with the first step cropping images based on prostate segmentation and the second step using MSR-CNN to further locate the DILs. The binary masks of DILs and prostates of testing patients are generated on the PET/CT images by the trained model. For evaluation, we retrospectively investigated 49 prostate cancer patients with PET/CT images acquired. The prostate and DILs of each patient were contoured by radiation oncologists and set as the ground truths and targets. We used five-fold cross-validation and a hold-out test to train and evaluate our method. The mean surface distance and DSC values were 0.666 ± 0.696 mm and 0.932 ± 0.059 for the prostate and 0.814 ± 1.002 mm and 0.801 ± 0.178 for the DILs among all 49 patients. The proposed method has shown promise for facilitating prostate and DIL delineation for DIL focal boost prostate radiation therapy.

Underwater marine object detection, as one of the most fundamental techniques in the community of marine science and engineering, has been shown to exhibit tremendous potential for exploring the oceans in recent years. It has been widely applied in practical applications, such as monitoring of underwater ecosystems, exploration of natural resources, management of commercial fisheries, etc. However, due to complexity of the underwater environment, characteristics of marine objects, and limitations imposed by exploration equipment, detection performance in terms of speed, accuracy, and robustness can be dramatically degraded when conventional approaches are used. Deep learning has been found to have significant impact on a variety of applications, including marine engineering. In this context, we offer a review of deep learning-based underwater marine object detection techniques. Underwater object detection can be performed by different sensors, such as acoustic sonar or optical cameras. In this paper, we focus on vision-based object detection due to several significant advantages. To facilitate a thorough understanding of this subject, we organize research challenges of vision-based underwater object detection into four categories: image quality degradation, small object detection, poor generalization, and real-time detection. We review recent advances in underwater marine object detection and highlight advantages and disadvantages of existing solutions for each challenge. In addition, we provide a detailed critical examination of the most extensively used datasets. In addition, we present comparative studies with previous reviews, notably those approaches that leverage artificial intelligence, as well as future trends related to this hot topic.

In this paper I demonstrate some major changes within the traditional disciplinary boundaries of archaeology during the last 25-30 years, and the subsequent formation of new frontiers of theory and practice. They are the result of the expansion and diversification of the discipline in modern society. In that process archaeology has lost its former hegemonic identity which is replaced by pluralism and overlapping functions and identities. This has resulted in institutional and organisational discrepances. My analysis serves as a platform for forrnulating a strategy for cooperation between these new sectors, especially the heritage sector and the universities, leading to the formation of a more coordinated archaeological research practice.

This paper considers the design of observational longitudinal studies with a continuous response and a binary time-invariant exposure, where, typically, the exposure is unbalanced, the mean response in the two groups differs at baseline and the measurement times might not be the same for all participants. We consider group differences that are constant and those that increase linearly with time. We study power, number of study participants (N) and number of repeated measures (r), and provide formulas for each quantity when the other two are fixed, for compound symmetry, damped exponential and random intercepts and slopes covariances. When both N and r can be chosen by the investigator, we study the optimal combination for maximizing power subject to a cost constraint and minimizing cost for fixed power. Intuitive parameterizations are used for all quantities. All calculations are implemented in freely available software.

Research on political apologies spans sociopolitical contexts and disciplines and methodological frameworks. In the rise of interest in political apologies, especially in light of ‘the age of apologies’, social psychologists strive to understand mechanisms of issuing, perception and evaluation of political apologies from many perspectives. This special issue aims to highlight the important role of social psychological theory in understanding political apologies and deepening knowledge in this field. The papers, which comprise the special issue, offer a detailed and comprehensive study of political apology, including both theoretical and methodological lens to enrich understanding of the topic. Concluding, all the papers of this special issue can be of interest in academics and researchers, as well as policy-makers and other stakeholders beyond academia.

This paper considers the musical output of Detroit-based hardcore punk band Negative Approach (and particularly its vocalist John Brannon), as a lens through which to understand Detroit’s place in what Andreas Huyssen calls the “imaginary of ruins.” During their short existence from 1981-1984, Negative Approach developed a sound that is frequently understood to reflect Detroit, the band’s intensity and Brannon’s vicious vocal timbre correlated with the image of a city ‘ruined’ by the economic decline and racial inequities hastened by its infamous 1967 riots. Drawing on ruin studies, a history of Detroit, the context of American hardcore rock, and on the timbral and structural qualities of Brannon’s music, the paper considers both the usefulness and problematic limitations of using ruin imagery to understand a surviving city, of reducing its material reality solely to metonymic expression of post-Fordist decline. While the paper does elucidate the correlation between Brannon’s music and the city’s struggles—which include a strained relationship with its wealthier, de facto segregated suburbs—it also illustrates the extent to which such designations are inherently problematic both for flattening the music’s affect and for overlooking the material reality of a city and its citizens, who struggle onwards with dignity and imagination rather than defining themselves solely in reference to their challenges.

This paper summarizes the perspectives of health and wellness tourism consumers, to better understand the factors that influence this tourism product. A quantitative approach was adopted to collect primary data through the application of an online survey to effective and potential health and wellness tourism consumers between January and April 2021. Results show that growing number of consumers tend to value health and wellness tourism as a holistic experience, in which not only products specifically related to health and wellness treatments are of particular importance, but also activities related to leisure, recreation and culture. This paper provides a basis of research and analysis for global wellness and tourism industry stakeholders. The aim is to help the industry understand consumer behaviour and preferences in the traveller’s process of choosing a destination for a wellness vacation. This is achieved by predicting wellness tourism trends and developments, by acknowledging the gaps in the research available for understanding wellness tourism and reflecting the experience economy perspective in the sector.

This companion paper is to support the replication of paper "Campus3D: A Photogrammetry Point Cloud Benchmark for Outdoor Scene Hierarchical Understanding", which was presented at ACM Multimedia 2020. The supported paper's main purpose was to provide a photogrammetry point cloud-based dataset with hierarchical multilabels to facilitate the area of 3D deep learning. Based on this provided dataset and source code, in this work, we build a complete package to reimplement the proposed methods and experiments (i.e., the hierarchical learning framework and the benchmarks of the hierarchical semantic segmentation task). Specifically, this paper contains the technical details of the package, including file structure, dataset preparation, installation package, and the conduction of the experiment. We also present the replicated experiment results and indicate our contributions to the original implementation.

Traditional deep learning compilers rely on heuristics for subgraph generation, which impose extra constraints on graph optimization, e.g., each subgraph can only contain at most one complex operator. In this paper, we propose AGO, a framework for graph optimization with arbitrary structures to boost the inference performance of deep models by removing such constraints. To create new optimization opportunities for complicated subgraphs, we propose intensive operator fusion, which can effectively stitch multiple complex operators together for better performance. Further, we design a graph partitioning scheme that allows an arbitrary structure for each subgraph while guaranteeing the acyclic property among all generated subgraphs. Additionally, to enable efficient performance tuning on complicated subgraphs, we devise a novel divide-and-conquer tuning mechanism to orchestrate different system components. Through extensive experiments on various neural networks and mobile devices, we show that our system can improve the inference performance by up to 3.3x when compared with state-of-the-art deep compilers.

Under the development goal of “Carbon Peak, Carbon Neutralization”, the concept of novel power system is proposed. Its representative features include AC/DC interconnection of power grid and large-scale access of new energy power stations. Under these characteristics, higher requirements are put forward for the short-circuit current breaking capacity of the circuit breaker. The DC component of short-circuit current and the injection of new energy into the system short-circuit current cannot be ignored. Based on the 330kV local power grid in Northwest China, this paper studies the power grid operation mode, DC component of short-circuit current and the influence of photovoltaic power station on short-circuit current. The influence law of DC component of short-circuit current on the actual breaking capacity of circuit breaker and access of photovoltaic power station on the short-circuit current are summarized. It can provide a theoretical basis for the selection of circuit breaker in novel power system.

(1) Background: Clinical reasoning is essential to the effective practice of autonomous health professionals and is, therefore, an essential capability to develop as students. This review aimed to systematically identify the tools available to health professional educators to evaluate students’ attainment of clinical reasoning capabilities in clinical placement and simulation settings. (2) Methods: A systemic review of seven databases was undertaken. Peer-reviewed, English-language publications reporting studies that developed or tested relevant tools were included. Searches included multiple terms related to clinical reasoning and health disciplines. Data regarding each tool’s conceptual basis and evaluated constructs were systematically extracted and analysed. (3) Results: Most of the 61 included papers evaluated students in medical and nursing disciplines, and over half reported on the Script Concordance Test or Lasater Clinical Judgement Rubric. A number of conceptual frameworks were referenced, though many papers did not reference any framework. (4) Conclusions: Overall, key outcomes highlighted an emphasis on diagnostic reasoning, as opposed to management reasoning. Tools were predominantly aligned with individual health disciplines and with limited cross-referencing within the field. Future research into clinical reasoning evaluation tools should build on and refer to existing approaches and consider contributions across professional disciplinary divides.

Waste activated sludge (WAS) is formed by a diverse microorganisms, organic and inorganic compounds merged and mixed together in an extracellular polymeric substances (EPS) network. EPS is a complex high-molecular weight macromolecules in WAS that happens to be one of the common analysis to determine the efficiency of treatment. Therefore, different extraction methods has been applied in order to achieve better EPS extraction yield. This paper serves as a base to review the commonly used chemical extraction methods to extract EPS components. The mechanisms, conditions and efficiencies of each of the chemical extraction methods were discussed and compared accordingly. The possible use of different chemical extraction methods for different type of activated sludge were summarized.

What are realistic emissions targets for the world's six largest emitters that sum up to Paris-compatible emissions? To answer this question, this paper varies key framework data on the available budget and the sharing mechanism to calculate top-down national emissions targets using the Extended Smooth Pathway Model (ESPM). The Paris ambition mechanism provides a combination of top-down and bottom-up approaches. For each country in the word the question arises to what extent their bottom-up targets fit with global needs. This might initiate a discourse on the global framework data that contributes to Paris-compatible NDCs in sum.

This paper evaluates the reaction of systemically important banks in Europe to the shock of the Russian invasion of Ukraine in 2022. Using the event study methodology and three of the most commonly used models for estimating theoretical returns (CAPM, Fama-French with 3 factors, Fama-French with 5 factors), we show that banks react differently relative to the event date (February 24, 2022) depending on the country. Overall, systemically important banks recorded massive cumulative abnormal returns in the event window. The results differ at the country level depending on the exposure of the respective banks to Russia, the dependence of countries on Russian gas and oil, and the level of informational efficiency of the markets on which they are traded.

Language MOOCs (L-MOOCs) are the MOOCs (Massive Open Online Courses) that focus on language learning. They may often present several problems in their design and development, such as their feasibility to improve students’ linguistic levels or in their materials’ adequacy and variety. Many of these courses have subsequently become Open Educational Resources (OERs), and their activities can be implemented in different learning situations. Our paper discusses the evaluation of the integration of the L-MOOC titled “Learn academic Spanish” (Aprende español académico) into existing curricula and the validation process carried out to evaluate its validity for the purpose of learning languages. The L-MOOC was developed within the MOOC2move project between 2018–2021 and was designed by the Open University, with the collaboration of the Spanish universities of León and Alicante. The evaluation and validation were carried out in October 2020. In an exceptional hybrid teaching situation, due to the COVID-19 pandemic, the L-MOOC was taken by 345 students from the Faculty of Education of the University of Alicante. The validation of the course consisted of taking the L-MOOC, participating in the forums on the MOOC and completing the questionnaires to improve the materials. In our study, a quantitative analysis was carried out through two questionnaires provided to the students before and after implementing this L-MOOC. The results obtained underlined the effectiveness of this L-MOOC. This course and the materials provided allowed the use of OERs to practice academic Spanish and improve communicative competence of its users.

This paper describes the design and development of an active device that was applied to shoulder rotation rehabilitation. It implements a force control in a similar way to the haptic devices that reflect a force on the user’s hand according to the rehabilitation parameters. This device was tested with patients, combining clinician manipulation and programmed exercises. The results were excellent, given that the range of movement of the shoulder increased in most of the pa-tients. The results of the Usability Scale questionnaire were also promising.

Eukaryotic autonomously replicating sequences (ARSs) are composed of three domains, A, B, and C. Domain A is comprised of an ARS consensus sequence (ACS), while the B domain has the DNA unwinding element and the C domain is important for DNA-protein interactions. In Saccharomyces cerevisiae and Kluyveromyces lactis ARS101, the ACS is commonly composed of 11 bp, 5ˊ-(A/T)AAA(C/T)ATAAA(A/T)-3ˊ. This core sequence is essential for S. cerevisiae and K. lactis ARS activity. In this study, we identified ARS-containing sequences from genomic libraries of the yeast Kluyveromyces marxianus DMKU3-1042 and validated their replication activities. The identified K. marxianus DMKU3-1042 ARSs (KmARSs) have very effective replication ability but their sequences are divergent and share no common consensus. We have carried out point mutations, deletions, and base pairs substitutions within the sequences of some of the KmARSs to identify the sequence(s) that influence the replication activity. Consensus sequences same as the 11 bp ACS of S. cerevisiae and K. lactis were not found in all minimum functional KmARSs reported here except KmARS7. Moreover, partial sequences from different KmARSs are interchangeable among each other to retain the ARS activity. We have also specifically identified the essential nucleotides, which are indispensable for replication, within some of the KmARSs. Our deletions analysis revealed that only 21 bp in KmARS18 could retain the ARS activity. The identified KmARSs in this study are unique compared to other yeasts’ ARSs, do not share common ACS, and are interchangeable., Highlights • Identification of minimal autonomously replicating sequences (ARSs) from the yeast Kluyveromyces marxianus DMKU3-1042. • The identities of the isolated ARSs are divergent and have no common consensus with the ARSs of other yeasts. • A short ARS sequence of twenty-one nucleotides functions as an effective replicator in K. marxianus DMKU3-1042. • Segments of ARSs from the yeast K. marxianus are interchangeable among each other. • Functional ARSs are found in both the intergenic and coding sequences of the strain DMKU3-1042.

In this paper we study metric deformations of indecomposable metric Lie superalgebras with dimensions less or equal to 6. We consider formal deformations obtained by even cocycles, because the odd ones can not be used for constructing formal deformations., Comment: 18 pages

Hadoop distributed file system (HDFS) is the file system whereby Hadoop is use it to store all the upcoming data inside it. Since it been declared, HDFS is consuming a huge memory amount in order to serve a normal dataset. Nonetheless, the current file saving mechanism in HDFS save only one file in one datablock. Thus, a file with just 5 Mb in size will take up the whole datablock capacity causing the rest of the memory unavailable for other upcoming files, and this is considered a huge waste of memory in serving a normal size dataset. This paper proposed a method called tiny datablock-HDFS (TD-HDFS) to increase the usability of HDFS memory and increase the file hosting capabilities by reducing the datablock size to the minimum capacity, and then merging all the related datablocks into one master datablock. This master datablock consists of tiny virtual datablocks that contain the related small files together; will exploit the full memory of the master datablock. The result of this study is a running HDFS with a minimum amount of wasted memory with the same read/write data performance. The results were examined through a comparison between the standard HDFS file hosting and the proposed solution of this study.TRANSLATE with x EnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster PortalBack

In the past years, a number of static application security testing tools have been proposed which make use of so-called code property graphs, a graph model which keeps rich information about the source code while enabling its user to write language-agnostic analyses. However, they suffer from several shortcomings. They work mostly on source code and exclude the analysis of third-party dependencies if they are only available as compiled binaries. Furthermore, they are limited in their analysis to whether an individual programming language is supported or not. While often support for well-established languages such as C/C++ or Java is included, languages that are still heavily evolving, such as Rust, are not considered because of the constant changes in the language design. To overcome these limitations, we extend an open source implementation of a code property graph to support LLVM-IR which can be used as output by many compilers and binary lifters. In this paper, we discuss how we address challenges that arise when mapping concepts of an intermediate representation to a CPG. At the same time, we optimize the resulting graph to be minimal and close to the representation of equivalent source code. Our evaluation indicates that existing analyses can be reused without modifications and that the performance requirements are comparable to operating on source code. This makes the approach suitable for an analysis of large-scale projects.

This paper proposes the initial strategy of designing two degree of freedom proportional integral derivative (2DOF-PID) made load frequency control (LFC) action optimized using Jaya optimization algorithm for a hydro-hydro system. At first, the PID optimized through Jaya is used for hydro-dominated system, and the comparative analysis of all possible error definitions are carried out to show the benefits of selecting integral time absolute error (ITAE) for LFC. Then, 2DOF-PID is designed for the hydro governing system, and its performance is compared with other designs to show the efficacy of the present LFC about computed error values gain of the various models via graphical LFC. The results obtained through simulations are promising but oscillatory with greater settling time. Hence, the proposed controller is retuned by considering the unified power flow control (UPFC) in arrangement with the tie-line and redox flow battery (RFB) units in area-2, and it is further seen that the outcomes of the application show the prevalence of the proposed work.

The use of Electric Vehicles (EVs) is almost inevitable in the near future for the sake of the environment and our plant’s long-term sustainability. The availability of an Electric-Vehicle-Charging Station (EVCS) is the key challenge that owners are worried about. Therefore, we suggest benefiting from individual EVs that have excess energy and are willing to share it with other EVs in order to maximize the availability of EVCSs without the need to rely on the existing charging infrastructure. The Internet of Electric Vehicles (IoEV) is gradually gaining traction, allowing for a more efficient and intelligent transportation system by leveraging these capabilities between EVs. However, the IoEV is considered a trustless environment, with untrustworthy trading partners such as data sellers, buyers, and brokers. Data exchanged between the EV and the Energy AGgregator (EAG) or EV/EV can be used to analyze users’ behavior and compromise their privacy. Thus, a Vehicle-to-Vehicle (V2V)-charging system that is both secure and private must be established. Several V2V-charging systems with security and privacy features have been proposed. However, even if the transmitted communications are entirely anonymous, anonymity alone will not prevent the tracking adversary from reconstructing the target vehicle’s route. These systems frequently fail to find a balance between privacy concerns (e.g., trade traceability to achieve anonymity, and so on) and security measures. In this paper, we propose an efficient privacy-preserving and secure authentication based on Elliptic Curve Qu–Vanstone (ECQV) for a V2V-charging system that fulfils the essential requirements and re-authentication protocol in order to reduce the overhead of future authentication processes. The proposed scheme utilizes the ECQV implicit-certificate mechanism to create credentials and authenticate EVs. The proposed protocols provide efficient security and privacy to EVs, as well as an 88% reduction in computational time through re-authentication, as compared to earlier efforts.

The analysis of the nonproductive time when drilling wells is conducted in the paper. it is established that the most of it is associated with the accidents and complications, with the main share (60%)-seizures. The statistical analysis of the reasons for the occurrence of seizures and the effectiveness of methods for their elimination is presented. A drill string disconnector (RBC) developed at the Tyumen Industrial University is proposed for unscrewing drill pipes and freeing them from trapped pipes. Keywords: well; drill pipes; accidents; seizure; drilling tool; drill string break.

The near-globally distributed ecto-parasitic mite of theApis melliferahoneybee,Varroa destructor,has formed a lethal association with Deformed wing virus, a once rare and benign RNA virus. In concert, the two have killed millions of wild and managed colonies, particularly across the Northern Hemisphere, forcing the need for regular acaricide application to ensure colony survival. However, despite the short association (in evolutionary terms), a small but increasing number ofA. melliferapopulations across the globe have been surviving many years without any mite control methods. This long-term survival, orVarroaresistance, is consistently associated with the same suite of traits (recapping, brood removal and reduced mite reproduction) irrespective of location. Here we conduct an analysis of data extracted from 60 papers to illustrate how these traits connect together to explain decades of mite resistance data. We have potentially a unified understanding of naturalVarroaresistance that will help the global industry achieve widespread miticide-free beekeeping and indicate how different honeybee populations across four continents have resolved a recent threat using the same suite of behaviours.

The Internet of Things (IoT) is composed of wireless embedded devices which sense, analyze and communicate the state of the physical world. To achieve truly wireless operation, today’s IoT devices largely depend on batteries for power. However, this leads to high maintenance costs due to battery replacement, or the environmentally damaging concept of disposable devices. Energy harvesting has emerged as a promising approach to delivering long-life, environmentally friendly IoT device operation. However, with the exception of solar harvesting, it remains difficult to ensure sustainable system operation using environmental power alone. This paper tackles this problem by contributing Static, a Radio Frequency (RF) energy harvesting and wireless power transfer platform. Our approach comprises autonomous energy management techniques, adaptive power transfer algorithms and an open-source hardware reference platform to enable further research. We evaluate Static in laboratory conditions and show that 1) ambient RF energy harvesting can deliver sustainable operation using common industrial sources, while 2) wireless power transfer provides a simple means to power motes at a range of up to 3 m through a variety of media.

Розмір пояснювальної записки – 103 аркуші, містить 25 ілюстрацій, 36 таблиць, 7 додатків. Актуальність теми. У роботі розглянуто проблему в галузі 3D моделювання для реконструкції зображень реального світу, показано основні особливості існуючих рішень проблеми реконструкції зображень, їх переваги та недоліки. Виявлено проблему в удосконаленні методів реконструкції зображень для отримання кращої якості утворених моделей, їх текстур, а також швидкості роботи алгоритмів для забезпечення можливості виконання реконструкцій в реальному часі. Метою цієї роботи є підвищення якості результуючої моделі об’єкту на основі нового алгоритму для перетворення 2D зображень в 3D моделі, прискорення алгоритму реконструкції 3D моделей на основі 2D зображень для забезпечення можливості відтворення в реальному часі з мінімальними втратами якості та покращення методів накладання текстур на 3D об’єкти для отримання кращої якості моделей та їх відповідність реальним об’єктам. Для досягнення мети необхідно виконати наступні завдання: - виконати аналіз основних методів перетворення 2D зображень в 3D моделі; - здійснити порівняльний аналіз зазначених методів; - розробити алгоритми перетворення 2D зображень в 3D моделі з високою швидкістю та якістю; - розробити алгоритми накладення текстур для моделей з високою якістю; - розробити програмне забезпечення, що реалізовуватиме розроблені алгоритми; - виконати аналіз результатів роботи створеного програмного забезпечення. Об’єкт дослідження – програмне забезпечення, що використовується для побудови тривимірних об’єктів. Предмет дослідження – Моделі, алгоритми та методи для обробки зображень та відеопотоків. Методи дослідження, застосовані в даній роботі базуються на підходах комп’ютерного зору, комп’ютерної графіки та машинного навчання. Наукова новизна одержаних результатів: запропоновано новий алгоритм, що утворений як комбінації алгоритмів виконання перетворення 2D зображень в 3D моделі. В результаті, алгоритм дозволяє отримувати моделі без видимих візуальних дефектів, що мають високий рівень схожості з реальним об’єктом. Практичне значення одержаних результатів: розроблений алгоритм та програмне забезпечення з підтримкою високої якості моделей дозволяє швидко генерувати 3D моделі порівняно з задіянням 3D дизайнерів в разі виникнення необхідності в генерації великого обсягу 3D моделей. Розроблений алгоритм та програмне забезпечення з підтримкою генерації моделей з високою швидкістю уможливлює ряд задач, таких як: відеорепортажі, VR конференції та інші. Зв'язок роботи з науковими програмами, планами, темами. Робота виконувалась на кафедрі інформатики та програмної інженерії Національного технічного університету України «Київський політехнічний інститут ім. Ігоря Сікорського» згідно з планом науково-дослідницьких робіт кафедри інформатики та програмної інженерії. Апробація. Наукові положення дисертації пройшли апробацію на Першій Всеукраїнській науково-практичній конференції молодих вчених та студентів «Інженерія програмного забезпечення і передові інформаційні технології» (SoftTech- 2021) – м. Київ. Публікації. Наукові положення дисертації опубліковані в: Линник В.В. Практичне застосування методу генерації текстур об’єктів в розрізі задачі тривимірної реконструкції/ В.В.Линник, О.П. Сирота // Матеріали першої всеукраїнської науково-практичної конференції молодих вчених та студентів «Інженерія програмного забезпечення і передові інформаційні технології» (SoftTech- 2021) – м. Київ: НТУУ «КПІ ім. Ігоря Сікорського», 22-26 листопада 2021 р. Explanatory note size – 103 pages, contains 25 illustrations, 36 tables, 7 applications. Topicality. Examines the problem of 3D modeling for the reconstruction of realworld images, shows the main features of existing solutions to the problem of image reconstruction, their advantages and disadvantages. The problem in improving the methods of image reconstruction to obtain the best quality of the formed models, their textures, as well as the speed of the algorithms to ensure the possibility of performing reconstructions in real time. The aim of the study. The main target is improving the quality of the resulting object model based on a new algorithm for converting 2D images to 3D models, accelerating the algorithm for reconstructing 3D models based on 2D images to provide real-time playback with minimal quality loss and improving methods of applying textures to 3D objects for obtaining the best quality models and their compliance with real objects. To achieve this goal, you must perform the following tasks: - perform an analysis of the main methods of converting 2D images into 3D models; - carry out the comparative analysis of the specified methods; - develop algorithms for high-speed converting 2D images into 3D models; - develop algorithms for converting 2D images into 3D models with high quality; - develop algorithms for texturing models with high quality; - develop software that will implement the developed algorithms; - perform analysis of the results of the created software. The object of research is software used to build three-dimensional objects. Subjects of research are models, algorithms and methods for processing images and video streams. The research methods used in this paper are based on the approaches of computer vision, computer graphics and machine learning. 10 The scientific novelty of the results is a proposing of a new algorithm, which is formed as a combination of algorithms for converting 2D images into 3D models. As a result, the algorithm allows to obtain models without visible visual defects that have a high level of similarity to real objects. The practical significance of the obtained results. The developed algorithm and software support high quality models and allows to quickly generate 3D models comparing to the use of 3D designers in case when a large volume of 3D models needs to be generated. The developed algorithm and software for high-speed model generation enables a number of tasks, such as: video reporting, VR conferencing etc. Relationship with working with scientific programs, plans, topics. The work was performed at the Department of Informatics and Software Engineering of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" according to the research works plan of informatics and software engineering department. Approbation. The scientific provisions of the dissertation were tested at the All- Ukrainian Scientific and Practical Conference of Young Scientists and Students “Software Engineering and Advanced Information Technologies” (SoftTech-2021) - Kyiv. Publications. Lynnyk V.V. Practical application of the method of generating textures of objects in the context of the problem of three-dimensional reconstruction / V.V. Lynnyk, O.P. Syrota // Proceedings of the All-Ukrainian Scientific and Practical Conference of Young Scientists and Students “Software Engineering and Advanced Information Technologies” (SoftTech-2021) - Kyiv: NTUU “KPI them. Igor Sikorsky”, November 22- 26, 2021.

Hadi Putra, No. BP. 1920842004, Evaluasi Kebijakan Pendirian Badan Usaha Milik Daerah PT. Balairung Citrajaya Sumbar, Program Magister Administrasi Publik, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Andalas, Padang, 2021. Dibimbing oleh: Dr. Hendri Koeswara, S.IP., M.Soc.Sc.dan Dr. Syamsurizaldi, S.IP., S.E., M.M. Tesis ini terdiri dari 169Halaman,34buku teori,7buku metode,1 Disertasi, 3 Tesis, 18Artikel Jurnal/Karya Ilmiah,2 Undang-undang, 1 Peraturan Pemerintah, 3 Peraturan Daerah, 1 Laporan, 2dokumen, dan7website internet. Evaluasi kebijakan merupakan bagian dari siklus kebijakan yang memiliki peran penting untuk menilai keberhasilan sebuah kebijakan. Salah satu bentuk kebijakan publik pemerintah daerah yaitu kebijakan Pendirian Badan Usaha Milik Daerah. Tujuan penelitian ini adalah mengevaluasi kebijakan Pendirian Badan Usaha Milik Daerah PT. Balairung Citrajaya Sumbar milik Provinsi Sumatera Barat yang menuai banyak sorotan.Teori yang digunakan adalah tipe evaluasi efektifitas dan evaluasi efisiensi oleh Althaus, Brigman & Davis dengan indikator evaluasi yaitu: input, proses, output, dan outcome. Pendekatan yang digunakan yaitu deskriptif kualitatif dengan pengumpulan data melalui telaah dokumen, observasi, dan wawancara dengan menggunakan teknik purposive sampling. Analisis data dengan cara reduksi data, pemodelan/display data, dan penarikan/verifikasi kesimpulan. Validitas data menggunakan triangulasi sumber. Hasil penelitian menunjukkan bahwa kebijakan pendirian PT. Balairung Citrajaya Sumbar belum efektif dan tidak efisien berdasarkan;(1) Pada input kebijakan terdapat komponen utama yang tidak disediakan yaitu feasibility study, sumber daya manusia sudah memadai, sumberdaya keuangan belum sepenuhnya diterima dari beberapa kabupaten/kota sesuai perjanjian kerjasama pendirian PT.BCS.(2) Proses kebijakan sudah mencapai sasaran yaitu terbentuk dan beroperasinya PT. BCS. Implementor kebijakan sudah menjalankan peran sesuai fungsi masing-masing. Namun belum efektif dalam pencapaian tujuan serta tidak efisien dalam mengelola input menjadi output,(3) Output kebijakan sudah diterima berupa deviden, namun belum bisa secara kontiniu danrasionya masih sangat kecil dibanding investasi yang dikeluarkan karena perusahaan selalu merugi akibat beban penyusutan aset tetap yang terlalu besar. (4) Outcome kebijakan sesuai tujuan formalnya belum signifikan karena kecilnya pendapatan daerah yang diterima dari BUMD ini. Dampak positif lainnya yaitu pada aspek sosial budaya Hotel Balairung menjadi iconkebanggaan dan meeting point masyarakat Sumatera Barat di Jakarta. Sedangkan dampak negatifnya antara lain image Pemerintah Provinsi Sumatera Barat yang tidak mampu mengelola PT.BCS dengan baik dan berkurangnya fungsi Balairung sebagai tempat bernaungnya orang Minang di Jakarta. Selain itu juga penambahan beban APBD untuk sewa kantor Badan Penghubung Provinsi Sumatera Barat di Jakarta. Kata Kunci : Evaluasi Kebijakan, BUMD, PT.Balairung Citrajaya Sumbar

The transmit error vector magnitude (EVM) performance measurements of a slant-polarized 28 GHz gapwaveguidebased phased array is analyzed in this paper. The performance is studied by using a large range of signals, with varied powers, symbol rates, and quadrature amplitude modulation (QAM) orders. The measurements have been conducted for four different scanning angles. A non-standardized over-the-air (OTA) link between the phased array and the receiver in a laboratory environment is used. The results show that the phased array antenna supports a 31 dB effective isotropic radiated power (EIRP) dynamic range at a maximum 2% EVM when transmitting a 64QAMmodulated signal with 250 MS/s symbol rate at all scanning directions.

This paper deals with the spread of diseases over both a population network and an infrastructure network. We develop a layered networked spread model for a susceptible-infected-susceptible (SIS) pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-water-susceptible (SIWS) model. The SIWS network is in the healthy state (also referred to as the disease-free equilibrium) if none of the individuals in the population are infected nor is the infrastructure network contaminated; otherwise, we say that the network is in the endemic state (also referred to as the endemic equilibrium). First, we establish sufficient conditions for local exponential stability and global asymptotic stability (GAS) of the healthy state. Second, we provide sufficient conditions for existence, uniqueness, and GAS of the endemic state. Building off of these results, we provide a necessary, and sufficient, condition for the healthy state to be the unique equilibrium of our model. Third, we show that the endemic equilibrium of the SIWS model is worse than that of the networked SIS model without any infrastructure network, in the sense that at least one subpopulation has strictly larger infection proportion at the endemic equilibrium in the former model than that in the latter. Fourth, we study an observability problem, and, assuming that the measurements of the sickness-levels of the human contact network are available, provide a necessary and sufficient condition for estimation of the pathogen levels in the infrastructure network. Furthermore, we provide another sufficient, but not necessary, condition for estimation of pathogen levels in the infrastructure network.

It is found that nodes in Delay Tolerant Networks (DTN) exhibit stable social attributes similar to those of people. In this paper, an adaptive routing algorithm based on Relation Tree (AR-RT) for DTN is proposed. Each node constructs its own Relation Tree based on the historical encounter frequency, and will adopt different forwarding strategies based on the Relation Tree in the forwarding phase, so as to achieve more targeted forwarding. To further improve the scalability of the algorithm, the source node dynamically controls the initial maximum number of message copies according to its own cache occupancy, which enables the node to make negative feedback to network environment changes. Simulation results show that the AR-RT algorithm proposed in this paper has significant advantages over existing routing algorithms in terms of average delay, average hop count, and message delivery rate.

This paper deals with the use of social networks in agricultural enterprises and focuses mainly on their role and share in increasing the competitiveness of agricultural enterprises in the market. Primary data were obtained from an extensive survey of the development of information and communication technologies in agricultural enterprises, which was conducted in the first quarter of 2021 throughout the Czech Republic (“Survey 2021”). The research was primarily focused on capturing current trends in the use of ICT with emphasis on selected key areas (broadband, social networks, communication tools, regional Internet portals, used hardware categories, used software, mobile communications, Internet of Things, data storage and security, social networks, etc.). This survey builds on previous extensive surveys conducted by the Department of Information Technologies, Faculty of Electrical Engineering, CULS in Prague in several phases since 1999, with the last stage being conducted in 2017. Some surveys were conducted in cooperation with the Ministry of Agriculture of Czech Republic.Compared to recent years, the survey includes new domains, such as the use of the Internet of Things in plant and animal production, data storage and security, the impact of the Covid-19 pandemic on the company's core operations, etc. The survey was prepared, conducted and administered by the Department of Information Technology, Faculty of Economics and Management, University of Life Sciences Prague.

This paper addresses an action that, from a Deleuzian perspective, is capable of modifying the despairing current social situation in which we are immersed, through the creation of political Ideas. Even though Deleuze conceives social Ideas as vast civilizing structures, we propose to bring into the political domain the logic of other acts of creation, such as the artistic or the philosophical, where the monumental coexists with minor figures that are nonetheless capable of introducing novelty into the world. The politician is the figure of those who are capable of having an Idea that allows to break the habits that perpetuate the current situation, and gives consistency to the intensive forms of life that continually create and dissolve themselves in the flow of becoming. Thus, macro- and micro-politics do not oppose each other, but offer in their immanence an alternative to social nihilism.

INTRODUCTION: Vaccination has significantly reduced morbidity and mortality resulting from rotavirus infection worldwide. However, rotavirus vaccine efficacy (VE) appears to wane over the first 2 years since vaccination, particularly in developing countries. Statistical methods for detecting VE waning and estimating its rate have been used in a few studies, but comparisons of methods for evaluating VE waning have not yet been performed. In this work we present and compare three methods – Durham’s method, Tian’s method, and time-dependent covariate (TDC) method – based on generalizations of the Cox proportional hazard model. METHODS: We developed a new stochastic agent-based simulation model to generate data from a hypothetical rotavirus vaccine trial where the protective efficacy of the vaccine may vary over time. Input parameters to the simulation model were obtained from studies on rotavirus infections in four developing countries. We applied each of the methods to four simulated datasets and compared the type-1 error probabilities and the powers of the resulting statistical tests. We also compared estimated and true values of VE over time. RESULTS: Durham’s method had the highest power of detecting true VE waning of the three methods. This method also provided quite accurate estimates of VE in each period and of the per-period drop in VE. CONCLUSIONS: Durham’s method is somewhat more powerful than the other two Cox proportional hazards model-based methods for detecting VE waning and provides more information about the temporal behavior of VE.

In this paper, we consider user selection and downlink precoding for an over-loaded single-cell massive multiple-input multiple-output (MIMO) system in frequency division duplexing (FDD) mode, where the base station is equipped with a dual-polarized uniform planar array (DP-UPA) and serves a large number of single-antenna users. Due to the absence of uplink-downlink channel reciprocity and the high-dimensionality of channel matrices, it is extremely challenging to design downlink precoders using closed-loop channel probing and feedback with limited spectrum resource. To address these issues, a novel methodology -- active channel sparsification (ACS) -- has been proposed recently in the literature for uniform linear array (ULA) to design sparsifying precoders, which boosts spectral efficiency for multi-user downlink transmission with substantially reduced channel feedback overhead. Pushing forward this line of research, we aim to facilitate the potential deployment of ACS in practical FDD massive MIMO systems, by extending it from ULA to DP-UPA with explicit user selection and making the current ACS implementation simplified. To this end, by leveraging Toeplitz structure of channel covariance matrices, we extend the original ACS using scale-weight bipartite graph representation to the matrix-weight counterpart. Building upon this, we propose a multi-dimensional ACS (MD-ACS) method, which is a generalization of original ACS formulation and is more suitable for DP-UPA antenna configurations. The nonlinear integer program formulation of MD-ACS can be classified as a generalized multi-assignment problem (GMAP), for which we propose a simple yet efficient greedy algorithm to solve it. Simulation results demonstrate the performance improvement of the proposed MD-ACS with greedy algorithm over the state-of-the-art methods based on the QuaDRiGa channel models.

In 2019, the National Archives of Korea (NAK) developed a blockchain recordkeeping platform to conduct R&amp, D on recordkeeping approaches. This paper introduces two types of R&amp, D studies that have been conducted thus far. The first is the use of blockchain transaction audit trail technology to ensure the authenticity of audiovisual archives, i.e., the application of blockchain to a new system. The second uses blockchain technology to verify whether the datasets of numerous information systems built by government agencies are managed without forgery or tampering, i.e., the application of blockchain to an existing system. Government work environments globally are rapidly shifting from paper records to digital. However, the traditional recordkeeping methodology has not adequately kept up with these digital changes. Despite the importance of responding to digital changes by incorporating innovative technologies such as blockchain in recordkeeping practices, it is not easy for most archives to invest funds in experiments on future technologies. Owing to the Korean government’s policy of investing in digital transformation, NAK’s blockchain recordkeeping platform has been developed, and several R&amp, D tasks are underway. Hopefully, the findings of this study will be shared with archivists around the world who are focusing on the future of recordkeeping.

This paper seeks to examine the concept of “Merdeka Belajar” or “Freedom of Learning” which was initiated by the Indonesian Minister of Education and Culture, Nadiem Makarim. The study of freedom of learning uses text study with content analysis method. The concept of “Freedom of Learning” is very interesting when studied with a multicultural education perspective. Moreover, the two concepts have the same relevance and spirit, namely freedom and justice in the human resources development context, particularly through the educational process. Based on the results, the implementation of “MerdekaBelajar” program so far includes four aspects, namely financing, teachers / educators, assessment, and graduates. In a multicultural perspective, problems in management and assessment aspects basically caused by a misunderstanding of the meaning of standards and standardization. Meanwhile, the teacher and graduate aspects lie in the importance of developing multicultural competencies.Integrating a multicultural education perspective in the “Freedom of Learning” policy also transforms an education system that is creative, innovative, and character.

This paper is a revised abundance analysis of four yellow supergiant stars Cepheids which are located in the Galactic nucleus. The results are based on the spectra secured with the help of Subaru telescope, which are of the better quality comparing to previously analysed spectra taken with the Infrared Telescope Facility. A significantly improved method of the effective temperature determination of program stars, which is based on the calibrating relations between the temperature and line depth ratios, was applied. The present results confirmed our previous finding about the solar metallicity level at the Galaxy centre. It is very likely that the four stars of our program were born from an interstellar medium having homogeneous chemical properties, since all the stars are located close to each other, have close pulsation periods, and hence the age. However, one of the stars has a somewhat increased abundance of all studied elements compared to the abundance in the other three stars. A possible reason of this fact is discussed.

Objective: To propose a deep-learning network for the diagnosis of two corneal diseases: Fuchs’ endothlelial dystrophy and keratoconus, based on optical coherence tomography (OCT) images of the cornea. Methods: In this paper, we propose a novel network with parallel resolution-specific encoders and composite classification features to directly diagnose Fuchs’ endothelial dystrophy and keratoconus using OCT images. Our proposed network consists of a multi-resolution input, multiple parallel encoders, and a composite of convolutional and dense features for classification. The purpose of using parallel resolution-specific encoders is to perform multi-resolution feature fusion. Also, using composite classification features enhances the dense feature learning. We implemented other related networks for comparison with our network and performed k-fold cross-validation on a dataset of 16,721 OCT images. We used saliency maps and sensitivity analysis to visualize our proposed network. Results: The proposed network outperformed other networks with an image classification accuracy of 0.91 and a scan classification accuracy of 0.94. The visualizations show that our network learned better features than other networks. Significance: The proposed methods can potentially be a step towards the early diagnosis of corneal diseases, which is necessary to prevent their progression, hence, prevent loss of vision.

Shield construction will cause the fluidization of soft soil which is characterized by flow plasticity. This paper presents two theoretical models of soil flow behavior based on a fluid mechanics framework to understand the behavior of soft soil during shield tunneling, especially under the shearing action of the shield skin and the cutting wheel. The characteristics of the flow field are discussed, and their relationships with shield construction parameters such as advancing speed, cutting wheel rotation, applied thrust and torque, and water content are analyzed, while the proposed theory is verified by the results of a numerical simulation. Considering the shear-thinning effect of the soil, a closed four-stage shear path to describe the complete process of the soil behavior during shield tunneling is further interpreted. The results indicate that the sheared region produced by the rotating cutting wheel was larger than that produced by the shield shell shearing and that it was significantly affected by soil properties and tunneling parameters. In addition, it is concluded that the sheared region was significantly expanded due to the shear-thinning effect.

Background: The term "outpatient surgery" has become a common procedure in most hospitals around the world. On other hand, Spinal aesthesia can mimic the outcome sought by the principle of outpatient surgeries since it takes a short time to recover and limits the need for post-operative pain medication Therefore, the objective of this study is to focus on finding a method to reduce the side effects that commonly accompany the procedure of spinal aesthesia and to avoid the possible hemodynamic changes that may occur. Methods: The method for the study will be a narrative review of various medical journals, conferences papers, and unpublished documents using the dual keywords, outpatient surgeries spinal aesthesia, and ambulatory aesthesia, we include in this research thirty-one original articles, fifty-three reviews articles, two books, three handbooks, and two guidelines searched in the deferent database (google scholar, Research gate, pub med, science direct). Results: Consideration should be given to the quality of patients who participate in outpatient concepts. Finally, in terms of cost, side effects, and patient satisfaction, the spinal aesthetic approach gives a favourable outcome since it covers post-operative time without the need for analgesia and reduces the percentage of postoperative nausea and vomiting, and reduces the time staying in the hospital. Conclusions: In conclusion, the study discovered that a major proportion of surgeries performed over our lifetimes are outpatient procedures. Therefore, Discharge criteria should be posed with one precise criterion. There is no standard protocol to serve these types of surgeries and patients. The only criteria found and practiced served general conditions for outpatients and inpatients. There have been several attempts to create a protocol that can meet the pleasing outcome of outpatient surgeries. Consequently, we need more research to cover this lack and serve the Genuine needs of a protocol to define the criteria and categories that concern the term outpatient and outpatient surgeries and lead to improving the quality of outpatient surgeries with fewer side effects and minimum hemodynamic changes.

The optimization of cutter shape has become one of the main innovation direction of PDC bit technology. At present, both domestic and foreign bit manufacturers have put forward various special shaped cutters to improve rock breaking efficiency. However, there are relatively few researches which focus on the rock breaking efficiency of special-shaped cutters. Therefore, three kinds of typical cutters (flat cutter, convex cutter and concave cutter) are selected as the study object in this paper. Based on the single cutter test, the relationship of axial cutting force, cutting area and cutting specific energy under different working conditions will be provided. The experimental results show that the axial cutting force and specific energy of concave cutter and convex cutter are lower than that of flat cutter in most test cases. The results are almost the same for both Vosges sandstone and Marcellus shale cases. In other words, the tested concave cutters are easier to intrude into rock and obtain higher rock brea king efficiency under the same cutting conditions, when compared with flat cutter and convex cutter. The experimental method provides a technica l reference for studying the rock breaking efficiency of three-dimensional cutters with different shapes.

Localization and mapping are key capabilities for self-driving vehicles. This paper describes a visual-inertial SLAM system that estimates an accurate and globally consistent trajectory of the vehicle and reconstructs a dense model of the free space surrounding the car. Towards this goal, we build on Kimera and extend it to use multiple cameras as well as external (e.g. wheel) odometry sensors, to obtain accurate and robust odometry estimates in real-world problems. Additionally, we propose an effective scheme for closing loops that circumvents the drawbacks of common alternatives based on the Perspective-n-Point method and also works with a single monocular camera. Finally, we develop a method for dense 3D mapping of the free space that combines a segmentation network for free-space detection with a homography-based dense mapping technique. We test our system on photo-realistic simulations and on several real datasets collected by a car prototype developed by the Ford Motor Company, spanning both indoor and outdoor parking scenarios. Our multi-camera system is shown to outperform state-of-the art open-source visual-inertial-SLAM pipelines (Vins-Fusion, ORB-SLAM3), and exhibits an average trajectory error under 1% of the trajectory length across more than 8 km of distance traveled (combined across all datasets). A video showcasing the system is available here: youtu.be/H8CpzDpXOI8

Neural Cryptography is a new thread that integrates cryptography and neural networks for cryptanalysis and encryption applications. We show that Neural Networks can execute symmetric encryption in an adversarial context in this paper, and we build on the existing literature on the subject. Cryptography's purpose is to make it difficult to decipher a cypher and recreate the plain text without the associated key. Your messages are encrypted with excellent cryptography in such a way that brute force attacks against the algorithm or key are nearly impossible. Good cryptography is secure because it employs extremely long keys and encryption techniques that are resistant to various types of attack. The neural net application is the next step in the evolution of good cryptography. This paper discusses the use of neural networks in cryptography, including how to create neural networks that can be utilized in cryptography. Keywords: Cryptography key, encryption system, encryption algorithm, artificial neural network,chaos maps, logistic encryption.

Introduction In the past decade there has been an increasing interest in the field of patient-reported outcome measures (PROMs) which are now commonly used alongside traditional outcome measures, such as morbidity and mortality. Since the FACE-Q Aesthetic development in 2010, it has been widely used in clinical practice and research, measuring the quality of life and patient satisfaction. It quantifies the impact and change across different aspects of cosmetic facial surgery and minimally invasive treatments. We review how researchers have utilized the FACE-Q Aesthetic module to date, and aim to understand better whether and how it has enhanced our understanding and practice of aesthetic facial procedures. Methods We performed a systematic search of the literature. Publications that used the FACE-Q Aesthetic module to evaluate patient outcomes were included. Publications about the development of PROMs or modifications of the FACE-Q Aesthetic, translation or validation studies of the FACE-Q Aesthetic scales, papers not published in English, reviews, comments/discussions, or letters to the editor were excluded. Results Our search produced 1189 different articles; 70 remained after applying in- and exclusion criteria. Significant findings and associations were further explored. The need for evidence-based patient-reported outcome caused a growing uptake of the FACE-Q Aesthetic in cosmetic surgery and dermatology an increasing amount of evidence concerning facelift surgery, botulinum toxin, rhinoplasty, soft tissue fillers, scar treatments, and experimental areas. Discussion The FACE-Q Aesthetic has been used to contribute substantial evidence about the outcome from the patient perspective in cosmetic facial surgery and minimally invasive treatments. The FACE-Q Aesthetic holds great potential to improve quality of care and may fundamentally change the way we measure success in plastic surgery and dermatology. Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.