Correct Priority Research Articles

Optimal tactics of ovarian and metachronous breast cancer treatment in <i>BRCA</i> mutations carriers

Treatment of patients with multiple primary malignant neoplasms caused by genetic mutations requires correct priorities from the clinician in selection of the most effective therapeutic tactics. An important aspect in this case is the identification of the neoplasm determining patient’s survival. The main goal is to achieve maximal treatment effect for this tumor and use therapy methods for control of other synchronous and metachronous tumors.The article presents a clinical case of a patient with BRCA1 mutation-associated recurrent ovarian cancer and de novo breast cancer of negative subtype. Combination multidisciplinary and personalized approach to treatment which led to the maximally effective result is described. Personalized approach to prescription of antitumor drug therapy, timing of surgical intervention and subsequent targeted therapy allowed to realize maximal antitumor effect and increase the patient’s lifespan.

SLIT: Achieving Fast Bandwidth Isolation Across Virtual Machines

Network performance guarantee in the cloud is one of the hottest research topics recently. However, current approaches either lack scalability or fail to achieve high performance. To avoid the hard tradeoff between the scalability and performance, we adopt a hybrid approach to get the best of both worlds. In this paper, we follow the stateless design principle and propose SLIT, which provides fast VM-level network performance isolation and maintains core-stateless characteristics. Specifically, at the end host, we develop a novel network-adaptive labeling mechanism and it computes the correct scheduling priority for each hop. At the switch, packets are scheduled based on their labels and we develop a novel straggler detection algorithm to find the new incoming flow. Our evaluation results show that SLIT can approximate the optimal performance of Weighted Fair Queuing (WFQ) effectively.

Application of data mining techniques for VAT-Registered Business compliance

World Bank recommends that Indonesia lower the turnover threshold required to be a VAT-Registered Business from Rp. 4,8 billion to Rp. 600 million to increase VAT-Registered Businesses numbers which will also increase VAT revenue. The number of VAT-Registered Businesses will be significantly increased, which will push Directorate General of Taxes to determine the correct audit priority because it is impossible to audit all taxpayers. This study aims to form a prediction model for formal compliance of VAT-Registered Businesses in the Sampit Tax Office towards 1270 VAT-registered Businesses as of December 31, 2019, which are classified as low-risk VAT-Registered Businesses. The prediction model will be useful for determining audit priorities for certain taxpayers. This study uses a qualitative method using the RapidMiner application and decision tree technique in making prediction models for VAT-Registered Business compliance. The model made has Prediction Efficiency of 67,9%, reduction in Examination Effort by 63.67%, and Strike Rate of 85.99%. The model made is used to predict new VAT-Registered Business data which registered in 2020 and predicts 76 VAT-Registered Businesses will be compliant and 7 VAT-Registered Businesses will not be compliant

ANALYZING PRIORITY VECTORS: GOING BEYOND INCONSISTENCY INDEXES

A great concern when utilizing the Analytic Hierarchy Process (AHP) is how the final priority vector, resulting from the inconsistent analysis, behaves when compared with the original priority ranking, resulting from the consistent analysis. The AHP utilizes an inconsistency index to predict rank reversal. In addition to the original inconsistency index of the AHP, several authors have worked on developing alternative inconsistency indexes, with the goal of improving the predictability of rank reversal. However, inconsistency indexes do not help clarify whether a rank reversal is a rejectable outcome or, to some extent, the correct answer. A rank reversal may express the correct priority, particularly when some positions in the original priority rank have small weight differences among them. Therefore, it is very important to develop a method to allow a clear and definitive analysis on how disturbed the weights and ranking of the final priority vectors are when compared to their original consistent rankings. Such a method is developed here and its utilization is demonstrated by analyzing a corporate governance scenario.

Prioritizing risk factors in sustainable supply chain using fuzzy Kano and interval-valued intuitionistic fuzzy QFD

PurposeThe purpose of the paper is to develop a hybrid method to prioritize risk factors (RFs) of sustainable supply chain (SSC) considering sustainable customer requirements (CRs) and uncertain evaluation.Design/methodology/approachIn the proposed method, fuzzy Kano model (FKM) is applied to prioritize sustainable CRs considering customer satisfaction (CS) and objective weight of each CR, the interval-valued intuitionistic fuzzy (IVIF) set theory is integrated with quality function deployment (QFD) to translate the sustainable CRs into RFs of SSC under uncertain environment and the IVIF cross-entropy is used to conduct objective analysis to prioritize RFs. Finally, a case in air-conditioner-manufacturing company is presented to demonstrate the proposed method.FindingsA case study of SSC risk management, the comparative analysis and associated discussions are conducted to illustrate the feasibility and effectiveness of the proposed method. The results obtained from the case study shows that RF5 (market share reduction) is the most important RF in the SSC. Compared with the existing methods, the proposed method can integrate sustainable CRs into SSC's RFs, handle uncertain information effectively and obtain objective importance of RFs.Originality/valueTheoretically, the paper develops a customer-oriented model based on the FKM, QFD, IVIF sets and entropy theory to prioritize RFs of SSC under uncertain environment. The model enables to integrate sustainable CRs into RFs managements and is efficient to deal with the subjectivity and conduct objective analysis to prioritize RFs. In practice, the systematic and correct RFs' priorities analysis provides reliable decision support for the managers to take measures to avoid or mitigate the critical RFs.

Vaccines for Travelers

When counselling travelers about the need, benefits and risks of travel vaccines, the following factors must be considered: Environmental factors, e.g., destination, duration of exposure (including expected cumulative life-time exposure), epidemiological situation, travel style (low budget associated with higher risk), travel purpose (visiting friends or relatives [VFR] - often results in higher risk) Host factors include e.g. age, origin (potential exposure at home vs. at destination, is there an incremental risk?), pre-existing illness, particularly immune suppression (e.g. HIV, medication), pregnancy, nursing A structured discussion about required, routine and recommended vaccinations is beneficial Required by destination country: yellow fever (special rules based on the International Health Regulations), meningococcal disease (Hajj), COVID-19 Routine: usual childhood / adolescence / adult / senior citizen vaccinations. Programs differ between countries. Some proof of vaccination may be required for schools mainly in North America. Recommended: depending on exposure to risk (incidence rate, also incremental risk compared to home country), impact of infection, cost of vaccines, etc. Essentials when protecting travelers against vaccine preventable diseases: Set correct priorities; base decisions on epidemiological evidence; consider contraindications Always state that No vaccine is 100% effective; All vaccines may have adverse reactions, rarely serious ones.

Optimal Pricing for Job Offloading in the MEC System With Two Priority Classes

Multi-Access edge computing (MEC) is an emerging paradigm where users offload computationally intensive jobs to the Access Point (AP). Given that the AP's resources are shared by selfish users, pricing is a useful tool for incentivising users to internalize the negative externality of delay they cause to other users. Nevertheless, different users have different negative valuations towards delay as some are more delay sensitive. To serve heterogeneous users, we propose a priority pricing scheme where users can get served first for a higher price. Our goal is to find the prices such that in decision making, users will choose the class and the offloading frequency that jointly maximize social welfare. With the assumption that the AP knows users' profit functions, we derive in semi-closed form the optimal prices. However in practice, the reporting of users's profit information incurs a large signalling overhead. Besides, in reality users might falsely report their private profit information. To overcome this, we further propose a partial-knowledge based pricing mechanism where no knowledge of individual user profit functions is required. At equilibrium, the optimal prices and average edge delays are learnt, and users have chosen the correct priority class and offload at the socially optimal frequency.

РЕКОМЕНДАЦІЇ ЩОДО ПРИЗНАЧЕННЯ ЗАВДАНЬ СТРІЛЬБИ АРТИЛЕРІЇ ДЛЯ УРАЖЕННЯ ВИСОКОМАНЕВРЕНИХ ЦІЛЕЙ

Analysis of armed conflicts in recent years shows the widespread use of highly maneuverable firearms, which are characterized by rapid movement during hostilities, frequent changes of position after the fire mission. The effectiveness of defeating a highly maneuverable target and performing a fire task depends on the correct choice and priority in assigning a particular artillery firing task. The main factors influencing the effectiveness of fire damage to highly maneuverable targets are: timeliness, accuracy, suddenness, obtaining complete and accurate data on the position, size and nature of targets, the correct choice of means of hitting the target, the purpose of the fire task and method of firing targets. The primary task of artillery units is to defeat highly maneuverable targets while they are in firing positions. This time is called the effective time to complete the fire task. The timeliness of hitting highly maneuverable targets can be assessed by the ratio of reaction time required to use the artillery unit in combination with additional reconnaissance means allocated for counterbattery combat, to hit the target with the set ammunition consumption and the probable time of target targeting after reconnaissance. The time spent by highly maneuverable targets at the position after their detection by reconnaissance means is random, distributed according to the law of equal probability and depends on the tactical and technical characteristics of weapons, time of fire task, terrain, season, time of day, etc., as well as at what point the target was identified. Fire on the target can be timely only if it is detected and the coordinates are transmitted to the fire units by the time it leaves its positions. When determining the degree of damage to highly maneuverable targets, it is necessary to take into account the probability of timely fire, ie all shells intended to hit the target, spent until the target left the position (out of range). To destroy the battery (platoon) of self-propelled armored guns at the firing position and the platoon of self-propelled armored SAM at the position, the task of firing is to prohibit action, even with the use of two artillery divisions. To defeat the battery (platoon) of MLRS and the battery (platoon) of self-propelled unarmored guns in the firing position, the task of one division is to suppress, and when two divisions are involved in firing on the battery (platoon) of MLRS – destruction. To defeat a platoon of self-propelled armored ATGMs at the deployment line, firing one division, firing task is a ban on action, and if at least two divisions are involved - there may be suppression. Keywords: firing tasks, highly maneuverable targets, effective time, effectiveness of fire damage.

Transformation of law in the context of digitalization: defining the correct priorities

The subject under analysis is the peculiarities around the legal regulation of digital technologies and products arising from digital technologies. The choice of this topic was predetermined by the active development of digital services and digital financial assets, and the necessity to adapt modern legislation to the needs of the digital economy. Despite the fact that several strategies for the development of digital law are being worked out at the level of international organizations, neither in theory nor in practice is there a single understanding of the legal nature of digital technologies and the foundations of their legal regulation.From this perspective, the purpose of this article is to understand the system and the main categories of the digital economy through the prism of fundamental legal institutions, based both on the traditional principles of scientific analysis and on the results steaming from applied data processing methods.Using methods of theoretical modeling, idealization, and theoretical experiments, the authors consider the categories of legal personality, security, and tort of digital technologies and products, compare them with similar legal institutions, and determine possible options for integrating new legal categories into traditional rule of law on contracts, liability, and the protection of intellectual rights.As a result of the study, the authors have assembled their vision of those benchmarks, on which international strategies for regulating the digital economy should be built. The authors proceed from the fact that the adaptive capabilities of traditional law are very limited in relation to digital technologies; furthermore, in relation to many of them, qualitatively new legal models should be developed. The article presents the results of a review of the main legal parameters of digital technologies. Formulations of legal personality and protection are proposed, definitions of digital technology products in civil and copyright law are formulated.The conclusion reached concerns the inconsistency of approaches to assessing the legal nature of digital objects, and the insufficient consideration of the technical aspects of digital technologies, as well as the need to develop — at the international level — a unified legal strategy for civil and intellectual law regarding digital technologies. This study underlines, among the priority tasks and directions, the issues of legal personality of digital technologies, and the essential mechanisms for the protection of products using digital technologies. The conclusions formulated in the article have important practical and methodological significance, and can be taken into account when reforming the current legislation.

Assessment of DSMs Using Backpack-Mounted Systems and Drone Techniques to Characterise Ancient Underground Cellars in the Duero Basin (Spain).

In this study, a backpack-mounted 3D mobile scanning system and a fixed-wing drone (UAV) have been used to register terrain data on the same space. The study area is part of the ancient underground cellars in the Duero Basin. The aim of this work is to characterise the state of the roofs of these wine cellars by obtaining digital surface models (DSM) using the previously mentioned systems to detect any possible cases of collapse, using four geomatic products obtained with these systems. The results obtained from the process offer sufficient quality to generate valid DSMs in the study area or in a similar area. One limitation of the DSMs generated by backpack MMS is that the outcome depends on the distance of the points to the axis of the track and on the irregularities in the terrain. Specific parameters have been studied, such as the measuring distance from the scanning point in the laser scanner, the angle of incidence with regard to the ground, the surface vegetation, and any irregularities in the terrain. The registration speed and the high definition of the terrain offered by these systems produce a model that can be used to select the correct conservation priorities for this unique space.

Determination of Risk Factors for Musculoskeletal Disorders and Corrective Priorities to Perform the Work in Dental Careers by Posture Analysis Using REBA in Shahrekord

Background and aims: Nowadays, work-related musculoskeletal disorders are the most common occupational diseases. The prevention of these disorders requires a posture analysis during work and the improvement of working conditions. The purpose of this study was to determine risk factors for musculoskeletal disorders and corrective priorities to perform the work by conducting postures analysis using Rapid Entire Body Assessment (REBA). Methods: In this descriptive-analytical study, the posture of dentists during working was analyzed using the REBA software. The incidence rate of musculoskeletal disorders was investigated by the Nordic Musculoskeletal Questionnaire (NMQ). A P value less than 0.05 was considered statistically significant. Results: In this applied study, the incidence rates of the pain in neck, waist, shoulders, and wrists were reported to be 68%, 55%, 41% and 28%, respectively. The above-mentioned values were higher in women than in men. The pain in thigh and leg was related to work and the pain in ankle and sole was related to body mass index (BMI). The relationship between musculoskeletal disorders and occupational postures of dentists was statistically significant (P<0.05). Conclusion: Training the principles of ergonomics and anthropometrics, the correct methods and principles of performing work, and the ways of using the instruments are necessary for the studied population. Occupational postures require ergonomic intervention and correction.

Developed watershed classification index determining management priority level based on watershed carrying capacity

Watershed classification index is important in terms of determining watershed management priority level based on its carrying capacity score whereby currently watershed is classified into two indexes which are “to be maintained” if the carrying capacity score is below 100 and “to be restored” if it is above 100. This index fails to capture existing condition where there are watersheds with carrying capacity score in between 90 and 110. The purpose of this paper is to propose developed watershed classification index to determine management priority level based on watershed carrying capacity score. The method used to develop the watershed classification index is Classification Interval approach. The analysis is resulting in rigorous management priority level based on developed watershed classification index which is 50 < carrying capacity ≤ 90 as Priority 3 (watershed indexed as “to be maintained”), 90 < carrying capacity ≤ 110 as Priority 2 (watershed indexed as “to be improved”) and 110 < carrying capacity ≤ 150 as Priority 1 (watershed indexed as “to be restored”). Therefore, the correct management priority level for Gangsa Watershed that has carrying capacity of 106 is Priority 2.

Brazilian Agriculture: Balancing Growth with the Need for Equality and Sustainability

SummaryBrazil's agricultural sector has grown rapidly over the past 20 years, but two reservations have been frequently expressed with respect to the country's development model. The first is that the benefits of agricultural growth have accrued principally to a narrow group of large‐scale commercial farmers, while smaller‐scale traditional farmers, and the rural economy more generally, have languished. A second concern relates to the environmental footprint of agricultural development, and in particular agriculture's contribution to the loss of rainforest. This article suggests that future growth can be reconciled with rapid poverty reduction and improved environmental sustainability. In order to sustain agricultural growth, policies need to support further innovation and tackle constraints that stem from the wider context in which the sector operates. Achieving that growth more equitably will require support for development pathways within and outside agriculture, with policies that take a more realistic view of which farmers have the potential to be economically viable. Improved environmental progress will mean putting ambitious legislation into practice. Government policies have identified the correct priorities, which need to be better reflected in the allocation of public funding.

Simulation platform for anticipative plant-level maintenance decision support system

Global competition and increasing customer expectations are forcing automobile manufacturers to improve their operations. Maintenance, being one of the most critical components in many industries, has a direct impact on the improvement of the overall production performance. In this paper, we introduce an anticipative plant-level maintenance decision support system (APMDSS) that provides guidance on corrective and preventive maintenance priorities based on the equipment bottleneck ranks with the objective of improving daily plant throughput. APMDSS anticipates the plant dynamics (i.e. bottlenecks, hourly buffer levels and likelihood of machine breakdowns) for upcoming shifts using starting state information of the production shift (e.g. equipment maintenance history, operational status of machines, buffer levels and scheduled production model mix). We also evaluate the performance of APMDSS using real data from an automotive body shop experiencing routine throughput difficulties due to frequent machine breakdowns. The results are compared with other methods from the literature and found to be superior in many settings.

Ethics of development assistance for health.

AbstractIn the past three decades, levels of and contributors to global health aid have increased at an unprecedented pace. Development assistance for health—financial contributions from public and private institutions to low‐ and middle‐income countries to help improve health and health systems—nearly quintupled from 1990 to 2012 (from $5.7 billion to $28.1 billion). DAH is now provided by more than one hundred seventy major global health agencies and organizations, 15 percent of which are private entities (such as the Bill and Melinda Gates Foundation), other not‐for‐profit organizations, and public‐private partnerships. Governments are still the largest source for DAH. While increased DAH is essential and welcome, these system developments raise numerous ethical questions. Are the resources sustainable, and do expenditures target correct priorities? Who should decide, and how should these decisions be made?.

A Comprehensive Implementation and Evaluation of Direct Interrupt Delivery

As the performance overhead associated with CPU and memory virtualization becomes largely negligible, research efforts are directed toward reducing the I/O virtualization overhead, which mainly comes from two sources: DMA set-up and payload copy, and interrupt delivery. The advent of SRIOV and MRIOV effectively reduces the DMA-related virtualization overhead to a minimum. Therefore, the last battleground for minimizing virtualization overhead is how to directly deliver every interrupt to its target VM without involving the hypervisor. This paper describes the design, implementation, and evaluation of a KVM-based direct interrupt delivery system called DID. DID delivers interrupts from SRIOV devices, virtual devices, and timers to their target VMs directly, completely avoiding VM exits. Moreover, DID does not require any modifications to the VM's operating system and preserves the correct priority among interrupts in all cases. We demonstrate that DID reduces the number of VM exits by a factor of 100 for I/O-intensive workloads, decreases the interrupt invocation latency by 80%, and improves the throughput of a VM running Memcached by a factor of 3.

Design and Development of an Agorithm for Prioritizing the Test Cases Using Neural Network as Classifier

Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Patient assessment: preparing for a predictable aesthetic outcome.

The flux of patients seeking to make changes to the appearance of their smile zone appears to be on a pathway of continual increase. This is possibly due to an increase in awareness towards oral health, and perhaps social, peer and media pressures, respectively. Cohorts of dental practitioners have thus responded to the latter demands by attending a plethora of educational courses, often focusing on either restorative techniques or other disciplines, notably orthodontics and clear aligners in particular. Consequently, treatment planning and thus treatment provision may carry the risk of being biased or indeed 'outcome driven' whereby the skills and knowledge of any clinician towards a particular faculty may significantly influence the ultimate treatment plan, with the unfortunate tendency sometimes to overlook the role of the interdisciplinary approach of concomitant restorative and contemporary techniques. The role of orthodontics to facilitate the provision of such treatment, along with predictable enamel bonding, has the distinct advantage of providing an acceptable aesthetic result with minimal biological intervention. However, to achieve an optimal result in such cases requires meticulous treatment planning and patient selection to avoid pitfalls with regards to long-term stability and function. This article suggests a standardized approach to patient assessment, with an interdisciplinary perspective in mind. Clinical Relevance: With the growth of patient demand for improving the appearance of the smile, a meticulous assessment protocol is required along with effective interdisciplinary communication. This enables a comprehensive treatment plan to be developed with the correct priorities.

Implementation of a triage score system in an emergency room in Timergara, Pakistan.

Following implementation of the South African Triage Scale (SATS) system in the emergency department (ED) at the District Headquarter Hospital in Timergara, Pakistan, we 1) describe the implementation process, and 2) report on how accurately emergency staff used the system. Of the 370 triage forms evaluated, 320 (86%) were completed without errors, resulting in the correct triage priority being assigned. Fifty completed forms displayed errors, but only 16 (4%) resulted in an incorrect triage priority being assigned. This experience shows that the SATS can be implemented successfully and used accurately by nurses in an ED in Pakistan.

Integral aided method for material selection based on quality function deployment and comprehensive VIKOR algorithm

In engineering design, the selection of material alternatives usually depends of different criteria based on the specific problem. Due to the different units of this criteria, a normalization process is needed in the selection model. A lot of normalization approach can be found in literature and at the same time many algorithms have been developed to ensure the optimal material selection for a certain industrial application. Two elements of reflection can be drawn from the analysis of these. The first is the absence of an aided support to the selection of the correct engineering criteria by whom operate the selection process. The second is the need to define a weighting method that at the same time can be user-friendly to use and representative of the project’s needs. A new selection model based on the integration between House of Quality and the Comprehensive Vikor Algorithm is presented in this paper. This approach, called Integral Aided Material Selection (IAMS), can overcome the main lack of traditional material selection model and provide a real support tool to the project team. That way the project team can optimally choose the selection criteria and assign to these the correct priority coherently with the project needs. A case study is presented to illustrate and justify the proposed method. The topic of the case study concerns the identification of the best coating for the protection of an aluminum alloy substrate (Al-7075) from the effects of abrasive wear against an alternating counterpart made by a high-strength cast iron.