Miracle-dz/UniFAR-FTUs huggingface dataset:
Birmingham A Survey and Taxonomy of Self-Aware and Self-Adaptive Cloud Autoscaling Systems

Autoscaling system can reconfigure cloud-based services and applications, through various configurations of cloud software and provisions of hardware resources, to adapt to the changing environment at runtime. Such a behavior offers the foundation for achieving elasticity in a modern cloud computing paradigm. Given the dynamic and uncertain nature of the shared cloud infrastructure, the cloud autoscaling system has been engineered as one of the most complex, sophisticated, and intelligent artifacts created by humans, aiming to achieve self-aware, self-adaptive, and dependable runtime scaling. Yet the existing Self-aware and Self-adaptive Cloud Autoscaling System (SSCAS) is not at a state where it can be reliably exploited in the cloud. In this article, we survey the state-of-the-art research studies on SSCAS and provide a comprehensive taxonomy for this field. We present detailed analysis of the results and provide insights on open challenges, as well as the promising directions that are worth investigated in the future work of this area of research. Our survey and taxonomy contribute to the fundamentals of engineering more intelligent autoscaling systems in the cloud.
Treatment of childhood adrenocortical carcinoma (ACC) with surgery plus retroperitoneal lymph node dissection (RPLND) and multiagent chemotherapy: Results of the Children’s Oncology Group ARAR0332 protocol.

10515Background: ACC is a rare pediatric malignancy with an aggressive clinical behavior and distinct biology. Treatment for this malignancy has followed the principles of management developed in adults; pediatric-specific studies are scarce. Methods: Study objectives were: 1) To describe the outcome of patients with stage I ACC treated with surgery only; 2) To describe the outcome of stage II patients (completely resected > 200 cc or > 100 g) treated with adrenalectomy and RPLND; and 3) To describe the outcome of patients with stage III/IV treated with mitotane and chemotherapy (eight cycles of cisplatin, etoposide, and doxorubicin). Results: Between 9/2006 and 5/2013, 78 patients (51 females) were enrolled. Stage IV patients were older (median age 13 y vs. 1.5, 2, and 3 y for stages I, II, and III, respectively, p < 0.0001) and presented with lower frequency of virilization (50% vs. 91.3%, 78.6%, and 70.8 for patients with stages I, II, or III, respectively, p = 0.05) and higher frequency of Cushing fea.
Prediction of 10 years risk of cardiovascular disease among adults aged 30-49 years residing in South Kolkata, West Bengal

Background: Cardiovascular disease (CVD) is a major cause of morbidity and mortality among 30-49 years i.e. 2nd and 3rd decade of adulthood who are vulnerable to utmost stress and strain of life. This study was conducted to predict the ten years risk of cardiovascular disease and calculate vascular age of adults aged 30-49 years.Methods: This community based, observational, cross-sectional study was done from August-October’17 among 182 individuals aged 30-49 years residing in South Kolkata, West Bengal. Data collection was done using a structured questionnaire along with B.P. measurement and lipid profile test. ‘Framingham heart study CVD risk calculator online version’ was used to calculate CVD risk and vascular age. Participants with known CVD, pregnancy were excluded from the study. Data was analyzed using SPSS software version 16.0 and descriptive statistics were employed to express results through appropriate tables and figures.Results: The mean ten years predicted CVD risk of the study subjects was 5.9%±5.3%, 63.7% participants had low risk of CVD and only 3.9% had high risk. CVD risk is well associated with increasing age, male gender, diabetes, hypertension, dyslipidemia and use of tobacco. The mean vascular age (46.5±6.1 years) was much higher than the actual mean biological age (39.1±15.0 years) of the participants. Almost 2/3rd of study subjects had more vascular age than their actual biological age.Conclusions: Further studies are required to prove the appropriateness of this online calculator and to establish vascular age as an alternate modality for prediction of CVD related events.
Study of Thyristor Controlled Series Capacitor (TCSC) as a useful FACTS Device

For transmission of large amounts of electric power, AC in the overwhelming majority of cases is the established as well as the most cost effective option at hand. In cases of long distance transmission, as in interconnection of power systems, care has to be taken for safeguarding of synchronism as well as stable system voltages in the interconnection, particularly for extreme load conditions and in conjunction with system faults. Use of Thyristor Controlled Series Capacitor (TCSC) as Flexible AC Transmission System (FACTS) device brings a number of benefits for the user of the grid, all contributing to an increase of the power transmission capability of new as well as existing transmission lines. These benefits include improvement in system stability, voltage regulation, reactive power balance, load sharing between parallel lines and reduction in transmission losses.
On Improving Handover Delay in Software-Defined Mobile Networks

The Software-Defined Networking (SDN) paradigm has become essential in tackling several issues and challenges in conventional networking, especially in mobile wireless networks. In order to realize the benefits brought by SDN to mobility management, we study the effects of SDN in conjunction with the OpenFlow protocol on the handover procedure. In this new setting, the completion of a handover procedure still requires the exchange of signaling messages between the control and data planes through OpenFlow channels, especially in the case of a hard handover, where the “breakage” in an on-going session is correlated to the exchange of management and reconfiguration messages. Consequently, the handover still suffers delay. One of the main causes of delay is the processing delay of those signaling messages. Three of the main factors contributing to the processing delay are the handling procedures, forwarding mechanisms of the network’s devices, and the load on controllers. Therefore, in this work, we target these three factors. First, we design an effective handling procedure of the exchange of signaling messages in the OpenFlow channels between the controllers and switches. Second, we provide a forwarding mechanism that is designed to reduce the number of switches involved in configurations of the data plane. Third, we propose a load balancing mechanism to mitigate the over-loading state that may cause longer delay periods. As for our first target, we provide an analytical model, which gave us the ability to model two handover-related OpenFlow messages. Following our analysis, we propose a novel solution to make handover more efficient and less interruptive. Furthermore, we study our solution in the Long Term Evolution (LTE) architecture. As for our second target, we take network heterogeneity into account, and accordingly, we provide an efficient approach using the MobileIP protocol, which shows improvement in decreasing total processing delay. Regarding the third target, we employ “vertical mobility” in our load balancing framework to minimize the maximum response time; thus, the users’ mobility-related procedures can be completed with less delay.
Effects of Lepidium Sativum (Tuffa) on Bone Mineral Density and Symptoms in Female University Students in Makkah, Saudi Arabia: Single-Blind Randomized Trail

Background: Osteoporosis affecting millions worldwide, with up to 200 million at risk of fracture. The seeds of Lepidium sativum (LS) are used in Saudi Arabia as traditional medicine (named Tuffa ) to promote healing of fractured bone. Objectives: To study the effect of Tuffa on bone mineral density (BMD) and changes on symptoms after consumption. Subjects and methods: A Clinical trial was conducted between 2014 – 2015 in 72 randomly selected university females' students. They were given daily dose of LS (2.5g for 6 weeks). A questionnaire was used for personal and bone health. Symptoms related to joint pain and stiffness and body health before and after treatment were also measured. BMD measured by DEXA. Results: Osteopenia occurred but no osteoporotic cases were reported, with significant changes from baseline after treatment from 40% osteopenic cases to 30.6%. T-Score at baseline improved from ـ0. 702±1.038 to -0.61±0.984 after treatment. Total BMD was 1.078±0.103 lowered to 1.067±0.092; Hip BMD was 0.904±0.134 lowered to 0.8732±0.133. Spinal (BMD) was 1.0092 ±0.134 increased to 1.0172±0.126, only the hip and T-score changes were significant (P<0.05). Stiffness and pain in the knee joints, hair loss, and dizziness improved after treatment (P<0.05) Conclusion: Tuffa (L.S.) improves bone structure and health related symptoms. A good herbal medicine may protect young adults, particularly those with family history and poor dietary and life style.
Multiple Step Financial Time Series Prediction with Portfolio Optimization

The Time Series Data Mining framework developed by Povinelli is extended to perform weekly multiple time-step prediction and adapted to perform weekly stock selection from a broader market. The stock selections are combined into weekly portfolios, and techniques from Modern Portfolio Theory and the Capital Asset Pricing Model are adapted to optimize the portfolios. The contribution of this work is the combination of stock selection and portfolio optimization to develop a temporal data mining based stock trading strategy. Results show that investors can increase overall wealth, obtain optimal weekly portfolios that maximize return for a given level of portfolio risk, overcome trading costs associated with trading on a weekly basis, and outperform the market over a given time range.
Feature-based multi-resolution topography

A three-dimensional (3D) representation of the topographic surface is an important element in planning, civil engineering and mapping. Many state-of-the-art representations provided graphical, 3D model of entire planet. However, the existing solutions to 3D topographic surface lack the geometric flexibility and accuracy on boundaries with models of other geographic features. Most of the contemporary approaches to digital Earth solutions focus on the visualization performance. The high visual performance is achieved by the use of special data structures optimized for rendering. However, this optimization towards visualization hampers the data management of spatial data, their analysis and distribution. Therefore, the introduced solution reflects on multiple requirements of digital Earth systems. In addition to the visualization performance, the requirements regarding data interoperability, data management and distribution, data analysis and the multiple level of detail (LOD) are considered as essential for the design of the new solution. The topographic surface is central to the proposed method. It provides the defining surface in terms of which other features can be geographically referenced to. Therefore, this work introduces a new, more functional data representation of multi-resolution topographic surface. This representation is globally applicable, allows to populate the terrain surface with new geographic features and supports the multiple LOD of both features and terrain. The presented solution to representation of spatial features for multiple LOD environment is rooted in the concept of footprint. Exploitation of this concept alleviates from the structural complexity of pure 3D solutions, however, it also supports the extension to true 3D, when needed. This work extends the existing usage of footprints by providing support for multi-resolution representation. Consequently, the footprint can be represented with variable resolution along its course in the reconstructed graphic scene. In a pursuit of interoperability, the method for footprint analysis is developed to deal with features originating from disparate data sources. Thereafter, the algorithm for simultaneous simplification of a set of footprints is proposed. It is designed to build the multiple LOD database of features in such a manner, that the topological relations between features are preserved in the multiple LOD environment, which is reconstructed on its grounds. Since the topological relation between the feature and terrain is essential for many geo-spatial analyses, this thesis proposes two methods to carry out the generalization of distinct spatial features with respect to the geometry of terrain. It is also shown, how the important morphological structure of the terrain can be obtained and subsequently preserved on coarser levels of resolution. The method introduced in this thesis employs the Global Indexing Grid (GIG) as an indexing and paging mechanism. GIG determines for any position of the observer within the 3D virtual environment the position-dependent LOD of currently visible features and underlying terrain.
Optimization of cultivation conditions to enhance theexpression of recombinant VDAC2 from gallus gallus

VDAC2 protein identified to be over expressed in over-stunned chicken is a potential biomarker in differentiating stunned chicken and the voltage applied during the process. The VDAC2 gene was amplified by proofread DNA polymerase, then purified and inserted into pENTR-TEV-D-TOPO entry vector and transformed into One Shot TOP 10 Chemically Competent E. coli. The entry clone then was sub cloned into pDEST17 expression vector using LR recombinasein E. coli DH5a as the host. The vector construct was transformed into E. coli BL21-AI for protein expression. Recombinant VDAC2 protein was purified by affinity chromatography using Ni-NTA spin-column. Western blot using polyclonal anti-N terminal human VDAC2 and anti-His tag, followed by secondary antibody AP goat anti-rabbit revealed a 34 kDa protein, confirming the expression of recombinant VDAC2. Post-induction temperature, concentration of L-arabinose and postinduction time were selected for optimization studies under Response Surface Methodology (RSM). The optimum predicted cultivation conditions for the maximum expression of recombinant VDAC2 was found to be at 29oC post-induction temperature, 6.8 hour post-induction time and 0.5% (w/v) L-arabinose with a predicted expression of recombinant VDAC2 intensity of 0.459. The experimental expression of recombinant VDAC2 intensity obtained was 0.496, which was very close to the predicted value. The expression of recombinant VDAC2 improved by almost 6-fold after the optimization process. Therefore, RSM is a suitable method for optimizing recombinant VDAC2 expression in E. coli to provide a better understanding of its characteristics and propertiesto become abiomarker in detecting over-stunned chicken.
Closing the Gap between Smart Manufacturing Applications and Data Management

Smart manufacturing refers to the intensified collaboration of machines, products, and people throughout the manufacturing and the supply chain. This facilitates innovative products, services, business models, and processes. Smart manufacturing is premised on emerging technologies such as cloud computing, mobile computing, the Internet of Things, data analytics, and artificial intelligence. A plethora of companies struggles with the implementation of corresponding applications. In research and practice, we see general data management approaches with primary attention on building architectures that are not tailored to fit a particular domain/ application scenario. However, a robust data management concept is vital, as smart manufacturing decisively depends on data. To address this substantial deficit, we conduct a comprehensive literature review, an expert workshop, and semi-structured expert interviews with one of the leading German automotive manufacturers. The result is a catalog of requirements and a framework for data management that fosters the implementation of smart manufacturing applications.
Time series classification based on arima and adaboost

In this paper, a novel time series classification approach, which using auto regressive integrated moving average model (ARIMA) features and Adaptive Boosting (AdaBoost) classifications. ARIMA is particularly suitable for distinguishing time series signal and Adaboost is suitable for features classification. The simulation results have shown that the algorithm is feasible. And this method is more accurate than many existing method in multiple time series problems.
Polyphenols analysed by UHPLC-ESI-MS/MS and antioxidant activities of molasses, acorn and leaves of oak (Quercus robur subsp. pedunculiflora)

Objectives: The leaves of oak trees have been boiled in water and the extracts have been evaporated to produce oak molasses. Colloidal precipitants have been widely used as dietary molasses since have very effective antiseptic functions as alternative medicine for ages in some parts of the world. Present study aimed to investigate the biological activities of oak products for elucidating the scientific basis of alternative medicine. Thus, antioxidant activities of ethanol and water extracts of acorn, leaves and molasses of oak trees (Quercus robur subsp. pedunculiflora) were evaluated. Results: We determined antioxidant activities of extracts by different in vitro methods including DPPH free radical scavenging, ABTS•+ radical scavenging, total antioxidant activity determination by ferric thiocyanate method, reducing power by FRAP methods, separately. The results were compared with BHA, BHT and ascorbic acid as standard antioxidant compounds. The acorn seed extract, which presented the highest antioxidant potential, was the most effective scavenger against DPPH free radical. Also, phenolic compounds of the molasses were identified by UHPLC-ESI-MS/MS. The highest phenolic compound was quinic acid (4556 ± 219 ppb). Conclusion: Acorns and leaves of oak trees (Quercus robur subsp. pedunculiflora), as well as traditional oak molasses” have high antioxidant potential for the food industry as a food ingredient to produce functional food products.
Reliability and Validity of the AOSpine Thoracolumbar Injury Classification System: A Systematic Review

Study Design: Systematic review. Objectives: The AOSpine thoracolumbar injury classification system (ATLICS) is a relatively simple yet comprehensive classification of spine injuries introduced in 2013. This systematic review summarizes the evidence on measurement properties of this new classification, particularly the reliability and validity of the main morphologic injury types with and without inclusion of the subtypes. Methods: A literature search was performed using PubMed and Embase in September 2016. A revised version of the COSMIN checklist was used for evaluation of the quality of studies. Two independent reviewers performed all steps of the review. Results: Nine articles were included in the final review, all of which evaluated the reliability of the ATLICS and had a fair methodological quality. The reliability of the modifiers was unknown. Overall, the quality of evidence for reliability of the morphologic and neurologic classification sections was low. However, there was moderate evidence for poor interobserver reliability of the morphologic classification when all subtypes were included, and moderate evidence for good intraobserver reliability with exclusion of subtypes. The reliability of the morphologic classification was independent of the observer’s experience and cultural background. Conclusions: ATLICS represents the most current system for evaluation of thoracolumbar injuries. Based on this review, further studies with robust methodological quality are needed to evaluate the measurement properties of ATLICS. Shortcomings of the reliability studies are discussed.
Kynurenine 3-Monooxygenase Interacts with Huntingtin at the Outer Mitochondrial Membrane

Background Kynurenine 3-monooxygenase (KMO), an outer mitochondrial membrane protein, catalyses the conversion of l-kynurenine to the neurotoxin 3-hydroxykynurenine (3-HK) – thereby playing a critical role in the kynurenine pathway (KP). Increased KMO activity likely contributes to the toxicity observed in neurodegenerative disorders by enhancing levels of 3-HK and the excitotoxin quinolinic acid (QUIN). Notably, genetic and pharmacological inhibition of KMO ameliorates disease-relevant phenotypes in models of Huntington’s disease (HD). Aims This study interrogates the subcellular localisation of human KMO and explores its interaction with the huntingtin (HTT) protein. Methods Confocal analysis was employed to explore KMO localisation and bimolecular fluorescence complementation (BiFC) and transmission electron microscopy was used to investigate KMO and HTT interactions in HEK293T cells. Results We found that KMO exclusively localises to mitochondria when expressed in HEK293T cells. A deletion of a C-terminal portion of KMO (tKMO) which contains a putative transmembrane domain causes the mislocalisation of the enzyme from mitochondria to other cellular compartments, suggesting a critical function for this region in mitochondrial targeting. We also found an interaction between KMO and both WT and mutant HTT fragments at the outer mitochondrial membrane. Notably, the strength of this interaction was inversely correlated to the length of the HTT polyglutamine expansion. No interaction between tKMO and HTT was observed indicating that mitochondrial localization of KMO is likely critical for HTT/KMO interactions. Conclusions This study suggests that KMO and HTT may interact at the outer mitochondria membrane. The biological significance of this interaction will be explored in future experiments.
Blockchain-Assisted Secure Device Authentication for Cross-Domain Industrial IoT

Industrial Internet of Things (IIoT) is considered as one of the most promising revolutionary technologies to prompt smart manufacturing and increase productivity. With manufacturing being more complicated and sophisticated, an entire manufacturing process usually involves several different administrative IoT domains (e.g., factories). Devices from different domains collaborate on the same task, which raises great security and privacy concerns about device-to-device communications. Existing authentication approaches may result in heavy key management overhead or rely on a trusted third party. Thus, security and privacy issues during communication remain unsolved but imperative. In this paper, we present an efficient blockchain-assisted secure device authentication mechanism $\textsf{BASA}$ for cross-domain IIoT. Specifically, consortium blockchain is introduced to construct trust among different domains. Identity-based signature (IBS) is exploited during the authentication process. To preserve the privacy of devices, we design an identity management mechanism, which can realize that devices being authenticated remain anonymous. Besides, session keys between two parties are negotiated, which can secure the subsequent communications. Extensive experiments have been conducted to show the effectiveness and efficiency of the proposed mechanism.