Miracle-dz/UniFAR-FTUs huggingface dataset:
CEOR_A_322087 693..701

1Department of Epidemiology and Biostatistics, College of Health and Medical Sciences, Haramaya University, Haramaya, Ethiopia; 2Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; 3Department of Public Health and Health Policy, College of Health and Medical Sciences, School of Public Health, Haramaya University, Harar, Ethiopia Background: Despite improvement in access to modern healthcare services in East African countries, health-service delivery and health status of the population remained poor mainly due to the weak health-sector financing system. Therefore, the current study aimed to assess the health insurance coverage and its associated factors among reproductive-age group (RAG) women in East Africa. Methods: The most recent (between 2010 and 2018) Demographic and Health Surveys (DHS) data of the ten East African countries (Burundi, Comoros, Ethiopia, Kenya, Malawi, Mozambique, Tanzania, Uganda, Zambia, and Zimbabwe) were included. STATA version 16.0 statistical software was used for data processing and analysis. In the multilevel mixedeffects generalized linear model, variables with a p-value ≤0.05 were declared as significant associated factors of health insurance coverage. Results: The overall health insurance coverage in East Africa was 7.56% (95% CI: 7.42%, 7.77%). The odds of health insurance coverage were high among educated, currently working, and rich RAG women whereas it was low among rural residents. Besides, RAG women who have media exposure, visited by field workers, and visited health facilities have a higher chance of health insurance coverage. Conclusion: Health insurance coverage in East Africa among RAG women was below ten percent. Educational status, working status, place of residence, wealth index, media exposure, visiting health facility within 12 months and being visited by field worker were significantly associated with health insurance coverage among RAG women in East Africa. Improving women’s access to health facilities, promoting field workers’ visit, and media exposure targeting uneducated, unemployed, and rural resident women of RAG will be a gateway to promote health insurance coverage.
Martinez-Luengo, Maria and Shafiee, Mahmood and Kolios, Athanasios (2019) Data management for structural integrity assessment of offshore wind turbine support structures : data cleansing and missing data

Structural Health Monitoring (SHM) and Condition Monitoring (CM) Systems are currently utilised to collect data from ofshore wind turbines (OWTs), to enhance the accurate estimation of their operational performance. However, industry accepted practices for efectively managing the information that these systems provide have not been widely established yet. This paper presents a four-step methodological framework for the efective data management of SHM systems of OWTs and illustrates its applicability in real-time continuous data collected from three operational units, with the aim of utilising more complete and accurate datasets for fatigue life assessment of support structures. Firstly, a time-eicient synchronisation method that enables the continuous monitoring of these systems is presented, followed by a novel approach to noise cleansing and the posterior missing data imputation (MDI). By the implementation of these techniques those data-points containing excessive noise are removed from the dataset (Step 2), advanced numerical tools are employed to regenerate missing data (Step 3) and fatigue is estimated for the results of these two methodologies (Step 4). Results show that after cleansing, missing data can be imputed with an average absolute error of 2.1%, while this error is kept within the [+ 15.2%−11.0%] range in 95% of cases. Furthermore, only 0.15% of the imputed data fell outside the noise thresholds. Fatigue is found to be underestimated both, when data cleansing does not take place and when it takes place but MDI does not. This makes this novel methodology an enhancement to conventional structural integrity assessment techniques that do not employ continuous datasets in their analyses.
An Efficient and Low Density Crossbar Switch Design for NoC

: Code Division Multiple Access (CDMA) is a sort of multiplexing that facilitates various signals to occupy a single transmission channel. In this medium, sharing is enabled in the code space by assigning a limited number of N-chip length orthogonal spreading codes to the processing elements sharing interconnect. Serial and parallel overloaded CDMA interconnect (OCI) architecture variants are presented to adhere to different area, delay, and power requirements. Compared with the conventional CDMA crossbar, on a Xilinx Artix-7 AC701 FPGA kit, the serial OCI crossbar achieves 100% higher bandwidth, 31% less resource utilization, and 45% power saving, while the parallel OCI crossbar achieves N times higher bandwidth compared with the serial OCI crossbar at the expense of increased area and power consumption. A 65-node OCI-based star NoC is implemented, evaluated, and compared with an equivalent space division multiple access based torus NoC for various synthetic traffic patterns. The evaluation results in terms of the resource utilization and throughput highlight the OCI as a promising technology to implement the physical layer of NoC routers.
Analysis of Variance for Item Differences in Verification Data with Unknown Groups

For sequentially collected data, this paper introduces a lag-one differencing method to estimate the random error standard deviation δR and then uses the estimate δ^R to calculate a change detection threshold in a moving window method to detect shifts in the short-term systematic error. Performance results on simulated and real data are presented. Fortunately, the impact of having to perform change detection on the estimated short-term systematic and random error variances is anticipated to be modest or small. The motivating example arises from facilities under nuclear safeguards agreements, where inspector data collected during International Atomic Energy Agency (IAEA) verifications are compared to corresponding operator data. The differences between the operator and inspector values are evaluated using an application of analysis of variance (ANOVA). Typically, it is assumed that short-term systematic errors change across inspection periods, so inspection periods form the groups used in the ANOVA. In some data sets, it appears that the short-term errors have changed at other times, so change detection methods could be used to detect the actual change times.
Response to Reviewers (cid:884) 2 nd Round

: Drawing from the research of green supply chain management and corporate social responsibility, this paper proposes a hierarchical structure of sustainable supply chain management and develops a multi-item measurement scale to reflect the specific management practices of sustainable supply chain management. In this research, sustainable supply chain management is operationalised as a third-order factor reflected by three second-order factors, namely external green supply chain management, internal green supply chain management and corporate social responsibility. Utilising a rigorous, multi-step scale development method and data from 293 Chinese manufacturers, this paper validates a 31-item measurement scale and approve the proposed third-order structure. The results confirm the multidimensionality of sustainable supply chain management, which suggests that it is necessary for the future researches to consider both environmental and social aspects. The valid measurement scales provide managers with a "to do list" to make the specific business decisions to achieve sustainable development in the supply chain. Abstract Drawing from the research of green supply chain management and corporate social responsibility, this research proposes a hierarchical structure of sustainable supply chain management and develops a multi-item measurement scale to reflect the specific management practices of sustainable supply chain management. In this research, sustainable supply chain management is operationalised as a third-order factor reflected by three second-order factors, namely external green supply chain management, internal green supply chain management and corporate social responsibility. Utilising a rigorous, multi-step scale development method and data from 293 Chinese manufacturers, this research validates a 31-item measurement scale and approve the proposed third-order structure. The results confirm the multidimensionality of sustainable supply chain management, which suggests that it is necessary for the future researches to consider both environmental and social aspects. The valid measurement scales (cid:393)(cid:396)(cid:381)(cid:448)(cid:349)(cid:282)(cid:286) (cid:373)(cid:258)(cid:374)(cid:258)(cid:336)(cid:286)(cid:396)(cid:400) (cid:449)(cid:349)(cid:410)(cid:346) (cid:258) (cid:862)(cid:410)(cid:381) (cid:282)(cid:381) (cid:367)(cid:349)(cid:400)(cid:410)(cid:863) to make the specific business decisions to achieve sustainable development in the supply chain.
CUSTOMER RELATIONSHIP MANAGEMENT ADOPTION

The global market is constantly evolving which means companies need to continuously innovate their businesses and understand new ways to keep in touch with their customers. One way to do it is by resorting to Information Technologies (IT) such as Customer Relationship Management (CRM). This kind of information system allows companies to gather data from their customers and transform it into information they can use to better achieve any expectations their clients may have while engaging in closer relationships with them. However, not all companies can successfully adopt or implement a CRM system, and because of that, they may lose their investments or worse, their customers. The purpose of this research is to find an answer to the question – What factors can help companies adopt a successful CRM system? To answer it, it is necessary to understand what aspects marketing and information systems (IS) professionals think as essential to successfully adopt the system. To accomplish this, we build two instruments based on a previous work (Pedron, 2009) in which a set of fundamental objectives (23) and a set of means objectives (49) were identified as influencing factors of a successful CRM system adoption. Using a sample of about 200 professionals we applied Churchill’s (1979) recommendations regarding the item’s purification. All data gathered was analysed through exploratory factor analysis and, consequently, an output resulted with all the factors perceived as important by the professionals that can indeed help with the adoption of a CRM system. Although there are several studies about CRM adoption they are mainly exploratory. Indeed, no measures of CRM adoption success have been previously proposed. This study tries to fulfil this gap in the literature by proposing and validating two instruments for assessing the CRM adoption success.
Positional Faithfulness and Learnability in Optimality Theory

ranking. As a result, constraint ranking plays a crucial role in many domains of language. For example, the phonology of a language (its phonotactic patterns and allophonic alternations) is the result of one particular constraint ranking. Typological patterns across languages reflect all possible constraint rankings. Learning a language requires learning its constraint ranking. Because phonology, typology, and learning all depend on constraint ranking, each of these three domains can contribute to our understanding of the others. Any new constraint that is proposed for the phonological analysis of one language must also make correct typological predictions — every possible reranking of that constraint must correspond to some possible human language. Furthermore, if the phonological analysis proposed for a given language includes a ranking that is not formally learnable, then that analysis must be discarded, since no language that corresponds to an unlearnable ranking can exist. There are many examples of OT analyses in which typological facts are used to refine the formulation of the constraints developed to account for some phonological phenomenon. One such proposal is the theory of positional faithfulness (Beckman 1995, 1998; Casali 1996), summarized in section 2 below. Positional faithfulness constraints are formulated in a particular way because certain (logically possible) phonological patterns are not observed in any language, so there must be no ranking of the constraints that is able to generate those patterns. This paper examines positional faithfulness from the perspective of learnability (as formulated in the Error-Driven Constraint Demotion learning algorithm of Tesar & Smolensky 1996, 1998, Smolensky 1996). Since positional faithfulness is a theory that takes into account both phonological phenomena and typological patterns, the question addressed here is the following: What can be learned about the grammar when phonology, typology, and learnability are considered simultaneously? It is shown below that a grammar with a positional faithfulness ranking is formally learnable only if a condition is placed on the ranking of constraints in the learner's Initial State. Namely, the set of positional faithfulness constraints must initially be ranked above the set of general faithfulness constraints.
Mitigating Some Security Attacks in MPLS-VPN Model “C”

—In certain models of inter-provider Multi-Protocol Label Switching (MPLS) based Virtual Private Networks (VPNs), spooﬁng and replay attacks against VPN sites are two key concerns. MPLS VPN model “C” can scale well with respect to maintenance of routing state when compared with models “A” and “B”. But this deployment model is not favoured due to the aforementioned security concerns in the data-plane. The inner labels associated with VPN sites are not encrypted during data transmission. Therefore it is possible for an attacker to spoof or replay data packets to a speciﬁc VPN site. We propose a label-hopping technique which uses a set of randomised labels and a method for hopping amongst these labels to address these type of attacks. To reduce the computation time complexity for such algorithms, we propose the use of Timing over Internet Protocol connection and Transfer of Clock (TicToc) based Precision Time Protocol. Simulations show that by using the TicToc protocol, along with the label-hopping technique, we can mitigate spooﬁng and replay attacks at line-rate. As we address key security and performance concerns, we make a plausible case for the deployment of MPLS based VPN inter-provider model “C”.
One-pot synthesis of organic conductive nanoparticles with high photothermal conversion efficiency

of unmodified (a) and FeCl 3 -treated (b) PMPC 43 - b -PHPMA 258 particles, PANI- and PPy-based nanospheres (c, e) as well as nanovesicles (d, f); UV/Vis spectra (D) of pH-sensitive vesicular PANI particles in neutral (a) and acidic water (b). Inset images illustrate a drastic colour change of PANI particles in response to solution pH.
A Flexible Arm Manipulator Control System Using Modified Discrete Sliding mode Model Following Controller with Sinusoidal Command Input

A Modified Discrete Sliding mode Model Following Control or MDSMFC design methodology for a flexible arm manipulator is presented. The MDSMFC algorithm uses the combination of an adaptive model following control and sliding mode control to improve the dynamics response for command tracking. A procedure is proposed for choosing the control function so that it guarantee the existence of a sliding mode and the nominal system stable in the absence of system uncertainties and disturbances. The MDSMFC approach has been simulated and applied to a position control of a tip of a single flexible link with sinusoidal command input. Simulation results showed that the MDSMFC gives a significant improvement on the tracking performances and robust to plant parameter variations and disturbances.
Fusing Appearance and Prior Cues for Road Detection

Road detection is a crucial research topic in computer vision, especially in the framework of autonomous driving and driver assistance. Moreover, it is an invaluable step for other tasks such as collision warning, vehicle detection, and pedestrian detection. Nevertheless, road detection remains challenging due to the presence of continuously changing backgrounds, varying illumination (shadows and highlights), variability of road appearance (size, shape, and color), and differently shaped objects (lane markings, vehicles, and pedestrians). In this paper, we propose an algorithm fusing appearance and prior cues for road detection. Firstly, input images are preprocessed by simple linear iterative clustering (SLIC), morphological processing, and illuminant invariant transformation to get superpixels and remove lane markings, shadows, and highlights. Then, we design a novel seed superpixels selection method and model appearance cues using the Gaussian mixture model with the selected seed superpixels. Next, we propose to construct a road geometric prior model offline, which can provide statistical descriptions and relevant information to infer the location of the road surface. Finally, a Bayesian framework is used to fuse appearance and prior cues. Experiments are carried out on the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) road benchmark where the proposed algorithm shows compelling performance and achieves state-of-the-art results among the model-based methods.
S. Karthikeyan

Firefly Algorithm (FA) is a nature-inspired optimization algorithm that can be successfully applied to continuous optimization problems. However, lot of practical problems are formulated as discrete optimization problems. In this paper a hybrid discrete firefly algorithm (HDFA) is proposed to solve the multi-objective flexible job shop scheduling problem (FJSP). FJSP is an extension of the classical job shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. Three minimization objectives - the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. This paper also proposes firefly algorithm’s discretization which consists of constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In the proposed algorithm discrete firefly algorithm (DFA) is combined with local search (LS) method to enhance the searching accuracy and information sharing among fireflies. The experimental results on the well-known benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective flexible job shop scheduling problems.
Autonomous Driving on Container Terminals

Terminals play an important role in the process of transporting containers from origins to destinations all over the world. Recent developments have led many terminals to explore the opportunities of automation, speciﬁcally those oﬀered by Automated Guided Vehicles (AGV’s). So far, AGV systems have primarily used central routing and driving methods to control movements of these vehicles. The aim of the system’s strategy is to prevent both collisions and deadlocks and to maximize container handling speed and eﬃciency. This thesis investigates the possibilities of autonomous AGV’s, which are responsible for making their own driving decisions and for coordinating with other vehicles around to prevent collisions and deadlocks. A decentralised strategy is developed and tested extensively by simulation experiments, the results of which show a performance that is roughly equal to that of a centralised strategy adopted by TBA’s TIMESquare software.
Large-Scale Analysis of Putative Soybean Regulatory Gene Expression Identiﬁes a Myb Gene Involved in Soybean Nodule Development

Nodulation is the result of a symbiosis between legumes and rhizobial bacteria in soil. This symbiosis is mutually beneﬁcial, with the bacteria providing a source of nitrogen to the host while the plant supplies carbon to the symbiont. Nodule development is a complex process that is tightly regulated in the host plant cell through networks of gene expression. In order to examine this regulation in detail, a library of quantitative reverse transcription-polymerase chain reaction primer sets was developed for a large number of soybean ( Glycine max ) putative regulatory genes available in the current expressed sequence tag collection. This library contained primers speciﬁc to soybean transcription factor genes as well as genes involved in chromatin modiﬁcation and translational regulation. Using this library, we analyzed the expression of this gene set during nodule development. A large number of genes were found to be differentially expressed, especially at the later stages of nodule development when active nitrogen ﬁxation was occurring. Expression of these putative regulatory genes was also analyzed in response to the addition of nitrate as a nitrogen source. This comparative analysis identiﬁed genes that may be speciﬁcally involved in nitrogen assimilation, metabolism, and the maintenance of active nodules. To address this possibility, the expression of one such candidate was studied in more detail by expressing in soybean roots promoter b -glucuronidase and green ﬂuorescent protein fusions. This gene, named Control of Nodule Development ( CND ), encoded a Myb transcription factor gene. When the CND gene was silenced, nodulation was reduced. These results, associated with a strong expression of the CND gene in the vascular tissues, suggest a role for CND in controlling soybean nodulation.
The Effect of Personal Coaching on Increasing Knowledge, Attitudes, and Actions about Lactation Nutrition, Uterial Involution, and Lochea in Public Mothers

--- During the puerperium, the mother will experience many changes both physically and physiologically. Suppose this physiological process does not run usually. In that case, it can cause complications during the puerperium such as uterine sub involution, breast swelling to mastitis, prolongation of the period of lochia discharge, which, if not handled quickly and easily. Can lead to the death of the mother. This study used a quasi-experiment with a pre-post-test with a control design, which involved two postpartum mothers, namely 43 respondents in the intervention and control groups. The sample selection was based on purposive sampling. The research was carried out in RSIA Bahagia Makassar City and RSIA Ananda Makassar City from March to April 2020. Data were analyzed using the Wilcoxon test, Mann Whitney test, and Chi-Square. There was a significant difference between the intervention group and the control group with a p-value = 0.036. There is an increase in knowledge, attitudes, and actions, namely the act of consuming protein, VITA, and VIT C in postpartum mothers. Involution and Lochea on Increased Knowledge, Attitudes and Actions of Postpartum Mothers. "