Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Assurance in NDT

The importance of Nondestructive Testing (NDT) as a Quality Control/ Quality Assurance tool in the industrial domain cannot be over-emphasized. With the rapid advancement in research and technology, the NDT field is becoming larger and more sophisticated day by day. Innovative research in materials science and digital technology is paving the way for more and more new methods in NDT technology. Although the NDT technology has improved over the years, the basic ‘human factor’ underlying the success of the NDT field remains the same. There are two major factors that influence the ‘Quality Assurance in NDT’. First, knowledgeable and skilled NDT Operators are the most important factor in assuring the reliable test results. Second, the Management oversight of the NDT operations plays a major role in assuring the overall quality of NDT. Management responsibilities include the implementation of a Quality Management System (QMS) that focuses on the NDT operations and apply all the elements of Quality Assurance relevant to NDT. Whether the NDT operations are performed in-house or by a contractor, periodic Management Self-assessments should include the following question: How can the Management assess and improve the ‘Quality Assurance in NDT’? This paper attempts to answer the above question. Some practical examples are provided to illustrate the potential quality incidents that could lead to costly failures, and the role of NDT Operator and the Management in preventing such quality incidents. Also, some guidelines are provided on how the Management can apply the elements of Quality Assurance to NDT in order to assess and improve the ‘Quality Assurance in NDT’.
Control of thin ferroelectric polymer films for non-volatile memory applications

The article presents the recent research development in controlling molecular and microstructures of thin ferroelectric polymer films for the application of non-volatile memory. A brief overview is given of the history of ferroelectric memory and device architectures based on ferroelectric polymers particularly emphasizing on the device elements such as metal/ferroelectric/metal type capacitor, metal-ferroelectric-insulator-semiconductor (MFIS) diodes and ferroelectric field effect transistor (FeFET) with ferroelectric poly(vinylidene fluoride) (PVDF) and its copolymers with trifluoroethylene (TrFE). Key material and process issues for optimizing the memory performance in each device architecture and thus realizing non-volatile ferroelectric polymer memory are in details discussed, including the control of crystal polymorphs, film thickness, various hetero-material interfaces between ferroelectric polymer and either metal or semiconductor, crystallization and crystal orientation. The current effort of micro and nanopatterning techniques is also addressed for high density and flexible memory arrays.
Efficiently Maintaining Distributed Model-Based Views on Real-Time Data Streams

Minimizing communication cost is a fundamental problem in large-scale federated sensor networks. Maintaining model-based views of data streams has been highlighted because it permits efficient data communication by transmitting parameter values of models, instead of original data streams. We propose a framework that employs the advantages of using model-based views for communication-efficient stream data processing over federated sensor networks, yet it significantly improves state-of-the-art approaches. The framework is generic and any time-parameterized models can be plugged, while accuracy guarantees for query results are ensured throughout the large-scale networks. In addition, we boost the performance of the framework by the coded model update that enables efficient model update from one node to another. It predetermines parameter values for the model, updates only identifiers of the parameter values, and compresses the identifiers by utilizing bitmaps. Moreover, we propose a correlation model, named coded inter-variable model, that merges the efficiency of the coded model update with that of correlation models. Empirical studies with real data demonstrate that our proposal achieves substantial amounts of communication reduction, outperforming state-of-the art methods.
Dietary Patterns and Breast Cancer Risk in Korean Women

We evaluated the association between dietary patterns and breast cancer risk according to menopausal and hormone receptor status among Korean women. In a study with 357 cases and 357 age-matched controls, dietary patterns (vegetable-seafood and meat-starch) were derived via principle component analysis based on 39 food groups from a food frequency questionnaire. The relation between dietary patterns and breast cancer risk was assessed by using multivariate logistic regression. The vegetable-seafood pattern was inversely associated with breast cancer risk [odds ratio (OR) and 95% confidence interval (CI) for high vs. low intake = 0.14 (0.08–0.25); P for trend < 0.001]. No association between the meat-starch pattern and breast cancer risk was found. The association between dietary patterns and breast cancer risk was not modified by menopausal and combined hormone receptor status. These findings indicate that a diet rich in vegetables and seafood is associated with a decreased breast cancer risk in Korean women.
A new approach of light microscopic immunohistochemical triple-staining: combination of Fos labeling with diaminobenzidine-nickel and neuropeptides labeled with Alexa488 and Alexa555 fluorescent dyes.

OBJECTIVE The aim of the present study was to introduce a new approach of the light microscopic immunohistochemical triple-staining enabling to study the differences in the activity of at least two different phenotypes of neurons on the same histological section. For this purpose combination of Fos (a product of the immediate early gene) labeling with nickel intensified diaminobenzidine (DAB-Ni) and two neuropeptides labeled with Alexa488 and Alexa555 fluorescent dyes on cryo-processed 35-40 µm thick free-floating brain sections was selected. METHODS The parallel occurrence of three antibodies studied, i.e. Fos, hypocretin (HCRT), and melanin-concentrating hormone (MCH), was studied by a new methodic approach utilizing combination of Fos immunolabeled with DAB-Ni and HCRT and MCH labeled with Alexa488 and Alexa555 fluorescent dyes, respectively. Fos stimulation was induced by a single immobilization (IM0) for 120 min. Then, the rats were sacrificed, the brains removed, soaked with 30% sucrose in 0.1 M phosphate buffer (PB), cryo-sectioned throughout the hypothalamus into 35-40 μm thick coronal sections, collected, and washed in the same buffer for 10-15 min. Fos was revealed by avidin-biotin-peroxidase (ABC) complex and visualized by diaminobenzidine chromogen containing nickel chloride salt. HCRT and MCH neurons were visualized by the above mentioned fluorescent dyes. Evaluation of the Fos and fluorescent staining was performed in the computerized Axo Imager Carl Zeiss microscope using light and fluorescent illuminations. RESULTS All the antibodies used showed clear immunoreactive staining. Fos staining occurred in the form of black color located in the cell nuclei. HCRH and MCH neuropeptides showed clear green and red fluorescence in the cell perikarya, respectively. The final merged picture showed Fos protein in the activated green HCRT or red MCH neurons in the form of white nuclei. CONCLUSIONS The present study clearly demonstrate that the combination of Fos labeling with DAB-Ni and neuropeptides labeled with Alexa488 and Alexa555 on cryo-processed 35-40 µm thick free-floating brain sections is an excellent approach providing further advantages for quick and reproducible triple immuno-staining enabling to compare the activity of at least two phenotypes of neurons on the same section. KEYWORDS Alexa488 and Alexa555 fluorescent dyes, Fos, hypocretin, melanin-concentrating hormone, cryostat sections, triple labeling immunohistochemistry, rat.
Talent balancing: staffing your company for long-term success

Talent Management (TM) has emerged as a concept of great interest to researchers and practitioners in HRD, as evidenced by a recent research report for the CIPD (Chartered Institute for Personnel and Development) carried out by Jim Stewart of Leeds Metropolitan University and colleagues from Nottingham Trent University (Tansley et al. 2007). Interest in TM has grown since a landmark McKinsey & Company study (Michaels, Hanfield-Jones and Axelrod 2001) on the ‘war for talent’; TM is now seen as critical to every company’s success, and the importance of hiring and nurturing top talent while proactively managing-out low performers is often stressed. According to Michaels, Hanfield-Jones and Axelrod (2001), there are three fundamental forces fuelling the war for talent: an irreversible shift from the industrial to the information age, an intensifying demand for high-calibre managerial/professional talent, and a growing propensity of employees to switch companies. However, TM is a concept with various meanings; originally linked to recruitment, performance management or performance development, it is now seen in terms of a common approach underpinning all these activities (Iles 2007; Preece, Chuai and Iles 2006). TM is also not new; in the 1980s, HR managers were urged to employ the BCG (Boston Consulting Group) matrix to differentiate between star, deadwood, solid and high-potential employees, and manage them differently. A more sophisticated recent approach to TM and branding (Martin 2006; Martin and Hetrick 2006) distinguishes between internally focused and externally focused business modes and between different kinds of psychological contracts, such as transactional, relational and ideological. This segments human capital into four modes, with different implications for employer branding: core knowledge workers; traditional human capital; idiosyncratic human capital and ancillary human capital/contract workers. It is often unclear whether such models are descriptions, predictions or prescriptions, as TM varies greatly in practice in contemporary organizations, including such areas as strategic workforce and competency assessments, implementation of recruiting, staffing, career development, performance management strategies, and the identification and development of the highest potential technical and leadership talent. TM can therefore be understood as referring to the identification, development, engagement/retention and deployment of those employees who are particularly valuable to an organization – either in view of their ‘high potential’ for the future or because they are fulfilling business/operation-critical roles. In some organizations, TM has often become synonymous with leadership development (Iles and Preece 2006) or succession planning Human Resource Development International Vol. 11, No. 2, April 2008, 215–218
Dependency-Based Bracketing Transduction Grammar for Statistical Machine Translation

In this paper, we propose a novel dependency-based bracketing transduction grammar for statistical machine translation, which converts a source sentence into a target dependency tree. Different from conventional bracketing transduction grammar models, we encode target dependency information into our lexical rules directly, and then we employ two different maximum entropy models to determine the reordering and combination of partial dependency structures, when we merge two neighboring blocks. By incorporating dependency language model further, large-scale experiments on Chinese-English task show that our system achieves significant improvements over the baseline system on various test sets even with fewer phrases.
Description of Zoonotic Pseudocowpoxvirus Infection of Cattle in Russia

Simple Summary This work describes a case study of pseudocowpoxvirus (PCPV) infection in Russia (Irkutsk region). The clinical manifestation, molecular identification, and molecular characterization of the disease were established. Epidemiological information were provided by the state veterinary service; additionally, the cows’ owners were interviewed using a semi-structured questionnaire. The description of clinical symptoms was based on clinical examination and farmer interviewing. Samples (blood, serum, scab) were collected from the affected cattle for virological studies and molecular analyses. The identification of PCPV was accomplished through the B2L gene fragment amplification, sequencing, and phylogenetic analysis. Based on the nucleotide identities and phylogenetic analysis of the partial-length B2L gene, the Irkutsk 2019 isolate was classified as PCPV. Because of high rates of virus transmission amongst cattle-to-cattle and cattle-to-humans through direct contact, it is important to raise farmers’ awareness of the clinical signs of the disease, highlight its preventive measures, and to develop a strategy to motivate them to seek qualified veterinary care. Abstract Parapoxviruses are worldwide epitheliotropic viruses that affect ruminants. Viruses of this genus have a narrow host range; however, the pseudocowpox virus (PCPV) also infects humans. Unfortunately, these cases are not well documented, and the epidemiology and the properties of the causative agents are not properly described. Here, we report the first case of PCPV in northern Russia (the Irkutsk region). The infection occurred in non-immune herds where no new arrivals of animals had been reported. Moreover, clinical signs of infection (skin lesions) were observed in humans. Based on the nucleotide identity and phylogenetic analysis of the partial-length B2L gene, the Irkutsk 2019 isolate was classified as PCPV. Phylogenetic analysis based on the nucleotide sequence of the B2L gene fragment of PCPV revealed a close phylogenetic relationship between the Irkutsk 2019 isolate and the PCPV strains isolated in Europe and the USA. The high degree of conservatism of the B2L gene does not allow for finding a correlation between their geographical origin and the results of phylogenetic analysis.
Non-Additive Effects of Genotypic Diversity Increase Floral Abundance and Abundance of Floral Visitors

Background In the emerging field of community and ecosystem genetics, genetic variation and diversity in dominant plant species have been shown to play fundamental roles in maintaining biodiversity and ecosystem function. However, the importance of intraspecific genetic variation and diversity to floral abundance and pollinator visitation has received little attention. Methodology/Principal Findings Using an experimental common garden that manipulated genotypic diversity (the number of distinct genotypes per plot) of Solidago altissima, we document that genotypic diversity of a dominant plant can indirectly influence flower visitor abundance. Across two years, we found that 1) plant genotype explained 45% and 92% of the variation in flower visitor abundance in 2007 and 2008, respectively; and 2) plant genotypic diversity had a positive and non-additive effect on floral abundance and the abundance of flower visitors, as plots established with multiple genotypes produced 25% more flowers and received 45% more flower visits than would be expected under an additive model. Conclusions/Significance These results provide evidence that declines in genotypic diversity may be an important but little considered factor for understanding plant-pollinator dynamics, with implications for the global decline in pollinators due to reduced plant diversity in both agricultural and natural ecosystems.
Efficient Non-Linear Editing of Large Point Clouds

Editing 3D models is often performed on triangular meshes. We generalize editing operations based on differential coordinates to work on point clouds without explicit connectivity information. This allows a point cloud to be interpreted as a surface or volumetric body upon which physically plausible deformations can be applied. Our multiresolution approach allows for a real-time editing experience of large point clouds with 1M points without any offline processing. We tested our method on a range of synthetic and real world data sets acquired by laser scanner. All of them were interactively editable and produced intuitive deformation results within few minutes of editing.
A Range Test Secure in the Active Adversary Model

In ACISP 2006, Peng et al proposed a novel range test technique, which tests whether the integer encrypted in a ciphertext is in an interval range. Their solution is more efficient than any previous solution to range test. However, their technique only works in the passive adversary model, so cannot be widely applied. In this paper, the range test by Peng et al is optimised to be secure in the active adversary model. Although the new range test protocol is less efficient than the original scheme by Peng et al, it is still an efficient solution and can be employed in a much wider application area.
Using Correlation Based Subspace Clustering for Multi-label Text Data Classification

With the boom of web and social networking, the amount of generated text data has increased enormously. Much of this data can be considered and modeled as a stream and the volume of such data necessitates the application of automated text classification strategies. Although streaming data classification is not new, considering text data streams for classification purposes has been extensively researched only recently. Before applying any classification method in text data streams, it is imperative that we apply them for existing well-known non-stream text data sets and evaluate their performance. One of the many characteristics of text data that has been pursued for research is its multi-labelity. A single text document may cover multiple class-labels at the same time and hence gives rise to the concept of multi-labelity. From classification perspective, an immediate drawback of such a characteristic is that traditional binary or multi-class classification techniques perform poorly on multi-label text data. In this paper, we extend our previously formulated SISC (Semi-supervised Impurity based Subspace Clustering) [1] approach and its multi-label variation SISC-ML [2]. We call this new algorithm H-SISC (Hierarchical SISC). H-SISC captures the underlying correlation that exists between each pair of class labels in a multi-label environment. Developing a robust multi-label classifier will allow us to apply such a model in classifying streaming text data more effectively. We have experimented with well known text data sets and empirical evaluation on these real world multi-label NASA ASRS (Aviation Safety Reporting System), Reuters and 20 Newsgroups data sets reveals that our proposed approach outperforms other state-of-the-art text classification as well as subspace clustering algorithms.
A broader view of research contributions: Necessary adjustments to DORA for hiring and promotion in psychology.

Recently Schönbrodt et al. (2022) released recommendations for improving how psychologists could be evaluated for recruitment, retention, and promotion. Specifically, they provided four principles of responsible research assessment in response to current methods that rely heavily on bibliometric indices of journal quality and research impact. They build their case for these principles on the San Francisco Declaration on Research Assessment (DORA) perspective that decries reliance on invalid quantitative metrics of research quality and productivity in hiring and promotion. The paper makes clear the tension panels have to address in evaluating applications—too little time to do an in-depth evaluation of an individual’s career and contribution, so reliance on easy to understand, but perhaps invalid, metrics. This dilemma requires an alternative mechanism rather than simply a rejection of metrics. To that end, the authors are to be congratulated for operationalising what those alternatives might look like. Nonetheless, the details embedded in the principles seem overly narrow and restrictive.
Fermentation Technology and Functional Foods.

Food is an integral part of our civilization. It is a cultural phenomenon that, while having evolved, is associated with societal traditions and identity. This work analyzes studies conducted to highlight the health properties of the most common ethnic foods. Although these foods were originally created from the need to preserve perishable produce, presently, we know that the fermentation process makes them nutritionally more complete. The basis of these transformations lies in that vast range of prokaryotic and eukaryotic microorganisms that, similar to small biochemical factories, can transform the initial nutrients into metabolically more active biomolecules through fermentation. Although naturally occurring microbes work together for mutual benefit, environmental conditions enhance or inhibit their development. Starting from a selection of microorganisms naturally present on a substrate, we attempt to select the most suitable species to obtain a fermented food with the best nutritional qualities and the richest in nutraceuticals.
The Association of Self-Assessed Emotional Intelligence with Academic Achievement and General Health among Students of Medical Sciences.

INTRODUCTION & AIM Emotional intelligence is one of the most important leading factors influencing different aspects of human life. It leads individuals to percept their feelings for appropriate decision making and fields for future accomplishments. The aim of this study was to Investigation of the associations of self-assessed EI with academic achievement and general health among medical students. MATERIALS & METHODS This cross-sectional study was conducted on 426 students of Zahedan University of Medical Sciences from October 2014 to May 2015. Random sampling method was used. Sibria Shring standard emotional intelligence questionnaire and Goldberg's standard general health questionnaire (GHQ-28) were used for data collecting. Data analysis was through descriptive statistics (mean, standard deviation) and inferential statistics (t-test, ANOVA and Pearson correlation coefficient) by SPSS v.21. The tests significant level was considered 0.05. FINDINGS The average total score of emotional intelligence in males (102.23±1.67) was better in comparison with females (98.54±2.23). There was not any significant difference in total mean scores of students of different fields of Study (P=0.211). According to ANOVA test, it has not observed any significant difference between scores of emotional intelligence scales of students from different domains of study. The results of Pearson correlation test confirmed a positive significant correlation between emotional intelligence, academic achievement and general health. CONCLUSION According to the results of this study that has shown a significant relationship between emotional intelligence, general health and academic achievement, it is needed to hold some workshops and classes for emotional intelligence improvement.
Exploring the stability of feature selection for imbalanced intrusion detection data

The class imbalance problem is of great importance to network intrusion detection data. Previous studies on feature selection always evaluate the performance of feature selection process according to the model performance and the size of selected feature subset, which neglect the stability of feature selection. We investigate the problem of the stability of feature selection and study in detail the properties of two state-of-the-art feature selection method, i.e. support vector machine recursive feature elimination (SVM-RFE) and random forest variable importance measures (RF-VIM) on the imbalanced intrusion detection data. Experimental results on KDD Cup 99 network intrusion data show the influence of imbalance rate on the stability of the algorithms, and demonstrate that stability is an important evaluation indicator of algorithm in practical applications of intrusion detection.