Miracle-dz/UniFAR-FTUs huggingface dataset:
Eggs of Atlantic Salmon (Salmo salar L) and Trout (S. trutta L); Identification by Phosphoglucoisomerase Zymograms*

Salmonid eggs were collected from spawning redds in the Norwegian rivers Alta, Gaula, and Driva in 1982. Their phosphoglucoisomerase (PGI; E.C. No. 5.3.1.9) patterns, as revealed by isoelectric focusing and histochemical staining, were compared to standard zymograms produced by Atlantic salmon (Salmo salar L.) and trout (S. trutta L.) white skeletal muscle extracts, and to the zymogram in salmon eggs of known origin. In salmon, the egg zymogram was identical with that of muscle. Two types of zymograms, identical with either salmon or trout muscle zymograms and thus regarded as species-determinants, were observed among the eggs from wild fish. Their proportions in the three rivers were as expected from current knowledge of species composition. The present findings are related to previous reports on PGI expression in salmonids. The PGI zymograms are probably diagnostic keys to species for eggs from Norwegian stream-dwelling salmonids, including Arctic char (Salvelinus alpinus L.). Some managemental implications of the present results are briefly discussed.
Development of Hybrid Learning Machine in Complex Domain for Human Identification

This paper presents a hybrid learning machine for human identification. It is a merger of eigenface with fisherface method, genetic fuzzy clustering and complex neural network. The non-linear aggregation based summation and radial basis function neural networks (NLA-SRBF NNs) are proposed as one of the functional component of the novel learning machine. The architecture of NLA-SRBF NNs incorporates hidden neurons, with summation and radial basis aggregation, and output neurons with only summation aggregation, along with complex resilient propagation (ČRPROP) learning procedure. The improved learning and speedy convergence of NLA-SRBF NN enables the hybrid machine to provide better recognition accuracy. The learning machine consists of feature extraction, unsupervised clustering and supervised classification module. The aim of our proposal is to enhance the performance of biometric based recognition system. The efficacy and potency of our hybrid learning machine demonstrated on three benchmark biometric datasetsextended Cohn-Kanade, FERET and AR face datasets to comprehend the motivation. The performance comparisons of different variations of hidden neuron and learning algorithm thoroughly presented the superiority of the proposed NN based hybrid learning machine.
Answering Comparison in Indonesian Question Answering System with Database

In this research, we build a question answering system that can answer comparative questions. Our system contains two components, question analysis and answer processing. In question analysis, we use information extraction method to extract entities, aspects, relations, and constants from the question. We also classify the question into five question types such as entity-mentioned, entity-other, entity-all, aspect, and yes/no. These processes in question analysis component are solved by machine learning technique. In answer processing component, we process the comparison by using word lists and rules. The result of comparison processing is used to find the answer by generating query to get relevant data from the database. The query generation process is performed by using rules based on the question type. After that, the data from database is also processed based on question type to generate the answer. Based on the experiment results, our proposed method for comparison question answering system is promising.
Adaptive Activation Functions For Artificial Neural Networks

: Activation functions are considered as main component in artificial neural networks. The current paper considers learning activation functions with combination of activation functions. We propose two approaches to use activation functions and construction of adaptive activation parameters to input data. Namely, to show effectiveness, we investigate linear form and non-linear form to combine activation functions, then introduce adaptive activation function. Numerical experiments show the proposed activation techniques overcome by performances and accuracy than standard rectified unit family functions
A theoretical warning for users of frequency-domain numerical simulators in the presence of metamaterials

In this paper it is shown that users of frequency-domain numerical simulators should be warned of the danger of using models with adjacent complementary media since such a configuration of materials can be a cause of a numerical instability which cannot be overcome by the presence of other lossy media or absorbing boundary conditions. The physical realizability at any frequency of models considering complementary media with sharp interfaces is then questioned by the contradiction between the deduced result and the one which holds true when the actual dielectric structure of metamaterials is considered.
Collaborative And Self-Directed Learning In A Virtual Campus Environment: A Potential Solution For Our Years?

In the current society, where the information flow has a big impact on the learner, and the learning methods differ from student to student, it is important to understand a virtual campus and its benefits. Nobody can doubt the impact of the new technologies on the educational system. In this new reality, universities must learn to work and collaborate with other universities or groups of interest in order to prepare learners to meet the requirements of the 21stcentury. The solution can be a virtual campus that offers powerful tools, access to content and services, personal learning environment, enabling the student to acquire information and learn new skills.
Totally transoral video-assisted thyroidectomy: report of 37 cases

Objective To evaluate the outcomes of totally transoral video-assisted thyroidectomy.Methods Clinical data of 37 cases of totally transoral video-assisted thyroidectomy from November 2011 to April 2013 at Zhongshan Hospital,Xiamen University were analyzed retrospectively.Results All cases underwent totally transoral video-assisted thyroidectomy successfully with a mean operation time of 109.5 min,blood loss of 15-60 ml,the mean postoperative hospital-stay was 3.5 days.The postoperative complications included infection in three cases,nasal congestion in one case,transient dysosphresia in one case.All were subject to symptomatic management and were recovered.There were no postoperative hoarse voice,secondary bleeding nor hematoma.With a follow-up of 0.5 to 15 months,no adverse events were found in all cases,patients were satisfied with the cosmetic result of the operation.Conclusions Totally transoral video-assisted thyroidectomy (TOVAT) is a safe and effective technique with the advantages of minor injury,quicker recovery,fewer complications and good cosmetic effect. Key words: Thyroid diseases ; Thyroidectomy ; Surgical procedures,minimally invasive
Twitter Sentiment Analysis Using Adaboost Classification

: In this paper, we study into the benefits of expressive features for recognizing the sentiment of Twitter messages i.e. Tweets. We analyse the effectiveness of existing lexical resources and additionally features that take information about the casual and innovative language used in Twitter. In this paper take a supervised classification approach to the problem, but authority obtaining hashtags into Twitter data for establishment training data
CARBON NANOTUBES: A RELIABLE ADDITIVE FOR THE NATURAL FIBER-REINFORCED COMPOSITES

Natural fiber-reinforced composites (NFRCs) has been proven to be the best alternative for synthetic fibers considering cost and environmental impacts. However, the main concerns faced by NFRCs are that they don’t show satisfactory mechanical properties, exhibit poor acoustic absorption notably in lower frequency spectrums, sensitive to microbial attack and offer poor resistance to heat and flame. In order to address the above concerns, Carbon Nanotubes (CNTs) can be an effective solution that can be added as an additive to NFRCs. The trend of adding CNTs to the NFRCs has been initiated earlier. However, this process has not been explored for many applications. This review covers the effect of CNTs on the mechanical properties of the NFRCs. Addition of CNTs to the composite exceptionally increases the mechanical properties of them due to their stronger interfacial bonding, catalytic reactions, and well dispersion. A decrease in mechanical properties was mainly due to the agglomeration of CNTs in the composite. This review also explains the other advantages of CNTs in different composites. In an overall basis, this review recommends, CNTs as a reliable additive for enhancing the various properties of the NFRCs.
A Novel Approach for Recommendation Based On Collaborative Filtering

– Recommendation is a technique used for determining an individual’s interest in products, services, e-reading etc. Based on that interest recommendations are given to a target user. There are various approaches present in the literature for recommendation but generally collaborative filtering, content-based filtering and hybrid methods are used. All these techniques suffer from some drawbacks such as cold start, sparsity, accuracy etc. Collaborative filtering is the most widely used method for recommendation because of ease and quality. This paper provides a novel approach which solves some of the drawbacks in the technique and provide better recommendations.
Behavioral and Demographic Antecedents to Household Food Waste

Researches about antecedents to household food waste generation are increasingly becoming popular. Various dimensions, such as food handling, purchasing behavior, waste management behavior, consumer values, the role of external cues and many other sets of predictors, including demographic variables, were identified by scholars as major influencers of food waste generation. However, there are conflicting inferences about the identified antecedents just as there remains no consensus as to how age, gender and income affect food waste. Moreover, there is limited number of literature on the influence of consumer values on food waste and in view of the local context. With the objective of augmenting extant literature, a survey of 180 primary purchasers of households was conducted, utilizing Partial Least Square Structural Equation Modelling (PLS-SEM) as a statistical tool. Findings of this research reveal that food habits, such as food conservation and response to food condition the acceptance of expiration date-based priced and suboptimal food, are very important to determine the extent of food waste generation. Environmental concern shows a positive effect on materialism, which supports literature positing that people who expressed deep environmental concern do not necessarily have low materialistic values and vice versa. Environmental concern could be a normative belief, which is an individuals perception of peoples expectations that are socially accepted and desirable. Thus, the respondents may have an environmental concern because this is the right behavior, but this does not hinder individuals in satisfying their material life domain.
Understanding Data Analysis Workflows on Spreadsheets: Roadblocks and Opportunities

Spreadsheets are widely used for data management and analysis by individuals and teams with varying degrees of programming expertise across a spectrum of domains. While several papers have studied the prevalence of errors on spreadsheets and performed ethnographic studies on spreadsheet use, little is known about how spreadsheet users approach and address computational tasks on spreadsheets, especially on relatively large datasets. To understand how users analyze data on spreadsheets, we conducted a study consisting of eight common analytical tasks, with thirty-two participants. Participants developed an execution strategy for each task and then attempted to operationalize this strategy within the spread-sheet system. From examining the study results and transcripts, we identified the successful and unsuccessful strategies participants adopted in addressing the tasks. In general, we find that unsuccessful spreadsheet users had difficulties mapping spreadsheet models to their predetermined execution strategies, comprehending online help documents when trying to learn how to use new formulae, and identifying workarounds when confronted with roadblocks. We identify opportunities to reduce barriers in computational task completion, including improvements to the spreadsheet interface and better training/educational methodologies and tools.
Study of Nd Deposition onto W and Mo Cathodes from Molten Oxide-Fluoride Electrolyte

Electrochemical reduction processes of Nd(III) on tungsten and molybdenum electrodes in NdF 3 +LiF and NdF 3 +LiF+Nd 2 O 3 were investigated by cyclic voltammetry, chronoamperometry and open circuit measurements. Electrolytes and electrodes were examined after neodymium electrodeposition by optical microscopy and XRD. It was found that tungsten and molybdenum working electrodes behave identically during neodymium complexed ion reduction processes. Their reversible potentials in the electrolytes used differed only by 10 mV, and so did the potentials of the neodymium ion reduction processes. The recorded results indicated that the Nd(III) ions in the melts were reduced in two steps: Nd(III) → Nd(II) and Nd(II) → Nd(0). These consecutive processes are predominantly mass transfer controlled. Electrolytically obtained metal appeared to accumulate on the cathode and no metal neodymium was recorded in the solidified electrolyte placed close to the cathode after completed electrodeposition process. However, it was found that NdF 2 formed by the disproportionation reaction between Nd(III) and that deposited Nd(0) coexists with other complex components in the electrolytes used.
iSmartML : An Interactive and User-Guided Framework for Automated Machine Learning

Recently, several automated machine learning (AutoML) approaches have been developed to automate the process of building machine learning pipelines without any human intervention. In practice, completely excluding the human from the loop creates several limitations. For example, most of these approaches ignore the user-preferences on defining or controlling the search space which consequently can impact the acceptance of the returned models by the end-users. In addition, these approaches are not interactive in a way that forces the users to passively wait till the end of the allocated time budget to receive the results of the automated search process without any ability to monitor or understand the search process. Furthermore, these solutions require the user to define non-straightforward parameters (e.g., time budget). To address these limitations, we demonstrate iSmartML , an interactive and user-guided framework for automating the machine learning modeling process. Our framework is designed to support the end-users in defining and refining the search space of the AutoML process. In addition, it provides the ability of explaining and understanding the results. The framework is also designed to allow its users to monitor the progress of the search process and reports a stream of models with alerts whenever a better pipeline is found during any point of the allocated time budget for the search process. Moreover, the framework is equipped with a recommendation engine that helps the end-users to define the effective search space and the adequate time budget of the AutoML process. Furthermore, the framework is equipped with a logging mechanism so that repeated runs on the same dataset can be more effective by avoiding exploring the same candidate configurations on the search space. We show that our framework can significantly improve the utility and usability of the automated machine learning process.
Neutrophil-to-lymphocyte ratio and pulse wave velocity in patients with controlled systemic hypertension — a preliminary report

Background. Increased arterial stiffness assessed by pulse wave velocity (PWV) measurement is a marker of arterial wall dysfunction and has an independent predictive value for adverse cardiovascular outcomes. A positive correlation between the neutrophil-to-lymphocyte ratio (NLR) and PWV has been reported in chronic inflammatory conditions and the general population as well. Furthermore, an association between NLR and PWV has been assumed in hypertensive patients. However, the available data are scarce. The objective of the study was to validate the association between NLR and PWV in a homogenous group of controlled-hypertensive patients without chronic inflammatory conditions. Material and methods. A retrospective observational study was conducted in outpatient cardiology and a general practice. A total number of 25 already on-target treated essential hypertensive, non-diabetic and non-chronic kidney disease (non-CKD) patients were selected. PWV was automatically calculated for each patient using the ABPM BPLab® device. The following laboratory data were collected: complete blood count, fibrinogen, alkaline phosphatase, lactate dehydrogenase, uric acid, serum glucose, total cholesterol, triglycerides, iron, calcium, and creatinine. Neutrophil-to-lymphocyte ratio was calculated. Antihypertensive treatment classes were also assessed. Results. A correlation between increased NLR and PWV in a homogenous group of controlled-hypertensive patients was identified. Conclusions. There is an evident relation between increased NLR and increased PWV in controlled hypertensive patients without evidence of chronic inflammatory conditions.
Laparoscopic versus Open Surgery in Lateral Lymph Node Dissection for Advanced Rectal Cancer: A Meta-Analysis

Aim To compare the clinical efficacies between laparoscopic and conventional open surgery in lateral lymph node dissection (LLND) for advanced rectal cancer. Methods We comprehensively searched PubMed, Embase, Cochrane Library, CNKI, and Wanfang Data and performed a cumulative meta-analysis. According to inclusion criteria and exclusion criteria, all eligible randomized controlled trials (RCTs) or retrospective or prospective comparative studies assessing the two techniques were included, and then a meta-analysis was performed by using RevMan 5.3 software to assess the difference in clinical and oncological outcomes between the two treatment approaches. Results Eight studies involving a total of 892 patients were finally selected, with 394 cases in the laparoscopic surgery group and 498 cases in the traditional open surgery group. Compared with the traditional open group, the laparoscopic group had a longer operative time (WMD = 81.56, 95% CI (2.09, 142.03), P = 0.008), but less intraoperative blood loss (WMD = −452.18, 95% CI (-652.23, -252.13), P < 0.00001), shorter postoperative hospital stay (WMD = −5.30, 95% CI (-8.42, -2.18), P = 0.0009), and higher R0 resection rate (OR = 2.17, 95% CI (1.14, 4.15), P = 0.02). There was no significant difference in the incidence of surgical complications between the two groups (OR = 0.52, 95% CI (0.26, 1.07), P = 0.08). Lateral lymph node harvest, lateral lymph node metastasis, local recurrence, 3-year overall survival, and 3-year disease-free survival did not differ significantly between the two approaches (P > 0.05). Conclusion Laparoscopic LLND has a similar efficacy in oncological outcomes and postoperative complications to the conventional open surgery, with the advantages of reduced intraoperative blood loss, shorter postoperative hospital stay, and higher R0 resection rate, and tumor radical cure is similar to traditional open surgery. Laparoscopic LLND is a safe and feasible surgical approach, and it may be used as a standard procedure in LLND for advanced rectal cancer.
A comparative evaluation of presence‐only methods for modelling species distribution

In spite of increasing application of presence‐only models in ecology and conservation and the growing number of such models, little is known about the relative performance of different modelling methods, and some of the leading models (e.g. GARP and ENFA) have never been compared with one another. Here we compare the performance of six presence‐only models that have been selected to represent an increasing level of model complexity [BIOCLIM, HABITAT, Mahalanobis distance (MD), DOMAIN, ENFA, and GARP] using data on the distribution of 42 species of land snails, nesting birds, and insectivorous bats in Israel. The models were calibrated using data from museum collections and observation databases, and their predictions were evaluated using Cohen's Kappa based on field data collected in a standardized sampling design covering most parts of Israel. Predictive accuracy varied between modelling methods with GARP and MD showing the highest accuracy, BIOCLIM and ENFA showing the lowest accuracy, and HABITAT and DOMAIN showing intermediate accuracy levels. Yet, differences between the various models were relatively small except for GARP and MD that were significantly more accurate than BIOCLIM and ENFA. In spite of large differences among species in prevalence and niche width, neither prevalence nor niche width interacted with the modelling method in determining predictive accuracy. However, species with relatively narrow niches were modelled more accurately than species with wider niches. Differences among species in predictive accuracy were highly consistent over all modelling methods, indicating the need for a better understanding of the ecological and geographical factors that influence the performance of species distribution models.
Consumers’ Preference for User-Designed Versus Designer-Designed Products: The Moderating Role of Power Distance Belief

Anecdotal evidence and extant research show that consumers can prefer both user-designed and designer-designed products. However, the factors that moderate such preferences are not well understood. The authors posit power distance belief (PDB) as a moderator such that low-PDB consumers prefer user-designed to designer-designed products because they identify more with user-driven companies. In contrast, high-PDB consumers prefer designer-designed to user-designed products due to their stronger trust in designer-driven companies. Six studies examining power distance belief at both the country and individual levels provide convergent support for the proposed moderating effect of PDB and underlying mechanisms. Furthermore, the authors demonstrate that the interaction between design philosophy and PDB is more likely for low-complexity than high-complexity products.
Effect of pH on flux during ultrafiltration of sweet whey and buttermilk

Summary The flux patterns for sweet whey and buttermilk were strongly influenced by pH. Increasing the pH of buttermilk from 6·6 to 8·0 tended to reduce initial flux values and reduce deposit formation on the membrane as indicated by lower values for the fouling coefficient. Flux was mostly controlled by concentration polarization. Reducing the pH below 6·6 increased the flux but caused more deposit on the membrane as indicated by high fouling coefficient values. Almost the opposite was found for sweet whey. The initial flux increased as pH increased, followed by considerable flux decline, which was linked to greater fouling of the membrane. Reducing the pH reduced the initial flux considerably but also reduced further fouling. These changes are thought to be brought about by the combined effects of pH change on the proteins and minerals, and in particular on calcium.
Extrapolation Accelerated PRESB Method for Solving a Class of Block Two-By-Two Linear Systems

We use extrapolation acceleration technique to speed up the preconditioned square block matrix splitting iteration method for two-by-two block linear systems. It is shown that for relaxation parameter ω = 4/3, the convergence factor of the iteration method under consideration is 1/3. This yields the robustness and efficiency of the method. Numerical examples confirm the theoretical results and demonstrate the effectiveness of the approach developed. AMS subject classifications: 65F10, 65F50, 65W05