Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of proliferating cell nuclear antigen and Ki-67 in renal cell carcinoma in eastern Indian patients

Background: Several molecular markers play important role in development and prognosis of renal cell carcinoma (RCC). Proliferating cell nuclear antigen (PCNA) and Ki-67 are such kind of molecular markers which may have prognostic significance in RCC and need to be studied about. Estimation of proliferation index by immunohistochemical expression analysis of PCNA and Ki-67 at different clinical stages of RCC samples and correlations of expression of the genes with different clinicopathological parameters between tumour tissue cells and adjacent normal tissue cells were the objectives.Methods: Thirty two patients of RCC who had been operated at one tertiary care institute of eastern India were taken for the study. Histopathological and immunohistochemistry analysis of PCNA and Ki-67 from tumour tissue and normal tissue were done. Patients who received radiotherapy, chemotherapy etc. before operation and who had benign tumours of the kidney in histopathological examination were excluded from the study.Results: Mean PCNA expression in normal renal tissue is 4.54%; whereas the clear cell RCC, papillary RCC and chromophobe RCC showed 49.81%, 50.75% and 66.50% of mean PCNA expression respectively. Mean expression of Ki-67 in normal tissues was 1.75%. Whereas the clear cell RCC, papillary RCC and chromophobe RCC showed 23.96%, 24.75% and 31% of mean Ki-67 expression respectively. Both molecular markers were positively correlated overall.Conclusions: PCNA and Ki-67 expression is increased in RCC when compared with normal tissues and it increases with Stage of RCC. PCNA expression is positively correlated with Ki-67 in different stages and histopathological groups of RCC.
Development of the Non-Iterative Supervised Learning Predictor Based on the Ito Decomposition and SGTM Neural-Like Structure for Managing Medical Insurance Costs

The paper describes a new non-iterative linear supervised learning predictor. It is based on the use of Ito decomposition and the neural-like structure of the successive geometric transformations model (SGTM). Ito decomposition (Kolmogorov–Gabor polynomial) is used to extend the inputs of the SGTM neural-like structure. This provides high approximation properties for solving various tasks. The search for the coefficients of this polynomial is carried out using the fast, non-iterative training algorithm of the SGTM linear neural-like structure. The developed method provides high speed and increased generalization properties. The simulation of the developed method’s work for solving the medical insurance costs prediction task showed a significant increase in accuracy compared with existing methods (common SGTM neural-like structure, multilayer perceptron, Support Vector Machine, adaptive boosting, linear regression). Given the above, the developed method can be used to process large amounts of data from a variety of industries (medicine, materials science, economics, etc.) to improve the accuracy and speed of their processing.
Development and Analysis for a New Compliant XY Micropositioning Stage Applied for Nanoindentation Tester System

A Compliant XY micropositioning stage is purported for situating a material sample in nanoindentation tester process. This paper aims to develop, analyze and optimize a XY compliant micropositioning stage. The working stroke of proposed XY stage is amplified by combining the four-lever and a bridge amplification mechanism. To enhance the performances of the stage, the main geometric parameters are optimized by an integration method of Taguchi method, response surface method (RSM) and genetic algorithm (GA). Firstly, static analysis and dynamic analysis are conducted by the finite element analysis in order to predict initial performances of the XY stage. Secondly, the number of experiments and the data are retrieved by combination of the finite element analysis-integrated Taguchi method. Thirdly, the effects of main design variables on the output response sensitivity are considered. Later on, mathematical model for the amplification ratio was established by the RSM. Finally, based on the mathematical equation, the GA is adopted to define the optimal design variables. The results of numerical validations are in a good agreement with the predicted results. The results depicted that the proposed hybrid approach ensures a high reliability for engineering optimization problems.
Hydrogel scaffolds for tissue engineering: the importance of polymer choice

Hydrogel scaffolds that can repair or regrow damaged biological tissue have great potential for the treatment of injury and disease. These biomaterials are widely used in the tissue engineering field due to their ability to support cell proliferation, migration and differentiation, to permit oxygen and nutrient transport, and to mimic native soft tissue. Careful design of the underlying polymer scaffold is therefore vital, dictating both the physical and biological properties of a hydrogel. In this review, we will provide a critical overview of hydrogel design from the perspective of the polymer chemistry, highlighting both the advantages and limitations of particular polymer structures, properties, and architectures. In doing so, we will help equip researchers with the tools needed to design new polymer systems and hydrogel scaffolds that address current limitations in the field and hinder clinical translation.
Augmentation of Fractional-Order PI Controller with Nonlinear Error-Modulator for Enhancing Robustness of DC-DC Boost Converters

This paper presents a robust-optimal control strategy to improve the output-voltage error-tracking and control capability of a DC-DC boost converter. The proposed strategy employs an optimized Fractional-order Proportional-Integral (FoPI) controller that serves to eliminate oscillations, overshoots, undershoots and steady-state fluctuations. In order to significantly improve the error convergence-rate during a transient response, the FoPI controller is augmented with a pre-stage nonlinear error-modulator. The modulator combines the variations in the error and error-derivative via the signed-distance method. Then it feeds the aggregated-signal to a smooth sigmoidal control surface constituting an optimized hyperbolic secant function. The error-derivative is evaluated by measuring the output-capacitor current in order to compensate the hysteresis effect rendered by the parasitic impedances. The resulting modulated-signal is fed to the FoPI controller. The fixed controller parameters are meta-heuristically selected via a Particle-Swarm-Optimization (PSO) algorithm. The proposed control scheme exhibits rapid transits with improved damping in its response which aids in efficiently rejecting external disturbances such as load-transients and input-fluctuations. The superior robustness and time-optimality of the proposed control strategy is validated via experimental results.
Difference in general behaviour and social interactions of young Yorkshire gilts in different social environments

In Sweden, there was a switch of breeding material for pigs in year 2012 where Swedish producers were introduced to the Dutch Yorkshire (DY) instead of the Swedish Yorkshire (SY). Gestating sows have, in Sweden, been kept in group housing since the 1980s while DY gilts on the contrary have been kept in individual stalls. Consequently, the genetic selection of these lines of Yorkshire pigs was conducted in different environments and are thus indirectly selected for behaviours beneficial for each respective environment. This may induce behavioural differences between them, which may be of importance in group housing systems. In the wild, piglets usually have the opportunity to socialise with other pigs outside the litter and piglets that can socialise outside the litter have better social skills later in life. Piglets that do not have the opportunity to engage in social interactions outside the litter may behave differently than piglets that have that opportunity. This Master thesis is a part of an ongoing project “Improving sow welfare in group housing systems” which aims to develop commercially relevant and sustainable breeding and rearing strategies for sows in group housing systems. The aims of this MSc thesis were to investigate if there is a difference in behaviours and social interactions between young gilts with two different lines of Yorkshire breeds and if the behaviours and social interactions are affected if they have the opportunity to socialise outside the litter during an early socialisation period. Direct observations where performed on 118 gilts where half were of the breed SY (49 gilts) and the other half DY (56 gilts). Approximately half of both breeds had access to the neighbouring pen during the last four weeks of the nursing period. Scan sampling was used to record different variables for body position, location in pen and activity. Continuous observations were performed for two minutes per animal on each observation occasion to record social interactions and stereotypes. Overall, the results displayed some behavioural differences between both breeds and treatments. In general behaviour, SY gilts were more active than DY gilts. In addition, gilts of the breed SY performed more social nosing and nosing belly region then DY gilts. Regarding receiving pig behaviour, gilts of the breed SY responds to a performing pigs’ social interaction with no reaction in a larger proportion of the observation occasions in comparison with gilts with the breed DY. Regarding different treatments, gilts held in an access pen (AP) slept less and were more active directly after weaning (when the pop holes were closed). It was also found that AP stimulates the gilts to perform a larger variation in social behaviours and showing different types of behaviours to a larger extent. The largest differences in behaviours occurred around weaning. This study includes the first steps of mapping differences in behaviours during early socialisation between these breeds and treatments, but further studies need to be done on the long-term effects.
Facile Synthesis of Co3O4 Nanoparticle-Functionalized Mesoporous SiO2 for Catalytic Degradation of Methylene Blue from Aqueous Solutions

In this study, a series of Co3O4 nanoparticle-functionalized mesoporous SiO2 (Co–SiO2) were successfully synthesized via a spontaneous infiltration route. Co species were firstly infiltrated into the confined spaces between the surfactant and silica walls, with the assistance of grinding CoCl3·6H2O and the as-prepared mesoporous SiO2. Then, Co3O4 nanoparticles (NPs) were formed and grown in the limited space of the mesopores, after calcination. Structures, morphologies, and compositions of the materials were characterized by X-ray diffraction, transmission electron microscopy, energy dispersion spectrum, N2 adsorption, and Fourier transform infrared spectra. Results showed that the high content of Co (rCo:Si = 0.17) can be efficiently dispersed into the mesoporous SiO2 as forms of Co3O4 NPs, and the structural ordering of the mesoporous SiO2 was well-preserved at the same time. The Co3O4 NP functionalized mesoporous SiO2 materials were used as Fenton-like catalysts for removing methylene blue (MB) from aqueous solutions. The catalyst prepared at rCo:Si = 0.17 could completely remove the high-concentration of MB (120 mg·L−1), and also showed an excellent performance with a removal capacity of 138 mg·g−1 to 180 mg·L−1 of MB. Catalytic mechanisms were further revealed, based on the degradation results.
Can Video-based Qualitative Analysis Help Us Understand User-algorithm Interaction?

There is growing debate in contemporary life over the roles played by algorithms when we browse online. In particular, concerns are raised that algorithmic processes to index, filter and personalise content can ‘manipulate’ user behaviours in ways that lead to detrimental outcomes both online and offline. This short paper reports on ongoing work to examine how users interact with algorithms when undertaking browsing tasks online. Drawing on insights from ethnomethodology and conversation analysis, this video-based approach produces rich and detailed observations of user behaviour and reveals several relevant patterns of interest. Our findings highlight that both user-algorithm interaction and users’ own practical reasoning play key roles in shaping the browsing experience.
A Cognitive Model of the Control of Unmanned Aerial Vehicles

We describe a workload model of a single pilot unmanned aerial vehicle (UAV) control, which can provide the basis for extension to multiple UAV control and supervision. The model predicts multi-task capabilities based upon the multiple-resource model of human time sharing. Elements of the model are described related to task demand, resource conflict, and resource allocation (task priority). We then demonstrate its applicability to predicting pilot performance in the MQ-1 Predator, describing the “workload spikes” during a typical mission, and demonstrating ways in which high workload can be mitigated.
Random-forest-based failure prediction for hard disk drives

Failure prediction for hard disk drives is a typical and effective approach to improve the reliability of storage systems. In a large-scale data center environment, the various brands and models of drives serve diverse applications with different input/output workload patterns, and non-ignorable differences exist in each type of drive failures, which make this mechanism much challenging. Although many efforts are devoted to this mechanism, the accuracy still needs to be improved. In this article, we propose a failure prediction method for hard disk drives based on a part-voting random forest, which differentiates prediction of failures in a coarse-grained manner. We conduct groups of validation experiments on two real-world datasets, which contain the SMART data of 64,193 drives. The experimental results show that our proposed method can achieve a better prediction accuracy than state-of-the-art methods.
Maturation of Neuronal Activity in Caudalized Human Brain Organoids

Human brain organoids are an emerging tool to study functional neuronal networks in health and disease. A critical challenge is the engineering of brain organoids with defined regional identity and developmental stage. Here we describe a protocol for generating hindbrain-like organoids from human pluripotent stem cells. We first generated a stable pool of caudalized stem cells that expressed hindbrain identity transcription factors and differentiated into tissue containing neurons and astrocytes. After maturation, caudalized brain organoids presented synaptically connected networks consisting of glutamate-, GABA-, and serotoninergic postmitotic neurons. These mature neurons displayed electric properties and dendritic trees resembling medulla oblongata neurons. They fired spontaneous and evoked repetitive action potentials, released serotonin and displayed excitatory and inhibitory synaptic currents, functionally resembling the activity patterns observed in normal human fetal brain. Reminiscent of infected human fetal brain, infection with Zika virus hampered organoid development, while the treatment with anticonvulsant drugs - carbamazepine and valproic acid - reduced organoid growth. Neuronal maturation also occurred in the grafted organoids in vivo. In conclusion, our approach enables efficient derivation of caudalized neuronal stem cells that differentiate into mature and functional neurons in organoids with hindbrain identity following human developmental trajectory. The organoids provide excellent model to study congenital abnormalities in brain development and for drug testing.
Effect of Copper Supplementation with Different Energy Levels on Broilers: (A) - Productive Performance

An experiment was conducted to determine the effect of dietary supplementation of two Cu sources: inorganic (copper sulfate) and organic (copper yeast) with different levels of metabolizable energy on productive performance of broiler chickens. Three dietary metabolizable energy levels were used in starter period from 1 to 28 days old (2900, 2800 and 3000 kcal/kg); the corresponding values in finisher period (29 to 42 days old) were 3000, 2900 and 3100 kcal/kg, respectively. One-day-old Cobb broiler chicks were randomly assigned into nine experimental groups, each with three replicate groups. Diets containing 2900 and 3000 kcal ME were used as controls for the starter and finisher periods, respectively. In the starter diets (2800 and 3000 kcal ME/kg) Cu was supplemented at 50 and 100 mg/kg as copper yeast and at 50 and 100 mg/kg as copper sulfate. In the finisher diets (2900 and 3100 kcal ME/kg) the same sources and levels of Cu were added. During the whole experimental period, dietary supplementation with organic and inorganic copper caused a significant increase in LBW of birds compared with their controls. Birds fed the high ME diets plus Cu yeast consumed significantly less feed compared with the control group, but chicks fed the low ME diets plus copper consumed approximately similar amounts of feed compared with the control. Birds fed the high ME diets plus organic or inorganic copper displayed significantly better FCR than the control. Dietary Cu supplementation had no significant effect on carcass yield of broilers, expect those fed the high ME diet plus 100 ppm Cu yeast which exhibited significantly higher carcass yield compared with their control group. Birds fed the low ME diets plus 50 ppm Cu yeast or 100 ppm CuSO4 and those fed the high ME diets plus 100 ppm Cu yeast and those given diets plus 50 or 100 ppm CuSO4 displayed significantly higher total edible parts compared with the control group. Broiler fed diets containing the high ME diets supplemented with 50 or 100 mg/kg organic copper had higher means of net revenue and economic efficiency compared with the control birds. It can be concluded that birds fed the high ME diets plus 100 ppm organic copper can improve productive performance of broilers.
MapReduce‐based storage and indexing for big health data

Locality Sensitive Hashing (LSH) uses randomized method to alleviate Nearest Neighbor Search issue in high dimensional spaces. However, handling of big dataset samples for LSH algorithm becomes difficult task because of computational complexity. So, the major aim of this work is to introduce a new LSH algorithm with Hadoop MapReduce framework for enhancing proficiency of arbitrary reads over big dataset samples. The proposed Hash index improves efficiency by reducing the amount of accessing data for range queries by creating buckets based on hyperplanes. A LSH on MapReduce is developed, which decreases the random data access time among map and reduce functions, in addition, it enhances proficiency. Lastly, with the aim of validating the performance of presented index for search query in MapReduce, five performance metrics such as changing cluster size, LSH for Bucket size Balancing, the overlapped boundary of a hyperplane, Bucket creation based on the configured capacity, and non‐indexed, Hash index, and global indexed dataset on the HDFS configured capacity are utilized. The effect of these metrics on dataset on the HDFS configured capacity for the period of map and reduce functions as well depicts the pre‐eminence of the presented Hash index.
The occurrence of chlorophenols, chlorocatechols and chlorinated methoxyphenols in drinking water of the largest cities in Poland

The purpose of this work was to determine the occurrence of phenol, chlorophenols, chlorocatechols and chlorinated methoxyphenols in the drinking water of the Polish cities of Łodź (Lodz), Warszawa (Warsaw), Poznan and Wroclaw. The compounds were adsorbed on octadecyl (C18) layer in a Baker-Separex system and eluted with methylene chloride, then analyzed using the methods of gas chromatography and mass spectrometry. In samples, chlorophenols, 4-chlorocatechol, chloroguaiacols, chlorosyringols and 5,6dichlorovaniline were detected. Higher concentrations and number of chlorophenols and their chlorinated derivatives were noted in summer. Among the most toxic compounds, 2,4,5-trichlorophenol in drinking water of Warszawa (summer and winter) and Łodź (winter) and tetrachlorophenol in water of Wroclaw (summer) were noted. Their concentrations were above the admissible standards of the EU and the US EPA. In some cases the concentrations of chloroguaiacols and 5,6-dichlorovanillin also were significant.
Détection et caractérisation de défauts de surface par analyse des nuages de points 3D fournis par un scanner

We have developed a software for the detection and characterisation of defects based on the analysis of 3D point clouds provided by a scanner. This software has been developed within an industrial application dealing with the control of an aircraft fuselage surface. It could be also used for other applications like the detection of defects on a car body surface.
Assessment of orange fruit colonization by biocontrol yeasts

A scanning electron microscope study of citrus fruits was performed to assess the colonization process of antagonistic yeasts to green mould of Tarocco oranges under artificial inoculation. Yeast suspensions of Debaryomyces hansenii DBVPG 4025, Pichia guilliermondii NRRL Y 18134, P. anomala J121 and Saccharomyces cerevisiae P1.6 with or without addition of 1% CaCl2 + 0.1% Tween 80 were evaluated. Penicillium digitatum was sprayed one hour later. Observation of fruit surface waxes revealed marked morphological diversity. Yeast cells and conidia were mostly localized on epicuticular waxes, particularly in naturally occurring small pits. The size of the wound affected the number of yeasts and conidia penetrating inside. Treatment with CaCl2 did not affect the waxes and/or the behaviour of the yeasts and pathogen.
Retrieval of Scholarly Articles with Similar Core Contents

Article history: Received 13 April 2017 Revised 29 July 2017 Accepted 01 August 2017 Retrieval of scholarly articles about a specific research issue is a routine job of researchers to cross-validate the evidence about the issue. Two articles that focus on a research issue should share similar terms in their core contents, including their goals, backgrounds, and conclusions. In this paper, we present a technique CCSE (Core Content Similarity Estimation) that, given an article a, recommends those articles that share similar core content terms with a. CCSE works on titles and abstracts of articles, which are publicly available. It estimates and integrates three kinds of similarity: goal similarity, background similarity, and conclusion similarity. Empirical evaluation shows that CCSE performs significantly better than several state-of-the-art techniques in recommending those biomedical articles that are judged (by domain experts) to be the ones whose core contents focus on the same research issues. CCSE works for those articles that present research background followed by main results and discussion, and hence it may be used to support the identification of the closely related evidence already published in these articles, even when only titles and abstracts of the articles are available.