Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of anastrozole loaded PEG-PLA nanoparticles: evaluation of apoptotic response of breast cancer cell lines

Purpose Anastrozole (ANS) is an aromatase inhibitor that is widely used as a treatment for breast cancer in postmenopausal women. Despite the wide use of ANS, it is associated with serious side effects due to uncontrolled delivery. In addition, ANS exhibits low solubility and short plasma half-life. Nanotechnology-based drug delivery has the potential to enhance the efficacy of drugs and overcome undesirable side effects. In this study, we aimed to prepare novel ANS-loaded PLA-PEG-PLA nanoparticles (ANS-NPs) and to compare the apoptotic response of MCF-7 cell line to both ANS and ANS-loaded NPs. Method ANS-NPs were synthesized using double emulsion method and characterized using different methods. The apoptotic response was evaluated by assessing cell viability, morphology, and studying changes in the expression of MAPK3, MCL1, and c-MYC apoptotic genes in MCF-7 cell lines. Results ANS was successfully encapsulated within PLA-PEG-PLA, forming monodisperse therapeutic NPs with an encapsulation efficiency of 67%, particle size of 186±27.13, and a polydispersity index of 0.26±0.11 with a sustained release profile extended over 144 hours. In addition, results for cell viability and for gene expression represent a similar apoptotic response between the free ANS and ANS-NPs. Conclusion The synthesized ANS-NPs showed a similar therapeutic effect as the free ANS, which provides a rationale to pursue pre-clinical evaluation of ANS-NPs on animal models.
Integration Between Agents and Remote Ontologies for the Use of Content on the Semantic Web

The Semantic Web proposes a structure of significant content for Web pages that is used in knowledge bases and developed from ontologies, that have recently come to coexist on the Web. There are studies to allow agents to navigate through these knowledge bases in search of answers to queries. This work proposes the adaptation of a well-known agent structure, named Jason, in order to allow the agent access to ontologies available on the Web. In this context, efforts have been made to perform the integration of agents with ontologies, most of which allow the knowledge of the agent to be based on a local ontology. However, applying the ability to use semantic data available on the Web to a consolidated belief-desire-intention (BDI) agent structure is a subject that still needs to be explored. Therefore, this work proposes changes in the implementation of the Jason interpreter that would allow agents to access ontologies available on the Web to perform the update of their belief base based on significant content. As validation, a case study of an educational quiz is presented that uses this information to formulate the questions and validate the answers
Optimizing Convolutional Neural Networks on the Sunway TaihuLight Supercomputer

The Sunway TaihuLight supercomputer is powered by SW26010, a new 260-core processor designed with on-chip fusion of heterogeneous cores. In this article, we present our work on optimizing the training process of convolutional neural networks (CNNs) on the Sunway TaihuLight supercomputer. Specifically, a highly efficient library (swDNN) and a customized Caffe framework (swCaffe) are proposed. Architecture-oriented optimization methods targeting the many-core architecture of SW26010 are introduced and are able to achieve 48× speedup for the convolution routine in swDNN and 4× speedup for the complete training process of the VGG-16 network using swCaffe, compared to the unoptimized algorithm and framework. Compared to the cuDNN library and the Caffe framework based on the NVIDIA K40m GPU, the proposed swDNN library and swCaffe framework on SW26010 have nearly half the performance of K40m in single -precision and have 3.6× and 1.8× speedup over K40m in double precision, respectively.
Investigation of a new fracture mechanics specimen for thin film adhesion measurement

We have investigated mechanical probing of a precracked fine line structure as a new type of thin film fracture mechanics specimen. An idealized mechanics analysis is first presented. Experimentally, two types of precracks are formed. A thin carbon layer to which other layers weakly adhere creates a “processed precrack” by integrated circuit processing techniques. An “indented processed precrack” is formed by precision alignment of a sharp microwedge. The processed precrack is found to reduce the critical tangential load by 50% from a non-precracked line, while the indented processed precrack lowers the load by 200%. From this, a reasonable value of adhesion may be directly calculated. Crack path behavior is observed to depend on strength of the interface. In the case of a weak interface, the crack remains in the interface as it extends. For a strong interface, it kinks into the substrate if the crack is initially short, but remains in the interface if it is initially long. Given the experimental evidence, the mechanics are slightly modified to quantitatively model the experimental data.
Serum microRNAs – potent biomarkers for radiation biodosimetry

as are the regulatory mechanisms leading to differential expression of radiation-inducible miRNAs depending on sex and their complex interactions with radiation mitigating or radioprotective agents. Moreover, if the observed miRNAs are exosome-bound, they could actively participate in cell-to-cell transfer and play an active role in mitigating radiation-induced damage, rather than acting only as biomarkers. However, studies suggest that novel biodosimetric miRNA-based tools and even RNA-based drugs will be within our reach in the near future. Furthermore, the utility of miRNAs in detecting and quantifying radiation exposure may be potentially translated to the field of radiotherapy. Our clinical paper showed that circulating serum miRNA profile changes in response to the delivered dose of radiation of radiation in patients treated for lung cancer [7], while another report confirmed that miRNAs could be used in personalized radiotherapy to achieve the best tumor control with minimal healthy tissue toxicity [8]. Such studies are of utmost importance because normal tissue toxicity prevents dose escalation in patients undergoing radiotherapy.
Structural insight into GRIP1-PDZ6 in Alzheimer’s disease: study from protein expression data to molecular dynamics simulations

Protein–protein interaction domain, PDZ, plays a critical role in efficient synaptic transmission in brain. Dysfunction of synaptic transmission is thought to be the underlying basis of many neuropsychiatric and neurodegenerative disorders including Alzheimer’s disease (AD). In this study, Glutamate Receptor Interacting Protein1 (GRIP1) was identified as one of the most important differentially expressed, topologically significant proteins in the protein–protein interaction network. To date, very few studies have analyzed the detailed structural basis of PDZ-mediated protein interaction of GRIP1. In order to gain better understanding of structural and dynamic basis of these interactions, we employed molecular dynamics (MD) simulations of GRIP1-PDZ6 dimer bound with Liprin-alpha and GRIP1-PDZ6 dimer alone each with 100 ns simulations. The analyses of MD simulations of Liprin-alpha bound GRIP1-PDZ6 dimer show considerable conformational differences than that of peptide-free dimer in terms of SASA, hydrogen bonding patterns, and along principal component 1 (PC1). Our study also furnishes insight into the structural attunement of the PDZ6 domains of Liprin-alpha bound GRIP1 that is attributed by significant shift of the Liprin-alpha recognition helix in the simulated peptide-bound dimer compared to the crystal structure and simulated peptide-free dimer. It is evident that PDZ6 domains of peptide-bound dimer show differential movements along PC1 than that of peptide-free dimers. Thus, Liprin-alpha also serves an important role in conferring conformational changes along the dimeric interface of the peptide-bound dimer. Results reported here provide information that may lead to novel therapeutic approaches in AD.
Towards a capability approach to child growth: A theoretical framework

Abstract Child malnutrition is an important cause of under‐5 mortality and morbidity around the globe. Despite the partial success of (inter)national efforts to reduce child mortality, under‐5 mortality rates continue to be high. The multidimensional approaches of the Sustainable Development Goals may suggest new directions for rethinking strategies for reducing child mortality and malnutrition. We propose a theoretical framework for developing a “capability” approach to child growth. The current child growth monitoring practices are based on 2 assumptions: (a) that anthropometric and motor development measures are the appropriate indicators; and (b) that child growth can be assessed using a single universal standard that is applicable around the world. These practices may be further advanced by applying a capability approach to child growth, whereby growth is redefined as the achievement of certain capabilities (of society, parents, and children). This framework is similar to the multidimensional approach to societal development presented in the seminal work of Amartya Sen. To identify the dimensions of healthy child growth, we draw upon theories from the social sciences and evolutionary biology. Conceptually, we consider growth as a plural space and propose assessing growth by means of a child growth matrix in which the context is embedded in the assessment. This approach will better address the diversities and the inequalities in child growth. Such a multidimensional measure will have implications for interventions and policy, including prevention and counselling, and could have an impact on child malnutrition and mortality.
Fecal Calprotectin: A Comparison of Two Commercial Enzymoimmunoassays and Study of Fecal Extract Stability at Room Temperature

Background The aims of the study were: 1) to compare the fecal calprotectin (fCal) assay results with Calprolab™ ELISA (HRP) (Calpro AS) versus our routine method, Elia™ fluoroenzymoimmunoassay (Thermo Fisher), and 2) to determine whether the fCal assay results do not vary following storage of the extract at room temperature for 4 days with the Calpro AS buffer, this being the estimated shipment time from the home of the patient, and an aspect little studied to date. Methods The fCal was determined in 198 patients divided into three groups: inflammatory bowel disease (IBD), organic intestinal disease, and functional intestinal disorders. Fecal extraction was carried out using the Roche Diagnostics kit with the corresponding specific buffers. Results The fCal assay with the Thermo Fisher method was found to be more sensitive but less specific than with the Calpro AS technique. The positive predictive value was low (just over 50%), though the negative predictive value was high (over 90%) with both methods. The likelihood ratios revealed small but occasionally important pre- versus post-test differences. When we compared the two methods, the Spearman correlation coefficient (ρ) was 0.819 (95% CI: 0.768 - 0.860) (P < 0.0001), reflecting a positive correlation. Similarly, when stratifying the fCal results into < 50 µg/g, 50 - 100 µg/g and > 100 µg/g, the resulting Cohen’s kappa coefficient was 0.7766 (95% CI: 0.7025 - 0.8507), reflecting a substantial agreement between both methods. The stability of fCal was high in fecal extracts with the Calpro AS extraction buffer at room temperature for 4 days, which yielded a Spearman correlation coefficient of 0.951 (95% CI: 0.933 - 0.965), when the results were compared to those of the recent extracts (P < 0.0001). Conclusions A positive correlation was observed between the two methods. In view of the high negative predictive value obtained with fCal, the presence of organic disease is highly unlikely in the presence of a normal concentration of this marker. We also confirmed the excellent stability of fCal in fecal extracts with the Calpro AS extraction buffer stored at room temperature. Thus, and for the sake of convenience and hygiene, it would be ideal for the patient to perform the extraction at home.
Emotion Classification of Duterte Administration Tweets Using Hybrid Approach

Nowadays, people engage in social networking sites to gain information, share thoughts and ideas, and give reaction to certain topics. The works of Duterte Administration has been a hot topic in the country since the day it started its term. This research has gathered tweets and determined the emotions based on the Ekman's six basic emotion classification namely happiness, sadness, anger, fear, disgust, and surprise. A hybrid approach was used to determine the classification using lexicon-based and machine learning. Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC) were used to train the classifier. Result shows that SVM gains a higher accuracy of 80.48% over NBC. Most tweets result to anger and a few express surprises as classification of emotions.
Improved clonality detection in Hodgkin lymphoma using a semi‐nested modification of the BIOMED‐2 PCR assay for IGH and IGK rearrangements: A paraffin‐embedded tissue study

The BIOMED‐2 PCR protocols targeting IGH and IGK genes may be useful for detecting clonality in Hodgkin lymphoma (HL). The clonality detection rates, however, have not been very high with these methods using paraffin‐embedded tumor sections. We previously described the usefulness of the semi‐nested BIOMED‐2 IGH assay in B‐cell malignancies. In this study, we devised a novel semi‐nested BIOMED‐2 IGK assay. Employing 58 cases of classical HL, we carried out the standard BIOMED‐2, BIOMED‐2 followed by BIOMED‐2 re‐amplification, and BIOMED‐2 followed by semi‐nested BIOMED‐2, all targeting IGH and IGK, using paraffin‐embedded tissues. In both IGH and IGK assays, semi‐nested assays yielded significantly higher clonality detection rates than the standard assays and re‐amplification assays. Clonality was detected in 13/58 (22.4%) classical HL cases using the standard IGH/IGK assays while it was detected in 38/58 (65.5%) cases using semi‐nested IGH/IGK assays. The detection rates were not associated with the HL subtypes, CD30‐positive cell density, CD20‐positive cell density, or Epstein–Barr virus (EBV) positivity. In conclusion, tumor clonality was detected in nearly two‐thirds of classical HL cases using semi‐nested BIOMED‐2 IGH/IGK assays using paraffin tumor sections. These semi‐nested assays may be useful when the standard IGH/IGK assays fail to detect clonality in histopathologically suspected HLs.
A single-step trans-vertical epoxy preparation method for maximising throughput of iron-ore samples via SEM-MLA analysis

A novel approach to creating a trans-vertical grain mount embedded in epoxy has been demonstrated through the creation of a new mounting mould, as well as a polisher adapter and sample holder for the Quanta 400 SEM. These rectangular moulds result in a sample that is 30 mm long × 10 mm high × 17 mm wide, thus leading to the ability to polish 10 samples at once. Up to 14 samples may fit in the SEM holder for analysis. This represents an increase in efficiency of over 50%, and with a slow-speed polishing method, the consumables used are reduced by at least a factor of 4. This has the potential to lead to significant financial savings. A comparison of mounting techniques using a −100+200 mesh size fraction of an iron-ore sample from Labrador demonstrates that this new mounting system removes any bias in analysis resulting from density stratification during the sample preparation. These moulds yield similar modal mineralogy abundances and standard deviation as the two-step trans-vertical method, but they are less labour-intensive to make and more efficient to analyse.
A study on human-robot collaboration for table-setting task

As the robot technology is advancing, it is possible to use robots for basic day-to-day chores, so that the burden can be taken off from humans. To make the robots perform such tasks, it is necessary for them to handle different types of objects. Manipulation of deformable objects such as cloth is a challenging task for a robot because of high dimensionality and large number of possible configurations of cloth. Previous studies have covered large number of simple manipulations of cloth articles. In this paper, we are focusing on table setting task that requires putting on a sheet of cloth on the table. This paper proposes human-robot collaboration for table-setting task based on visual assessment. We used Baxter robot to hold two corners of rectangular tablecloth and other two corners are held by human. A head-mounted Kinect sensor is used to get the state of cloth and Robot arms are used for controlling the position of cloth corners. We use features from Kinect sensor to assess whether the placement of the cloth is successful or not. We demonstrate an initial study of the system that can achieve promising results towards table setting task through human-robot interaction.
A 4.2-mW 10-MHz BW 74.4-dB SNDR Continuous-Time Delta-Sigma Modulator With SAR-Assisted Digital-Domain Noise Coupling

This paper introduces a high-order continuous-time (CT) delta-sigma modulator (DSM) that applies digital-domain noise coupling (DNC) based on the structural advantages of the successive-approximation register (SAR) analog-to-digital converter (ADC), which makes the implementation of second-order noise coupling very simple. Due to digital-domain implementation as well as the SAR ADC where the key building blocks are embedded for the proposed DNC, compact size and efficient power consumption could be designed. For low circuit noise, a feedback DAC is implemented with a tri-level current-steering DAC. Tri-level data-weight averaging (TDWA) improves the linearity of the DAC. With the proposed DNC and TDWA, a prototype CT DSM fabricated in a 28-nm CMOS achieves a peak 74.4-dB SNDR and an 80.8-dB dynamic range (DR) for a 10-MHz BW with an oversampling ratio of 16, resulting in a Schreier FoMDR of 174.5 dB. The chip area occupies 0.1 mm2, and the power consumption is 4.2 mW.
Combining static and dynamic data flow analysis: a hybrid approach for detecting data leaks in java applications

Protecting sensitive data requires controlling the behavior of third part software. Static and dynamic data flow analysis can aid, however both of them have limits. Static analysis often detects false data leaks, whereas the more precise dynamic analysis introduces a significant overhead. This paper proposes a novel hybrid approach that combines static and dynamic data flow analysis for detecting data leaks in Java applications. Our approach minimizes the overhead by computing a minimal set of "application points" that need to be monitored and injects control code on the target application. Our method has no loss in quality with respect to dynamic analysis. We show the feasibility of our approach by providing a tool and presenting a case study on a sample application.
Seismic Column-to-Footing Connections Using Grouted Splice Sleeves

Mechanical couplers have been used in connections between prefabricated reinforced concrete elements. Grouted splice sleeves offer good construction tolerance and a bond related load transfer mechanism between the connecting members. The present study investigates the seismic performance of grouted splice sleeve connections with the connectors placed in the column or footing of bridge subassemblies, and intentional debonding of the footing dowel bars. Quasi static cyclic loads were used to test three half scale precast column to footing specimens and one cast in place control specimen. The precast concrete specimens incorporated grouted splice sleeve connectors in which two bars were grouted at both ends. Experimental results show that the precast subassemblies had a lower displacement ductility capacity than the control specimen. Improved seismic response was observed when the splice sleeve connectors were located inside the footing rather than the column end. An intentional debonded reinforcing bar zone was used to further improve the displacement ductility capacity of the bridge subassembly.
Matrix Completion for Downward-Looking 3-D SAR Imaging With a Random Sparse Linear Array

Downward-looking linear array 3-D synthetic aperture radar (SAR) has attracted increasing attention in the field of radar imaging. As widely reported, the volume of data can be significantly reduced by a random sparse linear array. However, the 2-D under-sampled azimuth-cross-track data brought by the sparse linear array will produce high-level side-lobes, as well as the aliasing and the false-alarm targets. To deal with those problems, this paper introduces a recently developed theory, matrix completion (MC). The new theory could recover a matrix with a small subset of known elements of the matrix. It is founded on the assumption that the matrix is essentially low rank. For downward-looking 3-D SAR with a random sparse linear array, the received 3-D data can be treated as a series of uncorrelated 2-D matrices by the separated channel process. First, range compression can be realized by means of pulse compression. Then, the sets of the 2-D under-sampled azimuth-cross-track matrix can be completed into a full-sampled one via MC trick. The resulting 3-D images can be focused by synthetic aperture technique along the azimuth direction and beamforming operation along the cross-track direction, with the recovered full-sampled matrix. The proposed algorithm achieves high resolution and low-level side-lobes with the acceptable computational cost and memory consumption. It is verified by several numerical simulations and multiple comparative studies on real data. The experimental results clearly demonstrate the imaging performance across different under-sampling rates and signal-noise rates.
Temporal relationships between sleep and physical activity among breast cancer patients with insomnia.

OBJECTIVE The present study prospectively investigated the day-to-day bidirectional relationships between objective measures of sleep parameters and physical activity among breast cancer patients with insomnia symptoms. METHOD A subgroup of participants (N = 66) enrolled in a randomized controlled trial for insomnia comorbid with cancer wore an actigraphic recorder for seven 24-hr periods before the intervention. Multilevel models examined whether sleep parameters (sleep onset latency, wake after sleep onset [WASO], total wake time [TWT], sleep efficiency [SE], and total sleep time [TST]) on a given night predicted the levels of physical activity (daily activity counts and minutes of moderate to vigorous physical activity [MVPA]) the following day and vice versa. RESULTS Adjusted models revealed that a lower WASO (β= -.12, SE = .07, p < .05), TWT (β = -.14, SE = .05, p < .05), and TST (β = -.14, SE = .06, p < .05) were significantly associated with a greater daily activity count fluctuation the next day. Conversely, greater total daily count fluctuations were significantly associated with a higher WASO (β = .18, SE = .08, p < .05), TWT (β = .12, SE = .04, p < .05), and TST (β = .22, SE = .08, p < .05) the following night. CONCLUSIONS These findings support a reciprocal and complex relationship between sleep parameters and physical activity. While they do not confirm a possible beneficial effect of physical activity on objective sleep parameters, they suggest that successful insomnia treatment could increase daily physical activity in patients with cancer. (PsycINFO Database Record