Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytotoxicity induced by carbon nanotubes in experimental malignant glioma

Despite multiple advances in the diagnosis of brain tumors, there is no effective treatment for glioblastoma. Multiwalled carbon nanotubes (MWCNTs), which were previously used as a diagnostic and drug delivery tool, have now been explored as a possible therapy against neoplasms. However, although the toxicity profile of nanotubes is dependent on the physicochemical characteristics of specific particles, there are no studies exploring how the effectivity of the carbon nanotubes (CNTs) is affected by different methods of production. In this study, we characterize the structure and biocompatibility of four different types of MWCNTs in rat astrocytes and in RG2 glioma cells as well as the induction of cell lysis and possible additive effect of the combination of MWCNTs with temozolomide. We used undoped MWCNTs (labeled simply as MWCNTs) and nitrogen-doped MWCNTs (labeled as N-MWCNTs). The average diameter of both pristine MWCNTs and pristine N-MWCNTs was ~22 and ~35 nm, respectively. In vitro and in vivo results suggested that these CNTs can be used as adjuvant therapy along with the standard treatment to increase the survival of rats implanted with malignant glioma.
A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries

OBJECTIVE The authors' goal was to develop and evaluate machine-learning-based approaches to extracting clinical entities-including medical problems, tests, and treatments, as well as their asserted status-from hospital discharge summaries written using natural language. This project was part of the 2010 Center of Informatics for Integrating Biology and the Bedside/Veterans Affairs (VA) natural-language-processing challenge. DESIGN The authors implemented a machine-learning-based named entity recognition system for clinical text and systematically evaluated the contributions of different types of features and ML algorithms, using a training corpus of 349 annotated notes. Based on the results from training data, the authors developed a novel hybrid clinical entity extraction system, which integrated heuristic rule-based modules with the ML-base named entity recognition module. The authors applied the hybrid system to the concept extraction and assertion classification tasks in the challenge and evaluated its performance using a test data set with 477 annotated notes. MEASUREMENTS Standard measures including precision, recall, and F-measure were calculated using the evaluation script provided by the Center of Informatics for Integrating Biology and the Bedside/VA challenge organizers. The overall performance for all three types of clinical entities and all six types of assertions across 477 annotated notes were considered as the primary metric in the challenge. RESULTS AND DISCUSSION Systematic evaluation on the training set showed that Conditional Random Fields outperformed Support Vector Machines, and semantic information from existing natural-language-processing systems largely improved performance, although contributions from different types of features varied. The authors' hybrid entity extraction system achieved a maximum overall F-score of 0.8391 for concept extraction (ranked second) and 0.9313 for assertion classification (ranked fourth, but not statistically different than the first three systems) on the test data set in the challenge.
Shared musical knowledge in 11-month-old infants.

Five-month-old infants selectively attend to novel people who sing melodies originally learned from a parent, but not melodies learned from a musical toy or from an unfamiliar singing adult, suggesting that music conveys social information to infant listeners. Here, we test this interpretation further in older infants with a more direct measure of social preferences. We randomly assigned 64 11-month-old infants to 1-2 weeks' exposure to one of two novel play songs that a parent either sang or produced by activating a recording inside a toy. Infants then viewed videos of two new people, each singing one song. When the people, now silent, each presented the infant with an object, infants in both conditions preferentially chose the object endorsed by the singer of the familiar song. Nevertheless, infants' visual attention to that object was predicted by the degree of song exposure only for infants who learned from the singing of a parent. Eleven-month-olds thus garner social information from songs, whether learned from singing people or from social play with musical toys, but parental singing has distinctive effects on infants' responses to new singers. Both findings support the hypothesis that infants endow music with social meaning. These findings raise questions concerning the types of music and behavioral contexts that elicit infants' social responses to those who share music with them, and they support suggestions concerning the psychological functions of music both in contemporary environments and in the environments in which humans evolved.
COMPARISON TESTING IN A SIMULATED DATA PROCESSING / TELECOMMUNICATIONS FACILITY

Data processing and telecommunication facilities are commonly protected against fire with a gaseous clean agent system, an automatic sprinkler system, or with both a clean agent and an automatic sprinkler system. The degree of protection provided by these systems is vastly different, as is the cost incurred in employing these systems. The test comparison reported here was performed in order to illustrate the differences in the protection provided by automatic sprinkler systems and gaseous agent systems. The tests were performed in a simulated data processing/telecommunications facility, and examined the performance of the suppression systems on a plastics fire located inside a metal electronic equipment cabinet.
Draft Genome Sequence and Annotation of the Phytopathogenic Ralstonia pickettii (Previously Burkholderia glumae) Strain ICMP-8657

ABSTRACT Strain ICMP-8657 was formerly taxonomically classified as Burkholderia glumae and reported to be the producer of an antibacterial pyrazole derivative. Here, we report the draft genome sequence of ICMP-8657, which failed to demonstrate the biosynthetic capacity to produce the stated antibacterial compound, leading to its taxonomic reclassification as Ralstonia pickettii ICMP-8657.
Diversity of Silica-scaled Chrysophytes in High-altitude Alpine Sites (North Tyrol, Austria) Including a Description of Mallomonas pechlaneri sp. nov.

Abstract To expand on the biodiversity study of the eastern Alpine region of North Tyrol, we investigated silica-scaled chrysophyte flora of unexplored high-altitude Alpine sites. We concentrated mostly on lakes that were 1000–2500 m above sea level; some of them were still partly ice covered. Overall, 27 taxa were recorded at 12 sites, despite 21 sites being sampled altogether. In general, the sites were oligotrophic and species poor. Due to a restricted data set, an extensive analysis was not possible. However, altitude and pH were found to be important variables for explaining species distribution. We described the new species Mallomonas pechlaneri from two of the sampled sites. Mallomonas pechlaneri most closely resembles Mallomonas striata var. striata and M. striata var. serrata; these three taxa are clearly distinguished by bristle morphology and scale shape. The bristles of M. pechlaneri terminate in a bifurcated tip consisting of unequal diverging branches. Scale shape was captured my means of landmark-based geometric morphometries (GM) and evaluated using multivariate statistical analyses. GM methods proved to be an efficient tool to be employed in chrysophycean taxonomy.
Improving Optimization for Models With Continuous Symmetry Breaking.

Many loss functions in representation learning are invariant under a continuous symmetry transformation. For example, the loss function of word embeddings (Mikolov et al., 2013) remains unchanged if we simultaneously rotate all word and context embedding vectors. We show that representation learning models for time series possess an approximate continuous symmetry that leads to slow convergence of gradient descent. We propose a new optimization algorithm that speeds up convergence using ideas from gauge theory in physics. Our algorithm leads to orders of magnitude faster convergence and to more interpretable representations, as we show for dynamic extensions of matrix factorization and word embedding models. We further present an example application of our proposed algorithm that translates modern words into their historic equivalents.
Specific-Locus Amplified Fragment Sequencing Reveals Spontaneous Single-Nucleotide Mutations in Rice OsMsh6 Mutants

Genomic stability depends in part on an efficient DNA lesion recognition and correction by the DNA mismatch repair (MMR) system. We investigated mutations arising spontaneously in rice OsMsh6 mutants by specific-locus amplified fragment sequencing. Totally 994 single-nucleotide mutations were identified in three mutants and on average the mutation density is about 1/136.72 Kb per mutant line. These mutations were relatively randomly distributed in genome and might be accumulated in generation-dependent manner. All possible base transitions and base transversions could be seen and the ratio of transitions to transversions was about 3.12. We also observed the nearest-neighbor bias around the mutated base. Our data suggests that OsMsh6 (LOC_Os09g24220) is important in ensuring genome stability by recognizing mismatches that arise spontaneously and provides useful information for investigating the function of the OsMsh6 gene in DNA repair and exploiting MMR mutants in rice induced mutation breeding.
Geometric-Mean-Decomposition-Based Optimal Transceiver for a Class of Two-Hop MIMO-Aided Amplify-and-Forward Relay Channels

A geometric mean decomposition (GMD)-based joint transceiver is investigated in the context of a multiple-input-multiple-output (MIMO)-aided relay-assisted two-hop amplify-and-forward relaying system. The canonical form of the optimal weighting matrix is derived, which is capable of achieving the maximum received signal-to-noise ratio (SNR) at the destination. Furthermore, the optimal power allocation is formulated as a geometric programming problem. The proposed optimal design of the linear weighting matrix achieves an approximately 5-dB SNR gain over the naive weighting matrix at the bit error rate (BER) of 10-3 as a benefit of efficiently exploiting the low-complexity linear signal processing capability of the relay.
Impulse denoising via transform learning

This work addresses the problem of impulse denoising. Traditionally this was removed by median filtering (and its variants). In recent times, li-li denoising techniques that employ an li-norm on the data fidelity term and li-norm on the image's sparsifying transform has been proposed. This work proposes a transform learning based formulation for the said problem. Till date, it has been used for solving Gaussian denoising problems and MRI reconstruction problems. This is the first work, that proposes solving the impulse denoising problem using the said framework. Experimental results standard images show the superiority of our proposed method with respect to traditional (sparsity) and dictionary learning based approaches.
Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach

Background Internet is a particularly dynamic way to quickly capture the perceptions of a population in real time. Complementary to traditional face-to-face communication, online social networks help patients to improve self-esteem and self-help. Objective The aim of this study was to use text mining on material from an online forum exploring patients’ concerns about treatment (antidepressants and anxiolytics). Methods Concerns about treatment were collected from discussion titles in patients’ online community related to antidepressants and anxiolytics. To examine the content of these titles automatically, we used text mining methods, such as word frequency in a document-term matrix and co-occurrence of words using a network analysis. It was thus possible to identify topics discussed on the forum. Results The forum included 2415 discussions on antidepressants and anxiolytics over a period of 3 years. After a preprocessing step, the text mining algorithm identified the 99 most frequently occurring words in titles, among which were escitalopram, withdrawal, antidepressant, venlafaxine, paroxetine, and effect. Patients’ concerns were related to antidepressant withdrawal, the need to share experience about symptoms, effects, and questions on weight gain with some drugs. Conclusions Patients’ expression on the Internet is a potential additional resource in addressing patients’ concerns about treatment. Patient profiles are close to that of patients treated in psychiatry.
Atlantic Ocean CARINA data: overview and salinity adjustments

Water column data of carbon and carbon-relevant hydrographic and hydrochemical parameters from 188 previously non-publicly available cruise data sets in the Arctic Mediterranean Seas, Atlantic and Southern Ocean have been retrieved and merged into a new database: CARINA (CARbon dioxide IN the Atlantic Ocean). The data have gone through rigorous quality control procedures to assure the highest possible quality and consistency. The data for the pertinent parameters in the CARINA database were objectively examined in order to quantify systematic differences in the reported values, i.e. secondary quality control. Systematic biases found in the data have been corrected in the three data products: merged data files with measured, calculated and interpolated data for each of the three CARINA regions, i.e. the Arctic Mediterranean Seas, the Atlantic and the Southern Ocean. These products have been corrected to be internally consistent. Ninety-eight of the cruises in the CARINA database were conducted in the Atlantic Ocean, defined here as the region south of the Greenland-Iceland-Scotland Ridge and north of about 30° S. Here we present an overview of the Atlantic Ocean synthesis of the CARINA data and the adjustments that were applied to the data product. We also report the details of the secondary QC (Quality Control) for salinity for this data set. Procedures of quality control – including crossover analysis between stations and inversion analysis of all crossover data – are briefly described. Adjustments to salinity measurements were applied to the data from 10 cruises in the Atlantic Ocean region. Based on our analysis we estimate the internal consistency of the CARINA-ATL salinity data to be 4.1 ppm. With these adjustments the CARINA data products are consistent both internally as well as with GLODAP data, an oceanographic data set based on the World Hydrographic Program in the 1990s, and is now suitable for accurate assessments of, for example, oceanic carbon inventories and uptake rates and for model validation.
Energy Efficient Beamforming in MISO Heterogeneous Cellular Networks With Wireless Information and Power Transfer

The advent of simultaneous wireless information and power transfer (SWIPT) offers a promising approach to providing cost-effective and perpetual power supplies for energy-constrained mobile devices in heterogeneous cellular networks (HCNs). As energy efficiency (EE) has been envisioned as a key performance metric in 5G wireless networks, we consider a multiple-input single-output (MISO) femtocell cochannel overlaid with a Macrocell to exploit the advantages of SWIPT while promoting the EE. The femto base station sends information to information decoding (ID) femto users (FUs) and transfers energy to energy harvesting (EH) FUs simultaneously, and also suppresses its interference to Macro users. We maximize the information transmission efficiency (ITE) of ID FUs and energy harvesting efficiency (EHE) of EH FUs, respectively, with the QoS of all users, and investigate their relationship. We formulate these problems as fractional programming, which are nontrivial to solve due to the nonconvexity of ITE and EHE. To tackle these problems, we devise two beamformers namely zero-forcing (ZF) and mixed beamforming (MBF), and then propose an efficient algorithm to obtain the optimal power under both beamformers. Simulation results demonstrate that MBF provides better ITE and EHE than ZF, and there exists a tradeoff between ITE and EHE in general.
Udenafil, a Phosphodiesterase 5 Inhibitor, Reduces Body Weight in High-Fat-Fed Mice

Purpose High-fat (HF) feeding induces hypothalamic leptin resistance via the activation of toll-like receptor 4 (TLR4). TLR4 deficiency confers resistance to diet-induced obesity. Udenafil, an anti-impotence drug, inhibits TLR4 in airway epithelial cells in vitro. In this study, we evaluated whether udenafil suppressed the hypothalamic expression of TLR4 and reduced body weight. Materials and Methods The hypothalamic expression of TLR4, phosphodiesterase 5 (PDE5), nuclear factor-κB (NF-κB), and myeloid differentiation primary response gene 88 (Myd88) was analyzed by real-time polymerase chain reaction after treating mice for 2 days with udenafil (0, 12, 120, or 600 µg/d). Furthermore, the hypothalamic expression of TLR4, pro-opiomelanocortin (POMC), and neuropeptide Y (NPY) was analyzed after 9 days' treatment with udenafil and/or leptin. We also measured body weight and food intake following 9 days of udenafil and/or leptin treatment in control- and HF-fed mice. Results Udenafil suppressed hypothalamic TLR4 mRNA expression dose-dependently. The changes were associated with decreased PDE5, NF-κB, and Myd88 expression. Udenafil treatment for 9 days reduced body weight and caloric intake in HF-fed mice. This may have been associated with the suppression of NPY expression that was elevated by HF feeding. POMC expression was not affected by udenafil. However, udenafil did not augment the effects of leptin on the reduction of body weight and caloric intake in HF-fed mice. Conclusions These results suggested that udenafil reduced body weight by suppressing hypothalamic TLR4 mRNA expression in HF-fed mice and the combination effect of udenafil and leptin was additive rather than synergistic.
ESTIMATION OF SOME CHOSEN PHYSICAL PROPERTIES OF EXTRUDATES OBTAINED FROM CORN SEMOLINA AND OAT BRAN MIXTURES

Some chosen properties of the extrudates obtained from corn semolina and oat bran were studied. Two component mixtures were extruded using a single screw extrusion-cooker S-45. The purpose of the research was to estimate the influence of the moisture content in raw material and the process temperature on its course, the outflow stability and such physical properties as: radial expansion, specific density, texture and water absorption index. It was observed that higher process temperature low- ered water absorption of the product and water absorption index increased along with the increase of raw material moisture content and oat bran percentage. Higher content of bran altered density and lowered the level of extrudate expansion. It was found that higher moisture of raw material caused a decrease in the specific destruction energy of the
Heat-stabilised rice bran consumption by colorectal cancer survivors modulates stool metabolite profiles and metabolic networks: a randomised controlled trial

Rice bran (RB) consumption has been shown to reduce colorectal cancer (CRC) growth in mice and modify the human stool microbiome. Changes in host and microbial metabolism induced by RB consumption was hypothesised to modulate the stool metabolite profile in favour of promoting gut health and inhibiting CRC growth. The objective was to integrate gut microbial metabolite profiles and identify metabolic pathway networks for CRC chemoprevention using non-targeted metabolomics. In all, nineteen CRC survivors participated in a parallel randomised controlled dietary intervention trial that included daily consumption of study-provided foods with heat-stabilised RB (30 g/d) or no additional ingredient (control). Stool samples were collected at baseline and 4 weeks and analysed using GC-MS and ultra-performance liquid chromatography-MS. Stool metabolomics revealed 93 significantly different metabolites in individuals consuming RB. A 264-fold increase in β-hydroxyisovaleroylcarnitine and 18-fold increase in β-hydroxyisovalerate exemplified changes in leucine, isoleucine and valine metabolism in the RB group. A total of thirty-nine stool metabolites were significantly different between RB and control groups, including increased hesperidin (28-fold) and narirutin (14-fold). Metabolic pathways impacted in the RB group over time included advanced glycation end products, steroids and bile acids. Fatty acid, leucine/valine and vitamin B6 metabolic pathways were increased in RB compared with control. There were 453 metabolites identified in the RB food metabolome, thirty-nine of which were identified in stool from RB consumers. RB consumption favourably modulated the stool metabolome of CRC survivors and these findings suggest the need for continued dietary CRC chemoprevention efforts.
Successful verification of subcontracted work in the construction industry

Due to the introduction of new types of contracts, such as Design, Build, Finance, & Maintain (DBFM), a major shift in tasks and responsibilities from client to contractor can be seen in the construction industry. To manage these new contracts and corresponding shifts in responsibilities, systems engineering (SE) is seen as a relevant instrument and applied increasingly in this industry. When these new, integrated contracts are applied in combination with SE, the contractor becomes responsible for verification. The contractor, however, is not the only organization that executes verification tasks as contractors regularly subcontract work to suppliers. Although the main contractor bears the final responsibility toward the client, it may be expected that the supplier verifies its own work. This requires verification to be carried out further down the supply chain. However, many problems are experienced when allocating these verification responsibilities to the suppliers. This paper explores which verification problems are faced in construction work that is subcontracted to suppliers. A conceptual framework is applied to categorize these problems and to analyze the solutions applied in the construction industry. The major finding of this study is that causes of verification problems can be found at both the contractor and the supplier side. Improvements are suggested for both these sides.