Miracle-dz/UniFAR-FTUs huggingface dataset:
Calculation of Semantic Distances Between Words: From Synonymy to Antonymy

Abstract A new approach to numerically measure the semantic distances between lexical units (words and collocations) based on the geometric analogies and analytical calculation, is put forward. Having considered the cases of equal and different weights of semes, we obtained exact algebraic formulas describing different levels of the meanings proximity, ranging from absolute synonymy to full antonymy. It was emphasized that absolute synonymy arises when the compared units contain equal numbers of semes that fully coincide and have equal weights in the corresponding pairs. Calculation of the semes weights helps to locate the unit more precisely on the semantic sphere. It was shown that the level of synonymy and antonymy decreases if different semes are accentuated, while the semantic distance between the units without identical semes cannot be influenced by seme boosting. It was observed that depending on the context, a word may wander over this sphere, thus modifying its lexical semantic relations with other units. As the proposed approach contributes to formalization of the units comparison procedure, it is advisable for incorporation into relevant automatic tools, particularly into WordNet and FrameNet. The obtained results may be useful for various linguistic and associated studies including automatic text analysis and processing, computer lexicography, information search and retrieval, machine translation and other NLP applications that are related to the artificial intelligence problem.
ESL Live broadcast teaching service in a university library

The application of live broadcasting has caught attention in a wide variety of learning contexts in recent years. In higher education, university plays a very important role in teaching enhancement. Live broadcast media provide a platform for the library to establish an English self-learning social community and to encourage communication among the group members. Through the live video and instant messages delivered by the network, the library can adapt various strategies for presenting the content in different forms (live videos, graphics, texts, video, and links). In this study, the integration of live broadcasting in English as a second language (ESL) learning is implemented in a library. Together with the implementation, reactions from the librarian, the teacher, the students, and library support staff were gathered. From their reactions, the participants were positive about the broadcast approach to learning ESL. However, challenges exist for keeping all students committed to attending the class. More interesting topics and the use of interactive activities in the class are suggested in future implementations.
Development of a HTML5 game with Construct2 for learning applications

In this study, the researcher adopted a HTML5 game engine to develop a cross-platform educational game for learning applications. The developed game could be run on various platforms and several game elements and principles were considered during the design stage. The purpose of the educational game was to help new students to get familiar with the new school, and the learning missions were embedded into a macro-context to simulate a virtual campus for helping students learn and explore the environment, policies, and routines of the school. After the complete development of the game, a group of students were invited to use and test the game, and their feedback were collected through questionnaires. The structure and learning missions of the developed educational game, and the pilot evaluation resulted were reported in the paper.
Modeling of the Return and Risks of Investments Using Different Trading Strategies

When investing in stocks, companies and individuals are interested in gaining the highest return while controlling risks to a reasonable range. Many advisory companies claim that they excel in predicting the trend of the stock market using machine learning techniques while other investors, such as Warren Buffett, hold the view that money is made by investing and the best strategy is to buy and hold, but don't watch too closely. Here we use SPY and TQQQ in the Year 2016 and 2017, two of the most closely watched, commonly discussed and invested stocks, as an example to explore these options. We compare four different strategies, including buy and hold, no investment, machine learning prediction, and random guess. Our result shows that buy and hold is the best strategy in when investing in TQQQ, although prediction by machine learning achieves reasonable accuracy in predicting the trend, which is consistent with the suggestion for long-term investment from Warren Buffet. When investing in SPY, machine learning approach works similarly to the buy and hold strategy. Both strategies outperform the random guess strategy. Moreover, investing in either of the stocks will likely outperform no investment in a 3-month period that we tested. The application of such strategies in different scenarios is further discussed.
Enhanced Radiosensitization by Gold Nanoparticles with Acid‐Triggered Aggregation in Cancer Radiotherapy

An ideal radiosensitizer holding an enhanced tumor retention can play an incredible role in enhancing tumor radiotherapy. Herein, a strategy of acid‐triggered aggregation of small‐sized gold nanoparticles (GNPs) system within tumor is proposed and the resulting GNPs aggregates are applied as a radiosensitizer in vitro and in vivo. The GNPs system with the acid‐triggered aggregation achieves an enhanced GNPs accumulation and retention in cancer cells and tumors in the form of the resulted GNPs aggregates. As a consequence, the radiosensitization effect shows significant improvement in cancer radiotherapy, which is shown in the studies of DNA breakage and the comet assay, and the sensitizer enhancement ratio (SER) value of the GNPs system (1.730) with MCF‐7 cancer cells is much larger than that of the single GNPs (1.16). In vivo antitumor studies reveal that the GNPs system also enhances the sensitivity of MCF‐7 tumor xenograft to radiotherapy. Furthermore, the GNPs aggregates improve the signal of small GNPs in vivo photoacoustic imaging. This study provides a new strategy and insights into fabricating nanoaggregates to magnify the radiosensitive efficiency of nanosystems in cancer radiotherapy.
Do riparian forest strips in modified forest landscapes aid in conserving bat diversity?

Abstract Agricultural practices lead to losses of natural resources and biodiversity. Maintaining forests alongside streams (riparian forest strips) has been used as a mechanism to minimize the impact of clearing for agriculture on biodiversity. To test the contribution of riparian forest strips to conserve biodiversity in production landscapes, we selected bats as a biodiversity model system and examined two dimensions of diversity: taxonomic and functional. We compared bat diversity and composition in forest, with and without stream habitat, and in narrow forest riparian strips surrounded by areas cleared for agriculture. We tested the hypothesis that riparian forest strips provide potential conservation value by providing habitat and serving as movement corridors for forest bat species. Riparian forest strips maintained 75% of the bat species registered in forested habitats. We found assemblage in sites with riparian forest strips were dominated by a few species with high abundance and included several species with low abundance. Bat species assemblage was more similar between sites with streams than between those sites to forests without stream habitat. These results highlight the importance of stream habitat in predicting presence of bat species. We registered similar number of guilds between forest sites and riparian forest strips sites. Relative to matrix habitats, stream and edge habitats in riparian forest strips sites were functionally more diverse, supporting our hypothesis about the potential conservation value of riparian forest strips. Results from this study suggest that maintaining riparian forest strips within cleared areas for agricultural areas helps conserve the taxonomic and functional diversity of bats. Also, it provides basic data to evaluate the efficacy of maintaining these landscape features for mitigating impacts of agricultural development on biodiversity. However, we caution that riparian forest strips alone are not sufficient for biodiversity maintenance; their value depends on maintenance of larger forest areas in their vicinity.
Haemolysis and lipemia interfere with resistin and myeloperoxidase BioVendor ELISA assays

Introduction The aim of our study was to investigate the influence of haemolysis and lipemia on resistin (RES) and myeloperoxidase (MPO) measurement by BioVendor enzyme-linked immunosorbent assays (ELISA). Materials and methods Blood was taken from healthy volunteers into lithium heparin tubes. Plasma samples were spiked with Lipofundin® emulsion (B. Braun Melsungen AG, Germany) for lipemia interference testing. Haemolysed samples were obtained by drawing aliquots of heparinized blood through a 26 gauge needle. Index of haemolysis (H), lipemia (L) and triglyceride concentration were measured on Abbott Architect c8000. Haemoglobin concentration was measured on Sysmex XN-1000. Concentrations of RES and MPO in all samples were determined with RES and MPO ELISA kits (BioVendor, Czech Republic). All measurements were performed in triplicate. Biases from the native samples were calculated for both analytes and compared with an arbitrary value (e.g. ± 10%). Results Triglyceride concentration in the investigated samples ranged from 0.57 to 38.23 mmol/L, which corresponds to L index from - 0.01 to 13.77. Haemoglobin concentration in all samples ranged from 0 to 8 g/L which correspond to H index from 0.05 to 8.77. Both MPO and RES showed significant biases at 1 g/L haemoglobin (58.7% and 66.7%, respectively). Also, both MPO and RES showed significant biases at 4.66 mmol/L triglycerides (33.8% and - 12.2%, respectively). Conclusions Resistin BioVendor assays are affected by haemolysis and lipemia already at low degree of interferent. Haemolysis was found to interfere at 1 g/L haemoglobin for both assays, while lipemia interferes at 4.66 mmol/L of triglycerides.
QEOSA: A Pedagogical Model That Harnesses Cultural Resources to Foster Creative Problem-Solving

The nature of creative thinking is complex and multifaceted, often involving cognitive processes and dispositions modulated by implicit cultural belief systems and ways of thinking. In this article, we build on existing research on the relations of creative thinking and culture, and explore how specific cultural resources can be harnessed to foster creative problem-solving in education. We first review the recent changes in our understanding of creative thinking, from an exclusive focus on cognitive processes to a more inclusive view of creative problem-solving as socially negotiated and culturally modulated, carrying important cultural functions. We then introduce a pedagogical model, QEOSA, to illustrate how cultural resources, particularly culture-specific ways of thinking about the world, can be harnessed to foster creative thinking in education, and what developmental and pedagogical considerations are involved to make it effective. We finally conclude this article by indicating the value of this line of work that integrates psychological, cultural, developmental, and educational principles in fostering the development of a creative mind-set with relevant knowledge, skills, dispositions, and values.
K-means Clustering Using R A Case Study of Market Segmentation

In recent years, machine learning is widely used to support human decision making in several related scientific areas such as medical, biological, image processing and so on. However in market classification, marketing segmentation is facing numerous challenges in defining specific target customer zones to help enterprises launching their marketing strategies. On the other hand, modern technologies and programming languages are providing support for statistical estimations and graphic visualizations, especially in the R language. In this paper, a k-means machine learning (ML) algorithm with an R language implementation is utilized for marketing segmentation in a specific case study of Black Friday for determining potential customer zones to make reasonable marketing strategies.
A broadband low-noise front-end amplifier for ultra wideband in 0.13 μm CMOS

A front-end amplifier for ultra wideband (UWB) is described. The amplifier has a single-ended input and a differential output, with 16 dB power gain, a flat-gain bandwidth of 2-5.2 GHz, an output P1dB of -8 dBm and a NF of 4.7-5.7 dB. The amplifier is implemented in 0.13 /spl mu/m digital CMOS, occupies 0.4/spl times/0.6 mm/sup 2/, and consumes 38 mW power.
Distributed Differentially Private Computation of Functions with Correlated Noise

Many applications of machine learning, such as human health research, involve processing private or sensitive information. Privacy concerns may impose significant hurdles to collaboration in scenarios where there are multiple sites holding data and the goal is to estimate properties jointly across all datasets. Differentially private decentralized algorithms can provide strong privacy guarantees. However, the accuracy of the joint estimates may be poor when the datasets at each site are small. This paper proposes a new framework, Correlation Assisted Private Estimation (CAPE), for designing privacy-preserving decentralized algorithms with better accuracy guarantees in an honest-but-curious model. CAPE can be used in conjunction with the functional mechanism for statistical and machine learning optimization problems. A tighter characterization of the functional mechanism is provided that allows CAPE to achieve the same performance as a centralized algorithm in the decentralized setting using all datasets. Empirical results on regression and neural network problems for both synthetic and real datasets show that differentially private methods can be competitive with non-private algorithms in many scenarios of interest.
Acute Stress and an Electrolyte- Imbalanced Diet, but Not Chronic Hypoxia, Increase Oxidative Stress and Hamper Innate Immune Status in a Rainbow Trout (Oncorhynchus mykiss) Isogenic Line

In aquaculture, fish may be exposed to sub-optimal rearing conditions, which generate a stress response if full adaptation is not displayed. However, our current knowledge of several coexisting factors that may give rise to a stress response is limited, in particular when both chronic and acute stressors are involved. This study investigated changes in metabolic parameters, oxidative stress and innate immune markers in a rainbow trout (Oncorhynchus mykiss) isogenic line exposed to a combination of dietary (electrolyte-imbalanced diet, DEB 700 mEq Kg-1) and environmental (hypoxia, 4.5 mg O2 L-1) challenges and their respective controls (electrolyte-balanced diet, DEB 200 mEq Kg-1 and normoxia, 7.9 or mg O2 L-1) for 49 days. At the end of this period, fish were sampled or subjected to an acute stressor (2 min of handling/confinement) and then sampled. Feeding trout an electrolyte-imbalanced diet produced a reduction in blood pH, as well as increases in cortisol levels, hepato-somatic index (HSI) and total energy content in the liver. The ratio between the lactate dehydrogenase (LDH) and isocitrate dehydrogenase (IDH) activities decreased in the liver of trout fed the DEB 700 diet, but increased in the heart, suggesting a different modulation of metabolic capacity by the dietary challenge. Several markers of oxidative stress in the liver of trout, mainly related to the glutathione antioxidant system, were altered when fed the electrolyte-imbalanced diet. The dietary challenge was also associated with a decrease in the alternative complement pathway activity (ACH50) in plasma, suggesting an impaired innate immune status in that group. Trout subjected to the acute stressor displayed reduced blood pH values, higher plasma cortisol levels as well as increased levels of metabolic markers associated with oxidative stress in the liver. An interaction between diet and acute stressor was detected for oxidative stress markers in the liver of trout, showing that the chronic electrolyte-imbalance impairs the response of rainbow trout to handling/confinement. However, trout reared under chronic hypoxia only displayed changes in parameters related to energy use in both liver and heart. Taken together, these results suggest that trout displays an adaptative response to chronic hypoxia. Conversely, the dietary challenge profoundly affected fish homeostasis, resulting in an impaired physiological response leading to stress, which then placed constraints on a subsequent acute challenge.
DeepBouton: Automated Identification of Single-Neuron Axonal Boutons at the Brain-Wide Scale

Fine morphological reconstruction of individual neurons across the entire brain is essential for mapping brain circuits. Inference of presynaptic axonal boutons, as a key part of single-neuron fine reconstruction, is critical for interpreting the patterns of neural circuit wiring schemes. However, automated bouton identification remains challenging for current neuron reconstruction tools, as they focus mainly on neurite skeleton drawing and have difficulties accurately quantifying bouton morphology. Here, we developed an automated method for recognizing single-neuron axonal boutons in whole-brain fluorescence microscopy datasets. The method is based on deep convolutional neural networks and density-peak clustering. High-dimensional feature representations of bouton morphology can be learned adaptively through convolutional networks and used for bouton recognition and subtype classification. We demonstrate that the approach is effective for detecting single-neuron boutons at the brain-wide scale for both long-range pyramidal projection neurons and local interneurons.
Proceedings of the Annual Meeting of the Cognitive Science Society

Understanding the mechanisms of learning is one of the central questions of Cognitive Science. Recently Marcus et al. showed that seven-month-old infants can learn to recognize regularities in simple language-like stimuli. Marcus proposed that these results could not be modeled via existing connectionist systems, and that such learning requires infants to be constructing rules containing algebraic variables. This paper proposes a third possibility: that such learning can be explained via structural alignment processes operating over structured representations. We demonstrate the plausibility of this approach by describing a simulation, built out of previously tested models of symbolic similarity processing, that models the Marcus data. Unlike existing connectionist simulations, our model learns within the span of stimuli presented to the infants and does not require supervision. It can handle input with and without noise. Contrary to Marcus’ proposal, our model does not require the introduction of variables. It incrementally abstracts structural regularities, which do not need to be fully abstract rules for the phenomenon to appear. Our model also proposes a processing explanation for why infants attend longer to the novel stimuli. We describe our model and the simulation results and discuss the role of structural alignment in the development of abstract patterns and rules.
Projection effects in galaxy cluster samples: insights from X-ray redshifts

Presently, the largest sample of galaxy clusters selected in X-rays comes from the ROSAT All-Sky Survey (RASS). Although there have been many interesting clusters discovered with the RASS data, the broad point spread function of the ROSAT satellite limits the attainable amount of spatial information for the detected objects. This leads to the discovery of new cluster features when a re-observation is performed with higher-resolution X-ray satellites. Here we present the results from XMM-Newton observations of three clusters: RXC J2306.6−1319, ZwCl 1665, and RXC J0034.6−0208, for which the observations reveal a double or triple system of extended components. These clusters belong to the extremely expanded HIghest X-ray FLUx Galaxy Cluster Sample (eeHIFLUGCS), which is a flux-limited cluster sample (fX, 500 ≥ 5 × 10−12 erg s−1 cm−2 in the 0.1−2.4 keV energy band). For each structure in each cluster, we determine the redshift with the X-ray spectrum and find that the components are not part of the same cluster. This is confirmed by an optical spectroscopic analysis of the galaxy members. Therefore, the total number of clusters is actually seven, rather than three. We derive global cluster properties of each extended component. We compare the measured properties to lower-redshift group samples, and find a good agreement. Our flux measurements reveal that only one component of the ZwCl 1665 cluster has a flux above the eeHIFLUGCS limit, while the other clusters will no longer be part of the sample. These examples demonstrate that cluster–cluster projections can bias X-ray cluster catalogues and that with high-resolution X-ray follow-up this bias can be corrected.
Gi/o-Protein Coupled Receptors in the Aging Brain

Cells translate extracellular signals to regulate processes such as differentiation, metabolism and proliferation, via transmembranar receptors. G protein-coupled receptors (GPCRs) belong to the largest family of transmembrane receptors, with over 800 members in the human species. Given the variety of key physiological functions regulated by GPCRs, these are main targets of existing drugs. During normal aging, alterations in the expression and activity of GPCRs have been observed. The central nervous system (CNS) is particularly affected by these alterations, which results in decreased brain functions, impaired neuroregeneration, and increased vulnerability to neuropathologies, such as Alzheimer’s and Parkinson diseases. GPCRs signal via heterotrimeric G proteins, such as Go, the most abundant heterotrimeric G protein in CNS. We here review age-induced effects of GPCR signaling via the Gi/o subfamily at the CNS. During the aging process, a reduction in protein density is observed for almost half of the Gi/o-coupled GPCRs, particularly in age-vulnerable regions such as the frontal cortex, hippocampus, substantia nigra and striatum. Gi/o levels also tend to decrease with aging, particularly in regions such as the frontal cortex. Alterations in the expression and activity of GPCRs and coupled G proteins result from altered proteostasis, peroxidation of membranar lipids and age-associated neuronal degeneration and death, and have impact on aging hallmarks and age-related neuropathologies. Further, due to oligomerization of GPCRs at the membrane and their cooperative signaling, down-regulation of a specific Gi/o-coupled GPCR may affect signaling and drug targeting of other types/subtypes of GPCRs with which it dimerizes. Gi/o-coupled GPCRs receptorsomes are thus the focus of more effective therapeutic drugs aiming to prevent or revert the decline in brain functions and increased risk of neuropathologies at advanced ages.