Miracle-dz/UniFAR-FTUs huggingface dataset:
Computerized cognitive training and brain derived neurotrophic factor during bed rest: mechanisms to protect individual during acute stress

Acute stress, as bed rest, was shown to increase plasma level of the neurotrophin brain-derived neurotrophic factor (BDNF) in older, but not in young adults. This increase might represent a protective mechanism towards acute insults in aging subjects. Since computerized cognitive training (CCT) is known to protect brain, herein we evaluated the effect of CCT during bed rest on BDNF, muscle mass, neuromuscular function and metabolic parameters. The subjects that underwent CCT did not show an increase of BDNF after bed rest, and showed an anti-insular modification pattern in metabolism. Neuromuscular function parameters, already shown to beneficiate from CCT, negatively correlated with BDNF in research participants undergoing CCT, while positively correlated in the control group. In conclusion, BDNF increase can be interpreted as a standardized protective mechanism taking place whenever an insult occurs; it gives low, but consistent preservation of neuromuscular function. CCT, acting as an external protective mechanism, seems to modify this standardized response, avoiding BDNF increase or possibly modifying its time course. Our results suggest the possibility of differential neuroprotective mechanisms among ill and healthy individuals, and the importance of timing in determining the effects of protective mechanisms.
Interactions between pairs of transcranial magnetic stimuli over the human left dorsal premotor cortex differ from those seen in primary motor cortex

A single TMS pulse (110% resting motor threshold, RMT) to the left dorsal premotor cortex (PMd) (CS2) suppresses the amplitude of motor evoked potentials (MEPs) from a test pulse (TS) over the right motor cortex (M1), and facilitates MEPs from the left motor cortex. We probed how this interaction was changed by a prior conditioning pulse over PMd (CS1) using a paired pulse TMS design. In the main experiments, the intensity of CS1 was 80% RMT. Basal suppression of right M1 was removed when CS1–CS2 was 1 ms or 5 ms with a similar tendency at 15 ms. Basal facilitation of left M1 was suppressed at CS1–CS2 of 5 ms. A similar time course was seen if CS2 was increased to 100% RMT, but there was no significant effect if CS1 was 70% RMT. Preconditioning PMd with continuous or intermittent theta burst repetitive TMS (cTBS, iTBS) abolished the basal CS2–TS interaction between premotor and motor cortices. Finally, if very short interstimulus intervals between CS1 and CS2 were explored to detect interactions similar to I‐wave facilitation in M1, we found that the basal suppression of right M1 was abolished at CS1–CS2 intervals of 1.8 and 2.8 ms. We suggest that paired pulse TMS may be capable of investigating properties of intrinsic circuits in PMd and that their properties differ from those in the nearby M1. Paired TMS may be a useful method of studying the excitability of intrinsic circuits in non‐primary areas of the motor system.
Stability analysis of snake robot locomotion based on Poincaré maps

This paper presents an analysis of snake locomotion that explains how non-uniform viscous ground friction conditions enable snake robots to locomote forward on a planar surface. The explanation is based on a simple mapping from link velocities normal to the direction of motion into propulsive forces in the direction of motion. From this analysis, a controller for a snake robot is proposed. A Poincare¿ map is employed to prove that all state variables of the snake robot, except for the position in the forward direction, trace out an exponentially stable periodic orbit.
Bi-cross-validation of the SVD and the nonnegative matrix factorization

This article presents a form of bi-cross-validation (BCV) for choosing the rank in outer product models, especially the singular value decomposition (SVD) and the nonnegative matrix factorization (NMF). Instead of leaving out a set of rows of the data matrix, we leave out a set of rows and a set of columns, and then predict the left out entries by low rank operations on the retained data. We prove a self-consistency result expressing the prediction error as a residual from a low rank approximation. Random matrix theory and some empirical results suggest that smaller hold-out sets lead to more over-fitting, while larger ones are more prone to under-fitting. In simulated examples we find that a method leaving out half the rows and half the columns performs well.
Power-optimal scheduling for a Green Base station with delay constraints

We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.
Wideband inverted L-shaped dielectric resonator antenna for medical applications

Telecommunications has expanded rapidly. It's absolutely necessary to optimize the antenna's performance to support applications usage in medical development as microwave imaging. The radiation pattern basically needs to be directed toward the breast phantom and high gain. Investigated by high resolution breast cancer that makes antenna can be delivered in a wide spectrum. The role of this research is to design wideband dielectric resonator antenna (WDRA) by using inverted L-shape associated with a curved top face and inverted trapezoidal patch feed, specialized by engineering CST microwave studio for a bandwidth, gain, behavior of the wave, and radiation pattern demonstration. WDRA that make this replication can be used in the function of a medical technique.
Promoting resilience and biodiversity in tropical agricultural landscapes

Tropical species are facing multiple environmental pressures, whereby agricultural expansion is causing rainforest loss and climate warming is resulting in range shifts to higher elevations. In Southeast Asia, biodiversity is severely threatened by oil palm expansion and much of the remaining lowland rainforest persists within isolated fragments and protected areas (PAs). I assessed the permeability of oil palm plantations to forest dependent species by examining boundary crossing abilities of fruit-feeding butterflies. I showed that crossing was dominated by species that could potentially breed within oil palm plantations, suggesting that plantations may act as dispersal barriers to forest species. Using the PA network on Borneo as a model system, I examined the spatial distribution of climate within PAs in future, and examined the connectedness of PAs along elevation gradients. For the majority (~60-90%) of PAs, which were predominantly situated at low elevation, analogous climates in future will only be available at higher elevation, requiring species to move in order to track cooler climates. However, over half (~60-82%) of these PAs were too isolated for species with poor dispersal abilities to reach cooler, higher elevation PAs. Finally, I used a novel modelling approach based on electrical circuit theory to identify important areas of rainforest connecting PAs along elevation gradients, and showed considerable spatial overlap in expansion routes under contrasting projections of warming. Protected area extent on Borneo will need to increase by approximately one fifth (~17%) to conserve all important rainforest connections between PAs. I conclude that rainforest species may be particularly vulnerable to the impacts of continued agricultural expansion and climate change, as they may be unable to move across fragmented landscapes due to lack of connecting rainforest habitat. Management to improve linkage of PAs and ensure protection of important dispersal routes along elevation gradients should be a conservation priority.
Crystal structures of three sterically congested disilanes

Three sterically congested silanes, namely 1,1,2,2-tetraisopropyl-1,2-diphenyldisilane, 1,1,2,2-tetrakis(2-bromopropan-2-yl)-1,2-diphenyldisilane and 1,2-di-tert-butyl-1,1,2,2-tetraphenyldisilane, show lengthening of the Si—Si and Si—C bonds as compared with disilanes with smaller substituents. The packing of the tetrakis(2-bromopropan-2-yl) compound is partly organized by attractive Br⋯Br interactions.
Blockade of Cannabinoid CB1 Receptors in the Dorsal Periaqueductal Gray Unmasks the Antinociceptive Effect of Local Injections of Anandamide in Mice

Divergent results in pain management account for the growing number of studies aiming at elucidating the pharmacology of the endocannabinoid/endovanilloid anandamide (AEA) within several pain-related brain structures. For instance, the stimulation of both Transient Receptor Potential Vanilloid type 1 (TRPV1) and Cannabinoid type 1 (CB1) receptors led to paradoxical effects on nociception. Here, we attempted to propose a clear and reproducible methodology to achieve the antinociceptive effect of exogenous AEA within the dorsal periaqueductal gray (dPAG) of mice exposed to the tail-flick test. Accordingly, male Swiss mice received intra-dPAG injection of AEA (CB1/TRPV1 agonist), capsaicin (TRPV1 agonist), WIN (CB1 agonist), AM251 (CB1 antagonist), and 6-iodonordihydrocapsaicin (6-IODO) (TRPV1 selective antagonist) and their nociceptive response was assessed with the tail-flick test. In order to assess AEA effects on nociception specifically at vanilloid or cannabinoid (CB) substrates into the dPAG, mice underwent an intrinsically inactive dose of AM251 or 6-IODO followed by local AEA injections and were subjected to the same test. While intra-dPAG AEA did not change acute pain, local injections of capsaicin or WIN induced a marked TRPV1- and CB1-dependent antinociceptive effect, respectively. Regarding the role of AEA specifically at CB/vanilloid substrates, while the blockade of TRPV1 did not change the lack of effects of intra-dPAG AEA on nociception, local pre-treatment of AM251, a CB1 antagonist, led to a clear AEA-induced antinociception. It seems that the exogenous AEA-induced antinociception is unmasked when it selectively binds to vanilloid substrates, which might be useful to address acute pain in basic and perhaps clinical trials.
Space-Time Multiple-Mode Orthogonal Frequency Division Multiplexing With Index Modulation

Multiple-mode orthogonal frequency division multiplexing with index modulation (MM-OFDM-IM) improves the spectral efficiency of the conventional OFDM-IM scheme by considering multiple distinguishable constellations for signal modulation. In this paper, we propose a novel scheme, called space-time MM-OFDM-IM (ST-MM-OFDM-IM), to increase the transmit diversity of MM-OFDM-IM. In ST-MM-OFDM-IM, the signal matrix, which consists of multiple signal vectors of MM-OFDM-IM, is transmitted over multiple time slots by following a specific rule. A low-complexity detection is proposed to mitigate the high burden of the optimal maximum-likelihood detection at the receiver side. A closed-form upper bound on the bit error rate is derived to evaluate the performance of ST-MM-OFDM-IM. Moreover, a diversity improving scheme of ST-MM-OFDM-IM is also studied to obtain full transmit diversity. Simulation results verify the theoretical analysis and show that ST-MM-OFDM-IM outperforms the conventional MM-OFDM-IM scheme.
Epigenetic Inactivation of EFEMP1 Is Associated with Tumor Suppressive Function in Endometrial Carcinoma

Objective EFEMP1, the epidermal growth factor–containing fibulin-like extracellular matrix protein 1, functions as an oncogene or a tumor suppressor depending on the cancer types. In this study, we aim to determine whether EFEMP1 affects the tumorigenesis and progression of endometrial carcinoma. Methods The expression of EFEMP1 was investigated using immunohistochemistry in a panel of normal endometrium (n = 40), atypical hyperplasia (n = 10) and endometrial carcinoma tissues (n = 84). Methylation status of the EFEMP1 promoter was detected by methylation-specific PCR (MSP) and bisulphite genomic sequencing. Up- or down-regulation of EFEMP1 were achieved by stable or transient transfection with pCMV6/GFP/Neo-EFEMP1 or pGPU6/GFP/Neo-shEFEMP1 respectively. Effects of EFEMP1 on tumor proliferation, invasion and migration were evaluated by MTT, plate colony formation, Transwell and wound healing assay. The nude mouse tumor xenograft assay was used to investigate function of EFEMP1 in vivo. Results Compared with normal endometrium (32/40) and atypical hyperplasia (7/10), EFEMP1 expression was much lower in endometrial carcinoma tissues (16/84) (P<0.001 and P = 0.02). EFEMP1 promoter was hypermethylated in endometrial carcinoma tissues (67%) as compared to normal tissue (10%) and down-regulation of EFEMP1 was associated with promoter hypermethylation. Treatment with 5-aza-2′-deoxycytidine (5-aza-dC) and/or trichostatin A (TSA) altered EFEMP1 methylation status, and restored EFEMP1 expression. Moreover, EFEMP1 decreased secretion of MMPs and inhibited tumor cell proliferation, metastasis and invasion in vitro and suppressed tumorigenesis in nude mice. Besides, EFEMP1 increased expression of E-cadherin and suppressed expression of vimentin in endometrial carcinoma. Conclusion EFEMP1 is a new candidate tumor suppressor gene in endometrial carcinoma, and is frequently silenced by promoter hypermethylation. It could inhibit tumor growth and invasion both in vitro and in vivo. Our findings propose that targeting EFEMP1 might offer future clinical utility in endometrial carcinoma.
Material discrimination and mixture ratio estimation in nanocomposites via harmonic atomic force microscopy

Harmonic atomic force microscopy (AFM) was employed to discriminate between different materials and to estimate the mixture ratio of the constituent components in nanocomposites. The major influencing factors, namely amplitude feedback set-point, drive frequency and laser spot position along the cantilever beam, were systematically investigated. Employing different set-points induces alternation of tip–sample interaction forces and thus different harmonic responses. The numerical simulations of the cantilever dynamics were well-correlated with the experimental observations. Owing to the deviation of the drive frequency from the fundamental resonance, harmonic amplitude contrast reversal may occur. It was also found that the laser spot position affects the harmonic signal strengths as expected. Based on these investigations, harmonic AFM was employed to identify material components and estimate the mixture ratio in multicomponent materials. The composite samples are composed of different kinds of nanoparticles with almost the same shape and size. Higher harmonic imaging offers better information on the distribution and mixture of different nanoparticles as compared to other techniques, including topography and conventional tapping phase. Therefore, harmonic AFM has potential applications in various fields of nanoscience and nanotechnology.
Generalized RBF feature maps for Efficient Detection

Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning techniques of at most linear complexity and these are usually limited to linear kernels. This unfortunately rules out gold-standard kernels such as the generalized RBF kernels (e.g. exponential-c 2 ). Recently, Maji and Berg [13] and Vedaldi and Zisserman [20] proposed explicit feature maps to approximate the additive kernels (intersection, c 2 , etc.) by linear ones, thus enabling the use of fast machine learning technique in a non-linear context. An analogous technique was proposed by Rahimi and Recht [14] for the translation invariant RBF kernels. In this paper, we complete the construction and combine the two techniques to obtain explicit feature maps for the generalized RBF kernels. Furthermore, we investigate a learning method using l 1 regularization to encourage sparsity in the final vector representation, and thus reduce its dimension. We evaluate this technique on the VOC 2007 detection challenge, showing when it can improve on fast additive kernels, and the trade-offs in complexity and accuracy.
Self-similarity representation of Weber faces for kinship classification

Establishing kinship using images can be utilized as context information in different applications including face recognition. However, the process of automatically detecting kinship in facial images is a challenging and relatively less explored task. The reason for this includes limited availability of datasets as well as the inherent variations amongst kins. This paper presents a kinship classification algorithm that uses the local description of the pre-processed Weber face image. A kinship database is also prepared that contains images pertaining to 272 kin pairs. The database includes images of celebrities (and their kins) and has four ethnicity groups and seven kinship groups. The proposed algorithm outperforms an existing algorithm and yields a classification accuracy of 75.2%.
Constraining Balmer Alpha Fine Structure Excitation Measured in Geocoronal Hydrogen Observations

Cascade contributions to geocoronal Balmer α airglow line profiles are directly proportional to the Balmer β/α line ratio and can therefore be determined with near simultaneous Balmer β observations. Due to scattering differences for solar Lyman β and Lyman γ (responsible for the terrestrial Balmer α and Balmer β fluorescence, respectively), there is an expected trend for the cascade emission to become a smaller fraction of the Balmer α intensity at larger shadow altitudes. Near‐coincident Balmer α and Balmer β data sets, obtained from the Wisconsin H alpha Mapper Fabry‐Perot, are used to determine the cascade contribution to the Balmer α line profile and to show, for the first time, the Balmer β/α line ratio, as a function of shadow altitude. We show that this result is in agreement with direct cascade determinations from Balmer α line profile fits obtained independently by high‐resolution Fabry‐Perot at Pine Bluff, WI. We also demonstrate with radiative transport forward modeling that a solar cycle influence on cascade is expected, and that the Balmer β/α line ratio poses a tight constraint on retrieved aeronomical parameters (such as hydrogen's evaporative escape rate and exobase density).
Implementation of an Intelligent Tutoring System using Moodle

The paper presents the implementation of an Intelligent Tutoring System. The paper consists of two sections. The first section describes the framework of the Intelligent Tutoring System. In this framework, the elements of course design are identified as competencies, instructional activities and assessments. These elements are aligned using a tool called the Taxonomy Table. The second section describes the implementation. The system has been implemented on top of the Learning Management System Moodle. Prior to implementation, a study of the parameters required in a Learning Management System to build an Intelligent Tutoring System on top of, was carried out; and an evaluation of two open source Learning Management Systems was performed, which led to the decision to build the tutoring system using Moodle. Subsequently, the implementation of the expert, tutoring and student modules using Moodle are presented.
Positive Example Learning for Content-Based Recommendations: A Cost-Sensitive Learning-Based Approach

Existing supervised learning techniques can support product recommendations but are ineffective in scenarios characterized by single%class learning ; i.e., training samples consisted of some positive examples and a much greater number of unlabeled examples. To address the limitations inherent in existing single%class learning techniqu es, we develop COst%sensitive Learning%based Positive Example Learning (COLPEL), which constructs an automated classifier from a single% class training sample. Our method employs cost%prop ortionate rejection sampling to derive, from unlabeled examples, a subset likely to feature negative examples, according to the respective misclassification costs. COLPEL follows a committee machine strategy, thereby constructing a set of automated classifiers used together to reduce probable biases common to a single classifier. We use customers’ book ratings from the Amazon.com Web site to evaluate COLPEL, with PNB and PEBL as benchmarks. Our results show that COLPEL outperforms both PNB and PEBL, as measured by its accuracy, positive F1 score, and negative F1 score.
Recovery of mechano-electrical transduction in rat cochlear hair bundles after postnatal destruction of the stereociliar cross-links

Mechano-electrical transduction (MET) in the stereocilia of outer hair cells (OHCs) was studied in newborn Wistar rats using scanning electron microscopy to investigate the stereociliar cross-links, Nomarski laser differential interferometry to investigate stereociliar stiffness and by testing the functionality of the MET channels by recording the entry of fluorescent dye, FM1-43, into stereocilia. Preparations were taken from rats on their day of birth (P0) or 1–4 days later (P1–P4). Hair bundles developed from the base to the apex and from the inner to outer OHC rows. MET channel responses were detected in apical coil OHCs on P1. To study the possible recovery of MET after disrupting the cross-links, the same investigations were performed after the application of Ca2+ chelator 1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid (BAPTA) and allowing the treated samples to recover in culture medium for 0–20 h. We found that the structure and function were abolished by BAPTA. In P0–P1 samples, structural recovery was complete and the open probability of MET channels reached control values. In P3–P4 samples, complete recovery only occurred in OHCs of the outermost row. Although our results demonstrate an enormous recovery potential of OHCs in the postnatal period, the structural component restricts the potential for therapy in patients.
Cluster CLEAN: An application of CLEAN to LFMCW radar systems

The CLEAN algorithm is a widespread deconvolution method which is well suited for detecting frequency components in a signal. Originally developed to deconvolve images of the sky, over the years quite a lot of variants have been published which adapt the CLEAN algorithm to the demands of several fields of engineering. In this paper, we present Cluster CLEAN as enhancement to the CLEAN algorithm and show its application to measurement data collected with a linearly frequency-modulated continuous-wave radar system.
Mathematical and Experimental Analyses of Oppositional Algorithms

Evolutionary algorithms (EAs) are widely employed for solving optimization problems with rugged fitness landscapes. Opposition-based learning (OBL) is a recent tool developed to improve the convergence rate of EAs. In this paper, we derive the probabilities that distances between OBL points and the optimization problem solution are less than the distance between a given EA individual and the optimal solution. We find that the quasi-reflected opposition point yields the highest probability and is the most likely candidate to be closer to the optimal solution. We then employ CEC 2013 competition benchmark problems and select a set of trajectory optimization problems from the European Space Agency to study the performance of three OBL algorithms in conjunction with three different EAs. The CEC 2013 test suit simulations indicate that quasi-reflection accelerates the performance of the EA, especially for more difficult composition functions. The space trajectory experiments reveal that differential evolution with opposition generally returns the best objective function value for the chosen minimization problems.