Miracle-dz/UniFAR-FTUs huggingface dataset:
IoT-enabled multimodal sensing headwear system

With the proliferation of Internet of Things (IoT) paradigm, wearable devices and solutions aim to resolve unmet needs from military, automotive to healthcare domains. Particularly, there are growing interests in wearable Brain Computer Interface (BCI) from both commercial and research applications. Still uphill challenges lie ahead to bring such BCI technologies to mass market due to lack of technical, usability and application aspects. To fill these gaps, this paper presents design, development and evaluation of an IoT-enabled multimodal headwear system, iMESH. Our solution senses user's neural, physiological and physical states through direct measurements and derives health parameters. We then developed driving fatigue assessment application as exemplar to illustrate applicability and feasibility of the proposed solution. Initial results are promising and with ongoing development on methodologies, we are hoping to further develop and validate iMESH functionalities in different applications.
A compact triple-band multi-polarized slot antenna for WLAN/WiMAX application

A compact triple-band dual-polarized slot antenna is proposed for WLAN / WiMAX applications. A rectangular slot loop along with inverted L-shaped and C-shaped slots are introduced for achieving triple-band characteristics. By changing the slot-locations, CP behaviour is obtained at the highest operating frequency. The proposed antenna has good impedance bandwidth, compact size (0.248λ<inf>0</inf> × 0.248λ<inf>0</inf>, with λ<inf>0</inf> being the free-space wave length at 2.4 GHz) and reasonably high gain in the desired operating bands.
Anterior lumbar interbody fusion versus transforaminal lumbar interbody fusion – systematic review and meta-analysis

Purpose. To assess the clinical and radiographic outcomes and complications of anterior lumbar interbody fusion (ALIF) versus transforaminal lumbar interbody fusion (TLIF). Methods. A systematic literature search was conducted from six electronic databases. The relative risk and weighted mean difference (WMD) were used as statistical summary effect sizes. Results. Fusion rates (88.6% vs. 91.9%, P = 0.23) and clinical outcomes were comparable between ALIF and TLIF. ALIF was associated with restoration of disk height (WMD, 2.71 mm, P = 0.01), segmental lordosis (WMD, 2.35, P = 0.03), and whole lumbar lordosis (WMD, 6.33, P = 0.03). ALIF was also associated with longer hospitalization (WMD, 1.8 days, P = 0.01), lower dural injury (0.4% vs. 3.8%, P = 0.05) but higher blood vessel injury (2.6% vs. 0%, P = 0.04). Conclusions. ALIF and TLIF appear to have similar success and clinical outcomes, with different complication profiles. ALIF may be associated with superior restoration of disk height and lordosis, but requires further validation in future studies.
Gi-protein–coupled 5-HT1B/D receptor agonist sumatriptan induces type I hyperalgesic priming

Abstract We have recently described a novel form of hyperalgesic priming (type II) induced by agonists at two clinically important Gi-protein–coupled receptors (Gi-GPCRs), mu-opioid and A1-adenosine. Like mu-opioids, the antimigraine triptans, which act at 5-HT1B/D Gi-GPCRs, have been implicated in pain chronification. We determined whether sumatriptan, a prototypical 5-HT1B/D agonist, produces type II priming. Characteristic of hyperalgesic priming, intradermal injection of sumatriptan (10 ng) induced a change in nociceptor function such that a subsequent injection of prostaglandin-E2 (PGE2) induces prolonged mechanical hyperalgesia. However, onset to priming was delayed 3 days, characteristic of type I priming. Also characteristic of type I priming, a protein kinase C&egr;, but not a protein kinase A inhibitor attenuated the prolongation phase of PGE2 hyperalgesia. The prolongation of PGE2 hyperalgesia was also permanently reversed by intradermal injection of cordycepin, a protein translation inhibitor. Also, hyperalgesic priming did not occur in animals pretreated with pertussis toxin or isolectin B4–positive nociceptor toxin, IB4–saporin. Finally, as observed for other agonists that induce type I priming, sumatriptan did not induce priming in female rats. The prolongation of PGE2 hyperalgesia induced by sumatriptan was partially prevented by coinjection of antagonists for the 5-HT1B and 5-HT1D, but not 5-HT7, serotonin receptors and completely prevented by coadministration of a combination of the 5-HT1B and 5-HT1D antagonists. Moreover, the injection of selective agonists, for 5-HT1B and 5-HT1D receptors, also induced hyperalgesic priming. Our results suggest that sumatriptan, which signals through Gi-GPCRs, induces type I hyperalgesic priming, unlike agonists at other Gi-GPCRs, which induce type II priming.
Vagus Nerve Stimulation Attenuates Intestinal Epithelial Tight Junctions Disruption in Endotoxemic Mice Through &agr;7 Nicotinic Acetylcholine Receptors

ABSTRACT We tested the effect of vagus nerve stimulation in endotoxin-induced intestinal tight junction injury in mice challenged with lipopolysaccharide (LPS) and examined the role of &agr;7 nicotinic acetylcholine receptors (&agr;7nAchR) in this process. Endotoxemia was induced by intraperitoneal injection of LPS (10 mg/kg) in male Balb/c mice. Samples were collected 12 h after LPS treatment. Endotoxemia was associated with intestinal barrier dysfunction, as evidenced by increased amount of fluorescein isothiocyanate–dextran in circulation. Western blot and immunofluorescence was performed, and the results demonstrated decreased expression of occludin and zonula occludens 1 along intestinal epithelium in endotoxemic mice. The ultrastructure of tight junction was disrupted as shown by transmission electron microscopy, which was associated with increased intestinal permeability. Stimulation of the right cervical vagus nerve ameliorated the damage of tight junction ultrastructure, which was consistent with decreased permeability to fluorescein isothiocyanate–dextran, and also reversed the decreased expression of tight junction proteins occludin and zonula occludens 1. Vagus nerve stimulation inhibited the upregulated activity of myosin light chain kinase and nuclear factor &kgr;B. In contrast, &agr;-bungarotoxin (a specific &agr;7nAchR antagonist, 0.1 &mgr;g/mouse) administered before vagus nerve stimulation significantly abolished these protective effects of vagus nerve stimulation. Our results for the first time confirmed that vagus nerve stimulation attenuated the disruption of tight junction in intestinal epithelium in endotoxemic mice, which was mediated through suppressing translocation of nuclear factor &kgr;B p65, downregulating myosin light chain kinase, and the &agr;7nAchR may play an important role in this process.
Mechanical stress mediated by both endosperm softening and embryo growth underlies endosperm elimination in Arabidopsis seeds

Seed development in angiosperms demands the tightly coordinated development of three genetically distinct structures. The embryo is surrounded by the endosperm, which is in turn enclosed within the maternally derived seed coat. In Arabidopsis, final seed size is determined by early expansion of the coenocytic endosperm, which then cellularises and subsequently undergoes developmental programmed cell death, breaking down as the embryo grows. Endosperm breakdown requires the endosperm-specific basic helix-loop-helix transcription factor ZHOUPI. However, to date, the mechanism underlying the Arabidopsis endosperm breakdown process has not been elucidated. Here, we provide evidence that ZHOUPI does not induce the developmental programmed cell death of the endosperm directly. Instead ZHOUPI indirectly triggers cell death by regulating the expression of cell wall-modifying enzymes, thus altering the physical properties of the endosperm to condition a mechanical environment permitting the compression of the cellularised endosperm by the developing embryo. Summary: Elimination of the Arabidopsis endosperm during seed development involves a developmental programmed cell death process requiring cell wall modifications and mechanical stresses imposed by embryo growth.
Association of major dietary patterns with resting metabolic rate and body fatness in middle-aged men and women: Results from a cross-sectional study

Background: The association of dietary patterns and resting metabolic rate is still unclear. Aim: To study the relationship between the major dietary patterns, resting metabolic rate, and adiposity measures in Iranian adults. Methods: This is a cross-sectional study of 270 adults aged between 18–45 years old who lived in Tehran. Dietary intakes were achieved using food frequency questionnaire. Resting metabolic rate was measured using indirect calorimetry. Anthropometric measures were recorded using body composition analyzer. Results: Three major dietary patterns were identified by factor analysis labeled as healthy pattern (vegetables, fruits, and fruits juices, legumes, poultry, nuts, fish, egg, low fat dairy product, olive, and olive oil), mixed pattern (non-refined cereals, vegetables, vegetable oils, mayonnaise, high fat dairy product and, pickles), Western pattern (refined cereals, red or processed meat, soft drinks, sweets and desserts, Tea and coffee, salty snacks and French fries). After adjusting for covariates higher score of the Western dietary pattern was associated with lower resting metabolic rate (p = 0.023). There was significant decreasing difference in means for fat free mass across tertiles of mixed pattern when the first tertile was compared to the third tertile (p = 0.046). Higher adherence to healthy pattern was associated with lower body weight (p = 0.034), body mass index (p = 0.021), and higher resting metabolic rate (p = 0.033). Conclusions: Higher adherence to the Western dietary pattern was associated with a lower amount of resting metabolic rate. Also higher adherence to the healthy dietary pattern was associated with higher resting metabolic rate and lower body weight and body mass index. Further studies are required to examine the causal relationship between dietary patterns and resting metabolic rate.
Prediction of Bitcoin exchange rate to American dollar using artificial neural network methods

Cryptocurrency trade is now a popular type of investment. Cryptocurrency market has been treated similar to foreign exchange and stock market. However, because of its volatility, there's a need for a prediction tool for investors to help them consider investment decisions for cryptocurrency trade. Nowadays, Artificial Neural Network (ANN) computing based tools are commonly used in stock and foreign exchange market predictions. There has been much research about ANN predictor on stocks and foreign exchange as case studies but none on cryptocurrency. Therefore, this research studied variety of ANN method to predict the market value of one of the most used cryptocurrency, Bitcoin. The ANN methods will be used to develop model to predict the close value of Bitcoin in the next day (next day prediction). This study compares four ANN methods, namely backpropagation neural network (BPNN), genetic algorithm neural network (GANN), genetic algorithm backpropagation neural network (GABPNN), and neuro-evolution of augmenting topologies (NEAT). The methods are evaluated based on accuracy and complexity. The result of the experiment showed that BPNN is the best method with MAPE 1.998 ± 0.038 % and training time 347 ± 63 seconds.
Fast proton spectroscopic imaging employing k‐space weighting achieved by variable repetition times

A k‐space weighted spectroscopic imaging (SI) method is presented that allows a reduction in the total data acquisition time by up to 55% compared with standard SI. The k‐space weighting is achieved by varying the repetition time, thus realizing an inherent apodization that corresponds to a circularly symmetric generalized Hamming filter. The flip angle is varied with the repetition time to enhance the signal‐to‐noise ratio. These techniques were employed using a short echo time of 10 ms. In vivo measurements on healthy rat brain at 4.7 T were conducted, obtaining two‐dimensional spectroscopic imaging data from a 25 × 25 circularly reduced k‐space area in as little as 5 min. The signal‐to‐noise ratio is sufficiently high to detect J‐coupled resonances such as myo‐inositol or glutamate/glutamine, demonstrating the ability to combine short acquisition times with comprehensive metabolic information. The T1 dependency of the apodization and the corresponding point spread function was evaluated by computer simulations. The achievable signal‐to‐noise ratio per unit time was compared with standard SI giving a parameter‐dependent advantage of approximately 20% of the standard SI method.
Basic Physics and Numerical Modelling of Climate

Despite the basic significance of the environment to many needs of Mission Earth and humans, attainable climate models are likely to provide only general guidance to world simulation in the desirable time-frame, not detailed changes and statistical properties. Some aspects of climate simulation, however, illustrate difficulties that may appear in other large-scale, complicated simulations. The fundamental physics of atmospheric waves, their forcing functions and their interactions are described. As a thermodynamically open system, the atmosphere is not very close to macroscopic local detailed balance. There are interactions across many scales of physics, particularly in the budgets of latent heat and radiative flux divergence. The carbon dioxide stored in the ocean appears to be much greater than that for equilibrium with the present partial pressure in the atmosphere. Although release of stored methane appears the most likely large-scale violation of Le Châtelier's principle, it is not now known how far the atmosphere is from non-extremality of the entropy generation rate, or other major transition in thermodynamic regime, nor whether such phenomena are attainable beyond a previously suggested duality in ocean transports. One suggestion is that the climate system historically has switched between two major regimes as a result of internal and external fluctuations.
The Economics of Canadian Oil Sands

We analyze the status of Canadian oil sands and examine future prospects. Our analysis suggests sustained activity in the sector in the medium- to long-term even with challenging changes in the surrounding economic and policy circumstances (in particular low oil prices and a redoubled commitment to more aggressive climate policies by Canada’s provincial and federal governments). However, a combination of an expectation of a sustained increase in benchmark oil prices and the expected relaxation of transportation constraints will be needed to stimulate significant additional growth in production. We provide an overview of the basic production economics, as well as the economics and politics of getting product to market by pipeline and rail. A review of environmental impacts of Canadian oil sands development reveals significant concerns with respect to air quality, water quality, wildlife and other environmental impacts. However, we find that existing research on the environmental and wider social impacts is insufficient to underpin credible benefit–cost analysis of oil sands activities and development.
Performance analysis on wireless unicast with network coding

In this paper, network coding is used to improve the wireless unicast performance. We consider a wireless switching network model with erasure channel, where M nodes exchange their packets via relay node. The sender transmits packets to the receiver via relay node independently. The relay node combines packets transmitted to the same receiver from different source nodes to save bandwidth. This paper aims to analyze the performance of wireless unicast. We also analyze the performance of unicast in traditional transmission scheme and compare it with network coding scheme. Our result shows that, in terms of transmission bandwidth, the performance of unicast will be improved highly. The gains depend on the transport protocol, and network environment. In this paper, linear network coding would be used at the relay node for low complexity.
An Investigation into Perceived Productivity and Its Influence on the Relationship Between Organizational Climate and Affective Commitment

AN INVESTIGATION OF PERCEIVED PRODUCTIVITY AND ITS INFLUENCE ON THE RELATIONSHIP BETWEEN ORGANIZATIONAL CLIMATE AND AFFECTIVE COMMITMENT Kaitlynn M. Castelle Old Dominion University, 2016 Director: Dr. Charles B. Daniels The purpose of this research is to investigate the influence of individually perceived productivity on the relationship between individually assessed organizational climate and affective commitment, from heterogeneous survey participant data. A theoretical framework is adopted to explain how organizational climate shapes employee perception and how this relationship is moderated by a perceived productivity. This is a relatively unexplored concept in the defined context and has been developed by the researcher. Perceived productivity was measured using an instrument developed in this research to gauge respondents’ perception of their productivity. The instrument, named the General Measure of Perceived Productivity (GMPP), was developed in a mixedmethods approach that employed both qualitative and quantitative tools. Exploratory factor analysis (EFA) of the instrument was performed to establish validity and reliability, using pilot survey data. The main study applied the GMPP along with other research variable instruments to measure organizational climate and affective commitment, also at the individual unit of analysis. Moderated multiple regression analysis was used in the proposed model, in which perceived productivity moderates the relationship between organizational climate (the independent variable) and affective commitment (the dependent variable). The results demonstrate that the relationship between organizational climate and affective commitment depends on the level of perceived productivity, and is strengthened in the presence of higher perceived productivity. This research supports the existing body of literature relating to organizational behavior while developing a theory on a new concept, perceived productivity.
Optimal motion planning of mobile manipulators with minimum number of platform movements

In many practical applications the end effector of a mobile robotic manipulator is required to reach a set of desired positions and orientations. This is commonly achieved through a combination of platform repositionings and manipulator reconfigurations. Considering the fact that precise repositioning of the platform of an articulated mobile robot is complex and time-consuming, we propose a novel motion planning approach that would minimize the number of platform repositionings and manipulator reconfigurations for place to place tasks. The proposed approach would also guarantee that the joint limits are not crossed and obstacles are avoided. The approach comprises two steps. First the optimal manipulator configurations corresponding to desired end-effector poses are determined and then successive optimal configurations are connected with minimal paths. Rapidly-Exploring Random Trees (RRTs) are used to design configuration-connecting paths. Results of simulated experiments on a 10 DOF mobile manipulator have demonstrated the applicability and effectiveness of the proposed approach.
Quantitative determination of the reduction of phototoxicity and photobleaching by controlled light exposure microscopy

Phototoxicity and photobleaching are major limitations in live‐cell fluorescence microscopy. They are caused by fluorophores in an excited singlet or triplet state that generate singlet oxygen and other reactive oxygen species. The principle of controlled light exposure microscopy (CLEM) is based on non‐uniform illumination of the field of view to reduce the number of excited fluorophore molecules. This approach reduces phototoxicity and photobleaching 2‐ to 10‐fold without deteriorating image quality. Reduction of phototoxicity and photobleaching depends on the fluorophore distribution in the studied object, the optical properties of the microscope and settings of CLEM electronics. Here, we introduce the CLEM factor as a quantitative measure of reduction in phototoxicity and photobleaching. Finally, we give a guideline to optimize the effect of CLEM without compromising image quality.
Vehicle Re-Identification by Adversarial Bi-Directional LSTM Network

Vehicle re-identification (re-ID) is an area that has received far less attention in the computer vision community than the prevalent person re-ID. Possible reasons for this slow progress are the lack of appropriate research data and the special 3D structure of a vehicle. Previous works have generally focused on limited views (e.g. front and rear), but these methods are less effective in realistic scenarios where vehicles usually appear in arbitrary views to cameras. In this paper, we focus on the uncertainty of vehicle viewpoint in re-ID, proposing an Adversarial Bi-directional LSTM Network (ABLN). Our model exploits the great advantages of the Long Short-Term Memory (LSTM) to model transformations across continuous view variations of a vehicle and adopts the adversarial architecture to enhance training. Thus, a global vehicle representation containing all views' information can be inferred from only one visible view, and then used for learning to measure the distance between two vehicles with arbitrary views. To verify our model, we evaluate the proposed method on the public VehicleID and VeRi datasets. Experimental results illustrate that our approach achieves consistent improvements over state-of-the-art vehicle re-ID methods.
Correspondence between audio and visual deep models for musical instrument detection in video recordings

This work aims at investigating cross-modal connections between audio and video sources in the task of musical instrument recognition. We also address in this work the understanding of the representations learned by convolutional neural networks (CNNs) and we study feature correspondence between audio and visual components of a multimodal CNN architecture. For each instrument category, we select the most activated neurons and investigate existing cross-correlations between neurons from the audio and video CNN which activate the same instrument category. We analyse two training schemes for multimodal applications and perform a comparative analysis and visualisation of model predictions.
Building a Process Driven Organization with the Process Normalization Technique

Despite the importance, the methodological standards for business process modeling are still very much insufficient. One of the most important aspects which must be covered with the process models is essential unity of object oriented and process oriented views of a business system. To achieve such unity, this article introduces a process normalization technique as part of the Methodology for Modeling and Analysis of Business Processes (MMABP). This technique is freely inspired by the famous 'ancient' Normalization of Data Structures technique which we regard as relevant and correct because of the essential unity of objects and processes in the business system. At the same time it can be seen that harmonizing the structure of processes with the (conceptual) structure of the Real World directly fulfills the objective. The goal of this article is to illustrate the steps of process normalization with examples. Important connected problems of structural algorithmic thinking, as well as other ways of manifesting the previously mentioned essential object-processes unity in the business system, are also discussed in the article.