Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional glia-related metabolite levels are higher at older age and scale negatively with visuo-spatial working memory: A cross-sectional proton MR spectroscopy study at 7 tesla on normal cognitive ageing

Proton MR spectroscopy (1H-MRS) has been used to assess regional neurochemical brain changes during normal ageing, but results have varied. Exploiting the increased sensitivity at ultra-high field strength, we performed 1H-MRS in 60 healthy volunteers to asses age-related differences in neuron- and glia-related metabolite levels and their relation to cognitive ageing. Gender was balanced and participants were assigned to a younger, middle and older group according to their age, ranging from 18 to 79 years. They underwent 1H-MRS of anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus and thalamus and performed a visuo-spatial working memory task outside the scanner. Multivariate ANCOVA revealed a significant overall effect of age group on metabolite levels in all brain regions of interest. Considering specific metabolites, elevated levels of glia-related metabolites in older age groups were observed in all brain regions. For the neuron-related metabolites, differences among age groups were only observed in two regions. We found higher levels of total N-acetyl aspartate in hippocampus for the older than the middle group, and lower levels of glutamate in DLPFC in the older than the younger group. Working memory performance correlated negatively with levels of glia-related metabolites for total creatine and total choline in ACC and myo-inositol in hippocampus and thalamus, but not with neuron-related metabolites. Together, the results show that age effects on glia-related metabolites scale with cognitive ageing in multiple brain regions. We conclude that 1H-MRS-derived glia-related markers may be of value in longitudinal studies of brain ageing. Significance statement Neurochemical ageing is an integral component of age-related cognitive decline. Proton MR spectroscopy (1H-MRS) studies of in vivo neurochemical changes across the lifespan have, however, yielded inconclusive results. Due to the higher spectral resolution and sensitivity, 7 tesla 1H-MRS has potential to improve consistency of the results. Here we apply this technique to demonstrate that glia-related metabolites are elevated in older age in anterior cingulate cortex, hippocampus and thalamus with a novel link to cognitive ageing of visuo-spatial working memory. This study is the first to investigate normal ageing in these brain regions using 7 tesla 1H-MRS and the results indicate that glia-related metabolites could be of value in longitudinal studies of cognitive ageing.
Visual Indicator Based on Leuco Crystal Violet for Radiation Processing Technology

One of the important technologies for food preservation and processing is radiation processing, which is growing at ever increasing rate in India. Efforts are being done to make it more cost-effective, so there is always a need for cost-effective, indigenously developed visual indicators for providing an easy identification and segregation of irradiated products. Thus development of cost-effective visual indicator based on leuco crystal violet for doses ≥ 10 kGy was under taken. Current research works deals with fabrication and characterization of various parameters such as optimum composition, light stability, temperature effect and effect of relative humidity on the new indicator.
The Role of National Culture on the Design and Usability of E-Commerce Websites: An Indonesian Case

The purpose of this study is to observe national culture influence on the effectiveness of Indonesian e-commerce website. Ninety Indonesian subjects participated voluntarily in this study. Subjects were instructed to complete a transaction in three different tailored e-commerce websites. The first e-commerce website is designed following cultural guideline of web design. The second e-commerce website is designed opposing the guideline, whereas the third e-commerce website is designed in combination between following and opposing the cultural guideline. Completion time and error during task were recorded. In the end of the task completion, subjects filled out a questionnaire about the importance of design items that correlate with cultural dimensions. Result shows no significant differences on completion time and error for task completion among the three e-commerce websites, although the first e-commerce website has lowest process time and error. Most of design items that relates to cultural dimensions is rated positively by participants. Result of the study reveals that national culture is worth to be considered in the design of the Indonesian e-commerce website. Implications of the results were discussed.
Faster than thought: Detecting sub-second activation sequences with sequential fMRI pattern analysis

Neural computations are often anatomically localized and executed on sub-second time scales. Understanding the brain therefore requires methods that offer sufficient spatial and temporal resolution. This poses a particular challenge for the study of the human brain because non-invasive methods have either high temporal or spatial resolution, but not both. Here, we introduce a novel multivariate analysis method for conventional blood-oxygen-level dependent functional magnetic resonance imaging (BOLD fMRI) that allows to study sequentially activated neural patterns separated by less than 100 ms with anatomical precision. Human participants underwent fMRI and were presented with sequences of visual stimuli separated by 32 to 2048 ms. Probabilistic pattern classifiers were trained on fMRI data to detect the presence of image-specific activation patterns in early visual and ventral temporal cortex. The classifiers were then applied to data recorded during sequences of the same images presented at increasing speeds. Our results show that probabilistic classifier time courses allowed to detect neural representations and their order, even when images were separated by only 32 ms. Moreover, the frequency spectrum of the statistical sequentiality metric distinguished between sequence speeds on sub-second versus supra-second time scales. These results survived when data with high levels of noise and rare sequence events at unknown times were analyzed. Our method promises to lay the groundwork for novel investigations of fast neural computations in the human brain, such as hippocampal replay.
Towards Autonomous Intra-cortical Brain Machine Interfaces: Applying Bandit Algorithms for Online Reinforcement Learning

This paper presents application of Banditron - an online reinforcement learning algorithm (RL) in a discrete state intra-cortical Brain Machine Interface (iBMI) setting. We have analyzed two datasets from non-human primates (NHPs) - NHP A and NHP B each performing a 4-option discrete control task over a total of 8 days. Results show average improvements of ≈ 15%, 6% in NHP A and 15%, 21% in NHP B over state of the art algorithms - Hebbian Reinforcement Learning (HRL) and Attention Gated Reinforcement Learning (AGREL) respectively. Apart from yielding a superior decoding performance, Banditron is also the most computationally friendly as it requires two orders of magnitude less multiply-and-accumulate operations than HRL and AGREL. Furthermore, Banditron provides average improvements of at least 40%, 15% in NHPs A, B respectively compared to popularly employed supervised methods - LDA, SVM across test days. These results pave the way towards an alternate paradigm of temporally robust hardware friendly reinforcement learning based iBMIs.
Decentralized Diagnosis of Networked Discrete Event Systems Subject to Denial of Service Attacks

: In this paper, we address the problem of decentralized failure diagnosis of networked discrete event systems (NDES) in the presence of Denial-of-Service (DoS) attacks. We propose an automaton model for NDES subject to DoS attacks that represent the adverse eﬀects of DoS attacks on the observations of local diagnosers. We formulate a new diagnosis property, to be referred here to as DoS-robust codiagnosability, and present a systematic way to verify whether the language generate by a NDES is DoS-robustly codiagnosable.
An Assessment of Health Literacy Rates in a Sample of Active-Duty Military Personnel at a Major Medical Center

Abstract : Research in the national population has revealed a link between limited health literacy and disparities in health care utilization and resulting health status. Limited health literacy has also been found at higher rates among individuals who are non-whites, have lower education levels and/or income, and may differ by gender. In the military health system (MHS),gender, race, educational level and income should not impact the availability of health services as all active-duty personnel have universal access to health care. Yet disparities continue to exist in utilization of preventive services and achievement of goals related to improved health status and health outcomes. Limited health literacy may be contributing to these disparities in active duty military personnel with universal access to health care, services, and information. To date, there are no published research studies assessing health literacy in the active-duty military population. Before studies can be conducted to explore the relationship between limited health literacy and health status/outcomes in active duty personnel, research is needed to determine health literacy rates in active duty personnel and the comparability of these rates to rates in the national population. Objective. The purpose of this study was to determine health literacy rates in active duty military personnel receiving health care and services within a culture of universal access, and to compare the health literacy rates of the national population to those of the active duty military.
Personalized Medicine, Disruptive Innovation, and “Trailblazer” Guidelines: Case Study and Theorization of an Unsuccessful Change Effort

Policy Points For complex reasons, the promise of “precision medicine” based on molecular pathways remains unrealized for many conditions. Clinical practice guidelines (theoretically, at least) can act as “trailblazers” to introduce tests and treatments that reflect precision medicine discoveries. We describe a detailed case study from the United Kingdom in which such an attempt was (so far) unsuccessful and show how this case provides generalizable lessons. Policymakers should be wary of using clinical practice guidelines as the sole, or even the primary, lever for introducing precision medicine. Context Precision medicine, which addresses underlying molecular mechanisms of disease, depends on new technologies that measure specific biomarkers, leading (it is anticipated) to more accurate diagnosis, patient stratification, and tailored treatment. These technologies can be disruptive—that is, they make possible, and often require, radical changes to clinical practice and service organization—thereby improving quality, safety, or efficiency of care. Clinical practice guidelines may act as “trailblazers,” introducing and legitimizing novel technologies and practices. Methods We describe a case study of an attempt by academic researchers to radically change asthma management in the United Kingdom using a precision medicine biomarker (fractional exhaled nitric oxide, FeNO), measured using a portable breath device. We collected a wide‐ranging data set that included more than 100 documents, 61 interviews, and 150 hours of ethnographic observation, and we analyzed it using technology‐enhanced strong structuration theory (TESST). Findings Our study describes a so‐far unsuccessful attempt by academic respiratory medicine researchers to pave the way for a precision medicine approach to asthma using a government‐endorsed national guideline. These researchers considered asthma management, especially in primary care, to be characterized by overdiagnosis and poor tailoring of treatment; engaged a national guideline development body in an effort to fix this problem; and ensured that the guideline required primary care clinicians to use FeNO technology for diagnosis and monitoring. However, clinicians working outside the tertiary referral centers did not accept, or agree to enact, the vision of precision medicine inscribed in the guideline—for multiple professional, operational, and economic reasons. Conclusions “Trailblazer” guidelines, in which new technologies are recommended, may succeed as catalysts of change only in a limited way for interested individuals and groups. In the absence of a wider program of professionally led and adequately resourced change efforts, such guidelines will lack meaning, legitimacy, and authority among intended users and may be strongly resisted.
What are the important technologies for bin picking? Technology analysis of robots in competitions based on a set of performance metrics

ABSTRACT Bin picking is still a challenge in robotics, as patent in recent robot competitions. These competitions are an excellent platform for technology comparisons since some participants may use state-of-the-art technologies, while others may use conventional ones. Nevertheless, even though points are awarded or subtracted based on the performance in the frame of the competition rules, the final score does not directly reflect the suitability of the technology. Therefore, it is difficult to understand which technologies and their combination are optimal for various real-world problems. In this paper, we propose a set of performance metrics selected in terms of actual field use as a solution to clarify the important technologies in bin picking. Moreover, we use the selected metrics to compare our four original robot systems, which achieved the best performance in the Stow task of the Amazon Robotics Challenge 2017. Based on this comparison, we discuss which technologies are ideal for practical use in bin picking robots in the fields of factory and warehouse automation. GRAPHICAL ABSTRACT
Love Your Mistakes!-They Help You Adapt To Change. The New Scale Of Learning Culture

Purpose: There is no learning without making mistakes. Collaboration, knowledge, and learning culture shape organizational behaviors. Hence, this study aims to develop a theoretical model of the above constructs to determine how mistakes are related to organizational intelligence based on the structural model, including the relations between the above constructs. Methodology: New scales of the above constructs, including the learning culture scale, which is composed of the dimensions of â€œacceptance of mistakesâ€ and â€œlearning climate,â€ were developed and validated based on two samples: students aged 18â€“24 and employees aged >24 who work in knowledge-driven organizations. Structural equation models were then developed, assessed, and compared. Findings: Mediated by â€œacceptance by mistakes,â€ the effect of the â€œlearning climateâ€ on â€œchange adaptabilityâ€ has been detected for young students aged 18-24 but this relation is not significant for business employees aged >24. Limitations: Both samples were obtained from Poland, and â€œbusiness sampleâ€ is in majority represented by small- and medium-sized companies. Hence, the business sample may reflect national culture. Big companies, more mature, usually design their own culture fitted to their business aims. Therefore, this study can be replicated for big Polish companies, international companies located in Poland and, for other countries. Practical implications: Acceptance of mistakes is vital for learning culture development. Mistakes help employees adapt to change. Hence, a learning culture that excludes the acceptance of mistakes is somehow artificial and may be unproductive. Paradoxically, the fact that employee intelligence (change adaptability) is increasing via mistakes does not mean that organizational intelligence is increasing. It suggests that Polish knowledge organizations are not learning organizations. Scientific implications: In this study, mistakes are presented as a precious resource that enables the adaptation and development of intelligence. Hence, this study opens a new area of research in the â€œmanagement of organizational mistakes. â€ Novelty: This study breaks with the convention of â€œexcellenceâ€ and promotes the acceptance of mistakes in organizations to develop organizational intelligence. This study is also the first to propose a constant learning culture scale that embodies the acceptance of mistakes and â€œlearning climate. â€ Further, it empirically proves the value of mistakes.
Which is more beneficial in treating nausea and vomiting associated with pregnancy, serotonin antagonists, or dopamine antagonists?

causes, alternative treatments, and available support groups. Response to therapy was measured by the Massachusetts General Hospital Hairpulling Scale (MGHHS), which measures patient/guardianreported severity of urges, behavior, and consequences of hair pulling from trichotillomania with a multiquestion survey scored 0 (no symptoms) to 4 (constant/severe symptoms) for a total of up to 28 points. From baseline to 12 weeks, the N-acetylcysteine group improved its MGHHS score by 2.5 points (mean score 13.2–10.7) and the placebo group improved by 3.1 points (mean score 16.6–13.5). A linear mixed model analysis indicated that the improvement in both groups over time was significant (P5.002), but the difference between the groups was not significant (P51). This RCT was limited by small sample size, the impact of adverse effects of N-acetylcysteine including patients with nausea and rash (N51), failure to account for potential impact of repeated assessments, financial compensation for participants, and the use of a self-report measure instead of a clinician-rated measure or pill count.
First record of Acanthosiphonia echinata (Rhodomelaceae, Rhodophyta) in the Mediterranean Sea, molecular and morphological characterization

Abstract In this study we report the first finding of the red alga Acanthosiphonia echinata in the Mediterranean Sea. Specimens were identified using the DNA barcoding method and, in particular, the plastidial rbcL and the mitochondrial COI-5P markers. This species has been considered to be restricted to the western Atlantic and was reported in blooms from North Carolina to South Carolina. In 2015 the introduction of this species in Southeast Asia (Indonesia) was reported. Probably this taxon was introduced in the Mediterranean Sea from Indonesian populations associated with seaweed farming activities or hull fouling, via the western Atlantic-Mediterranean-Indonesia ship route.
Effect of Different Reduction Methods on the Structure of Graphene Oxide

The samples of graphene oxide were prepared by Hummers method, and then they were reduced and dried by different methods. The effects of different treatment methods on the graphene oxide’s morphology, size and oxygen content were analysed by IR, Roman and TEM. The results show that the reduction method of increasing temperature can effectively reduce the oxygen content of graphene oxide but increase the defect density. However, the ultrasonic cell pulveriser can effectively reduce the oxygen content of graphene oxide in the reduction process and has little effect on the defect density. Therefore, low-defect and low-oxygen reduced graphene oxide can be quickly obtained by an ultrasonic cell pulveriser.
Mapping Canadian Men’s Recent and Intended Health Behavior Changes Through the Don’t Change Much Electronic Health Program

Background Although evaluation studies confirm the strong potential of men’s electronic health (eHealth) programs, there have been calls to more fully understand acceptability, engagement, and behavior change to guide future work. Relatedly, mapping of behavior changes using health promotion theories including the transtheoretical model (or stages of change) has been recommended to build a translatable empirical base to advance design and evaluation considerations for men’s eHealth programs. Objective This study aimed to use a benchmark sample as a reference group to map the recent and intended health behavior changes in Canadian men who use the Don’t Change Much (DCM) eHealth program. The hypothesis being tested was that increased exposure to DCM would be positively associated with men’s recent and intended health behavior changes. Methods DCM users (n=863) were sampled for demographic data and self-reported recent and intended health behavior changes. Respondents also reported their usage (frequency and duration) for each of the 3 DCM components (web, newsletter, and social media) and were allocated to limited exposure (257/863, 29.8%), low exposure (431/863, 49.9%), and high exposure (175/863, 20.3%) subgroups. A benchmark sample (n=2000), comprising respondents who had not accessed DCM provided a reference group. Bivariate analysis of recent and intended health behavior changes and DCM exposure levels were used to compute the strength of association between the independent variables (exposure levels) and the 10 categorical dependent variables (recent and intended health behavior changes). Binary logistic regression models were computed for each of the 10 recent and intended health behavior changes. Linear regression was used to model the association between the number of recent and intended changes and the level of exposure to DCM. Results Compared with the benchmark reference group, DCM high-exposure respondents had significantly increased odds for 9 of the 10 health behavior changes, with the largest effect size observed for Changed diet or Improved eating habits (odds ratio [OR] 5.628, 95% CI 3.932-8.055). High-exposure respondents also had significantly increased odds for 9 intended health changes, with the largest effect sizes observed for Reduce stress level (OR 4.282, 95% CI 3.086-5.941). Moderate effect size (goodness of fit) was observed for increased total number of recent (F12,2850=25.52; P.001; adjusted R2=.093) and intended health behavior changes (F12,2850=36.30; P.001; adjusted R2=.129) among high-exposure respondents. Conclusions DCM respondents contrasted the predominately precontemplative benchmark sample mapping across the contemplative, preparation, and action stages of the transtheoretical health behavior change model. Almost 10% of variation in the recent and 13% of variation in the intended health behavior changes can be explained by DCM exposure and demographic factors, indicating the acceptability of this men’s eHealth resource.
A Survey on Electric Buses—Energy Storage, Power Management, and Charging Scheduling

In recent years, aiming to reduce the metropolitan air pollution caused by fossil fuel-powered vehicles, the electrification of transportation, such as electric vehicles (EVs) and electric buses (EBs), has attracted great attention from the automobile industry, academia, and public transportation. EBs, driven by decarbonized electricity, can reduce the air pollution and noise level. Besides, they can also recover electricity from regenerative braking. Recent years have witnessed continuous works on the topics of EB energy storage, power management, and charging scheduling. In this review, we have comprehensively surveyed three primary parts: important components; existing research topics; and open issues of EBs. Specifically, we first introduce the important components of EBs, including energy storage systems, powertrains, interleaving elements and electric motors, and driving cycles. Then, we review the existing research topics of EBs, including the energy storage system sizing, power/energy management, range remedy methods, charging design/scheduling, and trial projects. At last, extending from existing literatures, we further propose the future research opportunities and ongoing challenges, such as extending EV related research to EBs, EB charging demand modeling, and EB impact on power systems.