Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and performance of spectral efficient modified new diagonal code for a spectral amplitude code-optical code division multiple access system

Abstract. Our study contains performance and design of a spectral amplitude code-optical code division multiple access (SAC-OCDMA) system using proposed modified new diagonal (MND) code. The proposed MND code has advantages as very low cross-correlation value compared to other code sequences. Also the code has a short length for the higher code weight value. Furthermore, due to its enormous code property, it also introduces very low multiple access interference. Thus the MND code-based SAC-OCDMA system permits a higher number of users. The MND code construction method is also explained, which is very easy using diagonal matrices. Based on the theoretical analysis, bit error rate (BER) performance of MND code AND-subtraction scheme compare with conventional codes is better than random diagonal code, Pascal’s triangle matrix code (PTMC), and multidiagonal (MD) code, which makes it spectral efficient. It provides 5 dB lower BER compared to MD code and PTMC for 90 users. Simulation of the MND code-based system for four users with 2 Gbps data rate has been successfully demonstrated using the AND-subtraction scheme and the direct detection scheme.
How to Assess in vitro Probiotic Viability and the Correct Use of Neutralizing Agents

Probiotic viability is generally determined by quantifying its resistance to simulated gastric juice or to simulated intestinal fluid in in vitro tests, which measure microbial survival after given periods of contact. The use of a neutralizing agent is needed to avoid a carry-over of gastric or intestinal juice into the culture media of the subsequent analysis and to avoid any antimicrobial effect extended over the defined period of contact of the test. Neutralization of gastric juice and intestinal juice are of the utmost importance to present data accurately. Failing to do so determines a carry-over of bactericidal activity to the plates used for the enumeration, which further reduces the number of surviving cells. Examples of such incorrect adaptation of the test are available in literature. The purpose of this perspective stems from the discovery that many studies do not adhere to internationally recognized standards, e.g., EN 1040:2005 (European Committee for Standardization [ECS], 2005), to evaluate the basic, bactericidal activity of compounds, especially for the neutralization step.
The Distribution of Nickel in the West-Atlantic Ocean, Its Relationship With Phosphate and a Comparison to Cadmium and Zinc

Nickel (Ni) is a bio-essential element required for the growth of phytoplankton. It is the least studied bio-essential element, mainly because surface ocean Ni concentrations are never fully depleted and Ni is not generally considered to be a limiting factor. However, stimulation of growth after Ni addition has been observed in past experiments when seemingly ample ambient dissolved Ni was present, suggesting not all dissolved Ni is bio-available. This study details the distribution of Ni along the GEOTRACES GA02 Atlantic Meridional section. Concentrations of Ni were lowest in the surface ocean and the lowest observed concentration of 1.7 nmol kg–1 was found in the northern hemisphere (NH). The generally lower surface concentrations in the NH subtropical gyre compared to the southern hemisphere (SH), might be related to a greater Ni uptake by nitrogen fixers that are stimulated by iron (Fe) deposition. The distribution of Ni resembles the distribution of cadmium (Cd) and also features a so called kink (change in the steepness of slope) in the Ni-PO4 relationship. Like for Cd, this is caused by the mixing of Nordic and Antarctic origin water masses. The overall distribution of Ni is driven by mixing with an influence of regional remineralization. This influence of remineralization is, with a maximum remineralization contribution of 13% of the highest observed concentration, smaller than for Cd (30%), but larger than for zinc (Zn; 6%). The uptake pattern in the formation regions of Antarctic origin water masses is suggested to be more similar to Zn than to Cd, however, the surface concentrations of Ni are never fully depleted. This results in a North Atlantic concentration distribution of Ni where the trends of increasing and decreasing concentrations between water masses are similar to those observed for Cd, but the actual concentrations as well as the uptake and remineralization patterns are different between these elements.
A Comparative Study of Leisure Constraints in Outdoor Leisure Activities Depending on Recognition of the Level of Particulate Matter (PM10): Focused on Golf Participants in the Republic of Korea

Abstract Particulate matter, one of the most recent social problems in Korea, not only poses a threat to people’s health, but is also emerging as a constraint to discourage outdoor leisure activities. Golf, a leisure sport played outdoors for hours, is not free from such a threat, and now is time to analyze golfers’ recognition of particulate matter. To examine whether particulate matter, among other constraints for golfers, had a significant effect as well as how golfers recognized particulate matter, we used 324 collected questionnaires in this study. After exploratory factor analysis and reliability analysis through SPSS 23.0, we divided questionnaire participants into recognition and non-recognition groups based on whether they checked and recognized atmospheric conditions, including particulate matter, before playing golf, and used multivariate analysis of variance (MANOVA) to compare and analyze leisure constraints. Respondents in the recognition group who recognized particulate matter in advance experienced participation constraints in weather and health factors, while those in the non-recognition group experienced participation constraints in skill and confidence factors. In other words, respondents participated in outdoor leisure activities even though they recognized the level of hazardous particulate matter in the air beforehand, and particulate matter worked as a participation constraint for them; this finding confirmed that it will be necessary in the future to take preventative action more actively against the danger of particulate matter.
ACM Transactions on Internet of Things

The Internet of Things (IoT) demands synergy among several research domains and incorporates a broad range of multidisciplinary topics, including low-power wireless networking, embedded systems, data streaming architectures, data analytics and machine learning, cloud and edge computing, service computing and middleware, and security and privacy, as well as social computing. ACM Transactions on Internet of Things (TIOT) publishes novel research contributions and experience reports broadly related to these topics and their interrelations in the context of IoT, with a focus on system designs, end-to-end architectures, and enabling technologies, covering in principle the entire spectrum from hardware devices up to the application layer. Along with this large breadth of scope, another defining element of TIOT is that the results and insights reported in it must be corroborated by a strong experimental component. This is expected to offer evidence of the proposed techniques in realistic scenarios (e.g., based on field deployments or user studies) or public datasets, with the intent to facilitate adoption and exploitation in the real world of the novel ideas published in TIOT. In the same light, experience reports about the use or adaptation of known systems and techniques in real-world applications are equally welcome, as these studies elicit valuable insights for researchers and practitioners alike. This first, inaugural issue bears witness to the aforementioned breadth of topics and emphasis on experimental validation, as it begins with articles proposing novel system-level techniques concerned with wearable computing and light-based positioning, continues with contributions concerned with security at the edge and IoT services in the cloud, and then ends with the definition of ontologies for IoT applications. Many other interesting papers have already been accepted and will appear in the upcoming issues. All of these high-quality contributions have been selected from an outstanding number of submissions from all over the world. We are very excited to see that the research field of IoT is increasingly gaining momentum. In this respect, we are fortunate to have an outstanding editorial board helping us with the process of reviewing and selecting from these many and diverse submissions. The associate editors on the board reflect the scientific mission and values of TIOT and comprise top-notch researchers from academia and industry, with a balanced mix of seniority, gender, and geography. We sincerely thank all of them for accepting to help us in the delicate task of bringing the first issues of TIOT to reality. Indeed, ACM TIOT is the result of the work of many people, some of whom we want to publicly thank in this inaugural editorial. We are very grateful to Steve Welch and the ACM Publications Board for kickstarting the process by contacting us and planting the seed of a new transaction on IoT in our heads. Lothar Thiele and Tarek Abdelzaher drafted the journal proposal alongside us, offering insights that were key in defining the current scope of TIOT; we are honored to have both
More Traffic, Less Bat Activity: The Relationship between Overnight Traffic Volumes and Chalinolobus tuberculatus Activity along New Zealand Highways

Despite a growing body of evidence worldwide that bats are affected by roads, there has been little research into the effects of traffic volume on bat activity. In New Zealand, there is considerable uncertainty over whether, or to what extent, roads affect New Zealand's endemic bat populations, and this has resulted in uncertainty during the planning and consent phases of road development projects. This research investigated whether Chalinolobus tuberculatus (long-tailed bat) activity correlates with night-time traffic volume on New Zealand's highways. Bat activity was monitored at 57 traffic monitoring sites throughout New Zealand using pairs of bat detectors, with one placed beside the highway (highway) and one placed ≥ 200 metres from the highway (distant). Generalised linear mixed effects models were used to investigate the relationship between bat detections, position in relation to the highway, and various measures of traffic volume. The model that best explained the variation in bat detections was the interaction effect between bat detector position (highway, distant) and night-time traffic volume (volume). Outputs from this model show a negative relationship between bat activity and night-time traffic volume for highway bat detector units, while distant bat detector units had no discernible relationship with night-time traffic volume. These results indicate that night-time traffic volume affects the use of roads by bats, i.e. when overnight traffic increased, the probability of detecting bats decreased. Whether or to what extent this will affect the long-term viability of New Zealand's C. tuberculatus populations is a high priority for further investigation.
Latent Factor Decoding of Multi-Channel EEG for Emotion Recognition Through Autoencoder-Like Neural Networks

Robust cross-subject emotion recognition based on multichannel EEG has always been hard work. In this work, we hypothesize that there exist default brain variables across subjects in emotional processes. Hence, the states of the latent variables that relate to emotional processing must contribute to building robust recognition models. Specifically, we propose to utilize an unsupervised deep generative model (e.g., variational autoencoder) to determine the latent factors from the multichannel EEG. Through a sequence modeling method, we examine the emotion recognition performance based on the learnt latent factors. The performance of the proposed methodology is verified on two public datasets (DEAP and SEED) and compared with traditional matrix factorization-based (ICA) and autoencoder-based approaches. Experimental results demonstrate that autoencoder-like neural networks are suitable for unsupervised EEG modeling, and our proposed emotion recognition framework achieves an inspiring performance. As far as we know, it is the first work that introduces variational autoencoder into multichannel EEG decoding for emotion recognition. We think the approach proposed in this work is not only feasible in emotion recognition but also promising in diagnosing depression, Alzheimer's disease, mild cognitive impairment, etc., whose specific latent processes may be altered or aberrant compared with the normal healthy control.
Non-Mitogenic Fibroblast Growth Factor 1 Enhanced Angiogenesis Following Ischemic Stroke by Regulating the Sphingosine-1-Phosphate 1 Pathway

Ischemic strokes account for about 80% of all strokes and are associated with a high risk of mortality. Angiogenesis of brain microvascular endothelial cells may contribute to functional restoration following ischemia. Fibroblast growth factor 1 (FGF1), a member of FGF superfamily, involved in embryonic development, angiogenesis, wound healing, and neuron survival. However, the mitogenic activity of FGF1 is known to contribute to several human pathologies, thereby questioning the safety of its clinical applications. Here, we explored the effects and mechanism of action of non-mitogenic FGF1 (nmFGF1) on angiogenesis in mice after ischemia stroke and an oxygen-glucose deprivation (OGD)-induced human brain microvascular endothelial cells (HBMECs) injury model. We found that intranasal administration nmFGF1 significantly promoted angiogenesis in mice after stroke, and significantly increased the formation of matrigel tube and promoted scratch migration in a dose-dependent manner in OGD-induced HBMECs in vitro. However, the co-administration of an FGF receptor 1 (FGFR1)-specific inhibitor PD173074 significantly reversed the effects of nmFGF1 in vitro, suggesting that nmFGF1 functions via FGFR1 activation. Moreover, nmFGF1 activated sphingosine-1-phosphate receptor 1 (S1PR1, S1P1) in mice after stroke in vivo. S1P1 protein antagonist VPC23019 and agonist FTY720 were used to confirm that nmFGF1 promotes angiogenesis in vitro partially through the S1P1 pathway. OGD induced downregulation of S1P1 expression. The S1P1 antagonist VPC23019 blocked the stimulatory effects of nmFGF1, whereas the S1P1 agonist FTY720 exerted effects comparable with those of nmFGF1. Furthermore, PD173074 reversed the effect of nmFGF1 on upregulating S1P1 signaling. In conclusion, nmFGF1 enhanced angiogenesis in mice following stroke and OGD-induced HBMECs through S1P1 pathway regulation mediated via FGFR1 activation. This new discovery suggests the potential therapeutic role of nmFGF1 for the treatment of ischemic strokes.
Test Bench for Evaluation of a Soft Robotic Link

In this paper we describe the control approaches tested in the improved version of an existing soft robotic neck with two Degrees Of Freedom (DOF), able to achieve flexion, extension, and lateral bending movements similar to those of a human neck. The design is based on a cable-driven mechanism consisting of a spring acting as a cervical spine and three servomotor actuated tendons that let the neck to reach all desired postures. The prototype was manufactured using a 3D printer. Two control approaches are proposed and tested experimentally: a motor position approach using encoder feedback and a tip position approach using Inertial Measurement Unit (IMU) feedback, both applying fractional-order controllers. The platform operation is tested for different load configurations so that the robustness of the system can be checked.
Flexible Modelling of Longitudinal Medical Data

Using electronic medical records to learn personalized risk trajectories poses significant challenges because often very few samples are available in a patient’s history, and, when available, their information content is highly diverse. In this article, we consider how to integrate sparsely sampled longitudinal data, missing measurements informative of the underlying health status, and static information to estimate (dynamically, as new information becomes available) personalized survival distributions. We achieve this by developing a nonparametric probabilistic model that generates survival trajectories, and corresponding uncertainty estimates, from an ensemble of Bayesian trees in which time is incorporated explicitly to learn variable interactions over time, without needing to specify the longitudinal process beforehand. As such, the changing influence on survival of variables over time is inferred from the data directly, which we analyze with post-processing statistics derived from our model.
Mesoscale All-Atom Influenza Virus Simulations Suggest New Substrate Binding Mechanism

Influenza virus circulates in human, avian, and swine hosts, causing seasonal epidemic and occasional pandemic outbreaks. Influenza neuraminidase, a viral surface glycoprotein, has two sialic acid binding sites. The catalytic (primary) site, which also binds inhibitors such as oseltamivir carboxylate, is responsible for cleaving the sialic acid linkages that bind viral progeny to the host cell. In contrast, the functional annotation of the secondary site remains unclear. Here, we better characterize these two sites through the development of an all-atom, explicitly solvated, and experimentally based integrative model of the pandemic influenza A H1N1 2009 viral envelope, containing ∼160 million atoms and spanning ∼115 nm in diameter. Molecular dynamics simulations of this crowded subcellular environment, coupled with Markov state model theory, provide a novel framework for studying realistic molecular systems at the mesoscale and allow us to quantify the kinetics of the neuraminidase 150-loop transition between the open and closed states. An analysis of chloride ion occupancy along the neuraminidase surface implies a potential new role for the neuraminidase secondary site, wherein the terminal sialic acid residues of the linkages may bind before transfer to the primary site where enzymatic cleavage occurs. Altogether, our work breaks new ground for molecular simulation in terms of size, complexity, and methodological analyses of the components. It also provides fundamental insights into the understanding of substrate recognition processes for this vital influenza drug target, suggesting a new strategy for the development of anti-influenza therapeutics.
Hepatic Glucose Output Inhibition by Mexican Plants Used in the Treatment of Type 2 Diabetes

De novo hepatic glucose production or hepatic gluconeogenesis is the main contributor to hyperglycemia in the fasting state in patients with type 2 diabetes (T2D) owing to insulin resistance, which leads to at least twice as much glucose synthesis compared to healthy subjects. Therefore, control of this pathway is a promising target to avoid the chronic complications associated with elevated glucose levels. Patients with T2D in the rural communities of Mexico use medicinal plants prepared as infusions that are consumed over the day between meals, thus following this rationale (consumption of the infusions in the fasting state), one approach to understanding the possible mechanism of action of medicinal plants is to assess their capacity to inhibit hepatic glucose production. Furthermore, in several of these plants, the presence of phenolic acids able to block the enzyme glucose-6-phosphatase (G6Pase) is reported. In the present work, extracts of Ageratina petiolaris, Bromelia karatas, Equisetum myriochaetum, Rhizophora mangle, and Smilax moranensis, which are Mexican plants that have been traditionally used to treat T2D, were assayed to evaluate their possible hepatic glucose output (HGO) inhibitory activity with a pyruvate tolerance test in 18-h fasted STZ-NA Wistar rats after oral administration of the extracts. In addition, the in vitro effects of the extracts on the last HGO rate-limiting enzyme G6Pase was analyzed. Our results showed that four of these plants had an effect on hepatic glucose production in the in vivo or in vitro assays. A. petiolaris and R. mangle extracts decreased glucose output, preventing an increase in the blood glucose levels and sustaining this prevented increase after pyruvate administration. Moreover, both extracts inhibited the catalytic activity of the G6Pase complex. On the other hand, even though S. moranensis and B. karatas did not exhibit a significant in vivo effect, S. moranensis had the most potent inhibitory effect on this enzymatic system, while the E. myriochaetum extract only inhibited hepatic glucose production in the pyruvate tolerance test. Because of the traditional method in which diabetic patients use plants, hepatic glucose production inhibition seems to be a mechanism that partially explains the common hypoglycemic effect. However, further studies must be carried out to characterize other mechanisms whereby these plants can decrease HGO.
Phytochemical Profile, Pharmacological Attributes and Medicinal Properties of Convolvulus prostratus – A Cognitive Enhancer Herb for the Management of Neurodegenerative Etiologies

Convolvulus prostratus Forssk. , a nootropic herb used in traditional medicinal systems, is also frequently known by its taxonomic synonym Convolvulus pluricaulis. In Indian medicinal system – Ayurveda – it is named as Shankhpushpi. According to the ancient literature, this herb has been attributed with several therapeutic properties, such as anxiolytic, neuroprotective, antioxidant, analgesic, immunomodulatory, antimicrobial, antidiabetic and cardioprotective activities. This medicinal herb has been reported to contain many bioactive phytoconstituents, such as, alkaloid (convolamine), flavonoid (kaempferol) and phenolics (scopoletin, β-sitosterol and ceryl alcohol), that have been ascribed to the observed medicinal properties. Several research teams across the globe have highlighted the neuro-pharmacological profile of C. prostratus, wherein, the neuroprotective, nootropic and neuro-modulatory roles have been described. Besides, role of C. prostratus extracts in neurodegeneration has been well demonstrated. Despite of such elaborative preclinical pharmacological profile, detailed clinical investigations and mechanistic mode-of-action studies of this important herb are yet to be executed. The present review is attempted to showcase the phytochemical profile, pharmacological attributes and medicinal information of C. prostratus; with comprehensive research gap analysis. It is hoped that the scientific update on the ethnomedicinal aspects of this herb would thrive research propagation and development of the CNS phytopharmaceuticals, originated from C. prostratus.
Neurohumoral Control of Sinoatrial Node Activity and Heart Rate: Insight From Experimental Models and Findings From Humans

The sinoatrial node is perhaps one of the most important tissues in the entire body: it is the natural pacemaker of the heart, making it responsible for initiating each-and-every normal heartbeat. As such, its activity is heavily controlled, allowing heart rate to rapidly adapt to changes in physiological demand. Control of sinoatrial node activity, however, is complex, occurring through the autonomic nervous system and various circulating and locally released factors. In this review we discuss the coupled-clock pacemaker system and how its manipulation by neurohumoral signaling alters heart rate, considering the multitude of canonical and non-canonical agents that are known to modulate sinoatrial node activity. For each, we discuss the principal receptors involved and known intracellular signaling and protein targets, highlighting gaps in our knowledge and understanding from experimental models and human studies that represent areas for future research.