Miracle-dz/UniFAR-FTUs huggingface dataset:
An investigation of the multi-dimensional (1D vs. 2D vs. 3D) analyses of EEG signals using traditional methods and deep learning-based methods

Electroencephalographic (EEG) signals are electrical signals generated in the brain due to cognitive activities. They are non-invasive and are widely used to assess neurodegenerative conditions, mental load, and sleep patterns. In this work, we explore the utility of representing the inherently single dimensional time-series in different dimensions such as 1D-feature vector, 2D-feature maps, and 3D-videos. The proposed methodology is applied to four diverse datasets: 1) EEG baseline, 2) mental arithmetic, 3) Parkinson’s disease, and 4) emotion dataset. For a 1D analysis, popular 1D features hand-crafted from the time-series are utilized for classification. This performance is compared against the data-driven approach of using raw time-series as the input to the deep learning framework. To assess the efficacy of 2D representation, 2D feature maps that utilize a combination of the Feature Pyramid Network (FPN) and Atrous Spatial Pyramid Pooling (ASPP) is proposed. This is compared against an approach utilizing a composite feature set consisting of 2D feature maps and 1D features. However, these approaches do not exploit spatial, spectral, and temporal characteristics simultaneously. To address this, 3D EEG videos are created by stacking spectral feature maps obtained from each sub-band per time frame in a temporal domain. The EEG videos are the input to a combination of the Convolution Neural Network (CNN) and Long–Short Term Memory (LSTM) for classification. Performances obtained using the proposed methodologies have surpassed the state-of-the-art for three of the classification scenarios considered in this work, namely, EEG baselines, mental arithmetic, and Parkinson’s disease. The video analysis resulted in 92.5% and 98.81% peak mean accuracies for the EEG baseline and EEG mental arithmetic, respectively. On the other hand, for distinguishing Parkinson’s disease from controls, a peak mean accuracy of 88.51% is achieved using traditional methods on 1D feature vectors. This illustrates that 3D and 2D feature representations are effective for those EEG data where topographical changes in brain activation regions are observed. However, in scenarios where topographical changes are not consistent across subjects of the same class, these methodologies fail. On the other hand, the 1D analysis proves to be significantly effective in the case involving changes in the overall activation of the brain due to varying degrees of deterioration.
Association of folate and vitamin B12 imbalance with adverse pregnancy outcomes among 11,549 pregnant women: An observational cohort study

Objective This study aimed to evaluate maternal serum levels of folate, vitamin B12, and their ratio on admission for labor and determine whether an imbalance between folate and vitamin B12, represented by a higher or lower serum folate to vitamin B12 ratio (SFVB12R), was associated with adverse pregnancy outcomes. Methods A retrospective cohort study of 11,549 pregnant women attending a district specialized hospital and who had serum folate (SF) and serum vitamin B12 (SVB12) levels measured at delivery was performed. The levels of SF, SVB12, and SFVB12R were defined as high (>95th percentile), normal (5–95th percentile), and low (<5th percentile). Information on pregnancy outcomes was retrieved from medical records. Linear regression was performed to examine the association of abnormal SF, SVB12, and SFVB12R levels with fetal growth indicators. Logistic regression was applied to estimate the association between abnormal SF, SVB12, and SFVB12R levels and pregnancy outcomes. Results Lower SF levels were associated with higher risks of intrahepatic cholestasis of pregnancy (ICP, OR 1.58; 95% CI 1.15–2.17), pre-eclampsia (PE, OR 1.89; 95% CI 1.28–2.81), and a lower risk of gestational diabetes mellitus (GDM, OR 0.40; 95% CI 0.23–0.70), whereas higher SVB12 levels were associated with a higher risk of ICP (OR 2.22; 95% CI 1.67–2.96), PE (OR 1.69; 95% CI 1.04-2.74), and GDM (OR 1.62; 95% CI 1.24–2.11). A higher SFVB12R increased birthweight (β 60.99; 95% CI 29.52–92.45) and was associated with a higher risk of large-for-gestational-age (LGA) newborns (OR 3.08; 95% CI 1.63–5.83); a lower SFVB12R decreased birthweight (β −43.81; 95% CI −75.62, −12.00) and was associated with a lower risk of LGA newborns (OR 0.75; 95% CI 0.56–1.00), and with higher risks of ICP (OR 2.03; 95% CI 1.54–2.67) and pregnancy-induced hypertension (PIH, OR 1.81; 95% CI 1.09–3.00). Conclusion An imbalance between folate and vitamin B12, represented by a higher or lower SFVB12R before delivery, was significantly associated with adverse pregnancy outcomes (ICP/PIH/LGA).
A single dose of exenatide had no effect on blood flow velocity in the middle cerebral artery in elderly healthy volunteers: Randomized, placebo-controlled, double-blind clinical trial

Background and aims Glucagon-like peptide 1 (GLP-1) receptor agonists (GLP-1RA) are widely used for the treatment of type 2 diabetes, and recent studies indicate that they may be cardio- and neuroprotective. The safety and effect of a single dose of exenatide, a short-acting GLP-1RA, on cerebral and peripheral arterial function remain unknown. Methods In this randomized, double-blind pilot trial, we assigned elderly healthy volunteers without diabetes and no previous history of stroke to receive a single dose of subcutaneous exenatide (5 μg) or placebo. Primary outcome was immediate changes over time in blood flow velocity of the middle cerebral arteries (VMCA) assessed by repeated transcranial Doppler measurements. Secondary outcomes were changes in peripheral arterial function with finger plethysmography, ankle-brachial index (ABI), and inflammatory- and endothelial-specific biomarkers. Results Healthy volunteers (13 women and 17 men) were included: (mean ± standard deviation) age: 62 ± 8 years; body weight: 79.6 ± 12.7 kg; VMCA: 65.3 ± 10.7 cm/s; fasting plasma glucose: 5.5 ± 0.5 mmol/L; HbA1c: 33.9 ± 4.1 mmol/mol (5.3 ± 0.38%). No differences between exenatide and placebo group were seen regarding VMCA (p = 0.058), systolic ABI (p = 0.71), plethysmography (p = 0.45), tumor necrosis factor (p = 0.33), interleukin-6 (p = 0.11), interleukin-1β (p = 0.34), vascular cell adhesion molecule 1 (p = 0.73), intercellular adhesion molecule 1 (p = 0.74), or E-selectin (p = 0.31). No severe adverse events were observed. Conclusion A single dose of exenatide did not change cerebral blood flow velocity or peripheral vessel function in elderly healthy volunteers. The medication was safe to use in persons without diabetes allowing us to investigate this drug further in search of the neuroprotective mechanisms. Clinical Trial Registration https://clinicaltrials.gov, Identifier NCT02838589.
“Rogue” [DEspR+CD11b+] neutrophil subset correlates with severity in spontaneous intracerebral hemorrhage

Objective Cumulative clinical, cellular, and molecular evidence reinforces the role of neutrophils in secondary brain injury in spontaneous intracerebral hemorrhage (sICH). However, since generalized neutrophil inhibition is detrimental, identification of targetable “rogue” neutrophil subsets associated with sICH severity is key. Methods In a pilot prospective observational study of consented patients with sICH, we immunotyped whole blood to assess circulating neutrophil markers (~day 3 after ICH symptoms onset): (a) DEspR±CD11b± neutrophils by flow cytometry, (b) DEspR±CD11b± neutrophil extracellular trap (NET)-forming neutrophils by immunofluorescence cytology, and (c) neutrophil-lymphocyte ratio (NLR). Using Spearman rank correlation (r) with Bonferroni correction, we assessed the association of neutrophil markers with same-day clinical and neuroimaging parameters of sICH severity, index ICH score, 90-day modified Rankin Scale (mRS) score, and potential interrelationships. As comparators, we assessed same-day plasma biomarkers elevated in sICH: interleukin-6/IL-6, myeloperoxidase/MPO, soluble-terminal complement complex/sC5b-9, endothelin-1/ET-1, and mitochondrial/nuclear DNA ratio (mt/nDNA ratio). Results We detected strong correlations [r(n = 13) > 0.71, power > 0.8, Bonferroni corrected pB < 0.05] for all three neutrophil markers with 90-day mRS score, differentially for DEspR+CD11b+ neutrophil counts, and NLR with perihematomal edema (PHE) volume and for DEspR+CD11b+ NET-forming neutrophil counts with intraparenchymal hemorrhage (IPH)-volume. Only DEspR+CD11b+ neutrophil counts show a strong correlation with index ICH score, same-day Glasgow Coma Scale (GCS) score, and NLR and NET-forming neutrophil counts. The sum of the ICH score and three neutrophil markers exhibited the highest correlation: [r(n = 13) 0.94, pB = 10−5]. In contrast, plasma biomarkers tested were elevated except for MPO but exhibited no correlations in this pilot study. Conclusion Strong correlation with multiple sICH severity measures, NET formation, and NLR identifies DEspR+CD11b+ neutrophils as a putative “rogue” neutrophil subset in sICH. The even stronger correlation of the sum of three neutrophil markers and the index ICH score with 90-day mRS outcome reinforces early neutrophil-mediated secondary brain injury as a key determinant of outcome in patients with sICH. Altogether, data provide a basis for the formal study of the DEspR+CD11b+ neutrophil subset as a potential actionable biomarker for neutrophil-driven secondary brain injury in sICH. Data also show ex vivo analysis of patients with sICH neutrophils as a translational milestone to refine hypotheses between preclinical and clinical studies.
Transient and Steady-State Properties of Drosophila Sensory Neurons Coding Noxious Cold Temperature

Coding noxious cold signals, such as the magnitude and rate of temperature change, play essential roles in the survival of organisms. We combined electrophysiological and computational neuroscience methods to investigate the neural dynamics of Drosophila larva cold-sensing Class III (CIII) neurons. In response to a fast temperature change (–2 to –6°C/s) from room temperature to noxious cold, the CIII neurons exhibited a pronounced peak of a spiking rate with subsequent relaxation to a steady-state spiking. The magnitude of the peak was higher for a higher rate of temperature decrease, while slow temperature decrease (–0.1°C/s) evoked no distinct peak of the spiking rate. The rate of the steady-state spiking depended on the magnitude of the final temperature and was higher at lower temperatures. For each neuron, we characterized this dependence by estimating the temperature of the half activation of the spiking rate by curve fitting neuron’s spiking rate responses to a Boltzmann function. We found that neurons had a temperature of the half activation distributed over a wide temperature range. We also found that CIII neurons responded to decrease rather than increase in temperature. There was a significant difference in spiking activity between fast and slow returns from noxious cold to room temperature: The CIII neurons usually stopped activity abruptly in the case of the fast return and continued spiking for some time in the case of the slow return. We developed a biophysical model of CIII neurons using a generalized description of transient receptor potential (TRP) current kinetics with temperature-dependent activation and Ca2+-dependent inactivation. This model recapitulated the key features of the spiking rate responses found in experiments and suggested mechanisms explaining the transient and steady-state activity of the CIII neurons at different cold temperatures and rates of their decrease and increase. We conclude that CIII neurons encode at least three types of cold sensory information: the rate of temperature decrease by a peak of the firing rate, the magnitude of cold temperature by the rate of steady spiking activity, and direction of temperature change by spiking activity augmentation or suppression corresponding to temperature decrease and increase, respectively.
A Big Role for microRNAs in Gestational Diabetes Mellitus

Maternal diabetes is associated with pregnancy complications and poses a serious health risk to both mother and child. Growing evidence suggests that pregnancy complications are more frequent and severe in pregnant women with pregestational type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) compared to women with gestational diabetes mellitus (GDM). Elucidating the pathophysiological mechanisms that underlie the different types of maternal diabetes may lead to targeted strategies to prevent or reduce pregnancy complications. In recent years, microRNAs (miRNAs), one of the most common epigenetic mechanisms, have emerged as key players in the pathophysiology of pregnancy-related disorders including diabetes. This review aims to provide an update on the status of miRNA profiling in pregnancies complicated by maternal diabetes. Four databases, Pubmed, Web of Science, EBSCOhost, and Scopus were searched to identify studies that profiled miRNAs during maternal diabetes. A total of 1800 articles were identified, of which 53 are included in this review. All studies profiled miRNAs during GDM, with no studies on miRNA profiling during pregestational T1DM and T2DM identified. Studies on GDM were mainly focused on the potential of miRNAs to serve as predictive or diagnostic biomarkers. This review highlights the lack of miRNA profiling in pregnancies complicated by T1DM and T2DM and identifies the need for miRNA profiling in all types of maternal diabetes. Such studies could contribute to our understanding of the mechanisms that link maternal diabetes type with pregnancy complications.
Persistence of drug therapy is associated with ischemic stroke and other vascular events in high-risk stroke population

The high-risk stroke populations are significantly associated with an increased risk of stroke or other vascular events. Although proven primary and secondary stroke prevention medications are available, persistent use is required to be effective. However, the persistence of drug therapy and its association with outcomes in the high-risk stroke population have received limited study in China. Hence, according to the China National Stroke Screening Survey (CNSSS) program in 2015, we performed this multicenter population-based cross-sectional survey and prospective cohort study in Sichuan of southwestern China. The residents aged ≥ 40 years volunteered to participate in a face-to-face survey in 8 communities. Subjects with at least three of eight stroke-related risk factors or a history of stroke were defined as high-risk stroke population. The interviewers recorded individuals' medications at a face-to-face survey, and all the high-risk stroke population was followed up for 4.7 years. The persistence of antihypertensives, hypoglycemics, lipid-lowering medications, and antithrombotics for stroke was evaluated. The primary outcome was new stroke. Secondary outcomes included new composite vascular events of stroke, myocardial infarction, and death during follow-up periods. Among 16,892 participants, 2,893 (17.1%) participants were high-risk stroke population and 2,698 (93.3%) participants completed to follow-up. The 4.7-year persistence of therapy rate of antihypertensives, hypoglycemics, lipid-lowering medications, and antithrombotics was 38.0%, 39.9%, 43.9%, and 59.8%, respectively. The total persistence of therapy rate for antihypertensives, hypoglycemics, lipid-lowering medications, and antithrombotics was 47.6% (136/286) in patients with hypertension, diabetes, dyslipidemia, and stroke at the same time. During the 4.7-year follow-up, there were 118 (4.4%) new ischemic stroke, 24 (0.9%) hemorrhagic stroke, 53 (2.0%) myocardial infarctions, and 33 (1.2%) deaths. After adjusting for the covariates, 4.7-year persistence of antihypertensives, hypoglycemics, lipid-lowering therapy, antithrombotics, and total persistence was independently associated with less new ischemic stroke and less new composite vascular events. Thus, more effective public education and efforts to understand and enhance the persistence of drug therapy are crucial to improve population health and decrease stroke and other vascular events for the high-risk stroke population.
Interaction between patient and health care professionals in the management of tuberculosis

OBJECTIVE: To evaluate the effectiveness of health care services in the management of tuberculosis in Ribeirao Preto, SP, during the year of 2007 in promoting interaction between patient and health care professionals. METHODS: An adapted questionnaire that contains 10 indicators of interaction was used. The sample consisted of 100 patients with tuberculosis. RESULTS: More than 60% of patients reported they engaged in conversations about other issues besides tuberculosis with their health care professionals. The majority of the sample (90%) reported they have enough time to clarify their questions about the treatment of tuberculosis. More than 50% of patients from each outpatient clinic reported to contact their physician when they were in need for food or transportation voucher. CONCLUSION: The structure of the delivery of health care by specialized health care teams from the " Programs for Tuberculosis Control" had good indicators of interaction between patient and health care professionals, which may contribute to the identification of patients' needs and searching for resources to address those needs.
Regional Water Institutions and Participation in Water Governance: The Colorado River Delta as an Exception to the Rule?

Beginning in the 1990s, heightened attention has been paid to the promotion of cooperative efforts at the river basin level to promote joint management and protection of international rivers (Conca et al. 2006; Gerlak and Grant 2009). River basin organizations (RBOs) are seen as key to basin cooperation, and have been established in virtually every region of the world (Schmeier et al. 2015). RBOs are promoted by a host of international organizations, including the Global Environment Facility and the World Water Council (Cosgrove and Rijsberman 2000; Uitto and Duda 2002; Gerlak 2004). International law promotes the formation of RBOs. The United Nations 1997 Convention on the Law of the Non-navigational Uses of International Watercourses encourages states to establish joint mechanisms or commissions to facilitate transboundary cooperation. So too do the Berlin Rules promote basinwide joint agencies or commissions to undertake the integrated management of international waters. The idea of basin-level organizations is an old one. River basin management received considerable zeal with industrialization and development of technology for multipurpose river development in the first part of the 20th century (White 1969; Molle 2006). Unified basin management was often proposed under the command of a basin authority, albeit with limited application and success (White 1957; Ingram 1973). This expert-driven model spread throughout the world (Mukhtarov 2008; Delli Priscoli 2007), and by the 1950s, RBO discourse came to
Neutron dosimetry with the ORNL badge

The ORNL red-dot badge was designed to provide radiation dose estimation for personnel working in neutron, gamma, and mixed-field environments. The primary quantitative radiation-sensing components in the red-dot badge are TLDs, used to measure direct neutron, gamma, and albedo neutron response. The TLDs were calibrated with radium gammas and HPRR-generated neutrons. In this study, the badge is used as a crude spectrometer as well as a dosimeter. Intercomparison results from the Tenth PDIS are favorable, as would be expected since the exposures in the intercomparison were from the same source as the original calibrations. Other neutron- and gamma-emitting sources are being sought in order to confirm the sensitivity of the red-dot badge in a wide range of radiation environments. Whenever possible, dosimeter calibration factors should be determined from independent measurements of neutron spectral quality.
NONLINEAR NORMAL MODE EMBEDDING FOR MODEL REDUCTION

(SOD) considers both statistical and dynamical (or, spatial and temporal) properties of data. When using transient free response data, SOD performs well when dealing with lightly damped systems, but may encounter problems with high damping ratios. This is not a problem for random excitation response data. After describing the methods, their application to a simple four-degree-of-freedom system with nonlinear boundary condition is discussed.
An empirical study of demand forecasting of non-volatile memory for smart production of semiconductor manufacturing

As high-speed computing is crucial to empower intelligent manufacturing for Industry 4.0, non-volatile memory (NVM) is critical semiconductor component of the cloud and data centre for the infrastructures. The NVM manufacturing is capital intensive, in which capacity utilisation significantly affects the capital effectiveness and profitability of semiconductor companies. Since capacity migration and expansion involve long lead times, demand forecasting plays a critical role for smart production of NVM manufacturers for revenue management. However, the shortening product life cycles of integrated circuits (IC), the fluctuations of semiconductor supply chains, and uncertainty involved in demand forecasting make the present problem increasingly difficult in the consumer electronics era. Focusing on the realistic needs of NVM demand forecasting, this study aims to develop a decision framework that integrates an improved technology diffusion model and a proposed adjustment mechanism to incorporate domain insights. An empirical study was conducted in a leading semiconductor company for validation. A comparison of alternative approaches is also provided. The results have shown the practical viability of the proposed approach.
Gated Multi-task learning framework for text classification

Related tasks are generally dependent on each other and thereby perform better when solved in a joint framework. Considering the same fact, our team named ‘TCS Research Lab Gurgaon’ presents a deep learning-based multi-task framework that jointly identifies the presence of ‘Hate and Offensive’ (HOF) speech and further classifies the type of ‘HOF’ speech present (i.e. hate or offensive or profane) . For each tweet, we extract three forms of feature sets (i.e. word embeddings, topical distribution, and TF-IDF score) to convey diverse and distinctive information. As we know all these feature sets usually don’t have equal contribution in final decision-making, therefore we use the ‘gated’ mechanism to assign weights to these feature sets based on their importance in the final prediction. We have evaluated and validated our proposed approach on subtask1A and subtask1B [1] of HASOC-2021 challenge [2]. Evaluation results suggest and show that the multi-task learning (‘MTL’) framework provides better results as compared to the single-task learning (‘STL’) framework (i.e. solving both the subtasks independently) .
Carbonatite magmas

Abstract Normal carbonatite magmas are characteristically associated with ijolites and produce extensive fenitization by alkali metasomatism, commonly feldspathization or phlogopitization. The sequence of carbonatites developed from this magma are characterized by igneous isotopic ratios, high contents of incompatible elements, their distinctive pattern of differentiation from sövite to beforsite, and a late-stage rare-earth element, baryte, fluorite mineralization. Carbonatite rock is composed mainly of calcite, but fluid inclusion and related data indicate that the original magma was highly alkaline and chemically similar to that known at Oldoinyo Lengai volcano in Tanzania. It is suggested that this carbonatite magma is secondary magma produced from carbonated nephelinite magma by liquid immiscibility. Carbonatite magma can also occur associated with kimberlites but these carbonatites are alkali-poor and do not produce the characteristic fenitization.