Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptome Analyses Revealed the Key Metabolic Genes and Transcription Factors Involved in Terpenoid Biosynthesis in Sacred Lotus

As the largest group of structurally diverse metabolites, terpenoids are versatile natural compounds that act as metabolism mediators, plant volatiles, and ecological communicators. However, few terpenoid compounds have been identified in plant parts of sacred lotus (Nelumbo nucifera Gaertn.). To elucidate the molecular genetic basis of the terpene biosynthetic pathway, terpenes from different parts of the plant, including seeds (S), young leaves (YL), mature leaves (ML), white flowers (WF), yellow flowers (YF), and red flowers (RF), were identified by LC-MS/MS and the relative contents of the same terpenes in different parts were compared. The results indicate that all plant parts primarily consist of triterpenes, with only minor quantities of sesquiterpenes and diterpenes, and there were differences in the terpene content detected in different plant parts. To illustrate the biosynthesis of various terpenoids, RNA sequencing was performed to profile the transcriptomes of various plant parts, which generated a total of 126.95 GB clean data and assembled into 29,630 unigenes. Among these unigenes, 105 candidate unigenes are involved in the mevalonate (MVA) pathway, methyl-erythritol phosphate (MEP) pathway, terpenoid backbone biosynthesis pathway, and terpenoid synthases pathway. Moreover, the co-expression network between terpene synthase (TPS) and WRKY transcription factors provides new information for the terpene biosynthesis pathway.
Conditional Dynamic Dependence and Risk Spillover between Crude Oil Prices and Foreign Exchange Rates: New Evidence from a Dynamic Factor Copula Model

This paper proposes a dynamic factor model to accurately characterize the dynamic dependence and risk spillovers between the crude oil and exchange rate returns of oil-trading countries from 2000–2020, conditional on the common factors. To this end, we first identify the common factors related to returns of crude oil prices and exchange rates from 14 typical oil-trading countries. Then, we use the AR-GARCH model to filter the respective idiosyncratic factors and conduct a comparative study of conditional dynamic dependence between the crude oil and exchange rate returns of oil importers and exporters. Finally, we combine the dynamic factor copula model with the CoVaR method to measure the conditional risk spillover effect between crude oil and exchange rate markets. The empirical study indicates that the classical factor analysis can be used to precisely identify the common factors related to both financial markets, with the similar trend of macro-economic indicators. Furthermore, the factor copula model can capture the dynamic structure between crude oil and exchange rate markets more accurately than the traditional Copula–GARCH model. Specifically, the idiosyncratic factors related to each return series still have a significant impact on the dependence between the crude oil and exchange rate returns of oil importers, while the common factors have played an important role in the relationship of oil exporters’ exchange rates with crude oil prices. Finally, the crude oil market has enjoyed a relative risk premium to the exchange rate markets of oil-trading countries. However, there is almost no conditional risk spillover from the corresponding exchange rates to the crude oil prices. Finally, we discuss the implications for investors, policymakers and respective exchange rate regulators from oil-trading countries with further insights from the macro-economic perspective.
R&D participation and firm performance in the Caribbean

ABSTRACT Despite the benefits of R&D and the incentives available for such investments in most countries, the Caribbean has one of the lowest rates of R&D investment in the world. One potential reason for this is the financing constraints encountered by most Caribbean firms. Using a Cobb-Douglas production function augmented with innovation input and output variables and data from the LACES and PROTEqIN databases of the Enterprise Surveys and Compete Caribbean respectively, this research examines the extent to which past R&D experience and current innovative activities enhance the performance of manufacturing and service firms. The findings suggest that prior R&D participation contributes significantly to increased productivity levels of manufacturing firms. On the other hand, skillset is very important to the productivity of service enterprises. Furthermore, past R&D involvement increases the probability of innovation, specifically goods/service innovation and marketing improvements.
A high-performance, hardware-based deep learning system for disease diagnosis

Modern deep learning schemes have shown human-level performance in the area of medical science. However, the implementation of deep learning algorithms on dedicated hardware remains a challenging task because modern algorithms and neuronal activation functions are generally not hardware-friendly and require a lot of resources. Recently, researchers have come up with some hardware-friendly activation functions that can yield high throughput and high accuracy at the same time. In this context, we propose a hardware-based neural network that can predict the presence of cancer in humans with 98.23% accuracy. This is done by making use of cost-efficient, highly accurate activation functions, Sqish and LogSQNL. Due to its inherently parallel components, the system can classify a given sample in just one clock cycle, i.e., 15.75 nanoseconds. Though this system is dedicated to cancer diagnosis, it can predict the presence of many other diseases such as those of the heart. This is because the system is reconfigurable and can be programmed to classify any sample into one of two classes. The proposed hardware system requires about 983 slice registers, 2,655 slice look-up tables, and only 1.1 kilobits of on-chip memory. The system can predict about 63.5 million cancer samples in a second and can perform about 20 giga-operations per second. The proposed system is about 5–16 times cheaper and at least four times speedier than other dedicated hardware systems using neural networks for classification tasks.
Left-truncated effects and overestimated meta-analytic means

The meta-analytic by Mertens et al. (1) interprets nudges as a generally effective technique for increasing desirable decision-making, with an overall pooled effect size of d = 0.43. This research also reports large systematic variations (meta-analytic heterogeneity) in effects, primarily attributed to moderators such as the domain, as well as asymmetrically distributed effects, interpreted as moderate publication bias. Apart from publication bias, non-normality and high heterogeneity may be problematic for the representativeness of meta-analytic means (2). Here, we reanalyze the corrected data made available by Mertens et al. (1), finding evidence that nudges have more limited than general effectiveness. We show that effects are clearly left-truncated, likely due to substantial publication bias, consistent with another reanalysis (3). We also find that most of the pooled effects as reported in Mertens et al. (1) are overestimated and hence unrepresentative. First, we visualize the distributions of effects, by domain, using raincloud plots (4); see Fig. 1. Four domains (finance, food, other, and prosocial) show a concerning pattern of sharply left-truncated tails at or slightly below zero. The two remaining domains only have a handful of effects slightly below zero. A plausible mechanism for this left “cliff” is suppression of unfavorable results (5). Most domains also exhibit long right tails—a limited number of effects
Mothers with justice‐involved sons: Socioeconomic impacts of COVID‐19 by neighborhood disorder in the United States

Abstract Women, particularly mothers, have faced disparate socioeconomic consequences throughout the COVID‐19 pandemic. Research has yet to examine whether the consequences of the pandemic vary based on the level of neighborhood disorder, which is associated with various health conditions, including COVID‐19 complications. The present study utilizes data from a diverse sample of 221 women with justice‐involved sons interviewed during the early months of the COVID‐19 pandemic. Negative binominal and logistic regression analyses were conducted to examine whether perceived neighborhood social disorder is related to socioeconomic impacts of the COVID‐19 pandemic, and whether the relation varies for mothers with and without children in their home during the pandemic. The results suggest that greater perceived neighborhood social disorder was associated with increased in COVID‐19‐related socioeconomic consequences. Neighborhood social disorder affected socioeconomic impacts above and beyond the effects of having a child living in the home. Additionally, Latinas experienced greater socioeconomic impacts than women of other races and ethnicities. The results indicate a key relationship between the neighborhood conditions a woman lives in and the extent of the socioeconomic consequences they faced during the early months of the COVID‐19 pandemic. Future directions and direct implications of the study findings are discussed.
Enabling adaptive, personalised and context-aware interaction in a smart learning environment: Piloting the iCollab system

Smart learning environments (SLE) provide students with opportunities to interact with learning resources and activities in ways that are customised to their particular learning goals and approaches. A challenge in developing SLEs is providing resources and tasks within a single system that can seamlessly tailor learning experience in terms of time, place, platform, and form. In this paper we introduce the iCollab platform, an adaptive environment where learning activities are moderated through conversation with an intelligent agent who can operate across multiple web-based platforms, integrating formal and informal learning opportunities. Fifty-eight undergraduate computer science students were randomly assigned to either an intervention or control group for the 12 weeks of the pilot study. Learning analytics were used to examine their interactions with iCollab, while their course performance investigated the impact of using iCollab on learning outcomes. Results from the study showed a high level of interaction with iCollab, especially social interaction, indicating an interweaving of formal learning within their informal network spaces. These findings open up new possibilities for ways that SLEs can be designed to incorporate different factors, improving the ability of the system to provide adaptive and personalised learning experiences in relation to context and time.
SURVEY-AN EXPLORATION OF VARIOUS TECHNIQUES FOR SIGN DETECTION IN TRAFFIC PANELS

In Visual Object Detection, traffic sign detection and recognisation is a recurring application domain. The automatic visual recognition and classification of the information contained in the panel could be very useful to assist the driver. Traffic panels instructs the driver assistance on routes by means of iconic symbols and text strings. Based on the color and shape features, the traffic sign is detected and recognized. The various techniques have been used to extract the color and shape features of the traffic sign. This paper provides a survey of the traffic sign detection and recognition, to detail the system for driver assistance to ensure safe journey. A brief review of recent advancement techniques used by researchers has been provided for the detection and the recognisation stages.
Design of Wideband Circular-Slot Antenna for Harvesting RF Energy

The design of a wideband circular-slot antenna for RF signal harvesting is reported in this work. The proposed design frequency range accommodates the leading contributors to the available RF signals accessible by the RFEH node. These widely utilized frequency bands comprise GSM1800, UMTS2100, Wi-Fi2.450, and LTE2600. The antenna geometry comprises circular-ring radiating component filled with two orbital circular and rectangular slots. At the bottom plane, a pair of rectangular and semirectangular-circle slits are integrated. The antenna presented is designed on a double layer of 1.6 mm high FR-4 substrate. The source antenna achieved a simulated and measured impedance bandwidth (BW) of 1.510 and 1.590 GHz, amounting to 68% and 73% fractional BW (FBW), covering -10 dB reflection coefficient (|S11|) between 1.640 to 3.150 GHz and 1.550 to 3.140 GHz, in that order. The wideband circular-slot source antenna realized a maximum measured gain of 1.88, 2.13, 2.81, 3.22, and 4.32 dBi for 1.800, 2.100, 2.450, 2.650, and 3.20 GHz, respectively. The proposed design dimension on the printed board is 0.61 λ g × 0.70 λ g . The improved antenna gain is obtained from a circular parasitic patch coupled to the defected ground structure (DGS) for better RF energy harvesting in an ambient environment.
Optimisation of anti-interleukin-6 therapy: Precision medicine through mathematical modelling

Background Dysregulated interleukin (IL)-6 production can be characterised by the levels present, the kinetics of its rise and its inappropriate location. Rapid, excessive IL-6 production can exacerbate tissue damage in vital organs. In this situation, therapy with an anti-IL-6 or anti-IL-6 receptor (IL-6R) monoclonal antibody, if inappropriately dosed, may be insufficient to fully block IL-6 signalling and normalise the immune response. Methods We analysed inhibition of C-reactive protein (CRP) – a biomarker for IL-6 activity – in patients with COVID-19 or idiopathic multicentric Castleman disease (iMCD) treated with tocilizumab (anti-IL-6R) or siltuximab (anti-IL-6), respectively. We used mathematical modelling to analyse how to optimise anti-IL-6 or anti-IL-6R blockade for the high levels of IL-6 observed in these diseases. Results IL-6 signalling was insufficiently inhibited in patients with COVID-19 or iMCD treated with standard doses of anti-IL-6 therapy. Patients whose disease worsened throughout therapy had only partial inhibition of CRP production. Our model demonstrated that, in a scenario representative of iMCD with persistent high IL-6 production not controlled by a single dose of anti-IL-6 therapy, repeated administration more effectively inhibited IL-6 activity. In a situation with rapid, high, dysregulated IL-6 production, such as severe COVID-19 or a cytokine storm, repeated daily administration of an anti-IL-6/anti-IL-6R agent, or alternating daily doses of anti-IL-6 and anti-IL-6R therapies, could neutralise IL-6 activity. Conclusion In clinical practice, IL-6 inhibition should be individualised based on pathophysiology to achieve full blockade of CRP production. Funding EUSA Pharma funded medical writing assistance and provided access to the phase II clinical data of siltuximab for analysis.
Bifurcation of periodic solutions in a rotationally symmetric oscillation system.

On considere la bifurcation des solutions periodiques pour l'equation x+f(x,λ) x=0, ou x∈R 2 , λ∈R est petit, et F:R 2 ×R→R est reguliere, avec f(0,0)>0 et f(Rx,λ)=f(x,λ), ∀R∈0(2), ∀(x,λ)∈R 2 ×R
The Directionality of the Relationship Between Executive Functions and Language Skills: A Literature Review

It has been demonstrated that executive functions play a significant role in different aspects of the development of children. Development of language is also one of the most important accomplishments of the preschool years, and it has been linked to many outcomes in life. Despite substantial research demonstrating the association between executive function and language development in childhood, only a handful of studies have examined the direction of the developmental pathways between EF skills and language skills, therefore little is known about how these two constructs are connected. In this review paper, we discuss three possible directional relationships between EFs and language development throughout childhood. First, we discuss how EF might affect language functioning. Next, we discuss how language functioning might affect EF. Lastly, we consider other possible relationships between EF and language. Given that children with better EF and language skills are more likely to succeed in educational settings and demonstrate greater social–emotional competencies, investigating the relationship between EF and language in the preschool period provides insight into mechanisms that have not been extensively studied. Furthermore, it could create new opportunities for designing effective and efficient interventions aimed at addressing EF and language deficits during the preschool period which could in turn influence later development.
I Like the Food You Made! Overly Positive Feedback Is Most Likely Given to Those That Want to Excel in a Task and Handle Failure Badly

In this article, we focus on how people resolve the dilemma between honest feedback and a prosocial lie depending on the context. In a pre-registered study (N = 455), we asked participants to choose between telling the blatant truth or lying prosocially regarding a dish made poorly by a stranger. The results showed that participants were most eager to pass on overly positive feedback when the stranger cared about cooking and was very sensitive to negative feedback. Perceived harm in truth telling mediated the relationship between desire to excel in a task with high ability to handle failure and choosing a prosocial lie.
Theory of Correlation in VLBI

This lecture presents the general concepts of correlation and spatial coherence functions, as they apply to VLBI and VLBI correlator implementations. A uniform treatment, based in the spectral domain, is applied to both the conventional lag and the spectral or FX correlator architectures. Parallel presentations of both architectures are given, including their strengths and weaknesses, although more emphasis is placed on the FX correlator because it is less familiar.
Development of an Administrative Data-Based Frailty Index for Older Adults Receiving Dialysis

Visual Abstract Key Points Accounting for comorbidity, this frailty index demonstrates an independent association with mortality and hospitalizations. This frailty index has potential application for both observational studies and population health management. Background Frailty is present in ≥50% of older adults receiving dialysis. Our objective was to a develop an administrative data–based frailty index and assess the frailty index’s predictive validity for mortality and future hospitalizations. Methods We used United States Renal Data System data to establish two cohorts of adults aged ≥65 years, initiating dialysis in 2013 and in 2017. Using the 2013 cohort (development dataset), we applied the deficit accumulation index approach to develop a frailty index. Adjusting for age and sex, we assessed the extent to which the frailty index predicts the hazard of time until death and time until first hospitalization over 12 months. We assessed the Harrell’s C-statistic of the frailty index, a comorbidity index, and jointly. The 2017 cohort was used as a validation dataset. Results Using the 2013 cohort (n=20,974), we identified 53 deficits for the frailty index across seven domains: disabilities, diseases, equipment, procedures, signs, tests, and unclassified. Among those with ≥1 deficit, the mean (SD) frailty index was 0.30 (0.13), range 0.02–0.72. Over 12 months, 18% (n=3842) died, and 55% (n=11,493) experienced a hospitalization. Adjusted hazard ratios for each 0.1-point increase in frailty index in models of time to death and time to first hospitalization were 1.41 (95% confidence interval, 1.37 to 1.44) and 1.33 (95% confidence interval, 1.31 to 1.35), respectively. For mortality, C-statistics for frailty index, comorbidity index, and both indices were 0.65, 0.65, and 0.66, respectively. For hospitalization, C-statistics for frailty index, comorbidity index, and both indices were 0.61, 0.60, and 0.61, respectively. Data from the 2017 cohort were similar. Conclusions We developed a novel frailty index for older adults receiving dialysis. Further studies are needed to improve on this frailty index and validate its use for clinical and research applications.
On the theoretical ratio of some nebular lines.

47 Tuc, part of this "reddening" should be due to an opacity difference: adopting the usual value of E(B-V) = 0.8 for NGC 6553 (Webbink, 1985), an opacity difference of 0.2 magnitudes is found. For estimating the age, the magnitude difference between the turn-off and the HB is used (see Buonnano et al., 1989). NGC 6553 seems to be slightly younger than the classical globular clusters (see Ortolani et al., 1989), which would have important implications for the epoch of the inner bulge formation.
Impacts of climate change on mechanical ventilative cooling in high-rise buildings

Mechanical ventilation systems have great potential to provide cooling in high-rise buildings and reduces cooling energy consumption, i.e. mechanical ventilative cooling (MVC). However, the energy performance of MVC highly depends on weather conditions. In the previous studies, the energy performance of MVC usually was investigated under the typical or historical weather conditions. Considering that weather conditions will change due to global warming, it is necessary to assess the influences of climate change on the energy performance of MVC. This study uses the morphing method to predict the future weather conditions and a hybrid model to simulate the energy performance of MVC. The hybrid model combines the machine learning model built by multilayer perceptron and energy models. With a case study building in Montreal, the results show that the amount of energy saving of MVC will increase slightly due to climate change. This study contributes to the application of MVC systems in high-rise buildings.
Active sensor faults tolerant control for Takagi-Sugeno multiple models

In this communication, a method allowing the conception of a sensor faults tolerant control for the case of non linear systems described by Takagi-Sugeno models. The faults are initially estimated using a proportional integral observer. The synthetized control depends on the estimated fault and the error between the state of the system of reference and the state of the system affected by faults. The conditions of the observer convergence and of the control existence are formulated in terms of Linear Matrix Inequalities (LMI). The formulation in LMI shows that the synthesis of the control and the observer can be independently made. The theoretical results are validated on a noisy non linear system affected by sensor faults.
A linear cohesive model of zero degree peeling of a viscoelastic tape from a substrate

Abstract Peeling in viscoelastic materials has been studied experimentally for many years mostly at 90 or 180 degrees angle, and typically the classical Rivlin energy balance equation is used to obtain a velocity-dependent work of fracture. The latter has been shown to be the product of an angular term and a velocity-dependent term, but there is no simple model to explain this behaviour: attempts have been made to generalize the Kendall elastic equation to viscoelasticity, but they lead to no velocity dependence (and infinite load) with frictional dissipation at zero angles, and in general at large angles. In the present model, we consider the original Kendall’s “sticking conditions,” for which a linear cohesive model is formulated for the viscoelastic tape as being on an elastic foundation, and peeling velocity is found to be proportional to the cubic power of the force for Maxwell material, or standard material with a large ratio between instantaneous and relaxed moduli. An explicit closed-form solution to this problem is first derived in this work. Experimental results on zero peel angle are scarce, and may be affected by the finite length of adhered and unadhered parts: hence, a complete picture of peeling behaviour at zero angles is elusive.