Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of visual input on syllable parsing in a computational model of a neural microcircuit for speech processing

Objective. Seeing a person talking can help us understand them, particularly in a noisy environment. However, how the brain integrates the visual information with the auditory signal to enhance speech comprehension remains poorly understood. Approach. Here we address this question in a computational model of a cortical microcircuit for speech processing. The model consists of an excitatory and an inhibitory neural population that together create oscillations in the theta frequency range. When stimulated with speech, the theta rhythm becomes entrained to the onsets of syllables, such that the onsets can be inferred from the network activity. We investigate how well the obtained syllable parsing performs when different types of visual stimuli are added. In particular, we consider currents related to the rate of syllables as well as currents related to the mouth-opening area of the talking faces. Main results. We find that currents that target the excitatory neuronal population can influence speech comprehension, both boosting it or impeding it, depending on the temporal delay and on whether the currents are excitatory or inhibitory. In contrast, currents that act on the inhibitory neurons do not impact speech comprehension significantly. Significance. Our results suggest neural mechanisms for the integration of visual information with the acoustic information in speech and make experimentally-testable predictions.
Transposition and duplication of MADS-domain transcription factor genes in annual and perennial Arabis species modulates flowering

Significance Annual and perennial species differ in their timing and intensity of flowering, but the underlying mechanisms are poorly understood. We hybridized closely related annual and perennial plants and used genetics, transgenesis, and genomics to characterize differences in the activity and function of their flowering-time genes. We identify a gene encoding a transcription factor that moved between chromosomes and is retained in the annual but absent from the perennial. This gene strongly delays flowering, and we propose that it has been retained in the annual to compensate for reduced activity of closely related genes. This study highlights the value of using direct hybridization between closely related plant species to characterize functional differences in fast-evolving reproductive traits. The timing of reproduction is an adaptive trait in many organisms. In plants, the timing, duration, and intensity of flowering differ between annual and perennial species. To identify interspecies variation in these traits, we studied introgression lines derived from hybridization of annual and perennial species, Arabis montbretiana and Arabis alpina, respectively. Recombination mapping identified two tandem A. montbretiana genes encoding MADS-domain transcription factors that confer extreme late flowering on A. alpina. These genes are related to the MADS AFFECTING FLOWERING (MAF) cluster of floral repressors of other Brassicaceae species and were named A. montbretiana (Am) MAF-RELATED (MAR) genes. AmMAR1 but not AmMAR2 prevented floral induction at the shoot apex of A. alpina, strongly enhancing the effect of the MAF cluster, and MAR1 is absent from the genomes of all A. alpina accessions analyzed. Exposure of plants to cold (vernalization) represses AmMAR1 transcription and overcomes its inhibition of flowering. Assembly of the tandem arrays of MAR and MAF genes of six A. alpina accessions and three related species using PacBio long-sequence reads demonstrated that the MARs arose within the Arabis genus by interchromosomal transposition of a MAF1-like gene followed by tandem duplication. Time-resolved comparative RNA-sequencing (RNA-seq) suggested that AmMAR1 may be retained in A. montbretiana to enhance the effect of the AmMAF cluster and extend the duration of vernalization required for flowering. Our results demonstrate that MAF genes transposed independently in different Brassicaceae lineages and suggest that they were retained to modulate adaptive flowering responses that differ even among closely related species.
Neonatal Piglets Are Protected from Clostridioides difficile Infection by Age-Dependent Increase in Intestinal Microbial Diversity

C. difficile is an important bacterial pathogen that is the most common cause of infections associated with health care in the United States. It also causes significant morbidity and mortality in neonatal pigs, and currently there are no preventative treatments available to livestock producers. ABSTRACT While Clostridioides difficile is recognized as an important human pathogen, it is also a significant cause of gastroenteritis and associated diarrhea in neonatal pigs. Since clinical disease is rarely diagnosed in piglets older than 1 week of age, it is hypothesized that natural resistance is associated with the increased complexity of the intestinal microbiota as the animals age. To test this, piglets were challenged with C. difficile (ribotype 078/toxinotype V) at times ranging from 2 to 14 days of age, and the severity of disease and microbial diversity of the cecal microbiota were assessed. Half of the piglets that were challenged with C. difficile at 2 and 4 days of age developed clinical signs of disease. The incidence of disease decreased rapidly as the piglets aged, to a point where none of the animals challenged after 10 days of age showed clinical signs. The cecal microbial community compositions of the piglets also clustered by age, with those of animals 2 to 4 days old showing closer relationships to one another than to those of older piglets (8 to 14 days). This clustering occurred across litters from 4 different sows, providing further evidence that the resistance to C. difficile disease in piglets greater than 1 week old is directly related to the diversity and complexity of the intestinal microbiota. IMPORTANCE C. difficile is an important bacterial pathogen that is the most common cause of infections associated with health care in the United States. It also causes significant morbidity and mortality in neonatal pigs, and currently there are no preventative treatments available to livestock producers. This study determined the age-related susceptibility of piglets to C. difficile over the first 2 weeks of life, along with documenting the natural age-related changes that occurred in the intestinal microbiota over the same time period in a controlled environment. We observed that the populations of intestinal bacteria within individual animals of the same age, regardless of litter, showed the highest degree of similarity. Identifying bacterial species associated with the acquisition of natural resistance observed in older pigs could lead to the development of new strategies to prevent and or treat disease caused by C. difficile infection.
Time-Related Changes in Patient Reported Bladder Symptoms and Satisfaction after Spinal Cord Injury

Purpose: Increased time after spinal cord injury (SCI) is associated with a migration to bladder managements with higher morbidity such as indwelling catheter (IDC). Still, it is unclear how this affects bladder-related quality of life (QoL). We hypothesized that time from injury (TFI) would be associated with changes in bladder management, symptoms and satisfaction. Materials and Methods: Cross-sectional analysis of time-related changes in patient-reported bladder management, symptoms and satisfaction using the Neurogenic Bladder Research Group SCI Registry. Outcomes included Neurogenic Bladder Symptom Score (NBSS) and bladder-related satisfaction (NBSS-satisfaction). Multivariable regression was performed to assess associations between TFI and outcomes, adjusting for participant characteristics, injury specifics, and psychosocial aspects of health-related QoL. Participants with TFI <1 year were excluded and TFI was categorized 1–5 (reference), 6–10, 11–15, 16–20 and >20 years. Results: Of 1,420 participants mean age at injury was 29.7 years (SD 13.4) and mean TFI was 15.2 years (SD 11.6). Participants grouped by TFI included 298 (21%) 1–5, 340 (24%) 6–10, 198 (14%) 11–15, 149 (10%) 16–20 and 435 (31%) >20 years. As TFI increased, clean intermittent catheterization (CIC) declined (55% 1–5 vs 45% >20 years, p <0.001) and IDC increased (16% 1–5 vs 21% >20 years, p <0.001). On multivariable analysis, increased TFI was associated with fewer bladder symptoms at >20 years from injury (−3.21 [CI −1.29, −5.14, p <0.001]) and better satisfaction (6–10 years −0.20 [CI −0.41, 0.01, p=0.070], 11–15 years −0.36 [CI −0.60, −0.11, p=0.002], 16–20 years −0.59 [CI −0.86, −0.32, p <0.001], >20 years −0.85 [CI −1.07, −0.63, <0.001]). Conclusions: After SCI, CIC decreases and IDC increases over time; however, increasing TFI is associated with reduced urinary symptoms and improved bladder-related satisfaction.
Decomposing the Bulk Electrical Conductivity of Streamflow To Recover Individual Solute Concentrations at High Frequency

The ability to evaluate stream hydrochemistry is often constrained by the capacity to sample streamwater at an adequate frequency. While technology is no longer a limiting factor, costs and sample management can still be a barrier to high-resolution water quality instrumentation. We propose a new framework for investigating the electrical conductivity (EC) of streamwater, which can be measured continuously through inexpensive sensors. We show that EC embeds information about individual ion content that can be isolated to retrieve solute concentrations at high resolution. The essence of the approach is the decomposition of the EC signal into its “harmonics”, i.e., the specific contributions of the major ions that conduct current in water. The ion contribution is used to explore water quality patterns and to develop algorithms that reconstruct solute concentrations starting from EC during periods where solute measurements are not available. The approach is validated on a hydrochemical data set from Plynlimo.
Effect of Peroxide Treatment on Functional and Technological Properties of Fiber-Rich Powders Based on Spent Coffee Grounds

The preparation of coffee beverage, as well as the industrial production of soluble coffee, generates a considerable amount of residues, the spent coffee grounds, SCG. There are no current profitable applications for these residues and an adequate disposal must be carried out since they are heavily pollutant and can be used to adulterate roasted and ground coffee. Thus, the objective of this work was to evaluate the effect of alkaline hydrogen peroxide treatment on the chemical composition and technological properties of spent coffee grounds in order to verify its potential as source of antioxidant dietary fibers. Evaluated parameters included moisture, fat, ash, soluble and insoluble dietary fiber contents, phenolics and in-vitro antioxidant potential, hydration properties and color. Total dietary fibre contents were shown to be high in comparison to commonly employed fibre sources, and increased with peroxide concentration. Phenolics content and the antioxidant activity of the treated spent coffee grounds decreased with increasing hydrogen peroxide concentration. Luminosity values increased significantly, and hydration properties showed a slight improvement with the increase in peroxide concentration. Overall, the alkaline hydrogen peroxide treatment produced an insoluble-fiber-rich material with physical and chemical characteristics that allow for its utilization as a source of antioxidant dietary fibers. 
Application of Central Composite Design to Optimize Culture Conditions of Chlorella vulgaris in a Batch Photobioreactor: An Efficient Modeling Approach

Abstract Microalgae cultivation and their use is a promising approach for integrated CO2 biofixation, wastewater treatment and renewable energy production. To develop such an important technology, there is a need to optimize the culture conditions, maximizing CO2 consumption, degrading the nutrients present in the wastewater and maximise the microalgae biomass production. Central Composite Design (CCD) approach was applied to develop quadratic regression models. The developed models were employed separately to estimate optimal sets of three important input parameters (CO2 concentration, nitrogen-to-phosphorus ratio and culture temperature) for maximizing specific growth rate, biomass productivity and CO2 biofixation rate. The maximum specific growth rate of 1.93 ± 0.19 d-1 was observed at an optimal set of 34oC, 4:1 nitrogen-to-phosphorus ratio, and 6 % CO2 concentration. The maximum biomass productivity of 86.5 ± 20.0 mgL-1d-1 was obtained at 4.8 % CO2, 8:1 nitrogen-to-phosphorus ratio and 28oC. In addition, the maximum CO2 biofixation rate was calculated to be 251.9 ± 13.5 mgL-1d-1 at optimal values of 4 % CO2, 1:1 nitrogen-to-phosphorus ratio and 25oC. Finally, multi-objective optimization method was employed to predict the maximum CO2 biofixation rate and biomass productivity concurrently. The optimum values of CO2 biofixation rate (182.84 ± 8.42 mgL-1d-1) and biomass productivity (78.5 ± 10.0 mgL-1d-1) were obtained from operating conditions at 4 % CO2, 6:1 nitrogen-to-phosphorus ratio, 25oC culture temperature. These predicted data were in strong agreement with the experimental values.
Changing foodwebs of Indian aquatic ecosystems under the threats of invasive species: An overview

Biological invasions are a worldwide threat to the aquatic systems and have the potential to homogenize entire foodwebs and shift species abundance distributions to more skewed ones. Invasion impacts include effects on the foodweb structure and ecosystem functioning leading to a loss in native fish biodiversity and commercially important fisheries in many open water systems. The impacts of invasives are generally devastating as they spread in the foodweb with each species potentially interacting with multiple species. The foodweb modeling studies conducted in different inland aquatic ecosystems show that not all exotics cause a detrimental effect on the resilience of an ecosystem. Information on the foodweb structure and ecosystem properties is a prerequisite for formulating management protocols for conserving biodiversity, enhancement programmes and sustaining fisheries. The present paper reviews the impacts of invasive fishes in Indian aquatic ecosystems in the context of a changing foodweb scenario due to exotic fish species invasions. The information generated here could be applied for future research on similar ecosystems for deducing management actions.
Management strategies to regulate the introduction of exotic ornamental fish, the silent invaders of freshwater ecosystems in India

Ornamental fish culture and aquarium keeping have become a booming sector worldwide. It has been observed that a number of stakeholders are involved in introducing exotic ornamentals in India as well, as the takers are interested on variants and new species. Most of the exotic ornamental fishes are also being domesticated in India, since the demand is readily fulfilled through adequate supply to the hobbyists. This sector provides livelihood option to many people and helps to earn millions of dollars to our country every year, however, the invasion of exotic ornamentals in our natural water bodies needs to be assessed, monitored and controlled with due attention as it is a staid menace to our biodiversity. Around 400 species / variants of exotic freshwater ornamentals and around 100 exotic marine ornamental species including invertebrates are found to have introduced in the trade. It is significant to note that an apparent violation in the trade is taking place by concealing the Government of India approval, which is given only for 92 species / variants of fishes for import. Further, as some of the freshwater ornamental fishes currently available in the aquarium trade have invaded through natural water bodies, their impacts need to be studied in detail. To deal with the situation, the proper precautionary approach should be implemented by adopting measures after having proper quarantine, meticulous risk analysis and strategic prevention methods as well. Combined efforts of industry stakeholders with different government agencies, academic and research institutions is required and a suitable protocol has to be formulated for permissible import, sustainable production, supply and management.
Introduction to the Special Issue on Artificial Intelligence and Cyber-Physical Systems: Part 1

By using a combination of machines, sensors, embedded computational intelligence, and various communication mechanisms, Cyber-Physical Systems (CPSs) monitor and control physical elements with computer-based algorithms, capable of autonomously reacting to and affecting their physical surroundings. Advances in CPS should enable capability, adaptability, scalability, resilience, safety, security, and usability far beyond what is available in the embedded systems of today. In light of the rapid advancements in artificial intelligence (AI) and communications, there is an increasing demand for these intelligent CPSs, such as connected and autonomous vehicles that monitor and communicate with their surroundings and smart appliances that optimize energy consumption based on environment and occupant behavior. To realize the vision of AI-enabled CPS, there are several research areas we can expect to come to the fore. For example, new methods to combine data-driven machine leaning and model-based learning for decision making and real-time control of cyber-physical systems are very promising. Meanwhile, traditional ideas in CPS research are being challenged by new concepts emerging from AI and machine learning. For example, what do high confidence and assurance mean in the context of autonomous systems that learn from their experiences? How does one address the trinity of challenges of trustworthiness, resilience, and interpretability of artificial intelligence in its integration with high-assurance cyber-physical systems? How does one reconcile the concepts of machine learning and data-driven modeling with approaches used in model-based design and formal methods? To explore these new directions and address new challenges, this special issue features 12 articles on the topics of AI and CPS.
A Hierarchical Hybrid Locking Protocol for Parallel Real-Time Tasks

Parallel tasks have been paid growing attention in recent years, and the scheduling with shared resources is of significant importance to real-time systems. As an efficient mechanism to provide mutual exclusion for parallel processing, spin-locks are ubiquitous in multi-processor real-time systems. However, the spin-locks suffer the scalability problem, and the intra-task parallelism further exacerbates the analytical pessimism. To overcome such deficiencies, we propose a Hierarchical Hybrid Locking Protocol (H2LP) under federated scheduling. The proposed H2LP integrates the classical Multiprocessor Stack Resource Policy (MSRP) and uses a token mechanism to reduce global contentions. We provide a complete analysis framework supporting both heavy and light tasks under federated scheduling and develop a blocking analysis with the state-of-the-art linear optimization technique. Empirical evaluations showed that the H2LP outperformed the other state-of-the-art locking protocols in at least configurations when considering exclusive clustering. Furthermore, our partitioned approach for light tasks can substantially improve schedulability by mitigating the over-provisioning problem.
The TOR Agent:Optimizing Driver Take-Over with Reinforcement Learning

Various factors influence drivers’ response to Take-Over Requests in automated driving, and a wide range of designs have been proposed to improve transitions. Still, little research has investigated how systems could deliver Take-Over Requests at the best moment in time. In this paper, we sketch the idea of a reinforcement learning agent that learns to deliver Take-Over Requests at the right time so that drivers’ performance gets optimized, which could help to increase driving safety. We implemented such a system in Unity to evaluate this approach using a simple driver model. Our agent receives coordinates of the upcoming road segment and learns to deliver a Take-Over Request at an appropriate moment within a short time window. The reward function is composed to minimize the lateral deviation in the subsequent phase of manual driving. The initial results obtained are promising, and we will evaluate the concept with real human users soon.
Workshop on Exploring Interfaces for Enhanced Automation Assistance for Improving Manual Driving Abilities

With continually advancing automation capabilities in vehicles, there is increasing potential for these capabilities to be used not only as stopgaps towards full automation but to enhance humans’ manual driving capabilities during this transition phase and beyond. By employing smart automation assistance (e.g., highlighting of relevant roadside information, maneuver interventions and corrections), it might even be possible to enable automation assisted “manual” driving for those, who might not be able to drive otherwise (older adults, individuals with impairments). In this workshop, we intend to explore this problem together with the participants and identify potentials for automation assistance to enhance manual driving performance, and what in-vehicle interfaces can contribute in this regard.
Taking on driving tasks yourself? That was yesterday! How drivers would like to be supported by assistance systems

Advanced Driver Assistance Systems (ADAS) can be found in almost every vehicle nowadays. They support drivers and usually ensure comfort and road safety. While some ADAS have been on the market for years and have proven themselves, some have only recently become available or are still in development. The present study investigates in which situations and contexts ADAS are considered to be most useful. We explored in which contexts a high degree of automation is desired and which implications this has for the design of ADAS. We found that users prefer a high level of automation for motorway driving and parking, but not for urban and overland driving. Our results suggest that the use of and trust in ADAS is related to their complexity. Based on our results, we derive recommendations for interface designers and car manufacturers.
Evaluation of graphical human-machine interfaces for turning manoeuvres in automated vehicles

Autonomous vehicles may become an important part of traffic in the next few decades. One of the key factors that contribute to the acceptance of the technology is that the user can understand and to a certain degree predict the behaviour of the automation. One way to communicate the automation's intention and behaviour are graphical human-machine interfaces (HMIs). An online survey was conducted to evaluate five designs for HMIs for turning manoeuvres in automated vehicles. During the survey the participants rated the HMIs based on videos. The overall ratings don't show a clear favourite, however, a separation of the participants regarding their trust in automation and technical affinity indicate preferences regarding the preferred level of abstraction. Furthermore, 97% of the participants agreed that HMIs like the ones presented would help them gain or increase their trust in automated vehicles.