Miracle-dz/UniFAR-FTUs huggingface dataset:
The Roles of Porous Coral Sands in Initial Enrichment of Ammonia-Oxidizing Bacteria

The purpose of this study was to investigate the roles of coral sands in the enrichment and isolation of ammonium-oxidizing bacteria (AOB). We hypothesized that the porous coral sands provided additional surface area and nutrients for the growth of periphytic AOB. In the present study, an orthogonal test was designed to compare the AOB conversion rates of ammonium-nitrogen (NH4+N) to nitrite-nitrogen (NO2--N) among various combinations of culture media. Results showed that the conversion of NH4+N to NO2--N increased significantly when the coral sands were added, implying that coral sands were beneficial to the growth of AOB. Additions of potassium dihydrogen phosphate (KH2PO4) or sodium bicarbonate (NaHCO3) to the media became unnecessary when coral sands were used, but the addition of KH2PO4 was needed when the molar nitrogen to phosphorus (N:P) ratio reached 10 in the enrichment media using calcium carbonate (CaCO3) powder as a calcium source.
Protective Properties of Probiotics on Commercial Broilers Experimentally Infected With Salmonella Enteritidis

Performance and productivity in the poultry industry lately is predicated on the use of antimicrobials, which has led to various negative impacts; among which include the emergence of a variety of pathogens and bacterial resistance including salmonella sp. This study was designed to investigate periodic evaluation of the protective properties of probiotic on commercial broilers experimentally infected with Salmonella Enteritidis; specifically on bacterial shedding and mortality pattern of birds throughout the rearing period. One hundred and eighty day old commercial broilers were allotted into four treatment groups, G1 (antibiotics, probiotic & S. Enteritidis infected), G2 (antibiotics & S. Enteritidis infected), G3 (probiotic & S. Enteritidis infected) and G4 (antibiotics) each replicated thrice, with 15 birds per replicate. Antibiotic and probiotics were administered day 1-5 and 6-56 days respectively; thereafter, cultured Salmonella Enteritidis was inoculated at the dose rate of 107cfu orally. This study lasted for eight (8) weeks, during which freshly voided faecal samples were collected from the respective replicates for isolation, biochemical test and salmonellae counts; for pre-infection (0), 7, 10, 15, 18 and 21 day post infection (dpi). Data generated were subjected to descriptive statistical analysis and significant differences (p<0.05) between mean values determined with student t-test. The numbers of dead birds over a period of 8weeks were calculated and expressed as percentage of allotted birds in each treatment group.
Reachability Analysis and Safety Verification for Neural Network Control Systems

Autonomous cyber-physical systems (CPS) rely on the correct operation of numerous components, with state-of-the-art methods relying on machine learning (ML) and artificial intelligence (AI) components in various stages of sensing and control. This paper develops methods for estimating the reachable set and verifying safety properties of dynamical systems under control of neural network-based controllers that may be implemented in embedded software. The neural network controllers we consider are feedforward neural networks called multilayer perceptrons (MLP) with general activation functions. As such feedforward networks are memoryless, they may be abstractly represented as mathematical functions, and the reachability analysis of the network amounts to range (image) estimation of this function provided a set of inputs. By discretizing the input set of the MLP into a finite number of hyper-rectangular cells, our approach develops a linear programming (LP) based algorithm for over-approximating the output set of the MLP with its input set as a union of hyper-rectangular cells. Combining the over-approximation for the output set of an MLP based controller and reachable set computation routines for ordinary difference/differential equation (ODE) models, an algorithm is developed to estimate the reachable set of the closed-loop system. Finally, safety verification for neural network control systems can be performed by checking the existence of intersections between the estimated reachable set and unsafe regions. The approach is implemented in a computational software prototype and evaluated on numerical examples.
Do you believe in magic?

“Smoke and Mirrors” is the largest touring magic show in Arkansas and the midsouth region of the United States. The show is part of the “Arts on Tour” program sponsored by the Arkansas Arts Council, which promotes visual and performing arts across the state. Rocky and Lori perform at about 50 venues each year, including theaters, festivals, college campuses, and corporate events. The show involves more than $50,000 worth of equipment used to produce state-of-the-art illusions in addition to classic effects performed over the last 100 years by many of the legends of magic. The show is a journey through the history of magic, including tales of past magicians and magic shows, Vaudeville, sideshows, con-men, and ghost stories, all played out with ornate props, fascinating storytelling, and a beautiful stage set. The production promises to appeal to young and old alike, and will offer an artistic alternative for those looking for something outside the usual forms of entertainment. For more information on this event, contact Rhonda Cupp at 501-977-2085 or at cupp@uaccm.edu.
Adaptive Obstacle Detection for Mobile Robots in Urban Environments Using Downward-Looking 2D LiDAR

Environment perception is important for collision-free motion planning of outdoor mobile robots. This paper presents an adaptive obstacle detection method for outdoor mobile robots using a single downward-looking LiDAR sensor. The method begins by extracting line segments from the raw sensor data, and then estimates the height and the vector of the scanned road surface at each moment. Subsequently, the segments are divided into either road ground or obstacles based on the average height of each line segment and the deviation between the line segment and the road vector estimated from the previous measurements. A series of experiments have been conducted in several scenarios, including normal scenes and complex scenes. The experimental results show that the proposed approach can accurately detect obstacles on roads and could effectively deal with the different heights of obstacles in urban road environments.
Links between psychotic and neurotic symptoms in the general population: an analysis of longitudinal British National Survey data using Directed Acyclic Graphs

Abstract Background Non-psychotic affective symptoms are important components of psychotic syndromes. They are frequent and are now thought to influence the emergence of paranoia and hallucinations. Evidence supporting this model of psychosis comes from recent cross-fertilising epidemiological and intervention studies. Epidemiological studies identify plausible targets for intervention but must be interpreted cautiously. Nevertheless, causal inference can be strengthened substantially using modern statistical methods. Methods Directed Acyclic Graphs were used in a dynamic Bayesian network approach to learn the overall dependence structure of chosen variables. DAG-based inference identifies the most likely directional links between multiple variables, thereby locating them in a putative causal cascade. We used initial and 18-month follow-up data from the 2000 British National Psychiatric Morbidity survey (N = 8580 and N = 2406). Results We analysed persecutory ideation, hallucinations, a range of affective symptoms and the effects of cannabis and problematic alcohol use. Worry was central to the links between symptoms, with plausible direct effects on insomnia, depressed mood and generalised anxiety, and recent cannabis use. Worry linked the other affective phenomena with paranoia. Hallucinations were connected only to worry and persecutory ideation. General anxiety, worry, sleep problems, and persecutory ideation were strongly self-predicting. Worry and persecutory ideation were connected over the 18-month interval in an apparent feedback loop. Conclusions These results have implications for understanding dynamic processes in psychosis and for targeting psychological interventions. The reciprocal influence of worry and paranoia implies that treating either symptom is likely to ameliorate the other.
High‐Resolution Single Nucleotide Polymorphism Genotyping Reveals a Significant Problem among Breeder Resources

The logistics associated with a modern breeding program can be complex, relying on accuracy and communication between plant breeders, pathologists, quantitative geneticists, and support staff. International and academic facets may bring additional challenges to already error prone activities including the development, maintenance, and distribution of lines. Furthermore, practices such as bulking of seed and the maintenance of within‐accession variation among landraces must be considered when pursuing marker‐assisted approaches to breeding.
Operational locality in global theories

Within a global physical theory, a notion of locality allows us to find and justify information-processing primitives, like non-signalling between distant agents. Here, we propose exploring the opposite direction: to take agents as the basic building blocks through which we test a physical theory, and recover operational notions of locality from signalling conditions. First, we introduce an operational model for the effective state spaces of individual agents, as well as the range of their actions. We then formulate natural secrecy conditions between agents and identify the aspects of locality relevant for signalling. We discuss the possibility of taking commutation of transformations as a primitive of physical theories, as well as applications to quantum theory and generalized probability frameworks. This ‘it from bit’ approach establishes an operational connection between local actions and local observations, and gives a global interpretation to concepts like discarding a subsystem or composing local functions. This article is part of a discussion meeting issue ‘Foundations of quantum mechanics and their impact on contemporary society’.
Effect of Processing on the In Vitro and In Vivo Protein Quality of Beans (Phaseolus vulgaris and Vicia Faba)

In this work, the protein quality of different bean types after undergoing the preparatory methods of baking, cooking and extrusion was assayed. Protein quality was assessed using a rodent bioassay to evaluate growth and protein digestibility while amino acid composition was determined via HPLC. In vivo protein digestibility was compared to an in vitro assessment method. The average protein digestibility corrected amino acid score (PDCAAS) for processed beans was higher than the digestible indispensable amino acid score (DIAAS) (61% vs. 45%). Extrusion/cooking of Phaseolus varieties resulted in higher PDCAAS (66% on average) and DIAAS values (61% on average) than baked (52% and 48%) while baked faba beans had higher PDCAAS (66%) and DIAAS (61%) values. A significant correlation was found between PDCAAS and in vitro PDCAAS (R2 = 0.7497). This demonstrates which bean processing method will generate the optimal protein quality, which has benefits for both industrial production and individual domestic preparation.
Activity and torpor in two sympatric Australian desert marsupials

Many biological variables related to energy turnover including torpor, the most efficient energy-saving mechanism available to mammals, scale with body size, but the implications for animals living in their natural environment remain largely unknown. We used radio-telemetry to obtain the first data on the activity patterns and torpor use of two sympatric, free-ranging dasyurid marsupials, the stripe-faced dunnart Sminthopsis macroura (16.6±1.5 g) and the more than six-times larger kowari Dasyuroides byrnei (109.4±16.4 g), during winter in arid Queensland, Australia. Eight dunnarts and six kowaries were surgically implanted with temperature-sensitive radio-transmitters and monitored for 14–59 days. Both species commenced activity shortly after sunset, but while kowaries remained active through most of the night, dunnarts usually returned to their burrows before midnight. In dunnarts, short activity was associated with the frequent use of daily torpor (99.1% of observation days). Torpor often commenced at night, with body temperature (Tb) decreasing to a minimum of 11.3 °C, and torpor lasted up to 26 h. In contrast, only 50% of the kowaries entered torpor and torpor was brief (maximum 4 h), shallow (minimum Tb 25.3 °C) and restricted to the daytime rest-phase. Our study suggests that in winter, the smaller dunnarts can remain active only during the warmer first half of the night and energy-saving torpor becomes part of their daily routine. In contrast, it appears that the larger kowaries are less affected by cold winter nights and can maintain high night-time activity levels and commence reproduction already in winter. Hence, they enter torpor only occasionally and only during the rest phase.
Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model

Abstract Context: Accidental exposure to life-threatening radiation in a nuclear event is a major concern; there is an enormous need for identifying biomarkers for radiation biodosimetry to triage populations and treat critically exposed individuals. Objective: To identify dose-differentiating miRNA signatures from whole blood samples of whole body irradiated mice. Methods: Mice were whole body irradiated with X-rays (2 Gy–15 Gy); blood was collected at various time-points post-exposure; total RNA was isolated; miRNA microarrays were performed; miRNAs differentially expressed in irradiated vs. unirradiated controls were identified; feature extraction and classification models were applied to predict dose-differentiating miRNA signature. Results: We observed a time and dose responsive alteration in the expression levels of miRNAs. Maximum number of miRNAs were altered at 24-h and 48-h time-points post-irradiation. A 23-miRNA signature was identified using feature selection algorithms and classifier models. An inverse correlation in the expression level changes of miR-17 members, and their targets were observed in whole body irradiated mice and non-human primates. Conclusion: Whole blood-based miRNA expression signatures might be used for predicting radiation exposures in a mass casualty nuclear incident.
Headon

We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel realtime reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.
Structural covariance networks across the life span, from 6 to 94 years of age

Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. Despite significant interest in the influence of age on structural covariance patterns, no study to date has provided a complete life span perspective—bridging childhood with early, middle, and late adulthood—on the development of structural covariance networks. Here, we investigate the life span trajectories of structural covariance in six canonical neurocognitive networks: default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual. By combining data from five open-access data sources, we examine the structural covariance trajectories of these networks from 6 to 94 years of age in a sample of 1,580 participants. Using partial least squares, we show that structural covariance patterns across the life span exhibit two significant, age-dependent trends. The first trend is a stable pattern whose integrity declines over the life span. The second trend is an inverted-U that differentiates young adulthood from other age groups. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, our results suggest that structural covariance provides a reliable definition of neurocognitive networks across the life span and reveal both shared and network-specific trajectories. Author Summary The importance of life span perspectives is increasingly apparent in understanding normative interactions of large-scale neurocognitive networks. Although recent work has made significant strides in understanding the functional and structural connectivity of these networks, there has been comparatively little attention to life span trajectories of structural covariance networks. In this study we examine patterns of structural covariance across the life span for six neurocognitive networks. Our results suggest that networks exhibit both network-specific stable patterns of structural covariance as well as shared age-dependent trends. Previously identified hub regions seem to show a strong influence on the expression of these age-related trajectories. These results provide initial evidence for a multimodal understanding of structural covariance in network structure-function interaction across the life course.
Use of immersive virtual reality to assess episodic memory: A validation study in older adults

ABSTRACT Virtual reality (VR) allows for the creation of ecological environments that could be used for cognitive assessment and intervention. This study comprises two parts that describe and assess an immersive VR task, the Virtual Shop, which can be used to measure episodic memory. Part 1 addresses its applicability in healthy older adults by measuring presence, motivation, and cybersickness symptoms. Part 2 addresses its construct validity by investigating correlations between performance in the VR task and on a traditional experimental memory task, and by measuring whether the VR task is sensitive to age-related memory differences. Fifty-seven older and 20 younger adults were assessed in the Virtual Shop, in which they memorised and fetched 12 familiar items. Part 1 showed high levels of presence, higher levels of motivation for the VR than for the traditional task, and negligible cybersickness symptoms. Part 2 indicates that memory performance in the VR task is positively correlated with performance on a traditional memory task for both age groups, and age-related differences were found on the VR and traditional memory tasks. Thus, the use of VR is feasible in older adults and the Virtual Shop is a valid task to assess and train episodic memory in this population.
Landmine detection and reporting using light weight zumo bot

The purpose of this research work is to propose a simple bot to detect landmines and mark their locations using autonomous navigation using a simple Zumo32U4 robot. Landmine detection is an important and yet challenging aspect in many of the countries which are still plagued my landmine issues for several decades now. It is not only the problem of the military, but it is also a humanitarian concern. So, in order to address this issue we came up with simple, light weight, autonomous wireless controlled robot which is capable of detecting the landmine at the depth of 5cm to 9cm under group. The paper describes about the design and development of the landmine detection mechanism. The results are very promising that this bot can be well used in fields for identifying and locating the landmines.
Endothelial Cell Tetrahydrobiopterin Modulates Sensitivity to Ang (Angiotensin) II–Induced Vascular Remodeling, Blood Pressure, and Abdominal Aortic Aneurysm

GTPCH (GTP cyclohydrolase 1, encoded by Gch1) is required for the synthesis of tetrahydrobiopterin; a critical regulator of endothelial NO synthase function. We have previously shown that mice with selective loss of Gch1 in endothelial cells have mild vascular dysfunction, but the consequences of endothelial cell tetrahydrobiopterin deficiency in vascular disease pathogenesis are unknown. We investigated the pathological consequence of Ang (angiotensin) II infusion in endothelial cell Gch1 deficient (Gch1fl/fl Tie2cre) mice. Ang II (0.4 mg/kg per day, delivered by osmotic minipump) caused a significant decrease in circulating tetrahydrobiopterin levels in Gch1fl/fl Tie2cre mice and a significant increase in the N&ohgr;-nitro-L-arginine methyl ester inhabitable production of H2O2 in the aorta. Chronic treatment with this subpressor dose of Ang II resulted in a significant increase in blood pressure only in Gch1fl/fl Tie2cre mice. This finding was mirrored with acute administration of Ang II, where increased sensitivity to Ang II was observed at both pressor and subpressor doses. Chronic Ang II infusion in Gch1fl/fl Tie2ce mice resulted in vascular dysfunction in resistance mesenteric arteries with an enhanced constrictor and decreased dilator response and medial hypertrophy. Altered vascular remodeling was also observed in the aorta with an increase in the incidence of abdominal aortic aneurysm formation in Gch1fl/fl Tie2ce mice. These findings indicate a specific requirement for endothelial cell tetrahydrobiopterin in modulating the hemodynamic and structural changes induced by Ang II, through modulation of blood pressure, structural changes in resistance vessels, and aneurysm formation in the aorta.
Robust Multi-Classifier for Camera Model Identification Based on Convolution Neural Network

With the prevalence of adopting data-driven convolution neural network (CNN)-based algorithms into the community of digital image forensics, some novel supervised classifiers have indeed increasingly sprung up with nearly perfect detection rate, compared with the conventional supervised mechanism. The goal of this paper is to investigate a robust multi-classifier for dealing with one of the image forensic problems, referred to as source camera identification. The main contributions of this paper are threefold: 1) by mainly analyzing the image features characterizing different source camera models, we design an improved architecture of CNN for adaptively and automatically extracting characteristics, instead of hand-crafted extraction; 2) the proposed efficient CNN-based multi-classifier is capable of simultaneously classifying the tested images acquired by a large scale of different camera models, instead of utilizing a binary classifier; and 3) numerical experiments show that our proposed multi-classifier can effectively classify different camera models while achieving an average accuracy of nearly 100% relying on majority voting, which indeed outperforms some prior arts; meanwhile, its robustness has been verified by considering that the images are attacked by post-processing such as JPEG compression and noise adding.
Low-Power and High Speed High-to-Low Level Shifter

A novel structure of high speed high-to-low level shifter is proposed. Due to decrease in the number of input thickoxide transistors, the output frequency maximum is increased while providing 13.5% less power consumption than conventional designs. The utilization of dual thick-oxide NMOS input cascade provides smaller output signal jitter and approximately 50% duty-cycle. The circuit is designed in CMOS 40nm technology and simulated with SPICE.