Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil microbial activity in hydromorphic-subaqueous ecosystems: processes and functional biodiveristy

The hydromorphic and subaqueous soils have largely been overlooked on their pedogenic concepts or in soil C accounting studies considering their phisico-chemical properties. Conversely, little attention has been paid to the microbial activity playing a key role in regulating the biogeochemical cycle of elements. The aim of the study was to evaluate biological properties such as enzyme activities and the functional diversity of soil microbial population as bio- indicators, sensitive to processes affected by the water shallow. Eight soil profiles were opened along two transects: 1) a-a’ North and 2) b-b' South, in a dune ecosystem of the Adriatic coast, Ravenna (Italy). The soil chemical and biochemical properties were determined. In particular, soil enzyme activities and soil induced respiration were measured using the microplates technique in order to assess the microbial functional diversity. The soil biochemical properties such as the potential enzyme activities and microbial induced respiration, as well as microbial functional diversity were sensitive indicators to study hydromorphic and subaqueous soils. A general reduction of hydrolytic enzyme activities was observed in subaqueous soil with respect to hydromorphic one. Moreover, the endopedon of subaqueous soils showed a lower microbial functional diversity than hydromorphic one. In this study the ratio of enzyme activities involved in C to S cycles (SEIC/Aryl) as well as the C:S ratio showed a marked reduction in the subaqueous with respect to hydromorphic soils. In conclusion, in a coastal area the C and S biogeochemical cycles, in the hydromorphic and subaqueous soils, may depend on freshwater and saltwater interface equilibrium.
Prenatal Alcohol Exposure: Profiling Developmental DNA Methylation Patterns in Central and Peripheral Tissues

Background: Prenatal alcohol exposure (PAE) can alter the development of neurobiological systems, leading to lasting neuroendocrine, neuroimmune, and neurobehavioral deficits. Although the etiology of this reprogramming remains unknown, emerging evidence suggests DNA methylation as a potential mediator and biomarker for the effects of PAE due to its responsiveness to environmental cues and relative stability over time. Here, we utilized a rat model of PAE to examine the DNA methylation profiles of rat hypothalami and leukocytes at four time points during early development to assess the genome-wide impact of PAE on the epigenome and identify potential biomarkers of PAE. Our model of PAE resulted in blood alcohol levels of ~80–150 mg/dl throughout the equivalent of the first two trimesters of human pregnancy. Hypothalami were analyzed on postnatal days (P) 1, 8, 15, 22 and leukocytes at P22 to compare central and peripheral markers. Genome-wide DNA methylation analysis was performed by methylated DNA immunoprecipitation followed by next-generation sequencing. Results: PAE resulted in lasting changes to DNA methylation profiles across all four ages, with 118 differentially methylated regions (DMRs) displaying persistent alterations across the developmental period at a false-discovery rate (FDR) < 0.05. In addition, 299 DMRs showed the same direction of change in the hypothalamus and leukocytes of P22 pups at an FDR < 0.05, with some genes overlapping with the developmental profile findings. The majority of these DMRs were located in intergenic regions, which contained several computationally-predicted transcription factor binding sites. Differentially methylated genes were generally involved in immune function, epigenetic remodeling, metabolism, and hormonal signaling, as determined by gene ontology analyses. Conclusions: Persistent DNA methylation changes in the hypothalamus may be associated with the long-term physiological and neurobehavioral alterations in observed in PAE. Furthermore, correlations between epigenetic alterations in peripheral tissues and those in the brain will provide a foundation for the development of biomarkers of fetal alcohol spectrum disorder (FASD). Finally, findings from studies of PAE provide important insight into the etiology of neurodevelopmental and mental health disorders, as they share numerous phenotypes and comorbidities.
Audio Augmentation for Traffic Signs: A Case Study of Pakistani Traffic Signs

Augmented Reality (AR) extend the appearance of real-world by adding digital information to the scene using computer graphics and image processing techniques. Various approaches have been used to detect, identify and track objects in real environment depending upon the application, shape of the tracking object and environment type. The marker-based tracking technique is the most commonly used method in augmented reality applications in which fiducial markers are put in the real-world for tracking. In this work we proposed a model to detect and identify the traffic signs through marker based technique to improve the usability of marker-based detection in augmented reality applications. We developed an AR application that can detect and recognize the markers designed for Pakistani traffic signs and augment them with voice alert to the driver so that he does prepared for the upcoming hurdle on the road. As identified by literature no work has been performed on augmentation of voice for traffic signs. From experiments the model outperforms than baseline techniques.
Real-time proximal gradient method for linear MPC*

This paper presents a real-time implementation of the proximal gradient method (PGM) in a model predictive control (MPC) setting. In each control update only one iteration of the PGM is performed, while a next update is warm-started using the solution of the previous one. When applied to linear time-invariant (LTI) systems with simple input constraints, the resulting control law becomes extremely simple and offers possibilities to obtain fast control rates even on resource-constrained hardware. The paper provides a proof of closed-loop stability of the real-time PGM applied to LTI systems. A numerical simulation example validates the resulting closed-loop performance.
Gluing polyhedra with entanglement in loop quantum gravity

In a spin-network basis state, nodes of the graph describe unentangled quantum regions of space, quantum polyhedra. In this paper we show how entanglement between intertwiner degrees of freedom enforces gluing conditions for neighboring quantum polyhedra. In particular, we introduce Bell-network states, entangled states defined via squeezed vacuum techniques. We study correlations of quantum polyhedra in a dipole, a pentagram, and a generic graph. We find that vector geometries, structures with neighboring polyhedra having adjacent faces glued back to back, arise from Bell-network states. We also discuss the relation to Regge geometries. The results presented show clearly the role that entanglement plays in the gluing of neighboring quantum regions of space.
General-relativistic resistive-magnetohydrodynamic simulations of binary neutron stars

We have studied the dynamics of an equal-mass magnetized neutron-star binary within a resistive magnetohydrodynamic (RMHD) approach in which the highly conducting stellar interior is matched to an electrovacuum exterior. Because our analysis is aimed at assessing the modifications introduced by resistive effects on the dynamics of the binary after the merger and through to collapse, we have carried out a close comparison with an equivalent simulation performed within the traditional ideal magnetohydrodynamic approximation. We have found that there are many similarities between the two evolutions but also one important difference: the survival time of the hyper massive neutron star increases in a RMHD simulation. This difference is due to a less efficient magnetic-braking mechanism in the resistive regime, in which matter can move across magnetic-field lines, thus reducing the outward transport of angular momentum. Both the RMHD and the ideal magnetohydrodynamic simulations carried here have been performed at higher resolutions and with a different grid structure than those in previous work of ours [L. Rezzolla, B. Giacomazzo, L. Baiotti, J. Granot, C. Kouveliotou, and M. A. Aloy, Astrophys. J. Letters 732, L6 (2011)], but confirm the formation of a low-density funnel with an ordered magnetic field produced by the black hole--torus system. In both regimes the magnetic field is predominantly toroidal in the highly conducting torus and predominantly poloidal in the nearly evacuated funnel. Reconnection processes or neutrino annihilation occurring in the funnel, none of which we model, could potentially increase the internal energy in the funnel and launch a relativistic outflow, which, however, is not produced in these simulations.
Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration

The brightfield microscope is instrumental in the visual examination of both biological and physical samples at sub-millimeter scales. One key clinical application has been in cancer histopathology, where the microscopic assessment of the tissue samples is used for the diagnosis and staging of cancer and thus guides clinical therapy. However, the interpretation of these samples is inherently subjective, resulting in significant diagnostic variability. Moreover, in many regions of the world, access to pathologists is severely limited due to lack of trained personnel. In this regard, Artificial Intelligence (AI) based tools promise to improve the access and quality of healthcare. However, despite significant advances in AI research, integration of these tools into real-world cancer diagnosis workflows remains challenging because of the costs of image digitization and difficulties in deploying AI solutions. Here we propose a cost-effective solution to the integration of AI: the Augmented Reality Microscope (ARM). The ARM overlays AI-based information onto the current view of the sample through the optical pathway in real-time, enabling seamless integration of AI into the regular microscopy workflow. We demonstrate the utility of ARM in the detection of lymph node metastases in breast cancer and the identification of prostate cancer with a latency that supports real-time workflows. We anticipate that ARM will remove barriers towards the use of AI in microscopic analysis and thus improve the accuracy and efficiency of cancer diagnosis. This approach is applicable to other microscopy tasks and AI algorithms in the life sciences and beyond.
Pathways to Reduce the Environmental Footprints of Energy Inputs in Sesame Production in Jigawa State, Nigeria

This research investigates the pathways tto reduce the environmental footprints of energy inputs in sesame production in Jigawa State of Nigeria using data elicited from 99 sesame farmers via multi-stage sampling technique. Energy efficiency was studied and degrees of technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) were determined using data envelopment analysis (DEA). Additionally, wasteful uses of energy by inefficient farms were assessed and energy saving of different sources was computed. Results revealed that only 9.4% DMUs were technically efficient with average TE score of 0.624; based on BCC model 34.4% DMUs were identified to be efficient with mean PTE score of 0.79; while based on scale efficiency only 12.5% DMUs were efficient with mean SE score of 0.804. Furthermore it was observed that approximately 38.17% (1505.58MJha-1) of overall input energies can be saved if performance of inefficient DMUs rose to a high level.
Impact of Flow Velocity on Transport of Graphene Oxide Nanoparticles in Saturated Porous Media

We examined the influence of flow velocity on transport of graphene oxide nanoparticles (GONPs). Attachment efficiency (α) increased with increasing flow velocity for GONPs. Hydrodynamic shear cannot release the attached GONPs, even from nanoscale asperities. Increasing flow velocity increased attachment of GONPs at concave surfaces.
Observations of fine particulate nitrated phenols in four sites in northern China: concentrations, source apportionment, and secondary formation

Abstract. Filter samples of fine particulate matters were collected at four sites in northern China (urban, rural, and mountain) in summer and winter, and the contents of nine nitrated phenols were quantified in the laboratory with the use of ultra-high-performance liquid chromatography coupled with mass spectrometry. During the sampling periods, the concentrations of particulate nitrated phenols exhibited distinct temporal and spatial variation. On average, the total concentration of particulate nitrated phenols in urban Jinan in the wintertime reached 48.4 ng m−3, and those in the summertime were 9.8, 5.7, 5.9, and 2.5 ng m−3 in urban Jinan, rural Yucheng and Wangdu, and Mt. Tai, respectively. The elevated concentrations of nitrated phenols in wintertime and in urban areas demonstrate the apparent influences of anthropogenic sources. The positive matrix factorization receptor model was then applied to determine the origins of particulate nitrated phenols in northern China. The five major source factors were traffic, coal combustion, biomass burning, secondary formation, and aged coal combustion plume. Among them, coal combustion played a vital role, especially at the urban site in the wintertime, with a contribution of around 55 %. In the summertime, the observed nitrated phenols were highly influenced by aged coal combustion plumes at all of the sampling sites. Meanwhile, in remote areas, contributions from secondary formation were significant. Further correlation analysis indicates that nitrosalicylic acids were produced mostly from secondary formation that was dominated by NO2 nitration.
BEST PATH CHANGE RATE FOR UNSUPERVISED LANGUAGE MODEL WEIGHT SELECTION

Language model weight (LMW) is used in speech recognition systems as a scaling factor combining acoustic and language models. Conventionally, the LMW used for evaluation is selected to be the one yielding the best performance on development set. This method assumes that the data distributions of development and evaluation sets are similar. In this study, we propose an unsupervised LMW selection method based on best path change rate (BPCR). The new method estimates the optimal LMW using only evaluation set. Experimental results on various corpora suggest that BPCR can find the optimal LMW with high precision. The proposed method may be useful in many real world applications such as the fast adaptation of LMW to different domains.
Lenslet Light Field Panorama Creation: A Sub-Aperture Image Stitching Approach

Typically, a single light field camera only captures a limited portion of the visual scene and the rendered views offer low spatial resolution since the full sensor resolution also needs to capture the light arriving to the sensor from multiple directions. However, many applications require a large field of view and higher spatial resolution, which cannot be offered by a single lenslet light field image. In this paper, a lenslet light field panorama creation solution is proposed based on the stitching of the sub-aperture images associated to several lenslet light fields. The proposed approach consists in capturing multiple light fields with a single lenslet camera, which is rotated to capture different scene angles; corresponding sub-aperture images associated with the multiple light field images are then stitched while avoiding misalignments. The created lenslet light field panorama should preserve the directional light information, thus allowing to change a posteriorithe perspective and the objects in focus on a panorama basis.
Modified Shuffled Multi-Population Bat Algorithm

Shuffled Multi-Population Bat algorithm (SMPBat) is a recently proposed hybrid variant of bat algorithm. It incorporates the strengths of two recent variants of bat algorithm-Enhanced Shuffled Bat Algorithm and Bat algorithm with Ring Master-Slave strategy. SMPBat hybridizes the sub-population generation and manipulation mechanism of the two algorithms to device an enhanced variant of BA. There are multiple parameters controlling the flow of execution of SMPBat. These parameters are set at the beginning of the execution of the algorithm. This paper proposes incorporation of multi-parameter setting into SMPBat, where different sub-populations work with different sets of parameter values. Additionally, the impact of a refined search mechanism is also studied. The proposed variants are tested over 20 benchmark functions and a real-world optimization problem. Results establish the robustness of the proposed work.
Dissipated energy minimization for an electro-mechanical elevator of a DC microgrid

This paper extends some previous works on the dissipated energy minimization for an elevator system of a DC microgrid using a combination between differential flatness for the reference generation and predictive control for the reference tracking. The contribution of the present work resides in the validation of constraints at all times thanks to the effective use of B-splines parameterization properties. The proposed improvements are validated through simulation and comparison results for a particular electro-mechanical elevator system.
Algorithms for Access Localization to Objects of Scalable Concurrent Pools Based on Diffracting Trees in Multicore Computer Systems

This work proposes the implementation of scalable concurrent pool based on diffraction trees. Developed pool ensures localization of addresses to shared variables to maximize its throughput. The proposed approaches increase the throughput at high and low workload and provides acceptable level of FIFO/LIFO-order of operation execution and is characterized by low latency of tree traversal. We analyze the efficiency of developed pool. The pool provides large scalability of multithreaded programs compared with similar implementation of pool based on diffraction trees. Developed pools may be applied for producer-consumer model implementation in multithreading programs with constant number of active threads and requirements of high throughput of pools and low latency of operations with pools. Implemented data structure scales well for large number of threads and shows the increase of throughput as the number of threads comes near the number of processor cores. Increasing of tree size in the pool does not reduce the pool throughput. Recommendations for using of pool and the experimental results on multicore computer system are represented in the paper.
Genetics of Cronartium ribicola. IV. Population structure in western North America

Population genetic parameters were estimated for six populations of Cronartium ribicola in western North America from British Columbia to the southern Sierra Nevada, and two outgroups from eastern North America, using isozyme, random amplified polymorphic DNA (RAPD) and restriction fragment length polymorphism (RFLP) markers on cultured haploid clones. Diversity was low, with only 8% polymorphism in the 212 markers identified. Each polymorphic locus had only two alleles, except for an RFLP marker in the ribosomal DNA complex with multiple alleles, that resulted from variable numbers of tandem repeats. Expected heterozygosity within populations, estimated from diploid teliospores, was only 0.025. The three types of markers were highly consistent with each other for these parameters. Yet, populations were highly differentiated; the proportion of the total variation attributable to differences among populations was 0.205. Multivariate statistical analysis as well as different clustering algorithms based on contrasting evolutionary assumptions (drift, mutation) all showed similar relationships and differences among populations. Genetic distances were not associated with geographic distances; western populations within a few kilometres of each other were often more distant from each other genetically than they were from eastern populations across the continent. The lack of pattern over the landscape of this metapopulation is consistent with aspects of the life cycle and epidemiological behavior of the pathogen, in which genetic drift appears to play a major role.
Modified CMOS Peak Detector and Sample Hold Circuit for Biomedical Applications

In this paper a modified peak detector and sample hold (PDSH) circuit is proposed for analog front-end read out chain. This PDSH circuit captures the energy of a sensor output of analog read out chain. The circuit is designed in 180 nm CMOS technology. The proposed PDSH offers wide range (almost 1.8 V of wide input range) of input amplitude (from 0.5 V to 2.3 V) with maximum 10mV offset variation. Peak overshoot error is 0.9 percent for signal with high amplitude. The PDSH block also been modified to decouple the redundancy between slew rate and offset.
Spatial structure of Aspidosperma polyneuron in two semi-deciduous forests in Southeast Brazil

Description of the spatial structure of vegetation is the first step in generating hypotheses regarding underlying processes. It is also important to take into account variation in spatial structure between different localities to be able to distinguish between life history traits and the influence of environment on population processes. Correlogram analysis was used to examine spatial recruitment and mortality patterns of Aspidosperma polyneuron, an emergent tree species, at Reserva Municipal de Santa Genebra (SG), a forest fragment in southeast Brazil. The spatial structure of individuals was compared with two areas with similar physiognomy, one in the same forest and another at Mata do Ribeirao Cachoeira (RC), a semi-deciduous forest located ca. 14 km away. Seed- ling, sapling and adult mortality occurred in clumps, while seedling recruitment occurred mostly in one region of the area. The spatial pattern varied among the three study areas, and the differences were higher between fragments than within SG. The adults showed a negative correlation in space with sap- lings and seedlings in one of the SG areas, which could be a consequence of intraspecific competition, or the influence of density or distance dependent natural enemies. However, this pattern was not observed in the other areas. The results suggest that the mechanisms governing the spatial population dynam- ics of A. polyneuron vary among nearby and similar localities.
Reporting carbon losses from tropical deforestation with Pan-tropical biomass maps

The ‘Reduction of Emissions from deforestation and forest degradation’ (REDD+) activities under the United Nations Framework Convention on Climate Change (UNFCCC) are expected to offer results-based payments to developing countries for reducing greenhouse gas emissions from forested lands. It is necessary to determine reference data on forest carbon losses against which future rates of change can be evaluated, and to have reliable methods for monitoring, reporting and verification of such changes. Advances in satellite remote sensing approaches and techniques for measuring purposes are therefore of tremendous interest. A robust example advancing such approaches, applied on the full tropical belt, is provided in the recent paper of Tyukavina et al 2015 (Environ. Res. Lett. 10 074002). Data and methods are no longer an obstacle to the inclusion of REDD+ in a new climate agreement.