Process Streams Research Articles

Assessing the Environmental Impacts of the Valorization of Creole-Antillean Avocado via an Extractive-Based Biorefinery in the Montes de María Region

In recent years, the environmental evaluation of biorefineries has become critical for ensuring sustainable practices in bio-based production systems. This study focuses on the application of the Waste Reduction (WAR) Algorithm to assess the environmental impacts of an Extractive-based Creole-Antillean Avocado Biorefinery located in Northern Colombia, aimed at producing bio-oil, chlorophyll, and biopesticide from avocado pulp, peel, and seed, respectively. The environmental impacts were evaluated using the WAR algorithm, which quantifies the potential environmental impacts (PEI) of different process streams. The following four scenarios were developed: (1) considering only waste, (2) including waste and products, (3) including waste and energy sources, and (4) incorporating waste, products, and energy consumption. This study analyzed global impacts focusing on atmospheric and toxicological categories, with a detailed assessment of the most critical scenario. The results indicated that Scenario 4 had the highest PEI, particularly in the atmospheric and toxicological categories, driven by emissions of volatile organic compounds (VOCs), greenhouse gases (GHGs), and the presence of heavy metals. However, the avocado biorefinery process demonstrated a net reduction in overall environmental impacts, with negative PEI generation rates across all scenarios, suggesting that the biorefinery transforms high-impact substances into products with lower global impact potential. Energy consumption emerged as a significant contributor to environmental impacts, particularly in acidification potential (AP) and Atmospheric Toxicity Potential (ATP). Using natural gas as an energy source had a relatively lower environmental impact compared to coal and liquid fuels, emphasizing the need to optimize energy use in biorefinery design to improve environmental performance.

Out of Sight, Out of Mind? Neuronal Gamma Oscillations During Occlusion Events in Infants.

Object permanence allows infants to interact successfully with objects in the environment. What happens in the human infant brain when objects move in and out of sight? This study used high-density electroencephalography (hdEEG) to record induced oscillatory brain activities in 29 locomotor infants before, during, and after occlusion of a moving object traveling at different speeds. Temporal spectral evolution (TSE) showed that before and after the occlusion event, event-related synchronized (ERS) brain activity was observed, whereas event-related desynchronized (ERD) activity was detected when the car was hidden behind the occluder. Both synchronized and desynchronized brain activities were found in the gamma frequency band (>30Hz) in visual areas. Coherence connectivity analysis showed significant cluster differences before and during occlusion, during and after occlusion, and before and after occlusion in the gamma (30-150Hz) and theta range (4-7Hz) in several brain sources of interest. It was concluded that locomotor infants between 8.5 and 12 months of age show high-frequency brain oscillations while perceiving a moving object going temporarily out of sight. The significant cluster differences indicate the beginning of specialized connectivity networks, where object permanence is processed within dedicated visual, parietal, and central areas along the dorsal processing stream.

Acetate Shock Loads Enhance CO Uptake Rates of Anaerobic Microbiomes.

Pyrolysis of lignocellulosic biomass commonly produces syngas, a mixture of gases such as CO, CO2 and H2, as well as an aqueous solution generally rich in organic acids such as acetate. In this study, we evaluated the impact of increasing acetate shock loads during syngas co-fermentation with anaerobic microbiomes at different pH levels (6.7 and 5.5) and temperatures (37°C and 55°C) by assessing substrates consumption, metabolites production and microbial community composition. The anaerobic microbiomes revealed to be remarkably resilient and were capable of converting syngas even at high acetate concentrations of up to 64 g/L and pH 5.5. Modifying process parameters and acetate loads resulted in a shift of the product spectrum and microbiota composition. Specifically, a pH of 6.7 promoted methanogens such as Methanosarcina, whereas lowering the pH to 5.5 with lower acetate loads promoted the enrichment of syntrophic acetate oxidisers such as Syntrophaceticus, alongside hydrogenotrophic methanogens. Increasing acetate loads intensified the toxicity of undissociated acetic acid, thereby inhibiting methanogenic activity. Under non-methanogenic conditions, high acetate concentrations suppressed acetogenesis in favour of hydrogenogenesis and the production of various carboxylates, including valerate, with product profiles and production rates being contingent upon temperature. A possible candidate for valerate production was identified in Oscillibacter. Across all tested conditions, acetate supplementation provided additional carbon and energy to the mixed cultures and consistently increased carboxydotrophic conversion rates up to about 20-fold observed at pH 5.5, 55°C and 48 g/L acetate compared to control experiments. Species of Methanobacterium, Methanosarcina and Methanothermobacter may have been involved in CO biomethanation. Under non-methanogenic conditions, the bacterial species responsible for CO conversion remain unclear. These results offer promise for integrating process streams, such as syngas and wastewater, as substrates for mixed culture fermentation allowing for enhanced resource circularity, mitigation of environmental impacts and decreased dependence on fossil fuels.

Tracking cortical entrainment to stages of optic-flow processing

In human visual processing, information from the visual field passes through numerous transformations before perceptual attributes such as motion are derived. Determining the sequence of transforms involved in the perception of visual motion has been an active field since the 1940s. One plausible family of models are the spatiotemporal energy models, based on computations of motion energy computed from the spatiotemporal features the visual field. One of the most venerated is that of Heeger (1988), which hypotheses that motion is estimated by matching the predicted spatiotemporal energy in frequency space. In this study, we investigate the plausibility of Heeger’s model by testing for evidence of cortical entrainment to its components. Entrainment of cortical activity to these components was estimated using measurements of electro- and magnetoencephalographic (EMEG) activity, recorded while healthy subjects watched videos of dots moving left and right across their visual field. We find entrainment to several components of Heeger’s model bilaterally in occipital lobe regions, including representations of motion energy at a latency of 80 ms, overall velocity at 95 ms, and acceleration at 130 ms. We find little evidence of entrainment to displacement. We contrast Heeger’s biologically inspired model with alternative baseline models, finding that Heeger’s model provides a closer fit to the observed data. These results help shed light on the processes through which perception of motion arises in the visual processing stream.

Reexamining the Psychophysical Evidence for the Two Visual Streams

Reexamining the Psychophysical Evidence for the Two Visual Streams

The cell-type underpinnings of the human functional cortical connectome.

The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cerebral cortex. The cortical sheet can be broadly divided into distinct networks, which are embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here using microarray data from the Allen Human Brain Atlas and single-nucleus RNA-sequencing data from multiple cortical territories, we demonstrate that cell-type distributions are spatially coupled to the functional organization of cortex, as estimated through functional magnetic resonance imaging. Differentially enriched cells follow the spatial topography of both functional gradients and associated large-scale networks. Distinct cellular fingerprints were evident across networks, and a classifier trained on postmortem cell-type distributions was able to predict the functional network allegiance of cortical tissue samples. These data indicate that the in vivo organization of the cortical sheet is reflected in the spatial variability of its cellular composition.

Detecting biological motion signals in human and monkey superior colliculus: a subcortical-cortical pathway for biological motion perception.

Most vertebrates, including humans, are highly adept at detecting and encoding biological motion, even when it is portrayed by just a few point lights attached to the head and major joints. However, the function of subcortical regions in biological motion perception has been scarcely explored. Here, we investigate the role of the superior colliculus in local biological motion processing. Using high-field (3 T) and ultra-high-field (7 T) functional magnetic resonance imaging, we record the neural responses of the superior colliculus to scrambled point-light walkers (with local kinematics retained) in both humans and male macaque monkeys. Results show that the superior colliculus, especially the superficial layers, selectively responds to local biological motion. Furthermore, dynamic causal modeling analysis reveals a subcortical-cortical functional pathway that transmits local biological motion signals from the superior colliculus via the middle temporal visual complex to the posterior superior temporal sulcus in the human brain. These findings suggest the existence of a cross-species mechanism in the superior colliculus that facilitates the detection of local biological motion at the early stage of the visual processing stream.

Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies

Systems for graph processing are a key enabler for insights from large-scale graphs that are critical to many new advanced technologies such as Artificial Intelligence, Internet of Things, and blockchain. In this study, we benchmark another two widely utilized graph processing systems, Apache Spark GraphX and Apache Fink, concerning the key performance criterion by means of response time, scalability, and computational complexity. We demonstrate our results which show the capability of each system for real-world graph applications, and hence, providing a quantitative understanding to select the system for our purpose. GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. These performance characteristics emphasize how the capabilities of graph processing systems can match the requirements for the performance of different emerging technology applications. Our findings ultimately inform practitioners about system efficiencies and limitations, but also the recent advances in hardware accelerators and algorithmic improvements aimed at shaping the new graph processing frontier in diverse technology domains.

Spatiotemporal correlates of emotional conflict processing in typically developing adolescents using magnetoencephalography

Brain networks involved in emotional conflict processing have been extensively studied using functional magnetic resonance imaging in adults. Yet, the temporal correlates of these brain activations are still largely unknown, particularly in a key phase of emotional development, adolescence. Here, we elucidate the spatiotemporal profile of emotional conflict processing in 24 typically developing adolescents (10–18 years; 22 Caucasian) during an emotional face-word Stroop task. Using magnetoencephalography (MEG), we calculated dynamic statistical parametric maps and compared trials with and without emotional conflict whole-brain cluster-based permutation tests, followed by cluster-based ROI time-frequency analyses. Cluster analysis revealed four significant clusters, including early activation of the cingulate and temporal cortices, which may be related to dorsal and ventral streams of processing, respectively. This was followed by late components in the middle frontal and prefrontal cortices, which are likely related to response execution and post-response monitoring. Time-frequency analysis revealed event-related synchronizations and desynchronizations in beta and gamma bands across the cingulate cortex, which highlight the different roles of the cingulate subdivisions. Our findings provide further evidence of the cingulate's key role in emotional conflict processing across time. Improving our understanding of this key cognitive process will guide future work with neuropsychiatric populations, which may aid diagnosis and treatment outcomes.

Higher-order cortical and thalamic pathways shape visual processing streams in the mouse cortex.

Mammalian visual functions rely on distributed processing across interconnected cortical and subcortical regions. In higher-order visual areas (HVAs), visual features are processed in specialized streams that integrate feedforward and higher-order inputs from intracortical and thalamocortical pathways. However, the precise circuit organization responsible for HVA specialization remains unclear. We investigated the cellular architecture of primary visual cortex (V1) and higher-order visual pathways in the mouse, focusing on their roles in shaping visual representations. Using invivo functional imaging and neural circuit tracing, we found that HVAs preferentially receive inputs from both V1 and higher-order pathways tuned to similar spatiotemporal properties, with the strongest selectivity seen in layer 2/3 neurons. These neurons exhibit target-specific tuning and sublaminar specificity in their projections, reflecting cell-type-specific visual information flow. In contrast, HVA layer 5 pathways nonspecifically broadcast visual signals across cortical areas, suggesting a role in distributing HVA outputs. Additionally, thalamocortical pathways from the lateral posterior thalamic nucleus (LP) provide highly specific, nearly non-overlapping visual inputs to HVAs, complementing intracortical inputs and contributing to input functional diversity. Our findings suggest that the convergence of laminar and cell-type-specific pathways V1 and higher-order intracortical and thalamocortical pathways plays a key role in shaping the functional specialization and diversity of HVAs.

Zero-shot counting with a dual-stream neural network model.

To understand a visual scene, observers need to both recognize objects and encode relational structure. For example, a scene comprising three apples requires the observer to encode concepts of "apple" and "three." In the primate brain, these functions rely on dual (ventral and dorsal) processing streams. Object recognition in primates has been successfully modeled with deep neural networks, but how scene structure (including numerosity) is encoded remains poorly understood. Here, we built a deep learning model, based on the dual-stream architecture of the primate brain, which is able to count items "zero-shot"-even if the objects themselves are unfamiliar. Our dual-stream network forms spatial response fields and lognormal number codes that resemble those observed in the macaque posterior parietal cortex. The dual-stream network also makes successful predictions about human counting behavior. Our results provide evidence for an enactive theory of the role of the posterior parietal cortex in visual scene understanding.

Artificial intelligence assisted prediction of optimum operating conditions of shell and tube heat exchangers: A grey‐box approach

AbstractIn this study, a Grey‐box (GB) model was developed to predict the optimum mass flow rates of inlet streams of a Shell and Tube Heat Exchanger (STHE) under varying process conditions. Aspen Exchanger Design and Rating (Aspen‐EDR) was initially used to construct a first principle model (FP) of the STHE using industrial data. The Genetic Algorithm (GA) was incorporated into the FP model to attain the minimum exit temperature for the hot kerosene process stream under varying process conditions. A dataset comprised of optimum process conditions was generated through FP‐GA integration and was utilised to develop an Artificial Neural Networks (ANN) model. Subsequently, the ANN model was merged with the FP model by substituting the GA, to form a GB model. The developed GB model, that is, ANN and FP integration, achieved higher effectiveness and lower outlet temperature than those derived through the standalone FP model. Performance of the GB framework was also comparable to the FP‐GA approach but it significantly reduced the computation time required for estimating the optimum process conditions. The proposed GB‐based method improved the STHE's ability to extract energy from the process stream and strengthened its resilience to cope with diverse process conditions.

Neurocognitive dynamics of preparatory and adaptive cognitive control: Insights from mass-univariate and multivariate pattern analysis of EEG data.

Cognitive control refers to humans' ability to willingly align thoughts and actions with internally represented goals. Research indicates that cognitive control is not one-dimensional but rather integrates multiple sub-processes to cope with task demands successfully. In particular, the dynamic interplay between preparatory (i.e., prior to goal-relevant events) and adaptive (i.e., in response to unexpected demands) recruitment of neural resources is believed to facilitate successful behavioural performance. However, whether preparatory and adaptive processes draw from independent or shared neural resources, and how these align in the information processing stream, remains unclear. To address these issues, we recorded electroencephalographic data from 52 subjects while they performed a computerised task. Using a combination of mass-univariate and multivariate pattern analysis procedures, we found that different types of control triggered distinct sequences of brain activation patterns, and that the order and temporal extent of these patterns were dictated by the type of control used by the participants. Stimuli that fostered preparatory recruitment of control evoked a sequence of transient occipital-parietal, sustained central-parietal, and sustained fronto-central responses. In contrast, stimuli that indicated the need for quick behavioural adjustments triggered a sequence of transient occipital-parietal, fronto-central, and central parietal responses. There was also a considerable degree of overlap in the temporal evolution of these brain activation patterns, with behavioural performance being mainly related to the magnitude of the central-parietal and fronto-central responses. Our results demonstrate how different neurocognitive mechanisms, such as early attentional allocation and subsequent behavioural selection processes, are likely to contribute to cognitive control. Moreover, our findings extend prior work by showing that these mechanisms are engaged (at least partly) in parallel, rather than independently of each other.

Insights into Tetravalent Np Speciation in HNO3 through Spectroelectrochemistry and Multivariate Analysis.

In situ optical spectroscopy, spectropotentiometry, and multivariate analysis were applied to the Np(IV) nitrate system to better understand speciation and quantify HNO3 concentration. Thin-layer spectropotentiometry, or spectroelectrochemistry, was leveraged to isolate and stabilize Np(IV) without compromising the solution conditions and generate representative Vis-NIR absorption spectra from 0.5 to 10 M HNO3 and benchmark the corresponding Np(IV) molar absorptivity coefficients. Spectra were described with principal component analysis (PCA) to identify the purest Np(IV) absorbance spectra among other oxidation states [e.g., Np(V/VI)] at each acid concentration and then to identify the primary sources of variance within each Np(IV) spectrum with respect to Np(IV) nitrate complexes. Then, partial least-squares regression (PLSR) and support vector regression (SVR) models were built to predict HNO3 concentration from the Np(IV) spectral data. The nonlinear SVR model outperformed the linear PLSR model for the HNO3 concentration predictions. Finally, the inclusion of spectra collected in edge and center point HNO3 concentrations in the calibration set was determined to be crucial for producing models with strong predictive capabilities. The multivariate approach used in this study makes it possible to quantify HNO3 concentration solely based on Np(IV) absorption spectra, which is essential to quantifying processing streams in various online monitoring applications.

Speech-Processing Network Formation of Cochlear-Implanted Toddlers With Early Hearing Experiences.

To reveal the formation process of speech processing with early hearing experiences, we tracked the development of functional connectivity in the auditory and language-related cortical areas of 84 (36 female) congenitally deafened toddlers using repeated functional near-infrared spectroscopy for up to 36 months post cochlear implantation (CI). Upon hearing restoration, the CI children lacked the modular organization of the mature speech-processing network and demonstrated a higher degree of immaturity in temporo-parietal than temporo-frontal connections. The speech-processing network appeared to form rapidly with early CI experiences, with two-thirds of the developing connections following nonlinear trajectories reflecting possibly more than one synaptogenesis-pruning cycle. A few key features of the mature speech-processing network emerged within the first year of CI hearing, including left-hemispheric advantage, differentiation of the dorsal and ventral processing streams, and functional state (speech listening vs. resting) specific patterns of connectivity development. The developmental changes were predictable of future auditory and verbal communication skills of the CI children, with prominent contribution from temporo-parietal connections in the dorsal stream, suggesting a mediating role of speech-processing network formation with early hearing experiences in speech acquisition.

Determination of trace uranium concentrations in spent‐fuel reprocessing using online graphite crystal pre‐diffraction energy‐dispersive x‐ray fluorescence

AbstractAn online graphite crystal pre‐diffraction x‐ray fluorescence technique was developed for accurate real‐time detection of trace uranium concentrations in spent‐fuel reprocessing streams. Online analysis for determining uranium concentrations was established. The device was equipped with measurement windows in both the flow cell and a side wall of the glove box. X‐ray tubes and detectors were arranged outside the glove box, and the process stream flowing through the flow cell was measured through the measurement window. A cylindrical highly oriented pyrolytic graphite crystal was located in front of the detector to improve detection efficiency and to provide monochromatic uranium‐characteristic x‐rays. At the same time, the device could perform remote online automatic calibration. The uranium detection limit in a kerosene solution was 0.08 mg/L, and the quantitative limit was 0.27 mg/L. The detection limit in a nitric acid solution was 0.11 mg/L, and the quantitative limit was 0.37 mg/L. The relative standard deviation of measuring 0.5 mg/L uranium was less than 10%, which greatly improved online monitoring of trace uranium in spent‐fuel reprocessing samples.

Effective removal of Calcium and Magnesium Ions from boiler feed Water using Polyacrylonitrile supported titanium tungstovanadate composite ion exchange nanofiber

<p><em><strong>​​​​​​</strong></em><span style="font-family:"Times New Roman","serif";font-size:12.0pt;line-height:150%;">The challenge posed by the presence of calcium ions (Ca<sup>2+</sup>) in process streams is attributed to its adverse effects on the heat transfer efficiency of process equipment. In this study, a novel electrospun nanofibrous composite was synthesized by combining polyacrylonitrile (PAN) with well-dispersed Titanium tungestovanadate (TWV) cation exchanger. Homogeneous precipitation technique was employed to synthesize nano-titanium (IV) tungstovanadate (TWV) cation exchanger. Various synthesis parameters, including reactant volume ratio, amount of precipitating agent and reaction temperature, were optimized to achieve the highest ion exchange capacity (IEC). The prepared ion exchange material exhibited an ion exchange capacity (IEC) of 2.39 meq.g<sup>-1</sup> for Na<sup>+</sup> ions. The incorporation of the prepared nanoparticles into nanofibers conferred the sorption capabilities of the composite. The nanofibers' morphologies and structures were analyzed using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Batch sorption experiments were carried out to investigate the sorption properties. Controlled experiments were conducted to investigate the impact of various factors, including solution pH, temperature, dosage, contact time, and the initial concentration of the hard water. The results indicated that the optimum adsorption conditions that gave the highest percentage of removal 99%, 98% for Ca<sup>2+</sup> and Mg<sup>2+</sup>  ions respectively were 50 mg of adsorbent dosage, 500 ppm of Ca<sup>2+</sup> and Mg<sup>2+</sup>  solution =7, and a contact time of 30 min at room temperature .The  kinetic data were fitted to pseudo second order model. Furthermore, the thermodynamic study suggested that the adsorption on PAN/TWV NF was endothermic and spontaneous.</span></p>

Biotransformation of insect processing residues: Production of lactic acid bacterial biomass and associated partial removal of proteins from chitin

Processing of edible insects typically involves fractionating into high-value food ingredients, which results in by-products containing chitin and insoluble proteins. This study examined the effectiveness of lactic acid bacteria (LAB) in removing proteins from chitin in insect processing residues. Lesser mealworm processing residues were biologically treated for 48 and 120 h using LAB strains without added carbon sources. Results showed partial deproteinization, up to 29 % with Levilactobacillus brevis after 120 h. Most LAB grew up to 2 log10 colony-forming units/mL in the first 48 h. Confocal microscopy and Fourier-transform infrared spectra indicated that some protein remained attached to chitin. The molecular weight of solubilized proteins was affected by strain and time of incubation, with antioxidant activity increasing significantly after 120 h with Lacticaseibacillus paracasei. The biological treatment of insect processing streams can be a sustainable approach to producing high amounts of LAB biomass with subsequent protein solubilization and chitin release.

What Is Faster than Where in Vocal Emotional Perception.

Voices carry a vast amount of information about speakers (e.g., emotional state; spatial location). Neuroimaging studies postulate that spatial ("where") and emotional ("what") cues are processed by partially independent processing streams. Although behavioral evidence reveals interactions between emotion and space, the temporal dynamics of these processes in the brain and its modulation by attention remain unknown. We investigated whether and how spatial and emotional features interact during voice processing as a function of attention focus. Spatialized nonverbal vocalizations differing in valence (neutral, amusement, anger) were presented at different locations around the head, whereas listeners discriminated either the spatial location or emotional quality of the voice. Neural activity was measured with ERPs of the EEG. Affective ratings were collected at the end of the EEG session. Emotional vocalizations elicited decreased N1 but increased P2 and late positive potential amplitudes. Interactions of space and emotion occurred at the salience detection stage: neutral vocalizations presented at right (vs. left) locations elicited increased P2 amplitudes, but no such differences were observed for emotional vocalizations. When task instructions involved emotion categorization, the P2 was increased for vocalizations presented at front (vs. back) locations. Behaviorally, only valence and arousal ratings showed emotion-space interactions. These findings suggest that emotional representations are activated earlier than spatial representations in voice processing. The perceptual prioritization of emotional cues occurred irrespective of task instructions but was not paralleled by an augmented stimulus representation in space. These findings support the differential responding to emotional information by auditory processing pathways.

Continental-scale insights into the sugarbeet diffusion juice microbiomes.

Bacterial contamination of raw diffusion juice poses unique challenges during the sugar extraction process. This study profiled bacterial communities by using full-length 16S rRNA amplicon sequencing and quantified the carbohydrate concentrations in raw diffusion juice samples received from sugar factory regions across the USA and Canada. Juice samples were collected at four time points during the 2021 and 2022 processing campaigns. Firmicutes was the dominant phylum from the raw diffusion juice samples collected during both campaigns and comprised 85.5% of total bacterial abundance. Lactic acid bacteria such as Leuconostoc and Lactobacillus were among the core genera which also dominated the bacterial community in raw diffusion juice. Positive correlations in the abundance of functionally and taxonomically related bacterial communities were identified. During the 2021 campaign, 44 bacterial genera were differentially abundant in raw diffusion juice extracted from sugarbeet roots in Periods 1 to 4. This number declined sixfold during the 2022 campaign to three genera. The concentration of raffinose in raw diffusion juice positively correlated to the relative abundance of Leuconostoc. Furthermore, an in vitro assay was performed to assess the growth dynamics of Leuconostoc mesenteroides in sucrose or raffinose-rich medium and observed the rapid consumption of both carbohydrates by this bacterium. This finding is important for deciphering microbial growth dynamics in raw diffusion juice that can be useful in minimizing sugar loss during the factory processing.IMPORTANCEFindings additionally provide baseline information that can be used to develop mitigation strategies that reduce losses due to microbial contamination of sucrose processing streams.