Miracle-dz/UniFAR-FTUs huggingface dataset:
Corrosion Rate Prediction in Oil and Gas Pipelines Based on Multiphase Flow Modelling

Corrosion has severe consequences for the integrity of pipelines used in the petroleum industry. Modelling and optimising the parameters of a circulating fluid are two of the numerous methods for combating corrosion. The objective of this study was to develop a multiphase flow simulation model for estimating the corrosion rate of oil and gas pipelines, considering the erosional effect. In addition to carbon dioxide (CO2) and hydrogen sulphide (H2S) corrosion, the present model also takes into account the impacts of chloride concentrations. The current model evaluates and reflects a comprehensive understanding of corrosion in a saline environment, making it readily applicable for estimating corrosion rates for industrial applications. The model's results indicate a prediction accuracy of about 85%. Field data gathered under a broad range of environmental conditions confirms the model's prediction accuracy. The predictions from the present model are in good agreement with the field data. In addition, the present model was found to be more effective than the model created by Dewaard and Milliam. This research is likely to have widespread applications in the oil and gas industry for predicting more accurate corrosion rates.
Characterization of Coffee-Pulp Biochar as an Additive to Enhance Biogas Production from Coffee Mucilage

Biogas has been effectively produced from solid as well as liquid biomass waste through anaerobic digestion (AD). It has been proved that AD is the most efficient technology and less environmental effect in converting biomass to biogas. However, it is challenging that the rate of biogas production might slow down by many factors. It requires continues research in order to overcome the problem, such as by adding an additive. The use of several additives for AD has received great attention due to the positive influence in improving the production performance of biogas in terms of process stability and efficiency, and production capacity. Among all types of additives, carbon material in the form of bio-char has been considered as the most profitable due to low cost and easy to produce from various carbon source materials. This study aimed to determine the characteristics of coffee pulp bio-char which will be used as an additive in biogas production from coffee mucilage by the AD method. Coffee pulp biomass and coffee mucilage were obtained from Aceh Tengah, Indonesia. Preparation of bio-char was carried out by washing and soaking of the coffee pulp with tap water for 24 hours, then drying under the sun for three days. Carbonization of dried coffee pulp was then performed using a pilot plant-scale pyrolysis reactor at temperature of 400 °C for 60 minutes. Resulting biochar was then ground and sieved to 60 mesh size. Based on to proximate analysis result, it was found that the moisture, ash, volatile matter, and fixed carbon contents were respectively 1.98%, 11.93%, 42.36%, and 43.72%. N2-physisorption analysis of coffee-pulp bio-char suggested pore volume of 0.21 cm3/g. From BET calculation method it was found that the surface area was 224.1 m²/g. This high surface area is beneficial for providing sheltered spaces for microbes to attach and hindering them against metabolic inhibitors. The effect of adding biochar additives from coffee skin waste in the anaerobic digestion process of coffee mucilage waste provides significant results on the yield of biogas products. The yield of biogas products increased by 225% with the addition of 15 gr/L of biochar coffee pulp.
The Forum Factor: Exploring the Link between Online Discourse and Student Achievement in Higher Education

The growth of digital education has expanded the use of online forums like Piazza. However, their impact on academic achievement is still being determined. This study investigates the relationship between Piazza engagement and academic performance in computer science. We explored four hypotheses: Piazza activity rates, endorsements, post frequency on assessments, and pre-assessment viewing habits. Data analysis from an extensive programming course showed that active Piazza users and endorsed students performed significantly better academically. While the number of posts related to assessments was generally not correlated with performance, students who viewed more posts about an assessment within a week of its due date tended to perform better.
Distributional Learning for Network Alignment with Global Constraints

Network alignment, pairing corresponding nodes across the source and target networks, plays an important role in many data mining tasks. Extensive studies focus on learning node embeddings across different networks in a unified space. However, these methods have not taken the large structural discrepancy between aligned nodes into account, and thus is largely confined by the deterministic representations of nodes. In this work, we propose a novel network alignment framework highlighted by distributional learning and globally optimal alignment. By modeling the uncertainty of each node by Gaussian distribution, our framework builds similarity matrices on the Wasserstein distance between distributions, and applies Sinkhorn operation which learns the globally optimal mapping in an end-to-end fashion. We show that each integrated part of the framework contributes to the overall performance. Under a variety of experimental settings, our alignment framework shows superior accuracy and efficiency to the state-of-the-art.
In vivo optimized three-photon imaging of intact mouse tibia links plasma cell motility to functional states in the bone marrow

Intravital multi-photon imaging of the bone marrow is crucial to the study of cellular dynamics, communication with the microenvironment and functions, however, imaging of deep tissue areas is challenging and minimally invasive methods for deep-marrow imaging in intact long bones are needed. We developed a high pulse energy 1650 nm laser prototype, which permits to surpass >100 µm thick cortical bone and to perform three-photon microscopy (3PM) in more than 400 µm depth in the marrow cavity of intact mouse tibia in vivo. Its unique 3 and 4 MHz laser repetition rates allowed us to analyze motility patterns of rare cells over large fields of view deep within the unperturbed marrow. In this way, we found a bi-modal migratory behavior of marrow plasma cells. Besides, the analysis of third harmonics generation (THG) in the tibia identified this signal to be a label-free indicator of the abundance of cellular organelles, in particular the endoplasmic reticulum, reflecting protein biosynthesis capacity. We found that only one third of the plasma cells in the tibia marrow of adult mice have a strong THG signal and, thus, a high protein synthesis capacity, while the other two thirds of plasma cells display a low THG signal. Finally, we identified an inverse link between migratory behavior and THG signal strength in marrow plasma cells. As in these cells, the protein biosynthesis capacity indicated by a strong THG signal is mainly associated with antibody secretion, we could relate motility to functional states of plasma cells in vivo. Our 3PM method retains the ability to connect cellular dynamics to protein biosynthesis capacity in various marrow cell types beyond plasma cells, as THG is a ubiquitous signal, opening new perspectives on understanding how tissue microenvironment impacts on cellular functions in the bone marrow.
The synergy of inventor cooperative network dual embeddedness and firm innovation: the mediating role of ambidextrous learning

ABSTRACT Dual embeddedness of inventors’ cooperative networks influences firm innovation. This paper explores the mechanism of synergy between network structural embeddedness (network centrality and structural hole) and relational embeddedness (relational strength) on firm innovation using data from Chinese listed automobile companies. This paper further explores the mediating role of exploitative learning and exploratory learning between the synergy of cooperative network dual embeddedness and innovation. The results show that the synergy of network centrality and relational strength hinders innovation, while the synergy of the structural hole and relational strength promotes innovation. The synergy of centrality and relational strength hinders exploitative learning, while the synergy of the structural hole and relational strength promotes exploitative learning. Exploitative learning plays a mediating role between synergy of structure and relational embeddedness and innovation.
Locus Coeruleus Norepinephrine Neurons Facilitate Orbitofrontal Cortex Remapping and Behavioral Flexibility

To guide behavior, brain regions such as the orbitofrontal cortex (OFC) retain complex information about current tasks and expected outcomes in cellular representations referred to as cognitive maps. When actions produce undesirable results, OFC cognitive maps must update to promote behavioral change. Here, we show that this remapping is driven by the locus coeruleus (LC), a small brainstem nucleus that contains most of the brain’s norepinephrine (NE)-releasing neurons. In a task that tests behavioral flexibility in rodents, LC-NE activity correlated with task acuity and altered depending on trial outcome. Silencing LC neurons caused perseverative behavior and impeded cognitive remapping in OFC, while enhancing LC activity disrupted the ability of new maps to stabilize. These findings reveal a novel role for bidirectional LC-NE signaling in regulation of OFC cognitive map stability and promotion of flexible behavior that differs from the traditional function of this circuit as a global arousal signal.
Methods for assessing bee foraging preferences: a short review and a new automated apparatus

Bees are essential pollinators for many plant species, but multiple threats exist to both managed and wild bee populations. Their innate foraging behaviors and food preferences are subjects of intense research since bee nutrition is essential for maintaining hive and colony health. Multiple approaches have been developed to assess bee foraging behavior and associated preferences, but they are often labor-intensive and provide data on a limited number of parameters. In this manuscript, we provide a short review of these methods and present the design, build, and implementation of a new, inexpensive, and automated feeding apparatus capable of recording: (1) number of visits, (2) total food consumed, (3) photos and videos of bee behavior while inside of the feeder, and (4) environmental conditions. The efficacy of this apparatus is demonstrated through preference tests with artificial nectars, while also acknowledging the relative strengths and limitations of this approach.
Risk attitude toward epidemic and impulsive travel intention: influences on perceived helpfulness of online review

ABSTRACT To comprehend the unclear mechanisms through which risk attitude toward epidemics affects perceived helpfulness of online review, this study proposes a theoretical framework based on Dual Process Theory and Construal Level Theory to observe the mechanisms. Through empirical analysis based on 456 valid questionnaires, from review readers’ information processing manner perspective, risk-averse tourists prefer a systematic manner, whereas risk-appetite ones prefer heuristics manner, which leads to significantly higher perceived helpfulness for risk-averse than for risk-appetite ones. The mechanisms through which risk attitude directly negatively affects perceived helpfulness and also indirectly attenuates perceived helpfulness through inhibiting impulsive travel intention also are unveiled. As well as the moderating effects of two temporal distances that are defined as recovering from epidemic infection and near-future travel plans are underscored. These results indicate that risk attitude and impulsive travel intention are both antecedents of perceived helpfulness and provide new theoretical insights and feasible practical implications.
Characterizing the viscoelastic properties of different fibroblasts in 2D and 3D collagen gels

We assessed cell mechanical properties in both 2D and 3D environments employing compliant type I collagen matrices. Firstly, collagen gels of varying stiffness were prepared using a photocrosslinker to increase gel stiffness. Using methacrylic anhydride and UV light, a 10-fold increase in apparent Young’s modulus with respect to the soft collagen gel was achieved (0.2 kPa to 2 kPa). In addition, cells were plated onto the different collagen gels and hard Petri dishes (as a super stiff substrate) and their mechanical properties were evaluated. An increase in apparent Young’s modulus was observed in Dupuytren fibroblasts behavior when increasing substrate stiffness, supporting its myofibroblast phenotype (3.8 kPa to 5.2 kPa from soft collagen gels to hard Petri dishes). Secondly, gel’s mechanics, in which fibroblasts were embedded, were evaluated over time to assess cells contraction properties. Gel’s apparent Young’s modulus increased over time regardless of fibroblasts type and cells presented dendritic protrusions. Rheological properties of both cells and gels were extracted using AFM sweep frequency scheme and power law structural damping model for data analysis. As a summary, we have found that fibroblasts contractile properties, related to myofibroblast differentiation and development are highly influenced on the mechanical properties of the surrounding environment, being stiffer environments those that favor the increase in fibroblast mechanical tension.
Benchmarking the identification of a single degraded protein to explore optimal search strategies for ancient proteins

Palaeoproteomics is a rapidly evolving discipline, and practitioners are constantly developing novel strategies for the analyses and interpretations of complex, degraded protein mixtures. The community has also established standards of good practice to interrogate our data. However, there is a lack of a systematic exploration of how these affect the identification of peptides, post-translational modifications (PTMs) and protein and their significance (through the False Discovery Rate) and correctness. We systematically investigated the performance of a wide range of sequencing tools and search engines in a controlled system: the experimental degradation of the single purified bovine β-lactoglobulin (BLG), heated at 95 °C and pH 7 for 0, 4 and 128 days. We target BLG since it is one of the most robust and ubiquitous proteins in the archaeological record. We tested different reference database choices, a targeted dairy protein one, and whole bovine proteome and three digestion options (tryptic-, semi-tryptic- and non-specific searches), in order to evaluate the effects of search space and the identification of peptides. We also explored alternative strategies, including open search that allows for the global identification of PTMs based upon wide precursor mass tolerance and de novo sequencing to boost sequence coverage. We analysed the samples using Mascot, MaxQuant, Metamorpheus, pFind, Fragpipe and DeNovoGUI (pepNovo, DirecTag, Novor), and we benchmarked these tools and discussed the optimal strategy for the characterisation of ancient proteins.
A Mechanistic Model for the Release of Ceramide from the CERT START Domain

Ceramide transfer protein CERT is the mediator of non-vesicular transfer of ceramide from ER to Golgi. In CERT, START is the domain responsible for the binding and transport of ceramide. A wealth of structural data has revealed a helix-grip fold surrounding a large hydrophobic holding the ceramide. Yet little is known about the mechanisms by which START releases the ceramide through the polar region and into the packed environment of cellular membranes. As such events do not lend themselves easily to experimental investigations we used multiple unbiased microsecond-long molecular simulations. We propose a membrane-assisted mechanism in which the passage of the ceramide acyl chains is facilitated by the intercalation of a single phosphatidylcholine lipid in the cavity, practically greasing the ceramide way out. We verify using experimental lipidomics data that CERT forms stable complexes with phosphatidylcholine lipids, in addition to ceramide, thus providing a validation for the proposed computational model.
ZVAX - A Microservice Reference Architecture for Nation-Scale Pandemic Management

Domain-specific Microservice Reference Architectures (MSRA) have become relevant study objects in software technology. They facilitate the technical evaluation of service designs, compositions patterns and deployment configurations in realistic operational practice. Current knowledge about MSRA is predominantly confined to business domains with modest numbers of users per application. Due to the ongoing massive digital transformation of society, people-related online services in e-government, e-health and similar domains must be designed to be highly scalable at entire nation level at affordable infrastructure cost. With ZVAX, we present such a service in the e-health domain. Specifically, the ZVAX implementation adheres to an MSRA for pandemic-related processes such as vaccination registration and passenger locator form submission, with emphasis on selectable levels of privacy. We argue that ZVAX is valuable as study object for the training of software engineers and for the debate on arbitrary government-to-people services at scale. 2012 ACM Subject Classification Computing methodologies → Distributed computing methodologies
The α/β hydrolase domain-containing protein 1 (ABHD1) acts as a lysolipid lipase and is involved in lipid droplet formation

Lipid droplets (LDs) are the major sites of lipid and energy homeostasis. However, few LD biogenesis proteins have been identified. Here, using Chlamydomonas as a model, we show that ABHD1, a member of the α/β hydrolase domain-containing protein family, is a novel type of LD-associated protein which stimulates LD formation through two distinct actions on the LD surface, one enzymatic and the other structural. ABHD1 was localized to LD surface in Chlamydomonas cells. The knockout mutants contained similar amounts of triacylglycerols (TAG) but their LDs showed an increased content in lyso- derivatives of the betaine lipid diacylglyceryl-N,N,N-trimethylhomoserine (DGTS). Over-expression of ABHD1 in Chlamydomonas induced LD formation and boosted TAG content, suggesting a key role in LD biogenesis. The purified recombinant ABHD1 protein hydrolyzed lyso-DGTS, producing a free fatty acid and a glyceryltrimethylhomoserine moiety. In vitro experiments using droplet- embedded vesicles showed that ABHD1 promoted LD emergence. Taken together, these results identify ABHD1 as a new player in LD formation by its lipase activity on lyso-DGTS and by its distinct biophysical property. This study further suggests that lipases targeted to LDs and able to act on their polar lipid coat may be interesting tools to promote LD assembly in eukaryotic cells. Significant statement Lipid droplets are subcellular organelles specialized for triacylglycerol storage. Their dynamic turnover is key to managing energy homeostasis in response to cell cycle states and environmental cues. To gain insights into LD biogenesis, we characterized a putative α/β- hydrolase (ABHD1) in the model algae Chlamydomonas reinhardtii and show it is located at the LD surface. We found that ABHD1 overexpression promotes LD formation and acts as a lipase mainly on lyso derivatives of the betaine lipid diacylglyceryl-N,N,N-trimethylhomoserine (DGTS), the major lipid constituent of the LD hemi-membrane. We also show that ABHD1 has a remarkable biophysical property favoring LD budding. This work thus identifies a novel type of lipase acting on betaine lipid and provides a first example of a protein with a dual function nvolved in LD formation.
The prevalence, uses and cultural assimilation of shrub and tree invasive alien plants in a biodiversity hotspot along the Wild Coast, South Africa

ABSTRACT Invasive alien plant species (IAPS) frequently offer both ecosystem services and disservices to rural communities with high livelihood dependency on local landscapes. However, biocultural relationships with IAPS may go deeper than just provisioning uses, as they may be assimilated into local belief systems manifest in them becoming embedded in cultural constructions such as naming, stories, songs and ceremonies. It is likely that IAPS that are culturally assimilated will represent a greater conflict of interest in the face of proposed controls of IAPS in biodiversity hotspots where conservation priorities are frequently deemed paramount by external agencies. Using a mixed-methods approach we undertook roadside surveys of 17 selected IAPS along the 250 km Wild Coast section of the Maputaland-Pondoland-Albany biodiversity hotspot, accompanied by questionnaire interviews with 48 local people. The mean number of IAPS per site was four, ranging from zero (only one site) to ten, and local inhabitants deemed the abundance of all but one of the species to be increasing. All species had been in the region for decades, had a vernacular name, and all but one had direct consumptive uses. Species with multiple uses were more widely recognised. However, there was only marginal incorporation of the IAPS into stories, songs and ceremonies, although medicinal uses of some IAPS were for cultural/spiritual needs rather than physical ailments per se. These results show that despite widespread use, there was as yet relatively limited cultural assimilation of the IAPS in the Wild Coast region.
Neuronal Avalanches in Naturalistic Speech and Music Listening

Neuronal avalanches are cascade-like events ubiquitously observed across imaging modalities and scales. Aperiodic timing and topographic distribution of these events have been related to the systemic physiology of brain states. However, it is still unknown whether neuronal avalanches are correlates of cognition, or purely reflect physiological properties. In this work, we investigate this question by analyzing intracranial recordings of epileptic participants during rest and passive listening of naturalistic speech and music stimuli. During speech or music listening, but not rest, participants’ brains “tick” together, as the timing of neuronal avalanches is stimulus-driven and hence correlated across participants. Auditory regions are strongly participating in coordinated neuronal avalanches, but also associative regions, indicating both the specificity and distributivity of cognitive processing. The subnetworks where such processing takes place during speech and music largely overlap, especially in auditory regions, but also diverge in associative cortical sites. Finally, differential pathways of avalanche propagation across auditory and non-auditory regions differentiate brain network dynamics during speech, music and rest. Overall, these results highlight the potential of neuronal avalanches as a neural index of cognition. Author’s summary Neuronal avalanches consist of collective network events propagating across the brain in short-lived and aperiodic instances. These salient events have garnered a great interest for studying the physics of cortical dynamics, and bear potential for studying brain data also in purely neuroscientific contexts. In this work we investigated neuronal avalanches to index cognition, analyzing an intracranial stereo electroencephalography (iEEG) dataset during speech, music listening and resting state in epileptic patients. We show that neuronal avalanches are consistently driven by music and speech stimuli: avalanches co-occur in participants listening to the same auditory stimulus; avalanche topography differs from resting state, presenting partial similarities during speech and music; avalanche propagation changes during speech, music, and rest conditions, especially along the pathways between auditory and non auditory regions. Our work underlines the distributed nature of auditory stimulus processing, supporting neuronal avalanches as a valuable and computationally advantageous framework for the study of cognition in humans.