Small Amounts Research Articles

A Learning-Based Account of Phonological Tiers

Abstract Morphophonological alternations often involve dependencies between adjacent segments. Despite the apparent distance between relevant segments in the alternations that arise in consonant and vowel harmony, these dependencies can usually be viewed as adjacent on a tier representation. However, the tier needed to render dependencies adjacent varies crosslinguistically, and the abstract nature of tier representations in comparison to flat, string-like representations has led phonologists to seek justification for their use in phonological theory. In this paper, I propose a learning-based account of tier-like representations. I argue that humans show a proclivity for tracking dependencies between adjacent items, and propose a simple learning algorithm that incorporates this proclivity by tracking only adjacent dependencies. The model changes representations in response to being unable to predict the surface form of alternating segments—a decision governed by the Tolerance Principle, which allows for learning despite the sparsity and exceptions inevitable in naturalistic data. Tier-like representations naturally emerge from this learning procedure, and, when trained on small amounts of natural language data, the model achieves high accuracy generalizing to held-out test words, while flexibly handling cross-linguistic complexities like neutral segments and blockers. The model also makes precise predictions about human generalization behavior, and these are consistently borne out in artificial language experiments.

Sedimentological and geochemical evaluation of sandstones of the Ilaro formation, Dahomey Basin, Southwestern Nigeria : Insights into paleoenvironments, provenance, and tectonic settings

Grain size analysis, geochemistry, and petrography of sandstones of the Ilaro Formation exposed at the Ajegunle area were investigated to infer provenance, transportation history, tectonic setting, paleoenvironment, and degree of palaeoweathering of the sediments. Selected sandstones were analyzed, and the major, trace, and rare earth elements were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Results from the granulometric analysis showed that sandstones were deposited in fluvial conditions. The sandstones exhibit a coarse-grained texture, displaying poor sorting and being texturally immature. The petrographic analysis indicated that quartz was predominant, whereas opaque minerals, muscovite, and ferruginous ground mass were present in smaller quantities. The sandstones can be geochemically classified as arkose and subarenite. The sandstones have an average composition of SiO2 (82.87%) and Al2O3 (9.49%), while K2O, Na2O, MgO, CaO, and P2O5 have <1% each. The elevated Al2O3 content is associated with the lithic fragment composition, whereas the low concentrations of MgO (mean 0.03%), Na2O (mean 0.008%), and K2O (mean 0.04%) suggest chemical destruction in an oxidizing environment. The angularity of the grains indicated a short transportation history very close to the provenance. Bivariate and discriminant plots from major elements and trace elements suggest the sandstones were non-marine and sourced from intermediate rocks. The sandstones were deposited in an oxic-dyoxic condition under a humid climate and passive or active continental margins. The average values of the weathering indices indicate an intense degree of chemical weathering.

THE EFFECT OF BARIUM SUBSTITUTION WITH COMBINATIONS OF RARE EARTH ON PERMANENT MAGNETIC SURFACE MORPHOLOGY BASED ON BARIUM HEXAFERRITE

The development of hard magnets today is progressing very rapidly. Developing hard magnets based on rare earth metals becomes a severe problem when the raw materials are not readily available. The chosen solution is to replace oxide-based permanent magnets with small amounts of rare earth metals substituted to improve their magnetic properties. This study synthesized a permanent magnet oxide based on barium hexaferrite doped with lanthanum and cerium atoms. In the synthesis of this material, a mechanical wet milling technique is used to obtain a single-phase permanent magnetic Ba1-β-γLaβCeγFe12O19 system with composition (β = 0 - 0.5 and γ = 0 - 0.1). The precursors are weighted according to their stoichiometric composition. Each mixed composition was milled by high energy milling (PW 1000 in the mixer/mill) at a milling speed of 1000 rpm using steel balls with an average diameter of 12 mm. Grinding conditions included a ball-to-powder weight ratio of 2:1, milling time 5 hours, then compacted with 7000 Psi pressure and sintered at 1200oC for 2 hours. The surface morphology and microstructure of the resulting sample particles were observed using scanning electron microscopy (SEM) with the SEM JEOL JED 305 brand. The characterization results show that the particles are hexagonally homogeneous in shape with particle sizes in the range of 1000-2000 nm for β = 0 and γ = 0 (without doping). In general, the four samples with varying concentrations of doping ions La3+ and Ce4+ showed homogeneous hexagonal structures but smaller particle sizes than pure barium hexaferrite. The sample particle sizes ranged from 500-1000 nm for β = 0.02 and 300-1000 nm for β = 0.04.

Integration of Mechatronic Functions on Additively Manufactured Components via Laser‐Assisted Selective Metal Deposition

AbstractThe current industrial revolution derives much of its momentum from value creation based on interconnected products and related data based services. Such products must fulfill both mechanical and electrical requirements, making them mechatronic systems. The production of such systems via additive manufacturing (AM) processes offers advantages in achievable complexity, reduction of the amount of individual components, and cost‐effective as well as sustaina ble production of small quantities. In this work, a process chain is presented that allows for refining additively manufactured 3D structures made from industry‐standard materials into mechatronic components by creating electrically conductive structures directly on their surfaces. The process chain is based on masking the component's surface and selectively removing the masking according to the circuit geometry using laser radiation. In a wet–chemical bath process, the surface is then exposed to palladium nuclei, the masking is fully removed and metal layers (copper/nickel/gold) are deposited by electroless plating. The procedure is developed using stereolithography as a model process for AM and transferred to four additional AM methods. In all cases, despite markedly different surface properties, good selectivity of metal deposition is observed as well as adhesion strength and conductivity comparable to industrially common injection‐molded laser direct structured mechatronic interconnect devices.

Determination of the Absolute Configuration of Secondary Alcohols in a Compound Mixture via the Application of Competing Enantioselective Acylation Coupled with LC/MS Analysis.

The determination of natural product stereochemistry plays a significant role in drug discovery and development. Understanding the stereochemistry of natural products is essential for predicting and optimizing their interactions with biological targets, which, in turn, influences their therapeutic efficacy, safety, and overall impact on living organisms. Here, we present the first application of competitive enantioselective acylation (CEA) reactions in conjunction with LC/MS analysis for determining the absolute configuration of secondary alcohols in natural products which were purified as a mixture. This approach utilizes the enantiomeric pair of HBTM (homobenzotetramisole) catalysts, demonstrating sufficient kinetic resolution for the acylation of secondary alcohols. The rapid reaction kinetics were quantitatively estimated with LC/MS analysis as the characterization technique for the enantioselective transformations. Our study has expanded the application of the CEA reaction coupled with LC/MS analysis to mixtures. Utilizing LC/MS analysis, the CEA reaction offers a sensitive and simple method for stereochemistry determination. Additionally, the application of the CEA reaction is cost/time-effective since only small quantities of substrates and a short reaction time are required for characterizing the absolute configuration of secondary alcohols in natural products compared to other conventional methods.

Fundamental Experiment and Numerical Simulation of Ne/Xe Plasma Magnetohydrodynamic Electrical Power Generation

We conducted experiments in a shock-tube facility to test magnetohydrodynamic (MHD) electrical power generation with Xe-seeded Ne plasma. The performance and plasma behavior of the experimental generator were examined using time-dependent r-θ two-dimensional numerical simulations. In the experiment, an enthalpy extraction ratio of about 5.0% was obtained using a disk-shaped MHD generator with radio frequency pre-ionization. The numerical simulations show that the enthalpy extraction ratio is improved by adding small amounts of Xe to Ne, but also that adding excessive amounts of Xe deteriorates the generator performance. When an appropriate inlet electron temperature is assumed in the simulations, 5900–6450 K (inlet ionization degree of 0.25×10−4–0.72×10−4) for a seed fraction (mole % of Xe) of 0.1%, 6050–6280 K (1.08×10−4–1.70×10−4) for a seed fraction of 1.0%, and 5750–5950 K (1.27×10−4–1.97×10−4) for a seed fraction of 5.0%, the plasma structure almost becomes similar to the nonuniform plasma structure observed in the experiment, as too does the enthalpy extraction ratio. The simulations suggest that achieving an inlet ionization degree above 5–6×10−4 when using Ne/Xe with a seed fraction of 0.1–1.0% as the working gas should enable an enthalpy extraction ratio above 20%, which is expected to surpass that for pure Ar.

Influence of graphene-based nanostructures processing routes and aspect ratio in flexural strength and fracture mechanisms of 3Y-TZP-matrix composites

In this work, the influence of the aspect ratio of graphene-based nanostructures (GBNs) and content on the mechanical properties of 3 mol% yttria tetragonal zirconia polycrystalline 3Y-TZP matrix composites was analysed. The influence of the dispersion method and sintering parameters on the flexural strength and elastic modulus of the composites was studied, and the fracture surfaces were characterized to determine the fracture mechanisms that occur. The results showed that small amounts of exfoliated graphene nanoplatelets, with reduced lateral size, and few layer graphene, up to 1.0 and 2.5 vol%, respectively, slightly increase the 3Y-TZP flexural strength. This has been attributed to the tortuosity of the crack propagation pathways and strengthening mechanisms. Higher contents cause a decrease in flexural strength and stiffness because of overlapped GBNs, which can promote the crack propagation. The pull-out of GBN was more significant in composites with non-exfoliated graphene nanoplatelets, where no increase on the flexural or biaxial strength was measured.

Microscale Thermophoresis Analysis of Membrane Proteins

Microscale Thermophoresis Analysis of Membrane Proteins

L-Mn dielectronic recombination of cerium ions in a room-temperature EBIT

We explore the dielectronic recombination structures at the electron beam ion trap at Jagiellonian University in Cracow, emited by cerium that is produced by the high-current cathode made of iridium and cerium. Small amounts of these elements evaporate from the cathode and form low-intensity admixtures within the electron-ion plasma in the EBIT. Their presence and specific ionic population can be observed by examining the spectral characteristics resulting from the DR process. Results have been compared with flexible atomic code calculations, working in unresolved transition array mode, providing identification of the charge states. Here we show that this mode provides quick calculations of very complex data with enough reliability for experimental comparison. These observations highlight which DR features and corresponding charge states that should be present in spectra obtained in EBITs with similar cathode specifications.

Influence of Sm2O3/AgNPs Addition on the Properties of Lithium-Borate Glass-Ceramic System

This work reports the effect of adding Sm2O3 and silver nanoparticles, in small quantities up to 1 mol%, on the optical and structural properties of the B2O3-Li2O glass-ceramic system. The X-ray diffraction patterns of the samples show the presence of small quantities of the B2O3 crystalline phase, in addition to a major amorphous phase. Various structural units like BO3, BO4, and LiO4, present in the samples network, are responsible for the absorption bands from the FT-IR spectra. The optical spectra provided valuable information such as the identification of the observed electronic transitions, the energy gap, the refractive index, and metallization values. The luminescence data show the fact that with the addition of metallic NPs the quenching phenomenon can be observed after 0.5 mol% samarium ions. The studied systems are interesting for optical and semiconducting devices.

Larval fish community in the Bay of Whales (eastern Ross sea): Species composition, relative abundance and spatial distribution

Early life stages of fish represent a key component in the food chain of the pelagic ecosystem of the Southern Ocean, connecting producer trophic levels to those of higher predators. Pelagic larvae and early juveniles of notothenioid fishes overwhelmingly dominate the ichthyoplankton community living on the continental shelf. Scientific research surveys targeting early life stages of fish in the pelagic realm have been mainly carried out in the western Ross Sea, whereas the eastern side can be considered unexplored. As source of high primary production, the presence and timing of formation of wide ice-free areas throughout the year in the Ross Sea play a fundamental role in structuring larval fish community. The Ross Ice Shelf Polynya (RISP) is a large coastal polynya, which is driven and maintained by local prevailing winds and oceanic currents. In the present study, we report the first data on species composition, relative abundance and spatial distribution of larval fish community found off the Bay of Whales in the eastern Ross Sea. As reported for other areas of the Ross Sea, the Antarctic silverfish Pleuragramma antarcticum was by far the most abundant species, followed by other nototheniids and channichthyids in smaller amounts. The huge abundance of P. antarcticum early larvae supports the hypothesis of a potential nursery area near the Bay of Whales. Present results strongly advocate for future investigations in these poorly known and remote areas.

Enhanced low-temperature CO2 methanation over La-promoted NiMgAl LDH derived catalyst: Fine-tuning La loading for an optimal performance

LDH-derived Ni-based catalysts are gathering momentum due to their excellent thermal stability but their low-temperature CO2 methanation is limited. In this study, various concentrations of La were introduced into the LDH-derived Ni-based catalysts for CO2 methanation, and the underlying mechanisms were investigated. The optimal Ni/La0.2-MgAlOx catalyst presented a CO2 conversion level of 69.0 % at 225 °C, which is over 7 times higher than that of conventional Ni/MgAlOx. The addition of small amounts of La could significantly enhance H spillover to promote the reduction of Ni species, but the oxygen vacancy concentration became the dominant factor causing changes in low-temperature activity as the La contents continue to increase. CO2 was found to be adsorbed at the oxygen vacancies in the form of bidentate carbonates, which are more reactive under an enhanced electron-rich environment. The research offers guidance to design effective and sustainable catalysts for low-temperature CO2 methanation.

Improvement of Albedo and Snow-Cover Simulation during Snow Events over the Tibetan Plateau

Abstract The snow albedo is a vital component of land–atmosphere coupling models. It plays a critical role in regulating land surface energy exchange by controlling incoming solar radiation absorbed by the land surface and influencing the timing and rate of snowmelt. Accurate snow albedo simulation is essential to obtain surface energy balance and snow-cover estimates. Here, the simulation of albedo and snow cover using the Weather Research and Forecasting Model and an improved snow albedo scheme is verified against satellite-retrieved products during and immediately following eight snowfall events over the Tibetan Plateau. The improved model successfully characterizes the spatial pattern and inverted U-shaped temporal pattern of albedo over the entire Tibetan Plateau. This is attributed to the local optimization of snow-age parameters and explicit consideration of snow depth in the improved scheme. Compared with the previous model, the model proposed herein greatly decreases the overestimated albedo (by 0.13–0.27), yielding a bias range of ±0.08, mean relative bias decrease of 70%, and significant increase in the spatial correlation coefficient of 0.03–0.39 (mean: 0.13). The significant improvements of albedo estimates appear in deep snow-covered regions, largely attributed to parameter optimization related to snow albedo decay, while less improvements appear over the shallow snow-covered regions. Accurate reproduction of the spatiotemporal variation in albedo alleviated snow-cover overestimation by small amounts. For snow-cover estimates, the improved model consistently decreases the false-alarm rate by 0.03, and increases the overall accuracy and equitable threat score by 0.04 and 0.03, respectively. Moreover, the improved scheme shows an equivalent improvement of albedo estimates at both 1- and 5-km grid spacing over the eastern Tibetan Plateau; this is also true for snow-cover estimates. Significance Statement Snow albedo schemes in widely used numerical weather prediction models show notable shortcomings in complex mountainous regions, hindering accurate surface energy balance and snow-cover prediction. The purpose of this study is to better understand the role of snow albedo on snow-cover estimates and reveal the application potential of an improved snow albedo scheme across the Tibetan Plateau. This is important because snow albedo influences the timing and rate of snowmelt, and in turn snow-cover estimates, through regulating the surface energy budget. Our results highlight the strong application potential of our improved scheme in reducing snow simulation errors, confirm the importance of snow depth on snow albedo, and provide a new perspective for improving the accuracy of snow forecast over the topographically high Tibetan Plateau.

Toxicological Response of Zebrafish Exposed to Cocktails of Polymeric Materials and Valproic Acid

Microplastic pollution represents an emerging problem of great interest in the public domain in the last decade; in addition, it overlaps with another delicate problem—pollution with pharmaceutical products that can have negative effects on the environment and people, even in small amounts. The main purpose of this study was to assess the biochemical and behavioral effects of exposure of adult zebrafish (Danio rerio) to polyethylene (PE), polypropylene (PP) and valproic acid (VPA), respectively to their mixtures—possible situations in natural aquatic environments. In terms of behavioral responses, sociability appears to be more impaired in the PP group after 5 days of exposure. The mechanisms affected are more those of swimming performance than of sociability. Even more, VPA increases presence in the arm with conspecifics but decreases mobility and locomotion, indicating a possible anxiety mechanism. The mixtures decrease the aggressiveness, especially in the case of the PE+VPA group, where it reaches a super low level compared to the control, which could endanger the species in nature. Regarding the anxiogenic effect, PP and PE act differently: if PE has an anxiogenic effect, on the opposite side is the PP group, which shows a bolder and more agitated behavior. All four variants showed behavioral changes indicative of toxicity from the first dose.

Potential application of 2D nano-layered MXene in analysing and remediating endocrine disruptor compounds and heavy metals in water.

With the advancement of technologies and growth of the economy, it is inevitable that more complex processes are deployed, producing more heterogeneous wastewater that comes from biomedical, biochemical and various biotechnological industries. While the conventional way of wastewater treatment could effectively reduce the chemical oxygen demand, pH and turbidity of wastewater, trace pollutants, specifically the endocrine disruptor compounds (EDCs) that exist in µgL-1 or ngL-1 have further hardened the detection and removal of these biochemical pollutants. Even in small amounts, EDC could interfere human's hormone, causing severe implications on human body. Hence, this review elucidates the recent insights regarding the effectiveness of an advanced 2D material based on titanium carbide (Ti3C2Tx), also known as MXene, in detecting and removing EDCs. MXene's highly tunable feature also allows its surface chemistry to be adjusted by adding chemicals with different functional groups to adsorb different kinds of EDCs for biochemical pollution mitigation. At the same time, the incorporation of MXene into sample matrices also further eases the analysis of trace pollutants down to ng L-1 levels, thereby making way for a more cleaner and comprehensive wastewater treatment. In that sense, this review also highlights the progress in synthesizing MXene from the conventional method to the more modern approaches, together with their respective key parameters. To further understand and attest to the efficacy of MXene, the limitations and current gaps of this potential agent are also accentuated, targeting to seek resolutions for a more sustainable application.

Improved seizure liability detection by combining rat hippocampal brain slice electrophysiology with in vivo behavior observation following intracerebroventricular drug administration

An adverse effect of drug candidates, seizure is a serious issue in drug development. Improving evaluation systems for seizure liability is crucial for selecting good candidates. Firstly, in vitro electrophysiological measurement by a multielectrode array system in rat hippocampal brain slices was employed to confirm an increase in electrically evoked population spike (PS) area, the occurrence of multiple population spikes (MPSs), and thereby the seizure liability of five positive control chemicals: picrotoxin, 4-aminopyridine, pentylenetetrazole, penicillin G, and chlorpromazine. Aspirin, a negative control, did not affect PS area or generate MPSs. Furthermore, baclofen, an anticonvulsant drug, decreased PS area and inhibited the increase in PS area or occurrence of MPSs induced by picrotoxin. A comparative study of seizure liability among carbapenem antibiotics revealed that tienam > carbenin > omegacin and finibax. Despite leading to a strong decrease in PS area, physostigmine, cisplatin, and paroxetine still produced MPSs. Therefore, the increase in PS area or the occurrence of the MPS are considered significant evaluation parameters for seizure liability.In contrast, the in vitro electrophysiological measurement could not detect the seizure liability of diphenhydramine or fluvoxamine. A follow-up study of in vivo mouse behavioral change induced by intracerebroventricular administration of these drugs clearly detected convulsions. The in vitro electrophysiological study using hippocampal brain slices combined with in vivo behavior observation study of drug candidates administered by intracerebroventricular injection can implement to assess the seizure liability of even small amounts, especially in the early stages of drug development.

Use of local anesthetics in individuals with chronic renal failure

Individuals with chronic renal failure (CRF) undergoing hemodialysis often develop systemic arterial hypertension (SAH) and have to consider which anesthetic should be used in dental interventions. The objective of this study was to evaluate the action of anesthetics with (AV) and without vasoconstrictor (AWV) in individuals with CRF, in need of dental treatment. Randomly, dental hemiarchs were subjected to anesthetic infiltration with a 1.8 mL tube (for one moment with AV and another moment AWV). Oxygen saturation (SaO2), heart rate (HR), systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured before and after anesthesia. The results demonstrated a statistical difference only in SaO2 5 minutes after anesthesia in comparison with the AV and AWV groups, highlighting the safety of its use, as long as in small quantities, in individuals with CRF.

Praseodymium effects on great improving low-temperature hydrothermal stability of Cu/SAPO-34 NH3-SCR catalysts

Based on the previous findings that the presence of hydroxyl groups on the outer surface is crucial for maintaining skeletal stability, we propose a strategy modified Cu/SAPO-34 using Pr ions in this study. Therefore, we conducted several measurements to investigate the effect of Pr ions on the low-temperature hydrothermal stability of Cu/SAPO-34. We find that Pr exists only on the surface of Cu/SAPO-34 as ions and oxides, with Pr3+ ions playing a protective role in occupying surface acidic sites. The addition of small amounts of Pr leads to the re-dispersion of Cu, resulting in improved low-temperature selective catalytic reduction (SCR) activity in the as-synthesized samples. Furthermore, it enhances the resistance to decomposition of the Si–(OH)–Al framework during low-temperature hydrothermal aging, thereby preserving the framework structure and allowing detached active Cu species to return to exchangeable positions, ultimately restoring SCR activity. However, as the Pr content increases, the enhanced acidity causes some structural damage, gradually weakening the protective effect. Our work demonstrates that Pr modification is a simple and effective solution to the issue of poor low-temperature hydrothermal stability in Cu/SAPO-34, providing a promising way for the application of light rare earth elements.

Flow synthesis development and photocatalytic activity optimization of copper oxide nanoparticles using design of experiments

Many studies have focused on reducing the impact of carbon dioxide (CO2) on climate change. A promising approach for CO2 utilization is to use a photocatalyst to activate CO2 and generate valuable chemical compounds. One of the most commonly synthetized photocatalysts is cuprous oxide (Cu2O); however, low efficiency and fast deactivation still limit its industrial application. Here, a batch synthesis in nonaqueous media of Cu2O containing small amounts of metallic copper (Cu0) is investigated. By adjusting the ratio between Cu2O and Cu0 an enhanced photocatalytic efficiency is obtained. To overcome the deactivation limitations of Cu2O, a flow synthesis is developed that continuously supplies fresh photocatalysts to the reaction environment. The flow synthesis has the potential to allow the separate evaluation of the intrinsic reaction kinetic from the photocatalyst deactivation. This work optimizes the flow synthesis using a design of experiments (DOE) approach coupled with response surface methodology (RSM). The obtained surface responses for the measured factors were highly significant (p-value < 0.01 and R2 > 0.95). This novel methodology makes it possible to identify the optimum process conditions to simultaneously improve photocatalytic performance of the obtained material and reaction productivity. This approach enabled us to obtain in flow a combination of Cu2O/Cu0 photocatalyst and to propose a reaction mechanism and kinetic model for the Cu2O formation. The optimization procedure for flow synthesis proposed here provides an efficient path that can be extended to flow synthesis of a wide range of nanoparticles for photocatalytic applications.

Kinematic viscosity prediction of jet fuels and alternative blending components via comprehensive two-dimensional gas chromatography, partial least squares, and Yeo-Johnson transformation.

This work presents an accurate yet simplified partial least squares model to predict the kinematic viscosity of conventional and alternative jet fuels at -20°C using comprehensive two-dimensional gas chromatography coupled to a flame ionization detector (GC×GC/FID). Three different normalization methods (mean-centering, logarithmic, and Yeo-Johnson) were evaluated to identify their impact in the prediction of middle distillates' physical properties. Results using Yeo-Johnson transformation exhibited improved viscosity prediction capabilities over the validation set with a mean absolute percentage error of 5.3%, a root-mean-squared error of 0.23, and a coefficient of determination (R2 ) of 0.9404 using only 10 latent variables. Unlike previously reported correlations, this model allowed the identification of specific hydrocarbon groups and carbon numbers that drive jet fuel viscosity at low temperatures. The presence of even small amounts of large branched-alkanes (C15 -C17 ), dicyclic-alkanes (C10 ), and cycloaromatics (C11 ) have the potential to strongly increase the kinematic viscosity of jet fuels. Contrastingly, light monocycloalkanes and branched-alkanes (≤ C10 ) were associated with lower viscosity values. Novelly, this model suggests the implementation of Yeo-Johnson transformations to predict the physical properties of middle distillates to further improve the performance metrics of partial least squares models based on GC data.