Limited Volume Research Articles

Optimizing oil-water separation using fractal surfaces.

Oil has become a prevalent global pollutant, stimulating the research to improve the techniques to separate oil from water. Materials with special wetting properties-primarily those that repel water while attracting oil-have been proposed as suitable candidates for this task. However, one limitation in developing efficient substrates is the limited available volume for oil absorption. In this study, we investigate the efficacy of disordered fractal materials in addressing this challenge, leveraging their unique wetting properties. Using a combination of a continuous model and Monte Carlo simulations, we characterize the hydrophobicity and oleophilicity of substrates created through ballistic deposition (BD). Our results demonstrate that these materials exhibit high contact angles for water, confirming their hydrophobic nature while allowing significant oil penetration, indicative of oleophilic behavior. The available free volume within the substrates varies from 60% to 90% of the total volume of the substrate depending on some parameters of the BD. By combining their water and oil wetting properties with a high availability of volume, the fractal substrates analyzed in this work achieve an efficiency in separating oil from water of nearly 98%, which is significantly higher compared to micro-pillared surfaces made from the same material but lacking a fractal design.

A Fast, High-Sensitivity 96-Well Plate-Based MICROFASP Method for Processing Low Microgram Proteomics Sample within 1.5 h.

A rapid, sensitive, and high-throughput sample preparation method is of paramount significance for proteomics analysis. Here, we report a fast, high-sensitivity MICROFASP method that is capable of completing sample preparation within 1.5 h, enhancing the throughput by over 13 times compared to the previous reports. Protein digestion time was significantly cut from 17 h to 20 min in a limited volume. Simultaneous reduction and alkylation occurred within 30 min. The label-free quantitation intensities of proteins from the fast and conventional MICROFASP methods were highly correlated (r = 0.91), validating the reliability of the fast-MICROFASP method. When starting with 1 μg of K562 cell lysate, the fast-MICROFASP method identified over 6 times more protein groups and 19 times more peptides than did the iST method. A 96-well plate-based version was developed to process 8 brain tissue samples from APP/PS1 transgenic mice in parallel. Averagely, with only 1 μg of protein lysate, 2826 protein groups (n = 8, RSD = 0.7%) and 12,972 peptides (n = 8, RSD = 1.5%) were identified from each sample. Amyloid-beta protein was successfully identified as a highly expressed protein, which shows its potential for detecting diagnostic markers and proteome profiling with low-microgram samples. We anticipate the high-sensitivity 96-well plate-based fast-MICROFASP method will have wide application in high-throughput and rapid preparation of large cohorts of low-microgram samples (e.g., clinical biopsy) for comprehensive proteome profiling. Data are available via ProteomeXchange with the identifier PXD053720.

Diffuse Cyclin D1 and SPINK1 Expression in Gastric Oxyntic Gland Neoplasms: Promising Diagnostic Markers Identified by Spatial Transcriptome Analysis.

Oxyntic gland neoplasms typically arise in Helicobacter pylori-naïve stomachs and are composed predominantly of chief cells, with a smaller component of parietal cells. The pathologic diagnosis can be challenging due to minimal cellular atypia. Especially in biopsy specimens with limited tumor volume or when pathologists have limited experience in diagnosing this neoplasm, distinguishing it from normal oxyntic glands can be difficult, and no reliable diagnostic markers are currently available. In this study, single-cell spatial transcriptome analysis successfully identified significant upregulation of CCND1 and SPINK1 in all six analyzed cases of oxyntic gland neoplasms compared to normal oxyntic glands. Immunohistochemical analysis confirmed this finding in 21 endoscopically resected cases of oxyntic gland neoplasms, demonstrating that cyclin D1 and SPINK1 were diffusely expressed in oxyntic gland neoplasms, whereas their expression was scarcely observed in normal oxyntic glands with a few of them showing weak to moderate staining. Even in biopsy specimens, these two markers highlighted the tumor areas and clearly distinguished neoplastic from normal oxyntic glands. Nonneoplastic foveolar epithelia and mucous neck cells also showed positive staining for both cyclin D1 and SPINK1. Additionally, mild increase in cyclin D1 expression and patchy or mosaic expression of SPINK1 was observed in fundic gland polyps, Helicobacter pylori -associated gastritis and pyloric gland adenomas, while diffuse staining pattern was specific to oxyntic gland neoplasms. These observations suggest that cyclin D1 and SPINK1 are reliable markers in differentiating oxyntic gland neoplasms from nonneoplastic oxyntic glands and pyloric gland adenomas. Cyclin D1 is commonly used for immunostaining in many pathology departments, and due to its higher sensitivity and specificity compared to SPINK1, it is considered the best diagnostic marker.

Dynamic mechanisms for membrane skeleton transitions.

The plasma membrane and the underlying skeleton form a protective barrier for eukaryotic cells. The molecular players forming this complex composite material constantly rearrange under mechanical stress. One of those molecules, spectrin, is ubiquitous in the membrane skeleton and linked by short actin filaments. In this work, we developed a generalized network model for the membrane skeleton integrated with myosin contractility and membrane mechanics to investigate the response of the spectrin meshwork to mechanical loading. We observed that the force generated by membrane bending is important to maintain a regular skeletal structure suggesting that the membrane is not just supported by the skeleton, but has an active contribution to the stability of the cell structure. We found that spectrin and myosin turnover are necessary for the transition between stress and rest states in the skeleton. Simulations of a fully connected network representing a whole cell show that the surface area constraint of the plasma membrane and volume restriction of the cytoplasm enhance the stability of the membrane skeleton. Furthermore, we showed that cell attachment through adhesions promotes cell shape stabilization.

Real-world evaluation of the accuracy of the Viz.AI automated intracranial hemorrhage volume calculation tool

BackgroundAppropriate management of spontaneous intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) requires rapid, accurate volume estimation. Viz.AI has developed an artificial intelligence (AI)-powered ICH calculation tool that may improve existing...

Probing the Limits of Reactant Concentration and Volume in Primitive Polyphenyllactate Synthesis and Microdroplet Assembly Processes

Probing the Limits of Reactant Concentration and Volume in Primitive Polyphenyllactate Synthesis and Microdroplet Assembly Processes

Crystal structure validation of verinurad via proton-detected ultra-fast MAS NMR and machine learning.

The recent development of ultra-fast magic-angle spinning (MAS) (>100 kHz) provides new opportunities for structural characterization in solids. Here, we use NMR crystallography to validate the structure of verinurad, a microcrystalline active pharmaceutical ingredient. To do this, we take advantage of 1H resolution improvement at ultra-fast MAS and use solely 1H-detected experiments and machine learning methods to assign all the experimental proton and carbon chemical shifts. This framework provides a new tool for elucidating chemical information from crystalline samples with limited sample volume and yields remarkably faster acquisition times compared to 13C-detected experiments, without the need to employ dynamic nuclear polarization.

Angler catch data as a monitoring tool for European barbel Barbus barbus in a data limited recreational fishery

Large bodied freshwater fishes can be important target species for recreational anglers, with some species introduced intentionally to diversify angling experiences. European barbel Barbus barbus is an important target species in many riverine fisheries, including the River Severn and its River Teme tributary, western England, where it has supported a catch-and-release recreational fishery for approximately 50 years. The River Teme was renowned for the quality of its barbel angling from the 1980s. Since 2007, angler dissatisfaction has increased substantially in this fishery, being associated with alleged declines in the number of barbel being captured and in their population abundances. As there were few data available at that time to investigate these declines, data from periodic electric fishing surveys and some angler catch data were sourced. Analyses revealed temporal declines in the number of sampled barbel during electric fishing surveys, although the number of surveys was low, varied between years and did not target barbel specifically. Analyses of four angler catch data sets (1995–2022) involving more than 1000 captured barbel of 0.5–5.3 kg also revealed significant temporal declines in barbel catches (by number and catch-per-unit-effort). These catch declines were generally coincident with reductions in angler presence and effort on the river, suggesting low catches were a driver of angler dissatisfaction. These results provide empirical support for angler claims of substantial declines in barbel catches and abundances, and emphasise that even limited volumes of angler catch data are useful for understanding temporal changes in exploited but data limited fish populations.

Precise Embodied Data Selection with Haptic Feedback while Retaining Room-Scale Visualisation Context.

Room-scale immersive data visualisations provide viewers a wide-scale overview of a large dataset, but to interact precisely with individual data points they typically have to navigate to change their point of view. In traditional screen-based visualisations, focus-and-context techniques allow visualisation users to keep a full dataset in view while making detailed selections. Such techniques have been studied extensively on desktop to allow precise selection within large data sets, but they have not been explored in immersive 3D modalities. In this paper we develop a novel immersive focus-and-context technique based on a "magic portal" metaphor adapted specifically for data visualisation scenarios. An extendable-hand interaction technique is used to place a portal close to the region of interest. The other end of the portal then opens comfortably within the user's physical reach such that they can reach through to precisely select individual data points. Through a controlled study with 12 participants, we find strong evidence that portals reduce overshoots in selection and overall hand trajectory length, reducing arm and shoulder fatigue compared to ranged interaction without the portal. The portals also enable us to use a robot arm to provide haptic feedback for data within the limited volume of the portal region. In a second study with another 12 participants we found that haptics provided a positive experience (qualitative feedback) but did not significantly reduce fatigue. We demonstrate applications for portal-based selection through two use-case scenarios.

Limits of spectral measures for linearly bounded and for Poisson distributed random potentials

We show the existence of infinite volume limits of resolvents and spectral measures for a class of Schrödinger operators with linearly bounded potentials. We then apply this result to Schrödinger operators with a Poisson distributed random potential.

Social security for special categories of disabled people in the Ukrainian SSRin the 1920s.

The article is aimed at studying and analyzing the practical experience of the activities of state authorities in implementing the policy of social security for the disabled in the 1920s. The methodological basis of the study is the fundamental principles of historical research: historicism, consistency, objectivity in the course of working with documents. Among the special methods used in the study should be called problem-chronological, historical-systemic, historical-typological. The scientific novelty of the article is to highlight the features of state policy on the organization of social security of special categories of disabled. Conclusions. Having seized power on the territory of Ukraine, the Bolshevik government publicly announced its intentions to create an effective system of social security for the disabled strata of society. Material support for a special category of disabled people was assigned exclusively to the state. However, under the conditions of the new economic policy with its market principles, a small number of people could count on security. At the same time, despite the low size of social payments, the very fact of her appointment, the Soviet authorities tried to testify their value to the proletarian state. Social protection of special categories of the disabled, which included the Red Army, the disabled of the World War І and the Civil War, family members of the dead military, persons who had special merits before the Soviet state, was carried out by the People's Commissariat of Social Security through its departments on the ground at the expense of the state budget. Due to its limited volume, the amount of social payments was significantly inferior to payments made at the expense of insurance premiums.

Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator

In various practical noise control scenarios, such as duct noise mitigation, industrial machinery, architectural acoustics, and underwater applications, it is essential to develop noise absorbers that deliver effective low-frequency attenuation while maintaining compact dimensions. To achieve low-frequency absorption within a limited spatial volume, this study proposes an embedded Helmholtz resonator featuring a roughened neck and establishes a numerical computational model that incorporates thermos viscous effects. A quantitative investigation is conducted on three types of embedded rough-neck geometries (rectangular-grooved, triangular-grooved, and undulated) to elucidate their acoustic performance, with particular attention to differences in acoustic transmission loss and acoustic impedance characteristics. In response to the practical demand for even lower-frequency attenuation, this work further focuses on optimizing the structural parameters of an embedded rectangular-grooved Helmholtz resonator (ERHR). A back-propagation (BP) neural network models and predicts how structural parameters impact the acoustic transmission coefficient, elucidating the effects of geometric variations. Moreover, by coupling the BP network with the Golden Jackal Optimization (GJO) algorithm, a BP-GJO optimization model is developed to refine the structural parameters. The findings reveal that the proposed method significantly improves resonator spatial utilization at a specific noise frequency while preserving acoustic transmission loss performance. This work thereby provides a promising strategy for designing low-frequency, compact Helmholtz resonators suitable for a wide range of noise control applications.

Comparative Investigation of Vortex and Direct Plasma Discharge for Treating Titanium Surface.

Numerous studies have investigated the surface treatment of implants using various types of plasma, including atmospheric pressure plasma and vacuum plasma, to remove impurities and increase surface energy, thereby enhancing osseointegration. Most previous studies have focused on generating plasma directly on the implant surface by using the implant as an electrode for plasma discharge. However, plasmas generated under atmospheric and moderate vacuum conditions often have a limited plasma volume, meaning the shape of the electrodes significantly influences the local electric field characteristics, which in turn affects plasma behavior. Consequently, to ensure consistent performance across implants of different sizes and shapes, it is essential to develop a plasma source with discharge characteristics that are unaffected by the treatment target, ensuring uniform exposure. To address this challenge, we developed a novel plasma source, termed "vortex plasma", which generates uniform plasma using a magnetic field within a controlled space. We then compared the surface treatment efficiency of the vortex plasma to that of conventional direct plasma discharge by evaluating hydrophilicity, surface chemistry, and surface morphology. In addition, to assess the biological outcomes, we examined osteoblast cell activity on both the vortex and direct plasma-treated surfaces. Our results demonstrate that vortex plasma improved hydrophilicity, reduced carbon content, and enhanced osteoblast adhesion and activity to a level comparable to direct plasma, all while maintaining the physical surface structure and morphology.

DCA-YOLOv8: A Novel Framework Combined with AICI Loss Function for Coronary Artery Stenosis Detection.

Coronary artery stenosis detection remains a challenging task due to the complex vascular structure, poor quality of imaging pictures, poor vessel contouring caused by breathing artifacts and stenotic lesions that often appear in a small region of the image. In order to improve the accuracy and efficiency of detection, a new deep-learning technique based on a coronary artery stenosis detection framework (DCA-YOLOv8) is proposed in this paper. The framework consists of a histogram equalization and canny edge detection preprocessing (HEC) enhancement module, a double coordinate attention (DCA) feature extraction module and an output module that combines a newly designed loss function, named adaptive inner-CIoU (AICI). This new framework is called DCA-YOLOv8. The experimental results show that the DCA-YOLOv8 framework performs better than existing object detection algorithms in coronary artery stenosis detection, with precision, recall, F1-score and mean average precision (mAP) at 96.62%, 95.06%, 95.83% and 97.6%, respectively. In addition, the framework performs better in the classification task, with accuracy at 93.2%, precision at 92.94%, recall at 93.5% and F1-score at 93.22%. Despite the limitations of data volume and labeled data, the proposed framework is valuable in applications for assisting the cardiac team in making decisions by using coronary angiography results.

Science Mapping the Knowledge Base on Student Retention in Higher Education: A Bibliometric Review of Research Papers from 1914-2022

In this study, we systematically review existing research on college student retention. It utilizes a total of 5277 publications indexed either in Scopus or Web of Science from 1914 to 2022. The results show that most of the research on student retention has been conducted in English-speaking countries such as the United States, Australia, the United Kingdom, and Canada. The United States produces almost two-thirds of scholarly publications worldwide. The term ‘retention’ is commonly used alongside ‘persistence,’ ‘attrition,’ ‘engagement,’ and ‘success.’ Moreover, the term higher education is associated with dropout, completion, and academic performance, as well as new methodological terms like data mining, machine learning, learning analytics, and logistic regression. Retention is also studied in fields such as nursing, engineering, and STEM. Special attention is given to community colleges due to higher dropout rates. Unlike the United States, Australia, the United Kingdom, and Canada, where higher education research on retention is extensive, countries like China and India, which have recently expanded their higher education systems, show a comparatively limited volume of research output concerning student retention.

Investigation of the conditions for the development of quarries of non-metallic building materials on the Upper Belaya, taking into account their impact on the level regime

Currently, the Belaya River is in rather difficult hydrological and navigable conditions, which is generally due to the low water content in the region and the many years of mining of non-metallic building materials actively carried out here. Under existing conditions, it is not enough to ensure guaranteed dimensions of the ship's course only by carrying out track work and strict regulation of production volumes is necessary. As part of the research carried out, the main tasks of conducting hydraulic calculations and methods of their solution are considered, the results of hydraulic calculations of the landing of water levels from quarrying are presented, which showed that in a significant part of the site (33 km of the 76 km studied) further quarrying should be completely prohibited until the restoration of the riverbed and the introduction of building materials quarries on the site; the possibility of quarrying at three sites in limited volumes was allowed; recommendations were given on the parameters of building materials production at a promising field for development. The paper also assesses the impact of dredging for navigation purposes on the amount of water level landing, which showed that they play a secondary role in the general anthropogenic impact on the Upper Belaya riverbed, but at the same time intensive channel mining of building materials and dredging is impossible due to their significant combined effect on the level regime. The implementation of the conclusions and recommendations obtained from the research results will minimize the adverse impact of mining operations.

Integrated Optics Waveguides and Mesoporous Oxides for the Monitoring of Volatile Organic Compound Traces in the Mid-Infrared.

Volatile organic compounds (VOCs) are an ever-growing hazard for health and environment due to their increased emissions and accumulation in the air. Quantum cascade laser-based infrared (QCL-IR) sensors hold significant promise for gas monitoring, thanks to their compact, rugged design, high laser intensity, and high molecule-specific detection capabilities within the mid-infrared spectrum's fingerprint region. In this work, tunable external cavity QCLs were complemented by an innovative germanium-on-silicon integrated optics waveguide sensing platform with integrated microlenses for efficient backside optical interfacing for the tunable laser spectrometer. The waveguide chip was coated with a mesoporous silica coating, thereby increasing the signal by adsorptive enhancement of VOCs while at the same time limiting water vapor interferences. Different least square fitting methods were explored to deconvolute the resulting spectra, showing subparts-per-million by volume (sub-ppmv) limits of detection and enrichment factors of up to 22 000 while keeping the footprint of the setup small (29 × 23 × 11 cm³). Finally, a use-case simulation for the continuous detection of VOCs in a process analytical technology environment confirmed the high potential of the technique for the monitoring of contaminants. By successfully demonstrating the use of photonic waveguides for the monitoring of VOCs, this work offers a promising avenue for the further development of fully integrated sensors on a chip.

Ablative Five-Fraction Stereotactic Radiotherapy in Elderly Patients with Pancreatic Cancer: A Single Institution Experience.

Background: Pancreatic cancer, with its poor prognosis, is frequently diagnosed in elderly patients who may be ineligible for surgery or chemoradiation due to age or comorbidities. Stereotactic body radiotherapy (SBRT) offers a targeted approach by delivering precise, high-dose radiation to a limited volume in few fractions. This study aims to evaluate the efficacy and safety of SBRT in elderly pancreatic cancer patients. Methods: Patients with pancreatic cancer received SBRT using Volumetric Modulated Arc Therapy in schedules of five dose fractions tailored to the tolerance of adjacent tissues. Progression-free survival (PFS), local progression-free survival (LPFS), metastasis-free survival (MFS) and overall survival (OS) were analysed. Toxicities were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Results: Median follow-up was 9.5 months (range, 4-37.2 months). The 1-year, 2-year and 3-year LPFS rates were 88%, 73% and 54%, respectively (median not reached). Median PFS, MFS and OS were 29.6 months, 32.6 months, and 24.1 months, respectively. SBRT was well tolerated with acute and late toxicity rates of 6% and 9%, respectively. Conclusionsd: SBRT appears to be an effective and safe option for elderly pancreatic cancer patients, achieving high local control with minimal toxicity.

The finite volume effects of the Nambu–Jona–Lasinio model with the running coupling constant

Abstract With Schwinger’s proper-time formalism of the Nambu–Jona–Lasinio model, we investigate the finite volume effects with the anti-periodic boundary condition in the presence of magnetic fields. The model is solved with a running coupling constant G(B), which is properly fitted by the lattice average (Σ u + Σ d )/2 and the difference Σ u − Σ d . For the model in a finite or infinite volume, the magnetic fields can increase the constituent quark mass M while the temperatures can decrease it. M is close to the infinite volume limit when the box length L is appropriately large. For a sufficiently small value of L, M is close to the chiral limit. The finite volume effects behave intensely in the narrow ranges of L where the partial derivative ∂M/∂L is greater than zero. These narrow ranges can be reduced by stronger magnetic fields and by higher temperatures. In addition, the chiral limit can be restored by a sufficiently small finite volume and be broken by sufficiently strong magnetic fields. Finally, we discuss the thermal susceptibility and the crossover phase transition depending on the temperature at finite volume in the presence of magnetic fields.

Transfer Learning with a Graph Attention Network and Weighted Loss Function for Screening of Persistent, Bioaccumulative, Mobile, and Toxic Chemicals.

In silico methods for screening hazardous chemicals are necessary for sound management. Persistent, bioaccumulative, mobile, and toxic (PBMT) chemicals persist in the environment and have high mobility in aquatic environments, posing risks to human and ecological health. However, lack of experimental data for the vast number of chemicals hinders identification of PBMT chemicals. Through an extensive search of measured chemical mobility data, as well as persistent, bioaccumulative, and toxic (PBT) chemical inventories, this study constructed comprehensive data sets on PBMT chemicals. To address the limited volume of the PBMT chemical data set, a transfer learning (TL) framework based on graph attention network (GAT) architecture was developed to construct models for screening PBMT chemicals, designating the PBT chemical inventories as source domains and the PBMT chemical data set as target domains. A weighted loss (LW) function was proposed and proved to mitigate the negative impact of imbalanced data on the model performance. Results indicate the TL-GAT models outperformed GAT models, along with large coverage of applicability domains and interpretability. The constructed models were employed to identify PBMT chemicals from inventories consisting of about 1 × 106 chemicals. The developed TL-GAT framework with the LW function holds broad applicability across diverse tasks, especially those involving small and imbalanced data sets.