ABSTRACT: Iodixanol is an iso-osmolar nonionic dimeric hydrophilic contrast agent with a higher viscosity than the monomeric agents. It is the only Food and Drug Administration (FDA)approved isoosmolar agent in the United States, and it is the only contrast agent with an FDA-approved indication for use in cardiac computed tomographic angiography (CCTA), to assist in the diagnostic evaluation of patients with suspected coronary artery disease. In clinical studies, it has been noted to have fewer side effects and similar image quality when compared to low osmolar contrast media. This can be attributed to the pharmacological properties of iodixanol. In the field of cardiology, iodixanol among other intravenous contrast media is used for coronary computed tomography angiography and cardiac catheterization. In this article, the use, tolerability and efficacy of iodixanol in the field of cardiology are reviewed, specifically evaluating the use for CCTA and coronary angiography, including outcome studies, randomized trials and comparisons to other contrast agents.

Renal angiogram is a promising tool for diagnosing renal vasculature and structural alterations in renal diseases. In renal diseases, the vascular changes were observed earlier than the structural and other changes. However, the literature on angiograms in kidney diseases was limited. Six client-owned dogs with chronic kidney diseases with International Renal Interest Society (IRIS) stage II and III were selected for this study. Under general anesthesia, the femoral arterial catheterization was performed. With a Cobra (C2) catheter, Iohexol saline (50:50) was administered to evaluate the vascular changes of Renal failure, using selective and non-selective angiograms. The procedures were completed successfully with minimal complications. Serum biochemistry and urine protein creatinine ratio were estimated sequentially and quality of life was monitored. Due to contrast agent complications, a dog died within 14 days and necropsy was conducted. Though the renal angiogram has complications, it is a reliable tool for the diagnosis of vasculature changes associated with kidney diseases, in veterinary medicine.

Graphene/silicon (Si) heterojunction photodetectors are widely studied in detecting of optical signals from near-infrared to visible light. However, performance of the graphene/Si photodetectors is limited by defects created in the growth process and surface recombination at the interface. Herein, a remote plasma-enhanced chemical vapor deposition is introduced to directly grow graphene nanowalls (GNWs) at a low power, which can effectively improve the growth rate and reduce defects. Moreover, hafnium oxide (HfO2) grown by atomic layer deposition has been employed as an interfacial layer for the GNWs/Si heterojunction photodetector. It is shown that the high-k dielectric layer of HfO₂ acts as an electron blocking and hole transport layer, which minimizes the recombination and reduces dark current. By optimizing the thickness of HfO₂, an extremely low dark current of 3.85×10^(-10) A with a responsivity of 0.19 AW^(-1), as well as a specific detectivity of 1.38×10^12 Jones at zero bias can be obtained for the fabricated GNWs/HfO₂/Si photodetector. This work demonstrates a universal strategy to fabricate high-performance graphene/Si photodetectors.

In this paper, we delve into the realm of aspect-level sentiment analysis, a sophisticated analytical task focused on pinpointing and interpreting the sentiment directed towards specific elements within a sentence. Traditional methods in this domain, primarily based on neural networks, have often overlooked the critical role of syntactic structures in sentences. To bridge this gap, we have developed the Syntax-Enhanced Sentiment Graph Network (SentiSyn). This pioneering model represents a significant step forward in aspect-level sentiment analysis, bringing to the forefront the utilization of word dependency relationships to enrich sentiment analysis. SentiSyn stands out by its innovative use of a dependency graph, a tool that meticulously maps out the intricate web of syntactic relationships surrounding a target aspect in a sentence. This approach allows SentiSyn to effectively capture and channel sentiment-related characteristics that are deeply rooted in the syntactic context of the aspect target. By doing so, SentiSyn unlocks a deeper understanding of sentiment dynamics in textual content, enabling a more nuanced and accurate sentiment analysis. Our comprehensive experimental evaluation of SentiSyn showcases its remarkable capabilities. When combined with advanced embedding techniques like GloVe and BERT, SentiSyn demonstrates a superior performance edge over several existing sentiment analysis methods. This performance leap is not just incremental; it represents a significant enhancement in the field of sentiment analysis, underscoring the importance of syntactic context in understanding sentiments. Furthermore, our analysis delves into how SentiSyn effectively leverages these embeddings to gain a more profound and contextually rich insight into sentiment dynamics. The results from our tests indicate that SentiSyn, with its unique approach to integrating syntactic structures and advanced embeddings, sets a new benchmark in aspect-level sentiment analysis, offering both enhanced accuracy and deeper sentiment understanding.

Theoretical and experimental approaches have been applied to study the polymer physics under-lying compaction of DNA in the bacterial nucleoid. Knowledge of the compaction mechanism is necessary to obtain a mechanistic understanding of the process of segregation of replicating chromosome arms (replichores) during the cell cycle. In the first part of this review light microscope observations are discussed that have demonstrated that the nucleoid has a lower refractive index and thus a lower density than the cytoplasm. A polymer-physical explanation for this phenomenon was given by the theory of Theo Odijk pro-posed in 1998. By assuming a phase separation between nucleoid and cytoplasm and by imposing equality of osmotic pressure and chemical potential between the two phases, a minimal energy situation is obtained in which soluble proteins are depleted from the nucleoid, thus explaining its lower density. The theory is compared with recent views for DNA compaction that are based on mere exclusion of polyribosomes from the nucleoid or on the transcriptional activity of the cell. These new views raise the question of whether they can still explain the lower refractive index or density of the nucleoid. In the second part of this review the question is discussed how DNA segregation occurs in Esche-richia coli, in the absence of the so-called active ParABS system, present in the majority of bacteria. How is entanglement prevented of nascent chromosome arms, generated at the origin in the pa-rental network of the E. coli nucleoid? The observations of the groups of Sherratt and Hansen in 2006, that the four nascent chromosome arms synthesized in the initial replication bubble, segre-gate to opposite halves of the sister nucleoids implies that extensive intermingling of daughter strands does not occur. Based on the hypothesis that leading and lagging replichores synthesized in the replication bubble, fold into micro-domains that do not intermingle, a passive "four-excluding-arms model" for segregation is proposed. This model implies that the key for seg-regation already lies in the structure of the replication bubble at the very start of DNA replication; it explains the different patterns of chromosome arms as well as the segregation distances between replicated loci as experimentally observed.

Contrast-enhanced ultrasonography (CEUS) is useful for evaluation of the hemodynamics of hepatic tumors and surrounding he-patic parenchyma in real time. CEUS with intravenous contrast administration is well established for evaluation of hepatocellular carcinoma (HCC). On the other hand, intra-arterial (transcatheter) CEUS (IAUS) is an emerging technique that allows more selective evaluation of the arterial supply to the tumor. IAUS was performed by administration of Sonazoid® through the microcatheter and imaging of the area of the target lesion with a dedicated, contrast-specific technique. Sonazoid® (0.5 ml diluted with 49.5 ml of distilled water) was used as the contrast medium in IAUS. The diluted Sonazoid® was introduced into the feeding artery by in-termittent injection of 0.3-1.0 ml through a microcatheter placed in the artery and flushing with saline at the same flow rate. We report the three cases in which IAUS was useful in transarterial chemoembolization (TACE) for HCC. Two cases were performed TACE for hepatic metastasis. In any cases, plain computed tomography (CT) after TACE showed accumulation of Lipiodol® only in the metastases. One case was suspected having HCC rupture and urgent abdominal angiography was performed. IAUS was performed frequently to reduce the amount of iodinated contrast agent as much as possible because of renal failure. Concomitant use of IAUS enabled reduction of the amount of contrast agent.

Polymers are one of the most widely used chemicals in the oil and gas industry. They are used for mobility control in enhanced oil recovery, in conformance control as a crosslinked plugging agent, as a fracking fluid for fracture propagation and proppant transportation, and in drilling fluids as an additive for drilling mud enhancement. In the majority of its applications in the petroleum industry, the polymer needs to be injected under high pressures and temperatures. This can impact the polymer structure significantly and compromises the possibility of reusing the injected polymer for cost reduction and material sustainability. This research characterizes the polymer injectivity in different pore sizes under different conditions and evaluates the polymer conditions after injection. Based on this, the ability to reinject the polymer in the porous media is discussed. The factors studied include the pore size, the polymer concentration, the polymer injection flowrate, and polymer injectivity. Results showed that the polymer usually undergoes four main degradations during injection including dehydration, syneresis, shearing, and excessive hydrolysis. The experimental results showed that one or more of the polymer degradations resulted in the inability to reinject the polymer in most cases.

Background: Application of enhanced recovery after surgery principles decrease postoperative complications (POCs), length of stay (LOS), and readmissions. Pharmacoprophylaxis decreases morbidity, but the effect of specific regimens on clinical outcomes is unclear. Methods and Materials: Records of 476 randomly selected adult patients who underwent elective colorectal surgeries (ECRS) at 10 US hospitals were abstracted. Primary outcomes were surgical site infection (SSI), venous thromboembolism (VTE), postoperative nausea and vomiting (PONV), pain, and ileus rates. Secondary outcomes included LOS and 7- and 30-day readmission rates. Results: POC rates were SSI (3.4%), VTE (1.5%), PONV (47.9%), pain (58.1%), and ileus (16.1%). Cefazolin 2g/metronidazole 500mg and ertapenem 1g were associated with the shortest LOS; cefotetan 2g and cefoxitin 2g with the longest LOS. No SSI occurred with ertapenem and cefotetan. More Caucasians than Blacks received oral antibiotics before intravenous antibiotics without impact. Enoxaparin 40 mg subcutaneously daily was the most common inpatient and discharge VTE prophylaxis. All in-hospital VTEs occurred with unfractionated heparin. Most received rescue rather than around the clock antiemetics. Scopolamine patch, spinal opioids, and IV lidocaine continuous infusion were associated with lower PONV. Transversus abdominis plane block with long-acting local anesthetics, celecoxib, non-anesthetic ketamine bolus, ketorolac IV, lidocaine IV, and pregabalin were associated with lower in-hospital pain severity rate. Gabapentinoids and alvimopan were associated with lower ileus rate. Acetaminophen, alvimopan, famotidine, and lidocaine patch were associated with shorter LOS. Conclusions: Significant differences in pharmacotherapy regimens that may improve primary and secondary outcomes in ECRS were identified. Future research should identify latent pharmacotherapy variables that impact patient outcomes.

Traditional diagnosis of patent foramen ovale (PFO) in the heart has involved the use of transcranial doppler (TCD). However, TCD is essentially a blind test that cannot directly visualize the location of blood vessels. Since TCD relies on qualitative assessments by examiners, there is room for errors, such as misalignment of the ultrasound's angle of incidence with the actual blood vessels. This limitation affects the reproducibility and consistency of the examination. In this study, we presented an alternative approach for assessing right-to-left shunt (RLS) associated with PFO using contrast transcranial color-coded doppler (C-TCCD) with bubble contrast. The patient under consideration had been diagnosed with an ischemic stroke through imaging, but the subsequent cardiac work-up failed to determine the cause. Employing C-TCCD for RLS screening revealed a confirmed RLS of Spencer’s three grades. Subsequently, transesophageal echocardiography (TEE) was conducted to evaluate PFO risk factors, confirming an 8 mm PFO size, a 21 mm tunnel length, a hypermobile interatrial septum, and persistent RLS. The calculated high-risk PFO score was 4 points, categorizing it as a very high-risk PFO. This case underscores the importance of C-TCCD screening in detecting RLS associated with PFO, especially in cryptogenic stroke patients when identifying the underlying cause of ischemic stroke becomes challenging.

This study aimed to compare the efficacies and safety of enhanced and standard monofocal intraocular lenses (IOLs) in eyes with early glaucoma. Patients with concurrent cataracts and open-angle glaucoma (OAG) were enrolled. They underwent cataract surgery with IOL implantation. Manifest refraction; monocular uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), uncorrected intermediate visual acuity (UIVA), and uncorrected near visual acuity (UNVA); visual field (VF); contrast sensitivity (CS); defocus curves and questionnaires were assessed three months postoperatively. Thirty-four and 38 patients had enhanced and standard monofocal IOLs, respectively. The enhanced monofocal IOL provided better UIVA than the standard monofocal IOL (p = 0.003) but similar UDVA, CDVA and UNVA. The enhanced monofocal IOL had more consistent defocus curves than the standard monofocal IOL, especially at -1 (p = 0.042) and -1.5 (p = 0.026) diopters. The enhanced monofocal IOL provided better satisfaction (p = 0.019) and lower spectacle dependence (p = 0.004) than the standard monofocal IOL for intermediate vision, with similar VF and CS. In conclusion, the enhanced monofocal IOL is recommended for patients with OAG because they provide better intermediate vision, higher satisfaction, and lower dependence on spectacles than standard monofocal IOL, without worsening other visual outcomes.

The enzyme-linked immunosorbent assay (ELISA) coupled with surface-enhanced Raman spectroscopy (SERS) detection is a growing area of analytical chemistry emerged as a solution to a problem of sensitivity improvement. SERS-based ELISA with horseradish peroxidase as an enzymatic label, o-phenylenediamine (oPD) substrate, and 2,3-diaminophenazine (DAP) enzymatic product was one of the first examples of such systems. Surprisingly, the full potential of this long-known approach has not been revealed yet. The current study addresses a previously neglected problem of SERS detection stage performance. Using silver nanoparticles and model mixtures of oPD and DAP, the effects of pH, concentration of aggregating agent, and particle surface chloride stabilizer were extensively evaluated. At optimal mildly acidic pH of 3, 0.93 to 1 M citrate buffer, and AgNPs stabilized with 20 mM chloride, at least two orders of magnitude advantages in the detection limits of SERS over colorimetry both for DAP and HRP were demonstrated. We suppose that this improved detection system could become a useful tool for the development of SERS-based ELISA protocols.

Microemulsions with excellent properties have shown significant potential for enhancing oil recovery from tight formations through spontaneous imbibition. This work present a high-temperature-tolerant lower-phase microemulsion (HTLP-ME) using a microemulsion dilution method. The properties and morphological characteristics of HTLP-ME were evaluated and proposed a enhanced spontaneous imbibition oil recovery mechanism using imbibition tests and CT scanning technology. The results show that the optimum concentration of HTLP-ME is 0.2wt% has a superior thermal stability, small particle size, lower IFT, good wettability alteration ability, and minimum adsorption loss. Imbibition and CT experiments showed that the longer the imbibition distance, the better is the effect on spontaneous imbibition oil recovery. Furthermore, the solubilization coefficient and self-driving force were defined and calculated to quantitatively analyze the imbibition mechanisms. The imbibition mechanisms demonstrate that the reduction of oil/solid adhesion is due to the synergistic effect of IFT reduction and wettability alteration, and the ability to increase the imbibition distance through a larger self-driving force.

Enhanced oil recovery using nanoparticles is a promising method. However, when injected into a reservoir, nanoparticles can block pores and cause permeability damage. Therefore, enhancing their performance to lower the permeability damage effect is crucial. This study investigated the effect of pH alteration through carbon dioxide (CO2) injection on the permeability damage of limestone caused by the aluminum oxide (α-Al2O3) nanofluid. The methodology involved nanofluid alternating CO2 core flooding experiments by using nanofluids with pH of 4.5 and 2.8. After core flooding, permeability damage was calculated as a percentage of the reduction of the original permeability. The results revealed that the permeability damage in the case of nanofluid alternating CO2 injection was 23.23%. In only nanofluid with a pH of 4.5 injection case, permeability damage was 47.53%. In the 2.8 pH nanofluid injection case, permeability damage was 31.01%. The retention of nanoparticles was confirmed through scanning electron microscopy and energy dispersive X-ray analysis. Permeability damage could be attributed to a large nanoparticles’ agglomeration size, roughness of pore surfaces, and nanoparticle sedimentation. The results of the study revealed that altering pH through the α-Al2O3 nanofluid alternating CO2 injection can effectively reduce the permeability damage of limestone.

In this paper, we introduce Syntax-Enhanced Transformer Model (SET), a groundbreaking approach in the realm of Transformer-based language modeling that seeks to redefine the boundaries of linguistic analysis and comprehension. SET innovatively combine (i) the well-established high-level performance, scalability, and adaptability of traditional Transformers with (ii) a sophisticated analysis of syntactic structures. This synergy is enabled by a novel attention mechanism tailored to parse syntactic nuances and a deterministic process adept at transforming linearized parse trees into meaningful linguistic representations. Our comprehensive experiments reveal that SET significantly advance the field by surpassing existing benchmarks in sentence-level language modeling perplexity. They exhibit exceptional proficiency in tasks that require an acute awareness of syntax, setting new standards for language models in understanding complex linguistic structures. Furthermore, SET demonstrate an enhanced capability to grasp nuanced linguistic patterns that have traditionally been challenging for standard Transformer models. However, our studies also uncover a unique aspect of SET: while they excel in sentence-level tasks, their representation of sentences as singular vectors—owing to the syntactic composition constraints intrinsic to their design—introduces certain limitations in document-level language modeling. This observation points to an intriguing area for future exploration; it suggests the potential need for an alternative or complementary memory mechanism within Transformer models, one that functions independently from, yet in harmony with, syntactic structures. Such a mechanism could be pivotal in enhancing the model's ability to comprehend and process long-form texts effectively. In conclusion, SET mark a significant stride in the journey towards more sophisticated, syntax-aware language models. They offer promising insights into the integration of deep linguistic knowledge with cutting-edge machine learning techniques, potentially opening doors to a new era of natural language understanding and processing.

The Carbonic Anidrase isoform IX (hCA IX) is one of the main player in extracellular tumor pH regulation and it is known to be overexpressed in breast cancer as well as in many common tu-mors. hCA IX has shown to contribute to the growth and survival of tumor cells and its expres-sion is correlated to metastasis and resistance to therapies making it an interesting biomarker for diagnosis and potential image-guided therapy. The aim of this work is the development of an MRI Imaging probe able to target the extracellular non catalytic PG domain of CAIX. A new specific nano probe has been designed by conjugating a peptidic interactor of PG domain on the surface of a liposome loaded with Gd-based contrast agents. Mouse Mammary Adenocarcinoma Cell Line (TS/A ) has been chosen as in vitro breast cancer model to test the efficacy of the de-veloped probe. MRI results display a high selectivity towards hCA IX marker and a good sensi-tivity of the Imaging probe. These findings make this approach promising for future develop-ment of in vivo diagnostic protocols aimed at visualizing this enzyme expression.

Laser-induced periodic surface structures (LIPSS) have gained significant attention due to their ability to modify the surface morphology of materials at the micro-nanoscale and show great promise for surface functionalization application. In this study, we specifically investigate the formation of LIPSS in silicon substrates and explore their impact on Surface-Enhanced Raman Spectroscopy (SERS) applications. This study reveals a stepwise progression of LIPSS formation in silicon, involving three distinct stages of LIPSS: 1) integrated Low-Spatial-Frequency LIPSS (LSFL) and High-Spatial-Frequency LIPSS (HSFL), 2) principally LSFL and 3) LSFL at the edge of the irradiated spot, elucidating the complex interplay between laser fluence, pulse number, and resulting surface morphology. Furthermore, from an application standpoint, these high-quality multi-scale periodic patterns lead to the next step of texturing the entire silicon surface with homogeneous LIPSS for SERS application. The potential of LIPSS-fabricated silicon substrates for enhancing SERS performance is investigated using thiophenol as a test molecule. The results indicate that the Au-coated combination of LSFL and HSFL substrate showcased the highest enhancement factor (EF) of 1.38 × 10^6. This pronounced enhancement is attributed to the synergistic effects of Localized Surface Plasmon Resonance (LSPR) and Surface Plasmon Polaritons (SPPs), intricately linked to HSFL and LSFL characteristics. These findings contribute to understanding LIPSS formation in silicon and their applications in surface functionalization and SERS, paving the way for sensing platforms.

Due to combined climate and biodiversity crisis, the sustainable utilization of phytogenetic resources stands as one-way alternative while nutrient management strategies gain an increasing role in agriculture. Building on previous studies regarding the Endangered local endemic of Crete (Greece) Carlina diae (Asteraceae) with medicinal and ornamental value, this investigation focused on its pilot cultivation and fertilization (foliar or root application). Foliar application included chemical fertilizer (conventional) or integrated nutrient management (INM). Root application consisted of chemical fertilizer, biostimulant, or INM with biostimulant. Above-ground biomass content of nutrients, together with leaf chlorophyll fluorescence and colour parameters (SPAD meter, DA meter, Chroma Meter) were determined. The leaf content of chlorophyll, three key antioxidant compounds and minerals’ titers were also assessed. The fertilization scheme did not influence plant growth and visually perceived quality (leaf color and shape). Notably, foliar INM fertilization increased biomass partitioning to inflorescences (harvestable organ for either medicinal or ornamental purposes), and decreased tissue water content (facilitating processing). Considering all three antioxidants together, INM with biostimulant appeared the optimum scheme, being associated with the highest (carotenoids, phenolics) or the second highest (flavonoid) content. In C. diae, therefore, INM fertilization was optimal for upgrading yield (foliar) and herbal quality in terms of antioxidant profile (INM with biostimulant), which might be embraced as an eco-friendly approach for high quality yields.

Surface-enhanced Raman spectroscopy (SERS) can boost the pristine Raman signal by ~ 108 times that could be exploited for producing innovative sensing devices with advanced properties. However, the inherent complexity of SERS systems restricts their further applications in rapid detection, especially in situ detection in narrow aera. Here, we construct an efficient and flexible SERS-based LOP sensor by integrating Ag/Au nanocap arrays obtained by Ag/Au coating polystyrene nanospheres on the optical fiber face. We obtain rich “hotspots” at the nanogaps between neighboring nanocaps and further achieve the excellent SERS performance with the assistance of laser induced thermophoresis on the metal film that can achieve high efficiency aggregation of detected molecules. We achieve a high Raman enhancement with a low detection limitation of 10-7 mol/L for the most efficient samples based on the above sensor. This sensor also exhibits good repeatability and stability under multiple detections, revealing the potential application in situ detection based on the reflexivity of optical fiber.

Modelling both long and short-term user interests from historical data is crucial for accurate recommendations. However, unifying these metrics across multiple application domains can be challenging, and existing approaches often rely on complex, intertwined models which can be difficult to interpret. To address this issue, we propose a lightweight, plug-and-play interest enhancement module that fuses interest vectors from two independent models. After analyzing the dataset, we identify deviations in the recommendation performance of long and short-term interest models. To compensate for these differences, we use feature enhancement and loss correction during training. In the fusion process, we explicitly split long-term interest features with longer duration into multiple local features. We then use a shared attention mechanism to fuse multiple local features with short-term interest features to obtain interaction features. To correct for bias between models, we introduce a comparison learning task that monitors the similarity between local features, short-term features, and interaction features. This adaptively reduces the distance between similar features. Our proposed module combines and compares multiple independent long-term and short-term interest models on multiple domain datasets. As a result, it not only accelerates the convergence of the models but also achieves outstanding performance in challenging recommendation scenarios.

In this paper, I present a comprehensive theoretical framework for understanding surface-enhanced Raman scattering (SERS) measurements in both solution and thin film setups, focusing on electromagnetic enhancement principles. Two prevalent types of SERS substrates found in the literature are investigated: plasmonic colloidal particles, including spherical and spheroid nanoparticles, nanoparticle diameters, and thin-film-based SERS substrates like ultra-thin substrates, bundled nanorods, plasmonic, and porous thin films. The investigation explores the impact of analyte adsorption, orientation, and the polarization of the excitation laser on effective SERS enhancement factors. Notably, it considers the impact of analyte size on the SERS spectrum, by examining scenarios where the analyte is significantly smaller or larger than the hot-spot dimensions. The analysis also incorporates optical attenuations arising from the optical properties of the analyte and the SERS substrates. The findings provide possible explanations for many observations made in SERS measurements, such as variations in relative peak intensities during SERS assessments, reductions in SERS intensity at high analyte concentrations, and the occurrence of significant baseline fluctuations. The study offers valuable guidance for optimizing SERS substrate design, enhancing SERS measurements, and improving the quantification of SERS detection.

Recent advancements in neural language models, particularly attention-based architectures like the Transformer, have substantially surpassed traditional methods in various natural language processing tasks. These models adeptly generate nuanced token representations by considering contextual relations within a sequence. However, augmenting these models with explicit syntactic knowledge, such as part of speech tags, has been found to remarkably bolster their effectiveness, especially under constrained data scenarios. This study introduces the Linguistic Enhanced Transformer (LET), which integrates multiple syntactic features, showing a notable increase in translation accuracy, evidenced by an improvement of up to 1.99 BLEU points on subsets of the WMT '14 English-German dataset. Furthermore, this paper demonstrates that enriching BERT models with syntax-aware embeddings enhances their performance on several GLUE benchmark tasks.

This study investigated the characteristics of radio-frequency middle-pressure argon plasma used in the atomic layer deposition (ALD) of Al2O3 films. Based on the electrical characteristics, that is current, voltage, and phase shift between them, and stability of plasma plume, the optimum plasma power, allowing reliable switching on the plasma for any step of an ALD cycle, was determined. Spectral measurements were performed to determine the gas temperature and reactive species that could be important in the ALD process. The density of metastable argon atoms was estimated using tunable laser absorption spectroscopy. It was concluded that plasma heating of substrates did not affect film growth and proposed that the crystallization-enhancing effect of plasma was due to the action of OH radicals, produced in the plasma.

Pyridoxine is a versatile molecule that forms part of the family of B vitamins. It is used to treat and prevent vitamin B6 deficiency and certain type of metabolic disorders. Besides, pyridoxine molecule has been investigated as a suitable ligand toward metal ions. Nevertheless, the study of the magnetic properties of metal complexes containing lanthanide(III) ions and this biomolecule has been unexplored. We have synthesized and characterized a novel pyridoxine-based GdIII complex of formula [Gd(III)(pyr)2(H2O)4]Cl3 • 2 H2O (1) [pyr = pyridoxine]. 1 crystallizes in the triclinic system with space group Pī. In its crystal packing, the cationic [Gd(pyr)2(H2O)4]3+ entities are linked each other through H-bonding interactions involving non-coordinating water molecules and chloride anions. In addition, Hirshfeld surfaces of 1 were calculated to further investigate their intermolecular interactions in the crystal lattice. The study of the magnetic properties of 1 through ac magnetic susceptibility measurements reveals the occurrence of slow relaxation of magnetization in this mononuclear Gd(III) complex, this fact indicating an unusual single-ion magnet (SIM) behavior. We have also studied the relaxometric properties of 1, as a potential contrast agent for high-field MR imaging, from solutions of 1 prepared in physiological serum (0.0 - 3.2 mM range) and measured at 3 T on a clinical MR scanner. The relaxivity values obtained for 1 are larger than those of some commercial MR imaging contrast agents based on mononuclear Gd(III) systems

Fundus image registration plays a crucial role in the clinical evaluation of ocular diseases, such as diabetic retinopathy and macular degeneration, necessitating meticulous monitoring. The alignment of multiple fundus images enables the longitudinal analysis of patient progression, widening the visual scope, or augmenting resolution for detailed examinations. Currently, prevalent methodologies rely on feature-based approaches for fundus registration. However, certain methods exhibit high feature point density, posing challenges in matching due to point similarity. This study introduces a novel fundus image registration technique integrating U-Net for the extraction of feature points employing FIVES for its training and evaluation, a novel and large dataset for blood vessels segmentation, prioritizing point distribution over abundance. Subsequently, the method employs medial axis transform and pattern detection to obtain feature points characterized by the Fast Retina Keypoint (FREAK) descriptor, facilitating matching for transformation matrix computation. Assessment of the vessel segmentation achieves 0.7559 for Intersection Over Union (IoU), while evaluation on the Fundus Image Registration Dataset (FIRE) demonstrates the method’s comparative performance against existing methods, yielding a registration error of 0.596 for area under the curve, refining similar earlier methods and suggesting promising performance comparable to prior methodologies.

A fern, Polypodium aureum, possesses a specialized spore-releasing mechanism like a catapult induced by quick expansion of vaporized bubbles. This study introduces lipid-coated perfluorocarbon droplets to enable repeatable vaporization-condensation cycles, inspired by the repeatable vaporization of Polypodium aureum. Lipid-perfluorocarbon droplets have been considered not to exhibit repeatable oscillations due to bubble collapse by low surface tension of lipid layers. However, a single lipid-dodecafluoropentane droplet with a diameter of 9.17 µm shows expansion-contraction oscillations over 4,000 cycles by changing lipid composition and applying low power of 1.7 MHz ultrasound to induce partial vaporization of droplets. The optimal combinations of shell composition, droplet fabrication, and acoustic conditions can minimize damage on shell structure and quick recovery of damaged shell layers. The highly-expanding oscillatory microbubbles provide a new direction for fuel-free micro or nanobots as well as biomedical applications of contrast agents and drug delivery.

Recent advances in nanomaterials have been heavily influenced by low-dimensional nanocarbon allotropes. In particular, carbyne has attracted attention for its potential as a true one-dimensional carbon chain with sp1 hybridization. To maximize the capabilities of this material, we employ a focused data-driven inverse design approach based on the carbon nanomaterials genome concept. This involves using deep learning neural network models to identify key descriptors tied to desired properties, enabling property prediction and reverse engineering of nanocarbons. Our iterative approach entails: (i) gathering growth/property data on nanostructures; (ii) identifying informative numerical/categorical predictors; (iii) developing deep learning models mapping descriptors to properties; (iv) refining models with new insights; (v) determining required descriptors/conditions for target properties via inverse mapping; (vi) validating models by synthesizing predicted nanostructures; and (vii) enhancing models with validation data. This allows uncovering hidden growth-property connections, precisely tuning nanocarbons for desired attributes. We introduce new methodologies including exciting synergistic effects, synchronizing atomic vibrations, active screen plasma, energy-driven transformations, surface acoustic micro/nano-manipulation, doping and directed self-assembly to expose relationships and integrate insights into the inverse design flow. This research promises to accelerate discovery of next-generation low-dimensional nanocarbons with exceptional properties and applications.

Two-dimensional (2D) materials show advantages as surface enhanced Raman scattering (SERS) substrate over traditional noble metals, such as chemically inert flat surface and uniform SERS signals. However, due to the low density of free electrons of 2D materials, the enhancement mechanism is mainly restricted to chemical enhancement instead of electromagnetic enhancement, resulting a relatively low enhancement factor. In this work, we reported a sensitive 2D SERS substrate based on chemical vapor deposited MoN nanosheets with electromagnetic enhanced mechanism. The maximum enhancement factor can be 3×105 with a limit of detected concentration of 4×10-8 M, which is comparable to those noble metal SERS substrates without hot spots. The MoN nanosheets show strong surface plasmon resonance in the visible range as evidenced by the UV-vis absorption spectroscopy and first principle calculation. The MoN nanosheets SERS substrates exhibit excellent Raman signal uniformity within the nanosheets. Meanwhile, Distinct thickness dependent sensitivity was observed in the MoN nanosheets, higher sensitivity can be achieved by decreasing the thickness of the nanosheets. Furthermore, the MoN nanosheets SERS substrate also show high thermal stability, which can be annealed in air for more than 300℃ and maintain its SERS activity. The high stability of MoN nanosheets allows it to be reused for 20 cycles without obvious signal decay. The high sensitivity, stability, reusability and Raman signal uniformity, makes MoN nanosheets an ideal 2D SERS substrate for practical applications.

Gadolinium-based contrast agents (GBCA) are complexes, highly stable in vivo, used in Magnetic Resonance Imaging (MRI), administered in patients and then eliminated via renal, passing through wastewater treatment plants (WWTP) before being discarded in the receiving medium, without apparent removal. In this study, it was studied if different exposure periods to several environmental parameters (solar radiation, different salinities, temperatures and pH) will influence the stability of these complexes, namely, the Gd-DOTA. Gd-DOTA solutions were processed in a seaFAST-pico saline matrix pre-concentration and elimination system and Gd concentrations were determined by ICP-MS. Results showed that the complex remained stable in fresh, brackish and saline water environments, even when exposed to extreme temperatures (40ºC) or slightly acidic to basic conditions (6-10), for an exposure period of 96h. A small increase in the free Gd concentration was observed after 18 days when exposed to pH<4, in all tested salinities (0, 18 and 36 PSU), with a degradation increase of up to 29%, after 5 weeks of exposure in freshwater. When exposed to direct solar radiation a low Gd-DOTA degradation (4%) was observed after 24h at salinity 18 PSU and remained constant until the end of the exposure period (96h), while the remaining salinities showed negligible values.

Abstract Purpose Despite a considerable amount of literature on dual-energy-CT(DECT) iodine uptake of the head and neck, the physiologic iodine uptake of this region has not been defined yet. This study aims to establish reference values for the iodine uptake of healthy organs to facilitate clinical application. Material and Methods: Consecutive venous DECT scans of head and neck were reviewed, and unremarkable exams were included (n=617). 35 region of interest measurements were performed in 16 anatomical regions. Iodine uptake was compared among different organs/tissues and subgroup analysis was performed (male [n=403] vs female [n=214]; young [n=207] vs middle-aged [n=206] vs old [n=204]; normal weight [n=314] vs overweight [n=196] vs obese [n=107]]). Results: Overall mean iodine uptake values ranged between 0.5 and 9.4mg/ml. Women showed higher iodine concentration in the cervical vessels and higher uptake for the parotid gland, masseter muscle, submandibular glands, sublingual glands, palatine tonsils, tongue body, thyroid gland, and the sternocleidomastoid muscle than men (p0.04). With increasing age, intravascular iodine concentrations increased as well as iodine uptake for cerebellum and thyroid gland, while values for tongue and palatine tonsils were lower compared to younger subjects (p0.03). Iodine concentrations for parotid glands and sternocleidomastoid muscles decreased with higher BMI (p0.004), while normal-weighted patients showed higher iodine values inside the jugular veins, other cervical glands, and tonsils versus patients with higher BMI (p0.04). Conclusion: Physiologic iodine uptake values of cervical organs and tissues show gender-, age-, and BMI-related differences, which should be considered in clinical routine of head and neck DECT.

Poly(vinyl acetate) (PVAC) is a ubiquitous polymer in various industrial applications, including paints and adhesives. While extensive research has focused on understanding the degradation mechanisms of PVAC-based paint, under different environmental conditions, limited attention has been paid to the long-term stability of PVAC-based white glues, especially when used in artworks. This study investigates the accelerated degradation of a commercial PVAC-based white glue considered as representive of this class of materials as used in contemporary artworks, to predict its durability and assess its behavior in art objects. Through accelerated aging experiments and comparison with natural aging observed in artworks, the study reveals the formation of chromophores and the release of plasticizer as key degradation processes. Despite minimal structural modifications in PVAC, the loss of plasticizer leads to an increase in glass transition temperature, affecting the adhesive's cohesive strength and contributing to detachment of materials in artworks. The findings underscore the importance of preventive conservation measures to mitigate degradation issues in PVAC-based artworks.

The quartz tuning fork used as an acoustic sensor in Quartz-Enhanced Photo-Acoustic Spectroscopy gas detection systems is usually read-out by means of a transimpedance preamplifier, based on a low-noise operational amplifier closed in a feedback loop. The gain-bandwidth product of the operational amplifier used in the circuit is a key parameter which must be properly chosen to guarantee that the circuit works as expected. Here we demonstrate that, if the value of this parameter is not sufficiently large, the response of the preamplifier exhibits a peak at a frequency which does not coincide with the series resonant frequency of the quartz tuning fork. If this peak frequency is selected for modulating the laser bias current and is also used as reference frequency of the lock-in amplifier, a penalty results in terms of signal to noise ratio at the output of the QEPAS sensor. This worsens the performance of the gas sensing system in terms of ultimate detection limits. We show that this happens when the front-end preamplifier of the quartz tuning fork is based on some amplifier models that are typically used for such application, both when the integration time of the lock-in amplifier filter is long, to boost noise rejection, and when it is short, in order to comply with a relevant measurement rate.

Past research suggests a continuity between perception and memory, as reflected in influences of orienting of spatial attention by cues presented after a visual target offset (post-target cues) on target perception. Conducting two experiments, we tested and confirmed this claim. Our study revealed an elevated reliance on post-target cues for target detection with diminishing target visibility, leading to better performance in validly versus invalidly cued trials, indicative for contrast gain. We demonstrated this post-target cueing impact on target perception without a postcue response prompt, meaning that our results truly reflected a continuity between perception and memory rather than a task-specific impact of having to memorize the target due to a response prompt. We further showed an influence of attention by the post-target cues with cues presented away from a clearly visible target, meaning that visual interactions at the target location provided no better explanation of our results. Our results generalize prior research with liminal targets and confirm the view of a perception-memory continuum, so that visual target processing is not shielded against visuospatial orienting of attention elicited by events following offset of the visual target.

This paper introduces an innovative Particle Swarm Optimization (PSO) Algorithm in-corporating Sobol and Halton Random number samplings. It evaluates the enhanced PSO's performance against conventional PSO employing Monte Carlo Random Number Samplings. The comparison involves assessing the algorithms across nine benchmark problems and the renowned Travelling Salesman Problem (TSP). The re-sults reveal consistent enhancements achieved by the enhanced PSO utilizing Sob-ol/Halton samplings across the benchmark problems. Particularly noteworthy are the substantial improvements demonstrated by the enhanced PSO in solving the Travel-ling Salesman Problem. These findings underscore the efficacy of employing Sobol and Halton random number generation methods in enhancing algorithm efficiency.

Carbon dioxide (CO2)miscible fracturing huff and puff technology plays a pivotal role in enhancing the recovery rate of crude oil, particularly in reservoirs with challenging physical properties, strong water sensitivity, high injection pressure, and complex water injection dynamics. In this study, the oil-increasing mechanism and huff and puff effect of CO2 miscible fracturing fluid are investigated through a comprehensive experimental approach. Specifically, experiments on PVT gas injection expansion, minimum miscible pressure, and CO2 miscible fracturing huff and puff are conducted on the G fault block reservoir in J Oilfield. The findings demonstrate that injecting CO2 into reservoirs leads to oil volume expansion, viscosity reduction, and saturation pressure increase. Additionally, the inclusion of solubilizers and viscosity reducers further enhances the efficiency of crude oil extraction. Solubilizers not only improve oil recovery but also reduce the minimum miscible pressure required for effective CO2 dispersion. Furthermore, the shut-in time, permeability, and huff and puff method all have considerable impacts on huff and puff recovery rate. This study offers valuable technical insights, supporting the application of CO2 miscible fracturing huff and puff technology to enhance oil recovery in low-permeability reservoirs.

Gold nanohole arrays are periodic metastructures gathering huge interest for biosensing applica-tions. The grating-like structure defines their plasmonic mode features and their angular disper-sion can be used to highlight efficiently their interaction with the fluorescence emission of a properly tuned fluorophore. Resorting to a properly tuned/engineered/optimised plasmonic na-nohole array and a commercial organic dye, we performed an accurate resolved angle-resolved optical characterization. The plasmonic fingerprints was consequently identified as a modification of the dye photoluminescence signal in terms of both spectral redistribution and enhancement. Interestingly, by analyzing the results, an advantageous measurement configuration can be iden-tified to better engineer a suitable platform for efficiency maximization in plasmon-enhanced flu-orescence-based applications. Therefore, the coupling mechanism with the plasmonic modes, and nanostructure properties can be carefully co-optimized.

The sustainability of cities often changes as rapid urban developments and population growth affect the carrying capacity. Understanding the dynamics of carrying capacity then becomes crucial for tourist-oriented cities. This study focused on Baguio City, the "Summer Capital of the Philippines," attracting large crowds on holidays and actively promoting various events on non-holidays, thereby having temporal context variations classified as regular days, days with events, and holidays. Using the enhanced urban carrying capacity load number (EUCCLN) model, load number (LN) changes for different temporal contexts are calculated based on spatial indicators grouped into air, traffic, economy, and waste. The city experiences the worst pressures on air quality during holidays with $99.23\%$ districts under very high to critical levels followed by regular and days with events. However, the total LN is balanced by favorable economic conditions with only $9.23\%$ at critical. EUCCLN effectively pinpoints areas experiencing critical states at any time, advocating targeted government monitoring. We demonstrate that Night Time Light, for places with no economic data available, can be used as a proxy to highlight areas requiring improved urban vibrancy. This work suggests that EUCCLN monitoring urban pressures can easily be expanded to nowcasting with real-time data.

In the rapidly evolving field of sentiment analysis, the introduction of Transformer-based architectures, particularly the BERT model, has markedly improved accuracy levels, setting new standards in the analysis of textual sentiment. These advancements have been instrumental in enhancing the model's ability to grasp the nuances and complexities inherent in human language, thereby providing deeper insights into the sentiment expressed in various texts. However, the impressive performance of such deep learning models comes at the cost of increased computational demands and a lack of transparency in their decision-making processes. These challenges have reignited interest in rule-based sentiment analysis methods, which utilize sentiment lexicons for a more straightforward and computationally economical approach to determining text sentiment. Despite being overshadowed by the rise of machine learning models in recent years, these lexicon-based methods possess distinct advantages, including ease of interpretation and lower resource requirements, making them particularly appealing for certain applications. This paper seeks to re-evaluate the relevance and effectiveness of two prominent lexicon-based sentiment analysis methods, SO-CAL and SentiStrength, which have been specifically adapted for the language, in light of the advancements represented by Transformer-based models like SentBERT. Through a comprehensive comparative analysis, we examine the performance of these methodologies in contrast to SentBERT across an extensive collection of 16 text corpora, spanning a variety of genres and contexts. Our findings reveal a nuanced landscape of performance, where SentBERT's advanced capabilities typically afford it a significant advantage in accurately capturing sentiment. Nevertheless, in a surprising turn, the SO-CAL method exhibits exceptional performance on a substantial portion of the datasets, underscoring the continuing value and potential of lexicon-based approaches in sentiment analysis. This study not only highlights the strengths and weaknesses of both deep learning and lexicon-based methods but also opens the door for future hybrid approaches that could leverage the best of both worlds to achieve even greater accuracy and efficiency in sentiment analysis tasks.

This review paper delves into the multifaceted aspects of pineapple cultivation, focusing on morphology studies, harvesting challenges, and mechanization efforts. Pineapple, renowned for its commercial value and unique flavor, holds a prominent position in global agriculture, with India alone producing 19.64 lakh tonnes annually. However, the hilly terrains of regions like northeastern India pose significant hurdles to traditional harvesting methods, necessitating innovative solutions. Understanding the morphology of pineapple plants is crucial for optimizing cultivation practices and designing efficient harvesting equipment. Insights from various studies shed light on leaf structure, fruit maturity, and growth patterns, providing valuable information for engineering tailored solutions. Mechanization endeavors, including semi-mechanized harvesting machines and semi-manual harvesters, demonstrate promising results in improving efficiency and reducing labor-intensive practices. Despite challenges such as increased crop losses and operational costs, continued research and development in mechanization hold the key to sustainable pineapple cultivation. This paper underscores the importance of integrating morphology studies and mechanization efforts to address the unique challenges faced by pineapple farmers, particularly in hilly terrains, and highlights the need for ongoing innovation to ensure the long-term sustainability of pineapple cultivation.

Chemical flooding methods are used to recover the remaining oil after water flooding, and surfactant-polymer (SP) flooding is an important chemical flooding technology. It is of great significance to design and screen high-performance oil displacement agents in order to overcome the increasingly challenging high temperature (>70 ℃) and high salinity (>10,000 mg/L) reservoirs. Based on the characteristics of high temperature (70 ℃) and high salinity (151,000 mg/L) in the Qinghai Gasi reservoir, the performance of the SP flooding system was studied. This study considered interfacial tension, emulsification, viscosity, compatibility, and oil displacement efficiency. The selected formula demonstrated high resistance to both salinity (151,000 mg/L) and temperature (70 ℃), characterized by a low oil-water interfacial tension (10-2 mN/m) and high viscosity (18.13 mPa.s). After water flooding achieved an oil recovery rate of 64.64%, the subsequent replacement rate of crude oil increased by 26.95%, confirming that SP flooding can be used as a technology for enhancing oil recovery in high-temperature, high-salinity reservoirs represented by Qinghai Gasi reservoirs.

We present contrast information, a novel application of some specific cases of relative entropy measures, designed to be useful for cognitive modelling of sequential perception of continuous signals. We explain the relevance of entropy in cognitive modelling of music and language. Then, as a first step to demonstrating the utility of constrast information for that purpose, we show empirically that its discrete case correlates well with existing successful cognitive models in the literature. We explain some interesting properties of constrast information. Finally we propose future work towards a cognitive architecture that uses it.