Degradation Procedure Research Articles

Constructing a Type-II CdS/Bi2MoO6 Heterostructure: Promoting Photocatalytic Degradation of Contaminants.

Constructing a heterostructure is regarded as one of the most favorable approaches to attaining the separation ability of photogenerated carriers and strengthening photocatalysis efficiency. In this study, a CdS/Bi2MoO6 type-II heterostructure was constructed through a hydrothermal technique. The photocatalytic test result shows that the degradation efficiency of rhodamine B (RhB) and tetracycline (TC) over CS/BMO-1 was 100 and 92% under visible light, respectively, which is the highest compared to other samples. The exceptional photocatalytic efficiency is principally associated with generating an inherent electric field within a type-II heterostructure, effectively restraining the recombination of photogenerated electron hole pairs. The intermediate products during the photocatalytic degradation of RhB and TC were identified through liquid chromatography-mass spectrometry, and the hypotheses were formulated regarding the corresponding photodegradation mechanisms. Furthermore, the outcomes of capture tests exhibited that the primary active species were •O2- and h+, and a mechanism of the photocatalytic degradation procedure has been proposed.

β-cyclodextrin-modified cobalt oxide as a heterogeneous catalyst for efficient peroxymonosulfate activation towards the degradation of Ciprofloxacin: Performance and degradation pathways

In this study, β-cyclodextrin-modified cobalt oxide (Co3O4@β-CD) composites were developed through hydrothermal processes and employed for heterogeneous activation of peroxymonosulfate (PMS) for the removal of ciprofloxacin (CIP) antibiotics. The results revealed that the degradation of CIP by Co3O4@β-CD/PMS was 99.13 %, which was significantly higher than the degradation of CIP by Co3O4/PMS (79.06 %) in a 25-minute period under optimal conditions ([Co3O4@β-CD] = 0.25 g/L, [PMS] = 0.25 mM, pH=7.0). The enhanced degradation of CIP contributed to the greater surface area (162.84 m2/g) of the Co3O4@β-CD to the Co3O4 (121.47 m2/g). Besides, the study assessed the impact of several reaction variables and interrupting anions on the abatement of CIP. A possible degradation procedure for CIP has been established by identifying reaction intermediates. The activation of PMS was achieved by both radical and non-radical routes. Further, Co3O4@β-CD exhibited remarkable stability and maintained its degrading efficiency after five consecutive cycles.

Development and validation of stability-indicating method of etrasimod by HPLC/DAD/MS/MS technique with greenness profiling

Etrasimod, a novel selective sphingosine-1-phosphate receptor modulator, was recently approved by the U.S. Food and Drug Administration and the European Medicinal Agency for the treatment of moderately to severely active ulcerative colitis in adults. In this research, the forced degradation study as an integral part of drug product and packaging development, which generates data on degradation mechanisms, is published. The development and validation of the stability-indicating method using a superior high-performance liquid chromatography technique coupled with a diode array detector and tandem mass spectrometer was performed to support the forced degradation study and monitor the formation of degradation products. Etrasimod demonstrated good stability under elevated temperature and basic stress conditions, while acidic hydrolysis, oxidative, and photolytic degradation produced eight degradation products. The knowledge of degradation products will be useful in the long-term stability study for establishing the acceptance criteria of etrasimod as a drug substance and dosage form during quality control and stability assessment. The eco-friendliness of the developed forced degradation procedure was evaluated using various greenness appraisal tools. The green metric tools showed that the forced degradation procedure obeys eco-friendly conditions.

Temperature sensitivity and transition kinetics of uniform corrosion of zirconium alloys in superheated steam

Corrosion transition during uniform corrosion of zirconium alloys receives much attention since it is the major degradation procedure. However, predicting the time and oxide thickness at transition has been hindered by the lack of knowledge about transition kinetics and how it responds to varied temperatures. Current study investigated the temperature-sensitivity of corrosion kinetics, transition behavior and microstructures of various zirconium alloys corroded in superheated steam ranging from 390 °C/10.3 MPa to 455 °C/10.3 MPa by autoclave experiment and microscopy analyses. Transition time was found to follow Arrhenius-type relationship with temperature for the first time. Both the transition oxide thickness and metastable oxide thickness increased with temperature, which was theoretically deduced and experimentally confirmed. In Zr-4 oxides, a transition thickness varying from 3.3 μm at 390 °C to 4.2 μm at 455 °C was observed. Microstructure results presented rather large HCP-ZrO particles (200∼400 nm) at O/M interface and they were even larger at the protruded positions. An intense sub-stoichiometric atmosphere was identified at O/M interface, promoting the growth of metastable oxides. The activation energy of transition kinetics was 86∼114 kJ/mol, which is close to diffusion activation energy of oxygen in tetragonal zirconia. A new model based on parabolic-law empirical relationship was thus proposed to predict transition kinetics. Predictions regarding the time to oxidation breakaway at 900–1000 °C were reported, and the results were in good agreement with the experimental data.

Adaptive Responding to Stimulus-Outcome Associations Requires Noradrenergic Transmission in the Medial Prefrontal Cortex.

A dynamic environment, such as the one we inhabit, requires organisms to continuously update their knowledge of the setting. While the prefrontal cortex is recognized for its pivotal role in regulating such adaptive behavior, the specific contribution of each prefrontal area remains elusive. In the current work, we investigated the direct involvement of two major prefrontal subregions, the medial prefrontal cortex (mPFC, A32D + A32V) and the orbitofrontal cortex (OFC, VO + LO), in updating pavlovian stimulus-outcome (S-O) associations following contingency degradation in male rats. Specifically, animals had to learn that a particular cue, previously fully predicting the delivery of a specific reward, was no longer a reliable predictor. First, we found that chemogenetic inhibition of mPFC, but not of OFC, neurons altered the rats' ability to adaptively respond to degraded and non-degraded cues. Next, given the growing evidence pointing at noradrenaline (NA) as a main neuromodulator of adaptive behavior, we decided to investigate the possible involvement of NA projections to the two subregions in this higher-order cognitive process. Employing a pair of novel retrograde vectors, we traced NA projections from the locus ceruleus (LC) to both structures and observed an equivalent yet relatively segregated amount of inputs. Then, we showed that chemogenetic inhibition of NA projections to the mPFC, but not to the OFC, also impaired the rats' ability to adaptively respond to the degradation procedure. Altogether, our findings provide important evidence of functional parcellation within the prefrontal cortex and point at mPFC NA as key for updating pavlovian S-O associations.

Coupled image and kernel prior learning for high-generalized super-resolution

Deep convolution neural networks (DCNNs) have demonstrated great success on single image super resolution, where most existing methods aim to construct a deep model in an fully-supervised way using large amount of synthetic image pairs under ideal degradation assumption. The super-resolution performance would be significantly degraded for the low-resolution images captured under uncontrolled imaging conditions with complicated degradation procedures. To handle the above limitations, this work proposes a high-generalized image super-resolution framework by synergistically learning the latent image and the degradation process to achieve the specific priors for an under-studying observation in an unsupervised manner. Specifically, we incorporate dual branches of networks to configure our framework, where one is structured with both convolution and transformer blocks to learn local-to-global prior to generate high-quality image while the other aims to learn the kernel prior with a simple convolution-based architecture. The kernel prior subnet is pre-trained to enhance the stability of the joint optimization for the overall unsupervised learning procedure. With the estimated degradation kernel and target image, we produce the approximated low-resolution version with a convolution-based degradation block to formulate the loss function for the specific learning. Moreover, to pursue visually plausible image generation, we further incorporate a perceptual loss by leveraging a pre-trained discriminator in Gan-based SR model. Extensive experiments on several benchmark datasets have demonstrated the effectiveness of our proposed high-generalized super-resolution model, manifesting superiority over both supervised and unsupervised state-of-the-art SR models.

Identification and Structural Characterization of Degradation Products of Linagliptin by Mass Spectrometry Techniques.

As part of the development and production of pharmaceuticals, the purity of Active Pharmaceutical Ingredients stands as a fundamental parameter that significantly influences the quality, safety, and efficacy of the final drug product. Impurities in Active Pharmaceutical Ingredients are various unwanted substances that can appear during the whole manufacturing process, from raw materials to the final product. These impurities can stem from multiple sources, including starting materials, intermediates, reagents, solvents, and even degradation products resulting from exposure to environmental factors such as heat, light, or moisture. Their presence can potentially compromise the therapeutic effect of the drug, introduce unexpected side effects, or even pose safety risks to patients. This study aims to conduct the forced degradation of linagliptin and subsequently attempt to identify the resulting degradants. The degradation procedures were carried out in accordance with the guidelines of the International Committee for Harmonization. The degradation profile of linagliptin was investigated under various conditions, including acid hydrolysis, alkaline hydrolysis, oxidation, heat, and light exposure, utilizing ultra-performance liquid chromatography connected to a photo array detector. Identification and characterization of the degradation products were achieved using an ultra-performance liquid chromatography coupled with a single quadrupole detector mass spectrometer and also a liquid chromatography coupled with a high-resolution mass spectrometry. The identified degradation products demonstrate that linagliptin is particularly susceptible to degradation when exposed to acid and peroxide. Whereas, no significant degradation effects were observed under alkali, thermolytic, and photolytic conditions.

Hierarchical Similarity Learning for Aliasing Suppression Image Super-Resolution.

As a highly ill-posed issue, single-image super-resolution (SISR) has been widely investigated in recent years. The main task of SISR is to recover the information loss caused by the degradation procedure. According to the Nyquist sampling theory, the degradation leads to the aliasing effect and makes it hard to restore the correct textures from low-resolution (LR) images. In practice, there are correlations and self-similarities among the adjacent patches in the natural images. This article considers the self-similarity and proposes a hierarchical image super-resolution network (HSRNet) to suppress the influence of aliasing. We consider the SISR issue in the optimization perspective and propose an iterative solution pattern based on the half-quadratic splitting (HQS) method. To explore the texture with local image prior, we design a hierarchical exploration block (HEB) and progressive increase the receptive field. Furthermore, multilevel spatial attention (MSA) is devised to obtain the relations of adjacent feature and enhance the high-frequency information, which acts as a crucial role for visual experience. The experimental result shows that HSRNet achieves better quantitative and visual performance than other works and remits the aliasing more effectively.

Photo-Fenton efficient degradation of organic pollutants over S-scheme ZnO@NH2-MIL-88B heterojunction established for electron transfer channel

Combining photocatalysts with Fenton technology can improve the catalytic properties of materials and achieve efficient degradation of organic pollutants. However, preparing low-cost catalysts using simple methods remains a challenge. This paper selected a more environmentally friendly and cost-effective semiconductor material, zinc oxide, for the modification of NH2-MIL-88B and prepared a new S-scheme heterojunction photo-Fenton catalyst ZnO@NH2-MIL-88B (ZMFe-x) by a simple solvothermal method. Moreover, the Zn-O-Fe bonds that were formed between the interfaces enabled a fast channel for the photoelectron transport that was created by photoexcitation from the ZnO conduction band to the NH2-MIL-88B valence band. This allowed the ZMFe-x catalysts to have better removal performance for organic pollutants in the photo-Fenton reaction. The dominating role of hydroxyl radicals in the degradation procedure was determined by ESR analysis and free radical trapping experiments, and the degradation mechanisms and pathway of contaminants were predicted by intermediate analysis and DFT calculations. This study provides a stable and effective new strategy for preparing MOFs catalysts for removing various pollutants.

PVA-based bulk microneedles capable of high insulin loading and pH-triggered degradation for multi-responsive and sustained hypoglycemic therapy.

"Closed-loop" insulin-loaded microneedle patche shows great promise for improving therapeutic outcomes and life quality for diabetes patients. However, it is typically hampered by limited insulin loading capacity, random degradation, and intricate preparation procedures for the independence of the "closed-loop" bulk microneedles. In this study, we combined the solubility of microneedles and "closed-loop" systems and designed poly(vinyl alcohol)-based bulk microneedles (MNs@GI) through in situ photopolymerization for multi-responsive and sustained hypoglycemic therapy, which significantly simplified the preparation process and improved insulin loading. GOx/insulin co-encapsulated MNs@GI with a phenylboronic ester structure improved glycemic responsiveness to control the insulin release under high glucose conditions and reduced inflammation risk in the normal skin. MNs@GI could further degrade to increase insulin release due to the crosslinked acetal-linkage hydrolysis in the presence of gluconic acid, which was caused by GOx-mediated glucose-oxidation in a hyperglycemic environment. The in vivo results showed that MNs@GI effectively regulated glycemic levels within the normal range for approximately 10 h compared to that of only insulin-loaded microneedles (MNs@INS). Consequently, the highly insulin-loaded, multi-responsive, and pH-triggered MN system has tremendous potential for diabetes treatment.

Size exclusion chromatography as green support for forced degradation study of adalimumab.

Size exclusion chromatography (SEC) has become a powerful tool for analysing size variants of biologic drugs in their native form. Modern SEC can be defined by the use of chromatographic columns packed with sub-3 µm particles, allowing an increase in method throughput compared to that of conventional SEC. We performed the forced degradation study of adalimumab, the first genetically engineered fully humanised immunoglobulin G1 monoclonal antibody, and evaluated tha possibilities of an advanced SEC column packed with sub-3 µm particles for elucidation of the degradation pathway. Our results revealed the main adalimumab degradation products to be antibody fragments. Acidic and basic conditions had the most intensive effect on the degradation of the adalimumab while the drug exhibits relative stability under thermal and photolytic stress conditions. The AGREE and AGREEprep calculators were used for the evaluation of the environmental performance of the forced degradation procedure. The results of the green score evaluation are presented as round pictograms with a circle in the centre that shows the overall score of 0.81 and 0.61, respectively. Both pictograms are highlighted in green, indicating the eco-friendly conditions.

Theoretical analysis for free vibration of submerged conical motor stator

The conical rim-driven motor stator is a structure with variable thickness and non-standard boundaries, which can be treated as an orthotropic conical shell. To prevent resonance and reduce electromagnetic noise, a modal analysis of the stator is necessary. This paper presents an analytical model for the free vibration of the conical stator in both onshore and underwater environments. Due to the relatively large thickness of the motor stator, the first-order shear deformation theory (FSDT) is employed. The fluid loading is calculated by discretizing the conical shell into a series of narrow cylindrical shells featuring diverse radii and thickness. The resulting equations are solved employing the transfer matrix method (TMM), which is capable of different types of boundary conditions (BCs). The convergence and accuracy of the proposed method are validated through a comparative analysis involving numerical simulations and outcomes derived from the thin shell theory. The importance of considering shear deformation and rotatory inertia in determining the natural frequency of motor stators is demonstrated. Finally, the impact of fluid loading on the vibration behavior of stators with various geometric parameters and boundary conditions are investigated and discussed. The proposed model presents a precise and convenient approach for analyzing the free vibration of submerged conical motor stators, and can be extended to conventional cylindrical motor stators through appropriate degradation procedures.

Biowaste-derived Ni/NiO decorated-2D biochar for adsorption of methyl orange

Eco-friendly carbothermal techniques were used to synthesize nanocomposites of biowaste-derived Ni/NiO decorated-2D biochar. The use of chitosan and NiCl2 in the carbothermal reduction technique was a novelty to synthesize the Ni/NiO decorated-2D biochar composite. Potassium persulfate (PS) was found to be activated by Ni/NiO decorated-2D biochar, which is thought to oxidize organic pollutants through an electron pathway designed by the reactive complexes formed between PS and the Ni/NiO biochar surface. This activation led to the efficient oxidation of methyl orange and organic pollutants. Analyzing Ni/NiO decorated-2D biochar composite before and after the methyl orange adsorption and degradation procedure allowed us to report on the process of its elimination. The Ni/NiO biochar with PS activation showed higher efficiency than Ni/NiO decorated-2D biochar composite as this material was able to degrade over 99% of the methyl orange dye. The effects of initial methyl orange concentration, dosages effect, solution pH, equilibrium studies, kinetics, thermodynamic studies, and reusability were examined and evaluated on Ni/NiO biochar.

Monitoring biological degradation of historical stone using hyperspectral imaging

ABSTRACT Stone is one of the most common materials used as a building material in central Europe for centuries. Historical objects are endangered by degradation procedures coming from physical, chemical and biological weathering agents.The weathering process itself should be analysed in detail in order to prevent historical objects by application of proper restoration cleaning techniques. Within our research, a historical sandstone block was analysed during time to monitor biological changes on the surface. The object of interest is situated in the immediate vicinity of Charles Bridge in Prague, which is protected as a UNESCO heritage site. This site was chosen due to high overall humidity all year long. For investigation of the year- round process of biodegradation hyperspectral sensor was used. In the first place, data were processed using four vegetation indices (NDVI, RGRI, CRI1 and VREI1). All vegetation indices indicate that vegetation is thriving and subject to normal seasonal change. The second chosen method of data processing is to use spectral reflectance curves and their subsequence processing by Spectral Angle Mapper (SAM) classification algorithms. A decline in vegetation with the onset of autumn and during the winter months was detected.

Degradation of salicylhydroxamic acid in mineral beneficiation wastewater by dielectric barrier discharge and La-Fe3O4-doped activated carbon: Parametric optimization, kinetics, activation process, and transformation pathway

In this study, the degradation of salicylhydroxamic acid (SHA) in industrial beneficiation wastewater was investigated using dielectric barrier discharge (DBD) and La-Fe3O4-doped activated carbon (La-Fe3O4/AC). The physical and chemical properties of La-Fe3O4/AC were studied using several characterization techniques including scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The response surface methodology was used to optimize three critical experimental parameters of the catalyst: its dosage and the mass ratios of La and Fe3O4. These parameters contributed to the SHA degradation in the following decreasing order: mass ratio of La > catalyst dosage > mass ratio of Fe3O4. The SHA degradation efficiency reached 98.6%, and the synergistic factor was 2.83 at a peak-to-peak discharge voltage of 23 kV. The results showed that the DBD-La-Fe3O4/AC system improved the SHA degradation efficiency and exhibited a significant synergistic effect. Pb2+ and Cu2+ slightly increased the SHA degradation efficiency. Quenching experiments on activated substances confirmed that •OH and O2– were crucial to the degradation of SHA. The O3 and H2O2 generated by the DBD-catalyst system were absorbed by the La-Fe3O4/AC catalyst to produce more •OH. Ten main intermediates were detected in the degradation process of the DBD-catalyst system using HPLC-MS, and three degradation procedures were proposed.

Impedance-based health indicators determination for degradation diagnosis and fault identification of lithium-ion batteries under extreme operating conditions

Research is underway on ex-situ and in-situ methods for diagnosing the degradation of performance in lithium-ion batteries (LIBs) under various environmental conditions. Incremental capacity analysis (ICA) and electrochemical impedance spectroscopy (EIS) are a non-destructive in-situ method for determining battery health during operation. An electric vehicle (EV) operates for a long time under various environment and load conditions, so it is required to additionally investigate the battery degradation under extreme operating conditions. ICA-based and impedance-based health indicator (HI) are generally known to be capable of diagnosing a battery degradation mode (DM). Most of the EIS and ICA literatures are conducted at operating conditions, so it is questionable whether DM can be classified under extreme condition such as mechanical and high temperature conditions. This paper extracts impedance-based and ICA-based HI for diagnosing the soundness of lithium-ion batteries and proposes the optimal HI that can classify DM under extreme operating conditions. The degradation procedure was performed under extreme operating conditions, such as 60 °C temperature and vibration. The validity of the HIs was verified by comparing ICA-based and impedance-based HIs through environmental tests.

Electroreductive Defluorination of Unsaturated PFAS by a Quaternary Ammonium Surfactant-Modified Cathode via Direct Cathodic Reduction.

Remediation of per- and polyfluoroalkyl substances (PFAS) in groundwater remains a technological challenge due to the trace concentrations of PFAS and the strength of their C-F bonds. This study investigated an electroreductive system with a quaternary ammonium surfactant-modified cathode for degrading (E)-perfluoro(4-methylpent-2-enoic acid) (PFMeUPA) at a low cathodic potential. A removal efficiency of 99.81% and defluorination efficiency of 78.67% were achieved under -1.6 V (vs Ag/AgCl) at the cathode modified by octadecyltrimethylammonium bromide (OTAB). The overall degradation procedure started with the adsorption of PFMeUPA onto the modified cathode. This adsorption process was promoted by hydrophobic and electrostatic interactions between the surfactants and PFMeUPA, of which the binding percentage, binding mode, and binding energy were determined via molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The step-wise degradation pathway of PFMeUPA, including reductive defluorination and hydrogenation, was derived. Meanwhile, C-F bond breaking with direct electron transfer only was achieved for the first time in this study, which also showed that the C═C bond structure of PFAS facilitates the C-F cleavage. Overall, this study highlights the crucial role of quaternary ammonium surfactants in electron transfer and electrocatalytic activities in the electroreductive system and provides insights into novel remediation approaches on PFAS-contaminated groundwater.

Multivariate Chemometric Comparison of Forced Degradation and Electrochemical Oxidation LC-MS Profiles of Maraviroc.

In this study, nine forced degradation products of maraviroc were found using chemometric analysis. This antiretroviral drug was subjected to photolytic, oxidative, as well as neutral, basic and acidic hydrolysis stress conditions. Additionally, its electrochemical transformation on platinum, gold and glassy carbon screen-printed electrodes was examined. This study showed that maraviroc is especially susceptible to UVA, H2O2 and electrochemical degradation, while being resistant to neutral and acidic hydrolysis. A cluster analysis showed that the electrochemical transformation, with particular reference to the platinum electrode, is able to partially simulate the forced degradation processes, especially in the context of redox reactions. These findings indicate that the electrochemical methods can be considered as quick and relatively low-cost supplements to the commonly applied forced degradation procedures.

Zero-Shot Blind Learning for Single-Image Super-Resolution

Deep convolutional neural networks (DCNNs) have manifested significant performance gains for single-image super-resolution (SISR) in the past few years. Most of the existing methods are generally implemented in a fully supervised way using large-scale training samples and only learn the SR models restricted to specific data. Thus, the adaptation of these models to real low-resolution (LR) images captured under uncontrolled imaging conditions usually leads to poor SR results. This study proposes a zero-shot blind SR framework via leveraging the power of deep learning, but without the requirement of the prior training using predefined imaged samples. It is well known that there are two unknown data: the underlying target high-resolution (HR) images and the degradation operations in the imaging procedure hidden in the observed LR images. Taking these in mind, we specifically employed two deep networks for respectively modeling the priors of both the target HR image and its corresponding degradation kernel and designed a degradation block to realize the observation procedure of the LR image. Via formulating the loss function as the approximation error of the observed LR image, we established a completely blind end-to-end zero-shot learning framework for simultaneously predicting the target HR image and the degradation kernel without any external data. In particular, we adopted a multi-scale encoder–decoder subnet to serve as the image prior learning network, a simple fully connected subnet to serve as the kernel prior learning network, and a specific depthwise convolutional block to implement the degradation procedure. We conducted extensive experiments on several benchmark datasets and manifested the great superiority and high generalization of our method over both SOTA supervised and unsupervised SR methods.

High-Performance Integrated rGO-[Polymeric Ionic Liquid] [Heteropolyanions] for Catalytic Degradation of Azo Dyes

Polymeric ionic liquid (such as poly[ViEtIm]Br)-modified reduced graphene oxide (rGO), rGO-poly[ViEtIm]Br, was nominated as an open carrier to construct a degradation platform. The large specific surface of rGO together with the anion-exchange property of poly[ViEtIm]Br terminals led to the wide growth of heteropolyanions (like [PW12O40]3-, [PMo12O40]3-, and [SiW12O40]4-), thus assembling the integrated catalyst rGO-poly[ViEtIm][heteropolyanions]. The grafted poly[ViEtIm]Br provided an anchor point to interlink the polar heteropolyanions and the nonpolar rGO substrate, endowing this graphene-based catalyst with excellent dispersibility. The adequate exposure of heteropolyanions further promoted the decolorization capability during the degradation procedure. Morphology, structure, and properties of materials were confirmed and monitored via transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), ultraviolet-visible (UV-vis) spectroscopy, etc. rGO-poly[ViEtIm][PW12O40] was selected as the optimal catalyst with degradation efficiency toward methyl orange reaching 98.7% in 3 h. In addition, the excellent structural stability of the catalyst improved the decolorization efficiency, which reached 95% after recycling five times.