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Electrochemical energy storage is one of the effective ways that can address the mentioned issues as alternative energy/power produced through solar or windmills can effectively be stored for continuous usage. Hybrid/Asymmetric supercapacitors can deliver a significant amount of power density as well as increased energy density with better rate capability and longer lifespan. The fluffy carbonized hexagonal KCoPO4 synthesized via a simple sol‐gel method accompanied by calcination has delivered high capacitance and longer cyclibility as a positive electrode in aqueous asymmetric supercapacitors. The fluffy carbonized hexagonal KCoPO4 exhibited a specific capacitance equal to 725 F/g at 0.5 A/g current density with excellent cyclic stability. The predominant intercalative pseudocapacitive charge storage behavior seems to be the reason behind the high capacitance of the electrode due to the active involvement of Co2+/3+ redox couple mediate charge storage as intercalative (inner) and capacitive, (outer) surface charges storage on the electrode were close to 37 % and 63 % respectively. Aqueous Asymmetric supercapacitor mode with KCoPO4 being a positive electrode and activated carbon being a negative electrode (KCoPO4//AC) was designed to address its performance in 2 M KOH aqueous electrolyte. The fabricated device in AASc mode (AC//KCoPO4) achieved the highest energy density close to 121.1 Wh/kg with a high power density of 6945 W/kg in the potential window of 1.5 V in 2 M KOH electrolyte. [ABSTRACT FROM AUTHOR]

This study evaluated 14 new 4,5,6,7‐tetrabromo‐1H‐benzo[d][1,2,3]triazole derivatives (3a‐n) for their antimicrobial activities, identifying compound 3k as the most effective. In vivo oral toxicity tests confirmed its non‐toxic nature. Predictive ADME analysis indicated favorable drug development properties. Molecular docking and dynamics studies were performed to investigate the interactions of compound 3k with Mycobacterium TB (PDB ID 2X22) and glucosamine‐6‐phosphate synthase (PDB ID 2VF5). The reactivity properties and reactive sites were determined using DFT‐derived HOMO and LUMO orbitals, along with MEP, and ESP maps, providing insights into the electron density, electrophilicity, and nucleophilicity. The electronic properties of the TD‐DFT and IEFPCM models were analyzed in solvents such as acetonitrile, ethanol, and DMSO and results were compared using UV‐Vis spectroscopy. Structural–activity relationship (SAR) investigations elucidated biological activities. [ABSTRACT FROM AUTHOR]

Facial expression recognition (FER) plays a vital role for applications based on human–computer interaction. In the past few years, many deep learning models have been proposed for FER, but their performance is limited due to challenges such as variation in head pose, occlusion, illumination, etc. Moreover, existing models consider input image through holistic view without giving attention to features relevant to expressions. In this work, we propose a deep fusion framework for FER which employs self-attention mechanism to resolve this issue. Furthermore, to improve feature representation of the images, the proposed model transforms the input image to wavelet domain through discrete wavelet transform. The framework employs two parallel branches for shallow and deep features which are fused for better feature representation. The proposed model is evaluated on posed and in-the-wild datasets: CK+, JAFFE, MUG, YALE, RAF, and experimental results validate the effectiveness of the model. [ABSTRACT FROM AUTHOR]

The movement of organic anionic drugs across cell membranes is partly governed by interactions with SLC and ABC transporters in the intestine, liver, kidney, blood–brain barrier, placenta, breast, and other tissues. Major transporters involved include organic anion transporters (OATs, SLC22 family), organic anion transporting polypeptides (OATPs, SLCO family), and multidrug resistance proteins (MRPs, ABCC family). However, the sets of molecular properties of drugs that are necessary for interactions with OATs (OAT1, OAT3) vs. OATPs (OATP1B1, OATP1B3) vs. MRPs (MRP2, MRP4) are not well-understood. Defining these molecular properties is necessary for a better understanding of drug and metabolite handling across the gut–liver–kidney axis, gut–brain axis, and other multi-organ axes. It is also useful for tissue targeting of small molecule drugs and predicting drug–drug interactions and drug–metabolite interactions. Here, we curated a database of drugs shown to interact with these transporters in vitro and used chemoinformatic approaches to describe their molecular properties. We then sought to define sets of molecular properties that distinguish drugs interacting with OATs, OATPs, and MRPs in binary classifications using machine learning and artificial intelligence approaches. We identified sets of key molecular properties (e.g., rotatable bond count, lipophilicity, number of ringed structures) for classifying OATs vs. MRPs and OATs vs. OATPs. However, sets of molecular properties differentiating OATP vs. MRP substrates were less evident, as drugs interacting with MRP2 and MRP4 do not form a tight group owing to differing hydrophobicity and molecular complexity for interactions with the two transporters. If the results also hold for endogenous metabolites, they may deepen our knowledge of organ crosstalk, as described in the Remote Sensing and Signaling Theory. The results also provide a molecular basis for understanding how small organic molecules differentially interact with OATs, OATPs, and MRPs. [ABSTRACT FROM AUTHOR]

Brain tumor is an extremely dangerous disease with a very high mortality rate worldwide. Detecting brain tumors accurately is crucial due to the varying appearance of tumor cells and the dimensional irregularities in their growth. This poses a significant challenge for detection algorithms. Currently, there are numerous algorithms utilized for this purpose, ranging from transform-based methods to those rooted in machine learning techniques. These algorithms aim to enhance the accuracy of detection despite the complexities involved in identifying brain tumor cells. The major limitation of these algorithms is the mapping of extracted features of a brain tumor in the classification algorithms. To employ a combination of transform methods to extract texture feature from brain tumor images. This paper employs a combination of transform methods based on sub band decomposition for texture feature extraction from MRI scans, hybrid feature optimization methods using firefly and glow-worm algorithms for selection of feature, employment of MKSVM algorithm and stacking ensemble classifier for classification and application of the feature of fusion of different feature extraction methods. The algorithm under consideration has been put into practice using MATLAB, utilizing datasets from BRATS (Brain Tumor Segmentation) for the years 2013, 2015, and 2018. These datasets serve as the foundation for testing and validating the algorithm’s performance across different time periods, providing a comprehensive assessment of its effectiveness in detecting brain tumors. The proposed algorithm achieves maximum detection accuracy, detection sensitivity and specificity up to 98%, 99% and 99.5% respectively. The experimental outcomes showcase the efficiency of the algorithm in detection of brain tumor. The proposed work mainly contributes in brain tumor detection in the following aspects: a) use of combination of transform methods for texture feature extraction from MRI scans b) hybrid feature selection methods using firefly and glow-worm optimization algorithms for selection of feature c) employment of MKSVM algorithm and stacking ensemble classifier for classification and application of the feature of fusion of different feature extraction methods. [ABSTRACT FROM AUTHOR]

In this paper, we introduce two novel wavelet approximations tailored for functions g$$ g $$ exhibiting a restricted second derivative and a bounded Tth$$ {T}^{th} $$ derivative. Employing the Hermite wavelet method, we derive these approximations to address the need for effective representations of such functions. Our findings reveal that these new wavelet approximations offer enhanced accuracy and efficiency in capturing the underlying structure of g$$ g $$, making them valuable tools in various applications requiring precise function approximations with limited derivative constraints. [ABSTRACT FROM AUTHOR]

In this paper, we present explicit expressions for conforming finite element function spaces, basis functions, and degrees of freedom on the pentatope (the 4-simplex) and tetrahedral prism elements. More generally, our objective is to construct high-order finite element function spaces that maintain conformity with infinite-dimensional spaces of a carefully chosen de Rham complex in four dimensions. This paper is a natural extension of the companion paper entitled "Conforming finite element function spaces in four dimensions, part I: Foundational principles and the tesseract" by Nigam and Williams (2024). In contrast to Part I, in this paper we focus on two of the most popular elements which do not possess a full tensor-product structure in all four coordinate directions. We note that these elements appear frequently in existing space-time finite element methods. In order to build our finite element spaces, we utilize powerful techniques from the recently developed 'Finite Element Exterior Calculus'. Subsequently, we translate our results into the well-known language of linear algebra (vectors and matrices) in order to facilitate implementation by scientists and engineers. [ABSTRACT FROM AUTHOR]

AbstractObjectivesMethodsResultsConclusionsManagement of opioid withdrawal in the inpatient setting can vary widely depending on the patient, the physician, and the institution. Although buprenorphine and methadone are first-line therapy for withdrawal management, some patients experience barriers to those medications. In this case series, we explore high dose opioid agonist therapy (HDOAT) as a novel and effective option to bridge to recovery in this particular setting.This retrospective case series includes- five patients with opioid use disorder (OUD) who were treated with HDOAT while hospitalized and reports on their outcomes.All five patients completed lifesaving medical therapy, engaged with community health workers for resources, and successfully transitioned to medications for opioid use disorder (MOUD). More importantly, none of the patients had patient directed discharges (PDDs). Furthermore, there were no inpatient drug uses or overdoses requiring naloxone administration, even with very high doses of oxycodone. None of the five patients were readmitted within thirty days.Although more rigorous research is needed, HDOAT may be a viable strategy for OUD when patients continued to decline buprenorphine or methadone on admission. This case series demonstrated the successful use of this strategy toward preventing PDDs, promoting treatment completion, and allowing substance recovery and rehabilitation, in patients who elected to defer MOUD on arrival. [ABSTRACT FROM AUTHOR]

The stability, robustness, accuracy, and efficiency of space-time finite element methods crucially depend on the choice of approximation spaces for test and trial functions. This is especially true for high-order, mixed finite element methods which often must satisfy an inf-sup condition in order to ensure stability. With this in mind, the primary objective of this paper and a companion paper is to provide a wide range of explicitly stated, conforming, finite element spaces in four dimensions. In this paper, we construct explicit high-order conforming finite elements on 4-cubes (tesseracts); our construction uses tools from the recently developed 'Finite Element Exterior Calculus'. With a focus on practical implementation, we provide details including Piola-type transformations, and explicit expressions for the volumetric, facet, face, edge, and vertex degrees of freedom. In addition, we establish important theoretical properties, such as the exactness of the finite element sequences, and the unisolvence of the degrees of freedom. [ABSTRACT FROM AUTHOR]

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder. It is characterized by dopamine deficiency which leads to classical motor dysfunctions. In addition, Parkinson’s disease may include several non-motor impairments, including autonomic and cardiovascular dysfunction. At present clinical diagnostic criteria for Parkinson’s disease are exclusively based on motor symptoms and the treatment for Parkinson’s disease mainly improves motor symptoms. Non motor symptoms, especially autonomic symptoms are still under recognized in clinical practice. The current study aimed to evaluate these autonomic functions by using Heart Rate Variability (HRV) and Composite Autonomic Symptom Score 31 questionnaire (COMPASS 31). Materials and Methods: This cross-sectional study included 137 diagnosed cases of PD. The resting autonomic balance was assessed by HRV test which included frequency domain indices, time domain indices and nonlinear parameters. Non motor symptoms were assessed by using COMPASS 31 questionnaire which evaluated six domains namely orthostatic intolerance, vasomotor, secretomotor, gastrointestinal, bladder and pupillomotor domains. The six domain scores sum to a total score of 0 to 100 with a higher score indicating more severe autonomic symptoms. Results: The participants showed a sympathetic overdrive on assessing with HRV. Among the non-motor symptoms gastrointestinal symptoms were the most common symptoms (95.62%) in Parkinson’s disease patients. Subsequently there was involvement of secretomotor (85.4%), bladder symptoms (71.53%), pupillomotor symptoms (52.55%), orthostatic intolerance symptoms (50.36%) and vasomotor symptoms (13.14%) on evaluating autonomic functions by COMPASS 31 questionnaire. A statistically significant correlation was observed between HF (ms2) and COMPASS 31 questionnaire (p<0.05). Conclusion: The autonomic function tests can be used as a screening tool in outpatient department of Neurology. This could reduce the morbidity of Parkinson’s disease patients as we employ these autonomic function tests as an early intervention for Parkinson’s disease. COMPASS 31 questionnaire can be used in health care centres for early detection of neurodegenerative disorders like Parkinson’s disease which could prevent the disease progression and aid in early treatment plan. [ABSTRACT FROM AUTHOR]

We study a class of nonlocal games, called transitive games, for which the set of perfect strategies forms a semigroup. We establish several interesting correspondences of bisynchronous transitive games with the theory of compact quantum groups. In particular, we associate a quantum permutation group with each bisynchronous transitive game and vice versa. We prove that the existence of a C*-strategy, the existence of a quantum commuting strategy, and the existence of a classical strategy are all equivalent for bisynchronous transitive games. We then use some of these correspondences to establish necessary and sufficient conditions for some classes of correlations, that arise as perfect strategies of transitive games, to be nonlocal. [ABSTRACT FROM AUTHOR]

Tempted by the unique medicinal and biological potential of indole‐containing heterocycles, chemists, especially those specializing in heterocycle synthesis and drug discovery, are actively pursuing their efficient construction. This review spotlights the latest advancements in microwave‐assisted (M. W.) synthesis of diverse indole‐based heterocyclic compounds. We systematically categorize the reported methods based on the specific indole substitution patterns. This review concise the microwave assisted synthesis of indole based‐pyridine derivatives, indole based‐pyrimidine, indole based‐oxindole, spiro‐oxindole, Fischer indole Heck‐isomerization derivatives, functionalized indole, substituted indoles, indolyl quinoline, indole triazole and indolylnicotinonitriles derivatives. Ultimately, this review aims to provide organic and medicinal chemists with a concise yet informative guide to recent methodologies employing indole derivatives in the microwave‐powered synthesis of heterocycles. [ABSTRACT FROM AUTHOR]

The proposed work discusses discrete collocation and discrete Galerkin methods for second kind Fredholm–Hammerstein integral equations on half line [ 0 , ∞) using Kumar and Sloan technique. In addition, the finite section approximation method is applied to transform the domain of integration from [ 0 , ∞) to [ 0 , α ] , α > 0 . In contrast to previous studies in which the optimal order of convergence is achieved for projection methods, we attained superconvergence rates in uniform norm using piecewise polynomial basis function. Moreover, these superconvergence rates are further enhanced by using discrete multi-projection (collocation and Galerkin) methods. In order to support the provided theoretical framework, numerical examples are included as well. [ABSTRACT FROM AUTHOR]

Clinical trials are very important for determining the safety and efficacy of medical trials, which is further critical to the progress of the various healthcare businesses. Conducting such studies requires substantial preparation and adherence to the various ethical norms; such norms which are especially crucial when dealing with medical emergencies like the COVID-19 outbreak. This paper discusses the Site Initiation Visit (SIV) and the development of Essential Document Files (EDF) for clinical research. Site initiation visit specifies fundamental tasks to ensure team preparedness, logistical planning, and regulatory compliance. Team training, investigational product (IP) storage, and post-SIV follow-up procedures are all valuable considerations. On the other hand, throughout the trial's lifecycle, the document files play a very vital role in ensuring a complete documentation process thereby promoting transparency and adherence to Good Clinical Practice (GCP) guidelines. The paper highlights the importance of established protocols and regulatory compliance, in safeguarding safety by outlining these procedures. [ABSTRACT FROM AUTHOR]

Cystic fibrosis (CF) is a life‑threatening genetic disorder caused by mutations in the CFTR gene. This leads to a defective protein that impairs chloride transport, resulting in thick mucus buildup and chronic inflammation in the airways. The review discusses current and future therapeutic approaches for CFTR dysfunction and airway dysbiosis in the era of personalized medicine. Personalized medicine has revolutionized CF treatment with the advent of CFTR modulator therapies that target specific genetic mutations. These therapies have significantly improved patient outcomes, slowing disease progression, and enhancing quality of life. It also highlights the growing recognition of the airway microbiome’s role in CF pathogenesis and discusses strategies to modulate the microbiome to further improve patient outcomes. This review discusses various therapeutic approaches for cystic fibrosis (CFTR) mutations, including adenovirus gene treatments, nonviral vectors, CRISPR/cas9 methods, RNA replacement, antisense‑oligonucleotide‑mediated DNA‑based therapies, and cell‑based therapies. It also introduces airway dysbiosis with CF and how microbes influence the lungs. The review highlights the importance of understanding the cellular and molecular causes of CF and the development of personalized medicine to improve quality of life and health outcomes. [ABSTRACT FROM AUTHOR]

Crowd counting is one of the most complex research topics in the field of computer vision. There are many challenges associated with this task, including severe occlusion, scale variation, and complex background. Multi-column networks are commonly used for crowd counting, but they suffer from scale variation and feature similarity, which leads to poor analysis of crowd sequences. To address these issues, we propose a scale-aware deep convolutional pyramid network for crowd counting. We have introduced a scale-aware deep convolutional pyramid module by integrating message passing and global attention mechanisms into a multi-column network. The proposed network minimizes the problem of scale variation using SA-DPCM and uses a multi-column variance loss function to handle issues with feature similarity. Experiments have been performed over the ShanghaiTech and UCF-CC-50 datasets, which show the better performance of the proposed method in terms of mean absolute error and root mean square error. [ABSTRACT FROM AUTHOR]

Introduction: Persistent suppurative otitis media (CSOM) is a persistent inflammation of the middle ear and mastoid cavity that persists for more than two weeks. Pseudomonas aeruginosa is a common pathogen that causes CSOM. One of the best medications for treating Pseudomonas infections is carbapenem. The development of bacteria resistant to carbapenems is frequently linked to metallo-β lactamases. In an effort to stop and propagate resistance, identifying the strains that create MBLs can help guarantee that patients receive the best therapy possible. Aim and Objective: To study the molecular characterization of metallo-beta lactamase gene with special reference to blaIMP-1 gene in imipenem resistant Pseudomonas aeruginosa isolates from patients of chronic suppurative otitis media. Material and Methods: The present study was a cross sectional study carried out in the Department of Microbiology with collaboration with the ENT and the Pharmacology Department for a period of 1 year i.e between August 2022 to August 2023 at a tertiary care centre. A total of 352 patients clinically suspected cases for CSOM were studied. Swabs taken from discharging ears were sent for Gram's staining, culture and antibiotic sensitivity test was performed according to the CLSI guidelines 2022. The isolates were further tested for MBL by screening test, by Imipenem - EDTA combined disc test, and MBL E test (Imipenem). The DNA was extracted by using Qiagen DNA Extraction kit, which was further proceeded for the blaIMP-1 gene detection for Pseudomonas aeruginosa by the conventional PCR. Results: In the present study the clinically diagnosed suspected cases of CSOM were 352, out of which 118 (33.5%) was found to be positive for CSOM infection. The ratio of Male 74 (62.7%) was found to be more as compared to the Female 44 (37.2%), with the maximum cases in the age group of 0-10 and the least in the age group above 41 years. In our study it was observed that the maximum number of cases was observed in the Gram negative bacilli isolates (77.2%) as compared to the Gram positive isolates (19.4%) with sides of the ear almost equally affected. P. aeruginosa 58 (49.1%) was the most common isolate followed by Klebsiella spp with 19 (16.1%) and among gram positive isolate Staphylococcus aureus was found to be 15.2%, there was only 3 case found for candida albicans (2.5%). The sensitivity observed for P. aeruginosa for Colistin was (96.5%), Piperacillin-tazobactam (74.1%), Amikacin (77.5%), and Cefipime (74.1%) were found to be the most effective Antibiotics. The resistance to ciprofloxacin was (58.6%), Levofloxacin (50%), Piperacillin(25.8%), Gentamicin (36.2%), Imipenem (36.2%), Tobramycin and Ceftazidime with 27.5% respectively. The molecular characterization of the blaIMP-1 gene was detected in 18 (31%) of the isolates of Pseudomonas aeruginosa which were screening test-positives for MBL by Imipenem - EDTA combined disc test, and MBL E test (Imipenem). Conclusion: For a treatment to be effective and to prevent both medical problems and antibiotic resistance, it is essential to understand the etiological agents of CSOM and their antibiogram. It is imperative that wide spectrum antibiotics like imipenem be used for the need of the hour. [ABSTRACT FROM AUTHOR]

In this paper, the applicability of dual material stacked gate-oxide-Pocket doped-hetero-junction tunnel field effect transistor (DMSGO-PD-HTFET) for low power switching and radio frequency (RF) applications is investigated. In this context, gate workfunction engineering, the stacked-gate-oxide ($$Si{O_2}$$ Si O 2 + $$Hf{O_2}$$ Hf O 2 ) approach, and asymmetrical doping at the P+ source ($$S{i_{1 - X}}G{e_X}$$ S i 1 − X G e X ) and N+ drain regions are considered. N+ pocket at source-channel interface implements DMSGO-PD-HTFET and improves interband tunnelling rate. This research aims to improve the device's switching ratio ($${I_{ON}}$$ I ON / $${I_{OFF}}$$ I OFF ), average subthreshold swing ($$S{S_{Avg}}$$ S S Avg ), and radio frequency (RF) performance. For this, the control gate work function, mole fraction (X), pocket thickness, and doping concentration are optimised. Next, the DC, analog/RF and linearity figure of merits of the proposed device is analysed and the performance is compared with conventional all-silicon dual-material stack gate oxide tunnel field effect transistor (DMSGO-TFET) and dual-material stacked gate oxide-hetero-junction tunnel field effect transistor (DMSGO-HTFET) with $$S{i_{1 - X}}G{e_X}$$ S i 1 − X G e X source using technology computer-aided design (TCAD) device simulator. Based on the comparative analysis, the optimised design with $$S{i_{0.6}}G{e_{0.4}}$$ S i 0.6 G e 0.4 exhibits an average subthreshold swing ($$S{S_{Avg}}$$ S S Avg ) of 28.8 mV/decade, switching ratio ($${I_{ON}}$$ I ON / $${I_{OFF}}$$ I OFF ) of 2 × 1012, cut-off frequency ($${f_T}$$ f T ) of 216 (GHz), and other significant improvements in analog/RF and linearity performance parameters. The proposed device is therefore suitable for switching and RF applications. [ABSTRACT FROM AUTHOR]

In the present paper, we obtain the results on the degree of convergence of an H$$ H $$‐periodic continuous function in generalized Hölder spaces using Hausdorff operator with monotonically non‐decreasing and monotonically non‐increasing rows of its hexagonal Fourier series. Some important corollaries are also deduced from our main theorems. Applications of main theorems are also obtained in this paper. [ABSTRACT FROM AUTHOR]

Key challenges in tRNA next-generation sequencing (NGS) library preparations include efficient adapter ligation and overcoming extensive reverse transcriptase-blocking modifications and a highly stable RNA secondary structure. Computational challenges include accounting for the potential modifications in each tRNA and uniquely mapping each read to a reference, which can comprise hundreds of highly similar tRNA genes. Several recent applications forgo tRNA-seq in favor of hybridization-based approaches; however, hybridization-based approaches continued to be developed and improved. Validation approaches remain an issue among tRNA-seq studies – it is difficult to directly compare tRNA NGS datasets given their varied library preparation approaches, and many non-NGS based methods of corroboration are relatively low throughput. In the past decade tRNA sequencing (tRNA-seq) has attracted considerable attention as an important tool for the development of novel approaches to quantify highly modified tRNA species and to propel tRNA research aimed at understanding the cellular physiology and disease and development of tRNA-based therapeutics. Many methods are available to quantify tRNA abundance while accounting for modifications and tRNA charging/acylation. Advances in both library preparation methods and bioinformatic workflows have enabled developments in next-generation sequencing (NGS) workflows. Other approaches forgo NGS applications in favor of hybridization-based approaches. In this review we provide a brief comparative overview of various tRNA quantification approaches, focusing on the advantages and disadvantages of these methods, which together facilitate reliable tRNA quantification. [ABSTRACT FROM AUTHOR]

To review the application of laser flare photometry (LFP) in the objective quantification of aqueous flare (anterior chamber inflammation) post laser and surgical procedures for glaucoma. A search was undertaken using the following: PubMed (all years), the Web of Science (all years), Ovid MEDLINE (R) (1980 to 30 March 2023), Ovid MEDLINE (R) Daily Update 30 March 2023, MEDLINE and MEDLINE non-indexed items, Embase (1980–2021, week 52), Ovid MEDLINE (R) and Epub Ahead of Print, in-Process & Other Non-Indexed Citations and Daily (1980 to 30 March 2023), CENTRAL (including Cochrane Eyes and Vision Trials Register), metaRegister of Controlled Trials (mRCT) (), ClinicalTrials.gov () and the World Health Organization (WHO) International Clinical Trials Registry Platform (). Search terms included "aqueous flare," "anterior chamber inflammation," "tyndallometry," "laser flare photometry" combined with "laser," "iridotomy," "trabeculoplasty," "cataract surgery," "phacoemulsification," "glaucoma surgery," "minimally invasive glaucoma surgery," "trabeculectomy," "aqueous shunt," "glaucoma drainage" and "cyclophotocoagulation." The majority of studies utilizing laser flare photometry in grading flare have been post laser trabeculoplasty. The degree of flare produced varies according to the type of glaucoma laser or surgery performed, with filtration procedures and glaucoma drainage devices having marked and prolonged detectable levels. Aqueous flare in cyclodestructive procedures positively correlated with intraocular pressure (IOP) reduction. In comparison to clinician grading, laser flare photometry provides a more objective measure of post-surgical inflammation in eyes that have undergone laser and surgery for glaucoma. Further research is warranted into how this instrument can be utilized to identify eyes at high risk of failure and other adverse outcomes after glaucoma surgery. [ABSTRACT FROM AUTHOR]

SUMMARY: Mutant populations are crucial for functional genomics and discovering novel traits for crop breeding. Sorghum, a drought and heat‐tolerant C4 species, requires a vast, large‐scale, annotated, and sequenced mutant resource to enhance crop improvement through functional genomics research. Here, we report a sorghum large‐scale sequenced mutant population with 9.5 million ethyl methane sulfonate (EMS)‐induced mutations that covered 98% of sorghum's annotated genes using inbred line BTx623. Remarkably, a total of 610 320 mutations within the promoter and enhancer regions of 18 000 and 11 790 genes, respectively, can be leveraged for novel research of cis‐regulatory elements. A comparison of the distribution of mutations in the large‐scale mutant library and sorghum association panel (SAP) provides insights into the influence of selection. EMS‐induced mutations appeared to be random across different regions of the genome without significant enrichment in different sections of a gene, including the 5′ UTR, gene body, and 3′‐UTR. In contrast, there were low variation density in the coding and UTR regions in the SAP. Based on the Ka/Ks value, the mutant library (~1) experienced little selection, unlike the SAP (0.40), which has been strongly selected through breeding. All mutation data are publicly searchable through SorbMutDB (https://www.depts.ttu.edu/igcast/sorbmutdb.php) and SorghumBase (https://sorghumbase.org/). This current large‐scale sequence‐indexed sorghum mutant population is a crucial resource that enriched the sorghum gene pool with novel diversity and a highly valuable tool for the Poaceae family, that will advance plant biology research and crop breeding. Significance Statement: Although genome sequencing has identified most gene models in the genomes of many plants, the function of the majority of them remains unknown. The sorghum sequence‐indexed mutant library, which revealed 9 million induced mutations covering >98% of sorghum genes, provides a vital resource to study the function of putative genes, and to validate the candidate genes identified from genetic/genome mapping studies. [ABSTRACT FROM AUTHOR]

Technological advancement and exponential rise in the human population have led to severe modification of the land surface area. These human‐induced geomorphic modifications are considered as an active geomorphic process that interrupts dynamic equilibrium between landform and anthropogeomorphologic processes. The present study aimed to evaluate the efficiency of Nir's 'Index of potential anthropic geomorphology' used to quantify anthropogeomorphic process (AGP) impact. The model was applied in 11 talukas (sub‐districts) of Goa State, India. Goa is a good candidate to understand the impact of anthropogeomorphological process because it has a varied topography with different geomorphological landforms along with rapid increase in urbanisation and mining activities which are anthropocentric. Decadal results show that, during 1991, 2001, and 2011, the tourism hubs of North Goa Bardez (0.32, 0.36, and 0.40) and Tiswadi (0.44, 0.42, and 0.47) required least attention to curb human impact, while the major economic and tourism hubs of South Goa Marmugao (0.55, 0.53, and 0.40) and Salcete (0.40, 0.40, and 0.40) surprisingly showed no increase but instead a decline in the values. In addition, prominent mining talukas Bicholim (0.25, 0.30, and 0.20), Quepem (0.45, 0.39, and 0.15), and Sanguem (0.24, 0.22, and 0.18) also showed declining values, which is indicative of decreased human activities. The index results suggest 'no requirement of urgent and efficient measures' in any talukas because none of the values have been found to be above 0.50, which according to the model represents considerable damage to geomorphology. However, Goa is a world‐renowned tourism destination and all these talukas have witnessed massive urban development, high literacy rate, and exponential growth in National State Domestic Product and mining activities, especially since the turn of the millennium, which are contrary to Nir's index results. Therefore, the model has been found to be over‐generalised and ineffective in indicating actual AGP at the meso level. [ABSTRACT FROM AUTHOR]

Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents. Many types of models rely on descriptions of atom-centered environments, which are associated with an atomic property or with an atomic contribution to an extensive macroscopic quantity. Frameworks in this class can be understood in terms of atom-centered density correlations (ACDC), which are used as a basis for a body-ordered, symmetry-adapted expansion of the targets. Several other schemes that gather information on the relationship between neighboring atoms using "message-passing" ideas cannot be directly mapped to correlations centered around a single atom. We generalize the ACDC framework to include multi-centered information, generating representations that provide a complete linear basis to regress symmetric functions of atomic coordinates, and provide a coherent foundation to systematize our understanding of both atom-centered and message-passing and invariant and equivariant machine-learning schemes. [ABSTRACT FROM AUTHOR]

Symmetry considerations are at the core of the major frameworks used to provide an effective mathematical representation of atomic configurations that is then used in machine-learning models to predict the properties associated with each structure. In most cases, the models rely on a description of atom-centered environments and are suitable to learn atomic properties or global observables that can be decomposed into atomic contributions. Many quantities that are relevant for quantum mechanical calculations, however—most notably the single-particle Hamiltonian matrix when written in an atomic orbital basis—are not associated with a single center, but with two (or more) atoms in the structure. We discuss a family of structural descriptors that generalize the very successful atom-centered density correlation features to the N-center case and show, in particular, how this construction can be applied to efficiently learn the matrix elements of the (effective) single-particle Hamiltonian written in an atom-centered orbital basis. These N-center features are fully equivariant—not only in terms of translations and rotations but also in terms of permutations of the indices associated with the atoms—and are suitable to construct symmetry-adapted machine-learning models of new classes of properties of molecules and materials. [ABSTRACT FROM AUTHOR]

Background: A growing body of evidence underscores the beneficial impact of therapeutic drug monitoring (TDM) on the efficacy and cost-effectiveness of anti-tumour necrosis factor (TNF) therapy in patients with inflammatory bowel disease (IBD). Objectives: We surveyed clinician attitudes, perceptions and barriers related to TDM in IBD in the Middle East. Design: A 15-question survey was distributed through national gastroenterological societies in five Middle Eastern countries (UAE, Saudi Arabia, Kuwait, Lebanon and Egypt). Methods: Data on clinician characteristics, demographics, utilization patterns and obstacles related to the adoption of TDM with anti-TNFs were gathered. Logistic regression analysis was used to predict factors influencing the utilization of TDM. Results: Among 211 respondents (82% male), 82% were consultants, 8% were physicians with an interest in gastroenterology (GI), and 6% were GI trainees. Of these, 152 met inclusion criteria, treating >5 IBD patients per month and ⩾1 with an anti-TNF per month. TDM was used in clinical practice by 78% (95% CI: 71–85) of respondents. TDM was utilized following the loss of response (LOR) in 93%, for primary non-response (PNR) in 40% and before restarting anti-TNF therapy after a drug holiday in 33% of respondents, while 34% used TDM proactively. No specific factors were associated with the use of TDM. Barriers to TDM use included cost (85%), time lag to results (71%) and lack of insurance reimbursement (65%). Overall knowledge of TDM (70%), interpretation and actioning of results (76%) or awareness of clinical guidelines (57%) were not perceived as barriers. If barriers were removed, 95% would use TDM more frequently; 93% for LOR, 60% for PNR, 50% when restarting after a drug holiday, and 54% would use TDM proactively. Conclusion: Most gastroenterologists use TDM for LOR, with cost, time lag and insurance reimbursement being significant barriers. Addressing these barriers would increase the judicious use of reactive and proactive TDM to optimize anti-TNF therapy in IBD. Plain language summary: Attitudes, perceptions, and barriers in implementing therapeutic drug monitoring for anti-TNFs in inflammatory bowel disease: a survey from Middle East Anti-TNF therapies are perhaps the most widely used and available biological therapies for the treatment of inflammatory bowel disease globally even though other agents have been licensed in recent years. The role of therapeutic drug monitoring to optimise outcomes and mitigate against immunogenicity with anti-TNF agents are now being appreciated. Our study investigates clinician attitudes, perceptions, and barriers related to therapeutic drug monitoring (TDM) in the context of anti-tumor necrosis factor (TNF) therapy for inflammatory bowel disease (IBD) through a comprehensive survey distributed from five Middle Eastern countries. Among 211 respondents (82% male), 82% were consultants, 8% physicians with an interest in gastroenterology (GI), and 6% GI trainees. TDM was utilised following loss of response (LOR) in 93%, for primary non-response (PNR) in 40%, and before restarting anti-TNF therapy after a drug holiday by 33% of respondents, while 34% used TDM proactively. No specific factors were associated with the use of TDM. Barriers to TDM use included cost (85%), time lag to result (71%), and lack of insurance reimbursement (65%). Overall knowledge of TDM (70%), interpretation and actioning of results (76%), or awareness of clinical guidelines (57%) were not perceived as barriers. If barriers were removed, 95% would use TDM more frequently; 93% for LOR, 60% for PNR, 50% when restarting after a drug holiday and 54% would use TDM proactively. Most gastroenterologists use TDM for LOR, with cost, time lag, and insurance reimbursement being significant barriers. Addressing these barriers would increase judicious use of reactive and proactive TDM to optimise anti-TNF therapy in IBD. [ABSTRACT FROM AUTHOR]

Sustainable agricultural growth and management reduces over-utilization of farm resources and squeezes risk of negative impacts on environment. Monitoring continuous crop growth and health under various conditions at different spatio-temporal resolutions is a key to assess yield stability, crop diversity, adaptability, mitigation for stress and response. The quantification of crop biophysical and biochemical variables spatially from remotely sensed data with help of spectroscopic methods provide a reliable discerning information in the context of crop foliar condition like leaf greenness, senescence, canopy density, crop growth, stress and eco-physiological processes. Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) airborne hyperspectral data offers high spatial and spectral resolution giving a unique advantage and opportunity to test retrievals of crop biophysical (BP)-biochemical (BC) variables under varying conditions over different types of crops. A hybrid inversion of leaf-canopy Radiative Transfer model – PROSAIL-D complemented with use of data driven nonlinear non-parametric methods which offer simplicity, fastness, reliability and competency is a powerful method to retrieve crop biophysical and biochemical variables. The Hyperspectral band (feature) selection is a computationally cost efficient method to overcome data redundancy in high dimensional correlated input spectral bands. The determination of optimum subset or combination of hyperspectral bands specific to retrieval of vegetation properties (including canopy effects) determined using feature selection algorithm for regression-based retrievals are active research topic unlike classification problems in which it is more common. A band selection algorithm based on Gaussian Processes Regression was used to choose most sensitive bands from in-situ biophysical-biochemical measurements and crop spectral signatures collected for analysis in two different agricultural regions: Raichur (Karnataka) and Anand (Gujarat) districts of India representing diverse landscapes, heterogeneous crop canopies and agro climatic settings. The retrieval algorithm for AVIRIS-NG image employed a decision tree ensemble algorithm Canonical Correlation Forests using the optimum subset of bands for retrieval of targeted crop variable. Validation of retrieved crop variables were done using in-situ ground observations collected over heterogeneous diverse crop landscape. The results showed chlorophyll (RMSE = 6.61 µg cm−2), equivalent water thickness (RMSE = 0.002 cm), leaf area index (RMSE = 0.35 m2/m−2) and dry matter (RMSE = 0.003 g cm−2), carotenoid (RMSE = 14.3 µg cm−2), anthocyanin (RMSE = 12.92 µg cm−2) retrieved with better accuracies. The results obtained in context of feature (band) selection approach for Radiative Transfer model inversion show overlapping of sensitive spectral bands of chlorophyll-ab, carotenoid and anthocyanin especially between narrow spectral range 480 to 560 nm as predominant reason for decreased accuracies of anthocyanin and carotenoid compared to other variable. This poses a limitation as well as opportunity for further research in signal separation in context of feature selection approach especially in context of broader spectral bandwidths. It also sets ground for further development of feature selection algorithms that use hybrid regression methods customized for crop specific traits. [ABSTRACT FROM AUTHOR]

Importance: Given the importance of rigorous development and evaluation standards needed of artificial intelligence (AI) models used in health care, nationwide accepted procedures to provide assurance that the use of AI is fair, appropriate, valid, effective, and safe are urgently needed. Observations: While there are several efforts to develop standards and best practices to evaluate AI, there is a gap between having such guidance and the application of such guidance to both existing and new AI models being developed. As of now, there is no publicly available, nationwide mechanism that enables objective evaluation and ongoing assessment of the consequences of using health AI models in clinical care settings. Conclusion and Relevance: The need to create a public-private partnership to support a nationwide health AI assurance labs network is outlined here. In this network, community best practices could be applied for testing health AI models to produce reports on their performance that can be widely shared for managing the lifecycle of AI models over time and across populations and sites where these models are deployed. This article outlines the need for a nationwide public-private network of assurance laboratories that would aid in the evaluation and development of artificial intelligence (AI) in health care. [ABSTRACT FROM AUTHOR]

The approach to patients with choledochal cysts (CCs) remains varied and subject to institutional practices. Owing to the rarity of the disease, the optimal treatment remains poorly defined, particularly in the adult population. This study aimed to review the literature on adult patients with CCs to evaluate trends of diagnosis and management in Western countries. A literature search of 3 electronic databases was performed on adult patients diagnosed with CCs in Western institutions. A review of published literature was completed with comprehensive screening by 2 independent reviewers. Studies were analyzed, and data on surgical approach, malignancies, and follow-up were collected. Findings are presented in concordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Of the 3488 articles retrieved, 21 studies evaluated Western adults with CCs for a combined population of 1337 patients. The most common Todani subtypes included types I (64%) and IV (22%). Symptoms at presentation included abdominal pain and jaundice, although many were asymptomatic. Ultrasound was used most frequently for diagnosis, followed by computed tomography and endoscopic cholangiopancreatography. The combined malignancy rate was 10.9%, with cholangiocarcinoma being the most prevalent. Complete extrahepatic cyst resection was standard for type I and IV CCs. Among malignancies, 18.5% and 16.4% were observed in patients with prior resection and internal drainage, respectively. A significant proportion of patients who undergo resection of CC disease harbor malignancy. Cancer risk seems reduced but not eliminated with complete resection, which remains the standard treatment. Additional studies are needed to standardize guidelines for the diagnosis and postoperative care of patients in Western countries. [ABSTRACT FROM AUTHOR]

Timely detection of pest infestation in agricultural crops plays a pivotal role in the planning and execution of pest management interventions. In this study, a ground measured electromagnetic spectrum through hyperspectral sensing (400–2500 nm) was conducted in healthy and aphid-infested mustard crops in different regions of the Bharatpur district of Rajasthan state, India. The ground measured hyperspectral reflectance and its derivatives during the mustard aphid infestation period were used to identify the sensitive spectral regions in the electromagnetic spectrum concerning Aphid Infestation Severity Grade (AISG) to discriminate Lipaphis-infested mustard crops from the healthy ones. Further Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were utilized to identify specific spectral bands to differentiate the healthy from aphid-infested crops. The spectral regions of 493–497 nm (blue), 509–515 nm (green), 690–714 nm (red), 717–721 nm (red edge), and 752–756 nm (NIR) showed high correlation with AISG for reflectance, first and second order derivatives. Further analysis of the spectra using PCA and PLSR indicated that spectral bands of 679 nm, 746 nm, and 979 nm had high sensitivity for discriminating aphid-infested crops from the healthy ones. Average reflectance and various spectral indices such as ratio spectral index (RSI), difference spectral index (DSI), and normalized difference spectral index (NDSI) of identified spectral regions and absolute reflectance of identified specific spectral bands were used for predicting AISG. Several regression models, including PCR and PLSR, were examined to predict the AISG. PLSR was found to better predict infestation grade with RMSE of 0.66 and r2 0.71. Our outcomes counseled that hyperspectral reflectance data have the ability to detect aphid-infested severity in mustard. [ABSTRACT FROM AUTHOR]

Introduction: Multiple antibiotic resistances in the bacteria that cause infections in humans have been directly caused by the ongoing use of antibiotics in clinical practise. In undeveloped and impoverished nations, the overuse and inappropriate use of antibiotics may increase the risk of resistant bacteria emerging and proliferating throughout the population. Consequently, the antibiotics' effectiveness is declining. Therefore, there is now more interest in the therapeutic use of natural materials due to the need for innovative alternative antibacterial techniques. Aim and Objective: To study the antimicrobial activity of honey against clinical isolates of Methicillin-Resistant Staphylococcus aureus with special reference to Mec A gene, from various clinical samples at a tertiary care centre, Uttar Pradesh, India. Material and Methods: This was a prospective study carried out in the Department of Pharmacology and the Microbiology Department for a period of 1 year i.e, August 2022 to August 2023 at a Tertiary care centre, Uttar pradesh. The antibacterial activity of Dabur pasteurised honey was evaluated against the bacterial strains of Methicillin Resistant Staphylococcus aureus and Methicillin Sensitive Staphylococcus aureus. Their antibacterial sensitivity pattern was tested using Kirby-Bauer disc diffusion susceptibility testing technique according to the CLSI guidelines 2022 along with other commonly used antimicrobials. Results: A total of 200 clinical isolates were isolated, out of which 72 isolates were of S.aureus in which a total of 24 MRSA isolates were were identified by CX, OX, and E-test. The DNA was extracted using the DNA extraction Qiagen Kit and the Mec A gene was detected by the PCR. In the present study there were 24 isolates of MRSA out of which 15(62.5%) isolates were sensitive to honey and 48 isolates of (MSSA) Methicillin sensitive S. aureus out of which 42(87.5%) isolates were sensitive to honey. It was observed that all the Methicillin resistance isolates were resistant to Cefoxitin and Oxacillin whereas sensitive to linezolid, Teicoplanin and Vancomycin. In the present study the results of antibacterial activity of honey towards the two microorganisms tested were performed. MRSA as well as MSSA were sensitive to undiluted honey samples tested with an average zone of inhibition of 30.03± 0.1 and 41.06±0.2 respectively. Both MRSA and MSSA isolates were sensitive to honey. But MRSA were resistant to all antimicrobials tested except linezolid where as MSSA were sensitive to all except penicillin. Conclusion: Honey is undoubtedly a viable candidate for further research and testing as an antibacterial in the future. With more research on its mode of action at the molecular level, honey could find extensive application as an antibacterial agent in the future. [ABSTRACT FROM AUTHOR]

An innovative, cost-effective reverse phase high performance liquid chromatography (RPHPLC) approach has been devised to accurately and precisely determine the quantity of Nelaribine in both bulk and sterile dosage forms. The separation process was conducted using an Inertsil C18-ODS 3V column with dimensions of 250×4.6 mm and a particle size of 5 µm. Isocratic mode was employed, with a mobile phase consisting of a mixture of acetic acid pH-4.0 buffer and methanol in a ratio of 75:25 (v/v). The mobile phase was pumped into the column at a flow rate of 1.5 mL min-1. The eluent from the column was detected using a UV detector set at 260 nm. The whole duration of the experiment was 8 minutes, during which the column was kept at the ambient temperature. The observed retention time for Nelaribine was determined to be 3.99 minutes. The linearity of the standard curves was seen within the concentration range of 20-100 µg/ml, exhibiting a high coefficient of determination (R2 = 0.9998). The results of the experiment indicated a percentage recovery ranging from 100.0272% to 101.8%. Additionally, the relative standard deviation (RSD) was determined to be 0.3693%. The measured percentage content of a commercially available Nelaribine formulation was determined to be 100.20 %. The methodology was verified in accordance with the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) recommendations. The suggested RP-HPLC technique has been validated by investigations, which have shown that it has characteristics of simplicity, specificity, rapidity, reliability, and reproducibility. Therefore, the approach presented in this study may be used for the regular analysis of Nelaribine in both bulk and injectable dose forms, specifically for quality control purposes. [ABSTRACT FROM AUTHOR]

Pseudopeptide-based soft bioinspired materials have recently emerged as state-of-the-art soft matter for recognition and supramolecular self-assembly. Therefore, we synthesized L -valine and L -phenylalanine-based C2-symmetric pseudo-peptidic soft bioinspired materials for the selective and sensitive detection of Cu(II) ions in aqueous-organic media through the CHEQ mechanism. These pseudopeptides show 2 : 1 stoichiometry with Cu(II), with a high value of binding constant (Ka = 0.035 × 105 M−1, 0.02 × 105 M−1) and low detection (0.053 ppm and 0.0047 ppm), respectively, for 1 and 2. Also, the Cu(II) guided tuning of supramolecular nano-assembly is a promising field for material nano-architectonics applications. [ABSTRACT FROM AUTHOR]

This study aims to propose a new group multi-attribute decision-analysis (MADA) model to prioritize the renewable energy sources (RESs) from sustainability perspectives. The selection of RESs can be considered as a MADA problem due to considering the numerous conflicting sustainability indicators/factors. In this regard, we propose an integrated decision-making framework with the "criteria importance through inter-criteria correlation (CRITIC)", the "rank sum (RS)" and the "Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR)" approaches with intuitionistic fuzzy information called the "IF-CRITIC-RS-VIKOR" model. In the developed model, the CRITIC is applied to derive the objective weights, while the RS model is used to compute the subjective weights of the considered sustainability indicators. Further, an incorporated weight-determining formula is presented by combining the CRITIC and RS models under intuitionistic fuzzy environment. Moreover, the VIKOR method is employed to rank the candidate RESs by means of several sustainability indicators. In this line, new intuitionistic fuzzy distance measures are proposed to calculate the "group utility (GU)" and "individual regret (IR)" degrees of candidate RESs. Based on the obtained results, the most significant factors for RESs assessment are impact on ecosystem, technology cost and efficiency, respectively. The assessment outcomes show that the wind energy can serve as an effective RES followed by the solar energy, biomass energy and small hydel energy. Furthermore, comparative study and sensitivity analysis are discussed to show the utility and reasonability of the proposed method. [ABSTRACT FROM AUTHOR]

The World Health Organization (WHO) has recently published a new lung cytopathology reporting system, which simplifies the diagnostic categories into a five-tier system without subcategorization. The system encourages the use of ancillary diagnostic tests for better categorization of specimens and further management. This correspondence provides a brief outline of the lung reporting system, including standardized nomenclature and the use of terminologies harmonizing with the WHO Blue Book. The system includes categories such as non-diagnostic, benign, atypical, suspicious for malignancy, and malignant, with corresponding risk-based management strategies for clinicians. Ancillary techniques like immunocytochemistry can assist in upgrading the category from suspicious for malignancy to malignancy. The system aims to provide universal simplified criteria for categorizing lung cytology samples and their management options. [Extracted from the article]

This article discusses the development of a new reporting system for lymph node cytopathology by the World Health Organization (WHO). The system aims to use standardized nomenclature and terminology that aligns with the WHO Blue Book on hematolymphoid tumors. The article explains the process of collaboration between the International Academy of Cytology (IAC), the International Agency for Research on Cancer (IARC), and the WHO to create this system. It also provides an outline of the possible interpretation categories within the reporting system, including insufficient/inadequate/nondiagnostic, benign, atypical, suspicious for malignancy, and malignant. The authors believe that implementing this standardized reporting system will improve the quality of diagnostic assessment and communication between cytopathologists and clinicians. [Extracted from the article]

Alternaria blight is a destructive disease of mustard crops that causes significant economic loss and usually warrants extensive pesticide application. Characterization and estimation of pest severity for better management is the need of the hour to increase the scope of advisories to the farmers. In this study, statistical approaches like multiple stepwise linear regression, principal component regression and partial least square regression have been employed to detect the disease severity of Alternaria blight in mustard leaves using hyperspectral reflectance data. The predicted values of diseased leaves in all the regression models were significantly reduced vis-à-vis healthy mustard leaves. The results of this study indicate that it is possible to detect the disease severity of Alternaria blight in mustard crops using hyperspectral reflectance data. [ABSTRACT FROM AUTHOR]

The study of fungal endophytes and their metabolites isolated from medicinal plants of Withania somnifera reported dominant fungal species Gliocladium deliquescens, Mycelia sterilia, Phoma glomerata, Phoma humicola and Fusarium xylarioides. The fungi Fusarium xylarioides and Phoma humicola were reported to inhibit both gram positive and negative bacteria. The fungus Gliocladium deliquescens showed an inhibition for gram positive bacteria S. aureus. They show an efficacy of antibacterial property on E. coli, K. pneumoniae and S. aureus. These fungal isolates were found to produce metabolites rich in aldehydes, esters and ketones. [ABSTRACT FROM AUTHOR]

Introduction: Health workers faced overwhelming demands and experienced crisis levels of burnout before the COVID-19 pandemic; the pandemic presented unique challenges that further impaired their mental health. Methods: Data from the General Social Survey Quality of Worklife Module were analyzed to compare self-reported mental health symptoms among U.S. adult workers from 2018 (1,443 respondents, including 226 health workers) and 2022 (1,952, including 325 health workers). Logistic regression was used to examine associations between health workers’ reported perceptions of working conditions and anxiety, depression, and burnout. Results: From 2018 to 2022, health workers reported an increase of 1.2 days of poor mental health during the previous 30 days (from 3.3 days to 4.5 days); the percentage who reported feeling burnout very often (11.6% to 19.0%) increased. In 2022, health workers experienced a decrease in odds of burnout if they trusted management (odds ratio [OR] = 0.40), had supervisor help (OR = 0.26), had enough time to complete work (OR = 0.33), and felt that their workplace supported productivity (OR = 0.38), compared with those who did not. Harassment at work was associated with increased odds of anxiety (OR = 5.01), depression (OR = 3.38), and burnout (OR = 5.83). Conclusions and implications for public health practice: Health workers continued to face a mental health crisis in 2022. Positive working conditions were associated with less burnout and better mental health. CDC’s National Institute for Occupational Safety and Health has developed a national campaign, Impact Wellbeing, to provide employers of health workers with resources to improve the mental health of these workers. [ABSTRACT FROM AUTHOR]

Many physical problems represented as initial and boundary value problems are usually solved by transforming them into integral equations on the half-line. Therefore, this paper discusses the Galerkin and collocation methods along with the multi-Galerkin and multi-collocation methods for non-linear integral equations with compact and Wiener-Hopf kernel operators on the half-line in the space of piecewise polynomial subspaces. As Hammerstein integral equation on half-line has the unbounded domain, the finite section approximation method is applied; and afterward, we find an approximate solution for the finite section integral equation. In order to obtain improved superconvergence rates, we apply Sunil Kumar's method and then compare proposed convergence rates with the existing results of Nahid et al. [22] both theoretically and numerically. These results are further improved by applying multi-projection methods. In addition, it has shown that the proposed theory enhances the results of [22]. Finally, numerical examples are presented to demonstrate the given theoretical framework. [ABSTRACT FROM AUTHOR]