Recent Research Research Articles

Decoupling Between Brain Activity and Cerebrospinal Fluid Movement in Neurological Disorders.

Recent research has identified a link between the global mean signal of resting-state functional MRI (fMRI) and macro-scale cerebrospinal fluid movement, indicating the potential link between this resting-state dynamic and brain waste clearance. Consistent with this notion, the strength of this coupling has been associated with multiple neurodegenerative disease pathologies, especially the build-up of toxic proteins. This article aimed to review the latest advancements in this research area, emphasizing studies on spontaneous global brain activity that is tightly linked to the global mean resting-state fMRI signal, and aimed to discuss potential mechanisms through which this activity and associated physiological modulations might affect brain waste clearance. The available evidence supports the presence of a highly organized global brain activity that is linked to arousal and memory systems. This global brain dynamic, along with its associated physiological modulations, has the potential to influence brain waste clearance through multiple pathways through multiple pathways. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Short Fragmented Peptides from Pardachirus Marmoratus Exhibit Stronger Anticancer Activities in In Silico Residue Replacement and Analyses.

Cancer is a worldwide issue. It has been observed that conventional therapies face many problems, such as side effects and drug resistance. Recent research reportedly used marine-derived products to treat various diseases and explored their potential in treating cancers. This study aims to discover short-length anticancer peptides derived from pardaxin 6 through an in silico approach. Fragmented peptides ranging from 5 to 15 amino acids were derived from the pardaxin 6 parental peptide. These peptides were further replaced with one residue and, along with the original fragmented peptides, were predicted for their SVM scores and physicochemical properties. The top 5 derivative peptides were further examined for their toxicity, hemolytic probability, peptide structures, docking models, and energy scores using various web servers. The trend of in silico analysis outputs across 5 to 15 amino acid fragments was further analyzed. Results showed that when the amino acids were increased, SVM scores of the original fragmented peptides were also increased. Designed peptides had increased SVM scores, which was aligned with previous studies where the single residue replacement transformed the non-anticancer peptide into an anticancer agent. Moreover, in vitro studies validated that the designed peptides retained or enhanced anticancer effects against different cancer cell lines. Interestingly, a decreasing trend was observed in those fragmented derivative peptides. Single residue replacement in fragmented pardaxin 6 was found to produce stronger anticancer agents through in silico predictions. Through bioinformatics tools, fragmented peptides improved the efficiency of marine-derived drugs with higher efficacy and lower hemolytic effects in treating cancers.

The Astonishing Accomplishment of Biological Drug Delivery using Lipid Nanoparticles: An Ubiquitous Review.

Biotech drugs, including proteins, hormones, enzymes, DNA/RNA therapies, and cell-based treatments, are gaining popularity due to their effectiveness. However, effective delivery systems are needed to overcome administration challenges. Lipid nanoparticles (LNPs) have emerged as promising carriers for various therapies. LNPs are biocompatible, less likely to cause adverse reactions, and can stabilize delicate biological drugs, enhancing their stability and solubility. Scalable and cost-effective manufacturing processes make LNPs suitable for largescale production. Despite recent research efforts, challenges in stability, toxicity, and regulatory concerns have limited the commercial availability of LNP-based products. This review explores the applications, administration routes, challenges, and future directions of LNPs in delivering biopharmaceuticals.

Development and Outlook for Self-priming Pumps

Background: Self-priming pumps are a type of general mechanical equipment that is widely used in the petroleum, chemical, electric power, metallurgy, mining, shipbuilding, light industry, agriculture, civil defense, and other departments, and they play an important role in the global economy. The pump system is the most common piece of equipment that consumes the most electricity, and reducing the energy consumption of the pump will save a significant amount of energy. Objective: For the benefit of scholars and engineers, this paper summarizes the most recent research on self-priming pumps, analyzes their solutions to the problem of reducing energy consumption, and discusses their advantages and disadvantages. Methods: The typical self-priming pump patents are outlined below based on the many functions of the improved self-priming pump structure, including pump body protection, high efficiency, and energy savings, ease of movement, and improved seal. The current self-priming pump patents are used to examine the development trend for these pumps. Results: The fundamental issues with self-priming pumps are outlined and studied through comparisons of various types and functions, and a future course for their development is suggested. Conclusion: The development of self-priming pump technology benefits from the improvement of self-priming pump structure. A self-priming pump with a straightforward design, automation, high efficiency, and energy conservation has a promising future.

Topical Anti-ulcerogenic Effect of the Beta-adrenergic Blockers on Diabetic Foot Ulcers: Recent Advances and Future Prospectives.

Patients with diabetes suffer from major complications like Diabetic Retinopathy, Diabetic Coronary Artery Disease, and Diabetic Foot ulcers (DFUs). Diabetes complications are a group of ailments whose recovery time is especially delayed, irrespective of the underlying reason. The longer duration of wound healing enhances the probability of problems like sepsis and amputation. The delayed healing makes it more critical for research focus. By understanding the molecular pathogenesis of diabetic wounds, it is quite easy to target the molecules involved in the healing of wounds. Recent research on beta-adrenergic blocking drugs has revealed that these classes of drugs possess therapeutic potential in the healing of DFUs. However, because the order of events in defective healing is adequately defined, it is possible to recognize moieties that are currently in the market that are recognized to aim at one or several identified molecular processes. The aim of this study was to explore some molecules with different therapeutic categories that have demonstrated favorable effects in improving diabetic wound healing, also called the repurposing of drugs. Various databases like PubMed/Medline, Google Scholar and Web of Science (WoS) of all English language articles were searched, and relevant information was collected regarding the role of beta-adrenergic blockers in diabetic wounds or diabetic foot ulcers (DFUs) using the relevant keywords for the literature review. The potential beta-blocking agents and their mechanism of action in diabetic foot ulcers were studied, and it was found that these drugs have a profound effect on diabetic foot ulcer healing as per reported literatures. There is a need to move forward from preclinical studies to clinical studies to analyze clinical findings to determine the effectiveness and safety of some beta-antagonists in diabetic foot ulcer treatment.

Non-coding RNAs as Key Regulators of the Notch Signaling Pathway in Glioblastoma: Diagnostic, Prognostic, and Therapeutic Targets.

Glioblastoma multiforme (GBM) is a highly invasive brain malignancy originating from astrocytes, accounting for approximately 30% of central nervous system malignancies. Despite advancements in therapeutic strategies including surgery, chemotherapy, and radiopharmaceutical drugs, the prognosis for GBM patients remains dismal. The aggressive nature of GBM necessitates the identification of molecular targets and the exploration of effective treatments to inhibit its proliferation. The Notch signaling pathway, which plays a critical role in cellular homeostasis, becomes deregulated in GBM, leading to increased expression of pathway target genes such as MYC, Hes1, and Hey1, thereby promoting cellular proliferation and differentiation. Recent research has highlighted the regulatory role of non-coding RNAs (ncRNAs) in modulating Notch signaling by targeting critical mRNA expression at the post-transcriptional or transcriptional levels. Specifically, various types of ncRNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), have been shown to control multiple target genes and significantly contribute to the carcinogenesis of GBM. Furthermore, these ncRNAs hold promise as prognostic and predictive markers for GBM. This review aims to summarize the latest studies investigating the regulatory effects of ncRNAs on the Notch signaling pathway in GBM.

Cross-Modal Clustering With Deep Correlated Information Bottleneck Method.

Cross-modal clustering (CMC) intends to improve the clustering accuracy (ACC) by exploiting the correlations across modalities. Although recent research has made impressive advances, it remains a challenge to sufficiently capture the correlations across modalities due to the high-dimensional nonlinear characteristics of individual modalities and the conflicts in heterogeneous modalities. In addition, the meaningless modality-private information in each modality might become dominant in the process of correlation mining, which also interferes with the clustering performance. To tackle these challenges, we devise a novel deep correlated information bottleneck (DCIB) method, which aims at exploring the correlation information between multiple modalities while eliminating the modality-private information in each modality in an end-to-end manner. Specifically, DCIB treats the CMC task as a two-stage data compression procedure, in which the modality-private information in each modality is eliminated under the guidance of the shared representation of multiple modalities. Meanwhile, the correlations between multiple modalities are preserved from the aspects of feature distributions and clustering assignments simultaneously. Finally, the objective of DCIB is formulated as an objective function based on a mutual information measurement, in which a variational optimization approach is proposed to ensure its convergence. Experimental results on four cross-modal datasets validate the superiority of the DCIB. Code is released at https://github.com/Xiaoqiang-Yan/DCIB.

Athafnafólk í opinberri stefnumótun á óvissutímum: Hvernig hugmyndin um notendastýrða persónulega aðstoð varð að veruleika á Íslandi

Þessi rannsókn leitast við að útskýra tímamótaákvörðun í þjónustu við fatlað fólk á Íslandi. Opinber stefnumótun hefur löngum einkennst af hægfara breytingum, sem gerast í smáum skrefum. Stundum bregður þó svo við að meiriháttar breytingar verða og stefnumál, sem verið hefur baráttumál hagsmunahópa um margra ára skeið, ná fram að ganga. Dagskrárkenningar leitast við að útskýra meiriháttar stefnubreytingar með því m.a. að beina athyglinni að því hvernig og hvers vegna tiltekin málefni koma til kasta stjórnvalda á hverju tíma. Bandaríski stjórnmálafræðingurinn, John W. Kingdon, setti fyrst fram kenningu sína um straumana þrjá og glugga tækifæranna fyrir rúmum 30 árum. Nýlegar rannsóknir evrópskra stjórnmálafræðinga halda því nú fram að nálgun Kingdons geti varpað ljósi á það hvernig það pólitíska kerfi sem stefnumótunin fer fram í virkar og hvernig hegðun og aðferðir þátttakenda í ferlinu hafa áhrif. Í þessari eigindlegu rannsókn er skoðað hvernig hugmyndin um notendastýrða persónulega aðstoð (NPA) varð að veruleika á Íslandi. Rannsóknin byggir á fyrirliggjandi gögnum og viðtölum við lykilfólk um þá framvindu mála sem leiddi til ákvörðunar um að innleiða NPA hér á landi. Rannsóknin lýsir því hvernig og undir hvaða kringumstæðum NPA komst á dagskrá stjórnvalda. Niðurstöðurnar sýna hvernig breytingar á verkaskiptingu milli ríkis og sveitarfélaga gáfu tækifæri fyrir nýja hugmyndafræði sem nýttist bæði notendum, viðskiptahagsmunum og pólitískum hagsmunum. Niðurstöðurnar benda til þess að þar hafi ekki aðeins verið réttur maður á réttum stað á réttum tíma, heldur varpa þær fræðilegu ljósi á það hvað einkennir athafnafólk í opinberri stefnumótun og hvernig og hvers vegna það skiptir máli á óvissutímum í stjórnmálum.

Cement-Based Composites Containing Carbon Nanofibers and Carbon Nanotubes

Abstract: In cement-based composites, carbon nanotubes (CNTs) and carbon nano fibres (CNFs) can act as crack bridging, delaying the development of nano fractures into microcracks. Recent research on the use of CNTs and CNFs in cement-based composites was reviewed in this paper. Earlier studies have demonstrated that cement-based composites reinforced with CNTs/CNFs have lower porosities and superior mechanical properties to plain cement-based composites. Using CNTs or CNFs in cement-based composites presents challenges due to their low matrix dispersion and weak interfacial contact. Some projected future investigations were indicated. Results: Earlier studies have demonstrated that cement-based composites reinforced with CNTs/CNFs have lower porosities and superior mechanical properties to plain cement-based composites. Using CNTs or CNFs in cement-based composites presents challenges due to their low matrix dispersion and weak interfacial contact . Recommendation: some projected future investigations were indicated.

QSAR Studies on Thienopyrimidines as Potential Antimicrobial Agents

Background: Recent research has revealed promising antibacterial action for thienopyrimidines. To comprehend the underlying molecular features underlying their antibacterial potency, a thorough quantitative structure-activity relationship (QSAR) investigation is required. Objective: In order to clarify the structural parameters for effective antibacterial activity, we conducted QSAR analyses on a variety of thienopyrimidines in this work. Methods: Through the analysis of physicochemical properties and molecular descriptors, we aimed to develop predictive models that can guide the design of novel thienopyrimidine derivatives with enhanced antimicrobial potential. Results: It was discovered through the descriptor importance analysis that specific physicochemical characteristics, including lipophilicity, electronic distribution, and steric effects, significantly influenced the antibacterial efficacy of these drugs. Conclusion: The identified molecular characteristics and descriptors can be used to guide the development of new thienopyrimidine derivatives with higher antibacterial activity.

Maternal prenatal social disadvantage and neonatal functional connectivity: Associations with psychopathology symptoms at age 12 months.

Recent research has reported effects of socioeconomic status on neurobehavioral development as early as infancy, including positive associations between income and brain structure, functional connectivity, and behavior later in childhood (Ramphal, Whalen, et al., 2020; Triplett et al., 2022). This study extends this literature by investigating the relation of maternal prenatal social disadvantage (PSD) to neonatal amygdala and hippocampus functional connectivity and whether socioeconomic-related alterations in functional connectivity subsequently predict behavior at age 12 months in a large, socioeconomically diverse sample (N = 261 mother-infant dyads). PSD was assessed across gestation; neonatal magnetic resonance imaging was completed within the first weeks of life; and infant internalizing and externalizing symptoms were evaluated using the Infant-Toddler Social and Emotional Assessment at age 12 months. The results showed that PSD was significantly related to neonatal right amygdala and left hippocampus functional connectivity with prefrontal and motor-related regions. Social disadvantage-related right amygdala and left hippocampus functional connectivity with these regions was subsequently related to infant externalizing and internalizing symptoms at age 12 months. Building off an emerging literature exploring prenatal impacts on neonatal functional connectivity, this study further emphasizes the important role of the maternal environment during gestation on infant brain function and its relationship with externalizing and internalizing behavior in the first years of life. The results suggest that the prenatal socioeconomic environment may be a promising target for interventions aimed at improving infant neurobehavioral outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Chinese EMR Named Entity Recognition Using Fused Label Relations Based on Machine Reading Comprehension Framework.

Chinese electronic medical record (EMR) presents significant challenges for named entity recognition (NER) due to their specialized nature, unique language features, and diverse expressions. Traditionally, NER is treated as a sequence labeling task, where each token is assigned a label. Recent research has reframed NER within the machine reading comprehension (MRC) framework, extracting entities in a question-answer format, achieving state-of-the-art performance. However, these MRC-based methods have a significant limitation: they extract entities of various types independently, ignoring their interrelations. To address this, we introduce the Fusion Label Relations with MRC (FLR-MRC) model, which enhances the MRC model by implicitly capturing dependencies among entity types. FLR-MRC models interrelations between labels using graph attention networks, integrating these with textual data to identify entities. On the benchmark CMeEE and CCKS2017-CNER datasets, FLR-MRC achieves F1-scores of 0.6652 and 0.9101, respectively, outperforming existing clinical NER methods.

Vapor-Liquid Equilibrium of System Comprising Green Solvents: A Holistic Review

Abstract: The design and operation of distillation columns is based on vapor-liquid equilibrium data, which is a necessity for the chemical industry. In recent years, chemical industry has embraced green chemistry and sustainable development. Furthermore, green solvents are more environmentfriendly and cleaner than conventional solvents and thus offer a good alternative. Very limited work has been reported in the literature that focuses on the generation of isobaric/isothermal vapor-liquid equilibrium (VLE) data of systems comprising green solvents. In this paper, reported VLE data are explored for three emerging green solvents, such as cyclopentyl methyl ether (CPME), γ- valerolactone (GVL), and 2-methyltetrahydrofuran (2-MeTHF). Emerging green solvents have favorable environmental, health, and safety characteristics, making them attractive alternatives for a wide range of applications. The study focuses on two critical separations; the extraction of formic acid from Power-to-X chemical processes and purification of acetic acid from chemical synthesis or fermentation processes. Both processes are integral parts of the chemical industry's sustainable development. To facilitate these separations, accurate VLE data for these green solvents with acetic acid/formic acid systems are essential. The paper reviews literature related to VLE data for systems involving these green solvents. It provides insights into the experimental conditions, equipment, analysis methods, thermodynamic models, and error-minimizing functions used in the previous studies. The researchers can refer to this information as a useful reference prior to the VLE experimentation and modeling of systems comprising these three green solvents. Moreover, the paper presents an overview of recent research on green solvents and their applications, illustrating their versatility and potential for various industrial processes. Research efforts are needed to generate VLE data for green solvent systems and support the chemical industry in transitions towards more sustainable practices.

Promising Influences of Moringa oleifera in Functional Foods against Metabolic Syndrome: A Comprehensive and Mechanistic Review.

Metabolic syndrome (MetS) is now considered a global issue with a growing financial and health impact. Numerous herbal alternatives have been examined and researched due to the ever-increasing demand for new medications to treat metabolic syndrome disorders. People have empirically employed Moringa oleifera (MO), a native plant to several Asian nations, for a variety of diseases. We sought to examine recent research on MO in MetS and its potential mechanism of action in the current review. Four databases, including PubMed, Scopus, Web of Sciences, and Google Scholar, were thoroughly searched, and the data were then compiled. In total, 146 papers covering nonclinical and clinical MO investigations in metabolic syndromerelated disorders are included in this study. Numerous research confirmed MO's positive impact on the control of blood glucose, blood pressure, hyperlipidemia, and obesity. Many molecular processes have been investigated, including increasing glucose transporter type 4 (GLUT4) expression, inhibition of β-Hydroxy-β-methylglutaryl-coenzyme A (HMG-CoA), α-glucosidase inhibiting, AMP-activated protein kinase (AMPK) activation, and other suggested mechanisms. The current review established much data favoring MO's potential advantages in metabolic syndrome. However, further research involving human studies is required in this area to determine whether Moringa can effectively treat metabolic syndrome.

Nanotechnology-Based Approaches for Nose-to-Brain Drug Delivery in Neurodegenerative Diseases

: Drug delivery to the brain is a challenging task as many drugs do not cross the blood-brain barrier (BBB). As a result, designing strategies to target drugs to the brain requires significant effort. However, recent research has focused on the administration of drugs through the nose to the brain, a noninvasive way to bypass the BBB and deliver therapeutic molecules directly to the brain. Nose-to-brain drug delivery is a promising approach that allows for the direct transportation of therapeutic molecules to the brain while increasing drug concentration in the brain. This approach has gained considerable attention due to its non-invasive nature, which makes it feasible, reliable, and efficient. One promising approach for nose-to-brain drug delivery is the use of nanoparticles as a platform for drug and gene delivery. Nanoparticles offer several advantages, including the ability to protect therapeutic drugs from degradation and increase the efficacy of drug delivery due to their unique size, shape, and surface features. Nanoparticles can also be engineered to target specific cells or tissues, enabling more precise drug delivery to the brain. The use of nanoparticles for nose-to-brain drug delivery has been extensively studied, and recent developments have shown promising results. In addition, patents relating to medication targeting via the nasal route have been developed. These patents cover various aspects of drug delivery, including the use of different types of nanoparticles, methods for producing nanoparticles, and methods for delivering nanoparticles to the brain.

Recent Research on the Identification, Assessment, and Response to Fraud Risks: Implications for Audit Practice and Topics for Future Research

SYNOPSIS The financial statement auditor’s identification of fraud risk factors, their assessment of fraud risk, and their fraud risk responses are key to the auditor’s consideration of fraud and fraud detection. Given that the last review of research related to the search for fraud during the audit occurred nearly a decade ago, we provide a summary of recent academic research to update and inform practitioners, researchers, standard setters, regulators, and other stakeholders in the financial reporting process. We categorize and summarize findings from recent academic studies that focus on the auditor’s identification, assessment, and responses to fraud risks. Implications for practice are presented for each of these areas, along with topics and questions for future research. JEL Classifications: M40; M41; M42; M48.

Large-scale proteomics in the first trimester of pregnancy predict psychopathology and temperament in preschool children: an exploratory study.

Understanding the prenatal origins of children's psychopathology is a fundamental goal in developmental and clinical science. Recent research suggests that inflammation during pregnancy can trigger a cascade of fetal programming changes that contribute to vulnerability for the emergence of psychopathology. Most studies, however, have focused on a handful of proinflammatory cytokines and have not explored a range of prenatal biological pathways that may be involved in increasing postnatal risk for emotional and behavioral difficulties. Using extreme gradient boosted machine learning models, we explored large-scale proteomics, considering over 1,000 proteins from first trimester blood samples, to predict behavior in early childhood. Mothers reported on their 3- to 5-year-old children's (N = 89, 51% female) temperament (Child Behavior Questionnaire) and psychopathology (Child Behavior Checklist). We found that machine learning models of prenatal proteomics predict 5%-10% of the variance in children's sadness, perceptual sensitivity, attention problems, and emotional reactivity. Enrichment analyses identified immune function, nervous system development, and cell signaling pathways as being particularly important in predicting children's outcomes. Our findings, though exploratory, suggest processes in early pregnancy that are related to functioning in early childhood. Predictive features included far more proteins than have been considered in prior work. Specifically, proteins implicated in inflammation, in the development of the central nervous system, and in key cell-signaling pathways were enriched in relation to child temperament and psychopathology measures.

Sequential Point Clouds: A Survey.

Point clouds have garnered increasing research attention and found numerous practical applications. However, many of these applications, such as autonomous driving and robotic manipulation, rely on sequential point clouds, essentially adding a temporal dimension to the data (i.e., four dimensions) because the information of the static point cloud data could provide is still limited. Recent research efforts have been directed towards enhancing the understanding and utilization of sequential point clouds. This paper offers a comprehensive review of deep learning methods applied to sequential point cloud research, encompassing dynamic flow estimation, object detection & tracking, point cloud segmentation, and point cloud forecasting. This paper further summarizes and compares the quantitative results of the reviewed methods over the public benchmark datasets. Ultimately, the paper concludes by addressing the challenges in current sequential point cloud research and pointing towards promising avenues for future research.

Application of Quercetin and its Novel Formulations in the Treatment of Malignancies of Central Nervous System: An Updated Review of Current Evidence based on Molecular Mechanisms.

Quercetin, a naturally occurring polyphenolic compound found in abundance in vegetables and fruits, has emerged as a compelling subject of study in cancer treatment. This comprehensive review delves into the significance and originality of quercetin's multifaceted mechanisms of action, with a particular focus on its application in various brain tumors such as glioblastoma, glioma, neuroblastoma, astrocytoma, and medulloblastoma. This review scrutinizes the distinctive facets of quercetin's anti-cancer properties, highlighting its capacity to modulate intricate signaling pathways, trigger apoptosis, impede cell migration, and enhance radiosensitivity in brain tumor cells. Significantly, it synthesizes recent research findings, providing insights into potential structure-activity relationships that hold promise for developing novel quercetin derivatives with heightened effectiveness. By unraveling the unique attributes of quercetin's anti-brain tumor effects and exploring its untapped potential in combination therapies, this review contributes to a deeper comprehension of quercetin's role as a prospective candidate for advancing innovative treatments for brain cancer.

Ameliorating Gonorrhea: Recent Therapeutic Adaptations and Scope to Improve its Prevailing Condition.

Gonorrhea is a sexually transmitted infection (STI) caused by the bacteria Neisseria gonorrhoeae. According to recent research, the prevalence of gonorrhea has been increasing in many parts of the world, with some areas reporting high rates of antibiotic resistance. In the United States, the Centers for Disease Control and Prevention (CDC) reported that the number of reported gonorrhea cases increased by 56% between 2015 and 2019. Globally, the World Health Organization (WHO) estimated that there were 87 million new cases of gonorrhea in 2016, with the highest burden of infection in low- and middle-income countries. Research has also shown that gonorrhea is becoming increasingly resistant to conventional antibiotics, increasing the prevalence of gonorrhea. This raises concerns and challenges in disease management. The present review gives updated insight on the current state of the disease, challenges, and shortcomings of existing approaches along with the modern and alternative direction like vaccine development, its challenges, and scope to confront the existing state of drug resistance and increased rate of incidence. Alternative strategies like immunotherapy and phage therapy along with recent antibiotics researched for the treatment of gonorrhea. The review provides a thorough insight into the current state of the disease and various available methods used currently and recommended by WHO. To overcome disease prevalence, various alternate therapies are coming into the limelight. However, scientists and researchers show a lack of interest in the drug development and research of gonorrhea, due to less commercial scope, lack of funding, and limited scope in the scientific scenario. These hurdles need to be overcome to meet the WHO vision of reducing gonorrhea by 90% by 2030. So, there is a need to optimize the drug therapy (optimizing dosing schedule, and precision monitoring) to reduce the chance of drug resistance. Also, there is a wide scope for drug and therapeutic system development.