Dual Chain Research Articles

Indigenous Development of MIC-Based C-Band Dual Chain Down Converter Unit for GEOSAT- Spacecraft Checkout System

As part of miniaturization, the development work for the C-band dual-chain down converter, which is extensively used in TM (Telemetry) data acquisition system in GEOSAT spacecraft checkout system has been taken up in MIC (Microwave Integrated Circuit) approach using microstrip line structure. A prototype unit is realized using standard surface mount devices (SMD) and few indigenously developed MIC components namely, the directional couplers, the power dividers etc. The MIC-based down converter module, which forms the heart of the unit is housed in an Aluminium milled box having the dimension of 150 x 150 x 25 mm3. Except internal Local Oscillator (LO), RF Switches and Power supply, all other circuitry are mounted withinthis milled box which is housed in 1U chassis. It meets all the requirements of a conventional down converter. The paper describes the salient features of the unit, its detailed design approach and realization plan and finally the test and evaluation results of the prototype unit developed indigenously.

Tennis teaching assistance model based on double chain shared unsupervised action recognition algorithm

The traditional self-supervised methods based on skeleton data frequently categorize the various enhancements of a given sample as positive examples, while the remaining samples are designated as negative examples. This approach results in a significant imbalance in the ratio of positive to negative samples, which in turn constrains the efficacy of samples with identical semantic information. Therefore, to further improve the training quality in tennis teaching and enhance the accuracy of action recognition, a dual chain sharing unsupervised action recognition algorithm has been proposed. This study first designs a skeleton topology data augmentation method based on the physical connections of human joints to obtain advanced semantic embeddings. Then, an improved positive sample expansion strategy is utilized to enhance the diversity and quality of training data. Next, an unsupervised learning mechanism is employed to autonomously learn and recognize complex patterns of tennis movements. To measure the performance of the model, tests were conducted on its accuracy, F1 score, recognition time, and fitting degree. The experimental results showed that the proposed algorithm could reach its optimal state after 23 iterations of training, and its F1 value reached 0.918, with an average accuracy of 92.9 % and an average recognition time of 7.4 s. The research algorithms were superior to the multi-input branch graph convolutional network action recognition algorithms used for comparison, pull-push contrastive loss action recognition algorithms, and multi-granularity anchor contrastive representation learning action recognition algorithms. Its accuracy was leading by 8.6 %-23.5 %, and the recognition time has been reduced by 2.3s-7.4 s. In addition, in terms of the fitting degree of action recognition, compared with other methods, the proposed method had a fitting degree of up to 95.7 %, which was at least 8.1 % higher. This research method can improve the timeliness of feedback from trainers by accurately and quickly recognizing movements, helping coaches develop more targeted training plans, thereby improving the efficiency and quality of tennis teaching.

Longitudinal motion calibration for connected and automated vehicles in the presence of packet loss

Connected and automated vehicles (CAVs) equipped with vehicle-to-vehicle wireless communication can enhance traffic stability by effectively shortening the following distances. However, packet loss can lead to decline in performance and efficiency, potentially affecting driving safety. To address the destabilising impact on longitudinal motion calibration during packet loss, this paper proposes a dual chain calibration framework (DCCF). This framework consists of a transmission chain for real-time calibration through compensation calculations and a storage chain for periodic auxiliary calibration by reproducing packet loss data. The effectiveness is validated through a series of simulation experiments. The results demonstrate that the proposed DCCF, irrespective of the packet loss rate (PLR) and in both ideal and packet loss communication environments, can effectively maintain a stable following.

Synthesis of model heterojunction interfaces reveals molecular-configuration-dependent photoinduced charge transfer

Control of the molecular configuration at the interface of an organic heterojunction is key to the development of efficient optoelectronic devices. Due to the difficulty in characterizing these buried and (probably) disordered heterointerfaces, the interfacial structure in most systems remains a mystery. Here we demonstrate a synthetic strategy to design and control model interfaces, enabling their detailed study in isolation from the bulk material. This is achieved by the synthesis of a polymer in which a non-fullerene acceptor moiety is covalently bonded to a donor polymer backbone using dual alkyl chain links, constraining the acceptor and donor units in a through space co-facial arrangement. The constrained geometry of the acceptor relative to the electron-rich and -poor moieties in the polymer backbone can be tuned to control the kinetics of charge separation and the energy of the resultant charge-transfer state giving insight into factors that govern charge generation at organic heterojunctions.

Changing the Linking Functionality in a Triblock Co-Polymer for Electrolyzer or Fuel Cell Membrane or Ionomer for Chemical Stability Improvements and Potentially Other Consequences.

We have developed a versatile scalable triblock polymer system for anion exchange membrane (AEM) based electrochemical energy conversion devices. This system is uniquely suited to solving both the membrane and ionomer challenges for the commercialization of AEM water electrolysis or fuel cells. Using our advanced fundamental understanding of AEMs based on our work which began in 2010, we can design systems from first principles to match the needs of the device. A triblock ABA polymer is readily fabricated that has both chemical and mechanical stability. The synthesis of these systems is robust, high yield and amenable to high volume production. It utilizes a novel dual chain transfer agent to mediate the chain-transfer ring-opening metathesis polymerization (ROMP) of cyclooctene (COE) or the polymerization of isoprene (IP) to give the hydrophobic B block of the polymer. This is followed by the reversible addition-fragmentation chain transfer radial polymerization of chloromethylstyrene (CMS). The polyCMS (pCMS) blocks are then quaternized with an amine to give the cationic hydrophilic A block. Before quaternization the B block is hydrogenated to give either semi-crystalline polyethylene (pE) or amorphous polymethylbutylene (pMB) from pCOE and pIP respectively. The obvious achilles heal in this system from a chemical durability standpoint is the linking ether functionality between the hydrophobic and hydrophilic blocks. The material we have synthesized to date have exceptional chemical and mechanical stability. It performs very well in ex-situ testing with KOH solutions and in device testing we have demonstrated >500 h at 50°C in water electrolysis in 5 cm2 cells in 1M carbonate electrolyte at 0.5 A cm-2. We attribute the chemical stability to the fact that we post quaternize the membrane to give methylpipiridinium cations and we assume that this reaction does not fully penetrate down the hydrophilic chain. This leaves a hydrophobic un-quaternized region close to the hydrophobic block that does not allow access to the ether linkage by the hydrated hydroxide anion. Recently a new approach to the telehelic mid block pCOE has been reported that has no ether linkages and allows the hydrophobic outer blocks to be linked by a methylene linker. This gives use an opportunity to directly contrast the chemical stability of two identical triblock co-polymers one with an ether linkage and one with a methylene linkage between blocks. In this presentation we will show the results from ex-situ chemical stability test one at low temperatures and higher hydroxide concentration and one at higher temperature and lower hydroxide concentration. There are many examples in polymer electrolyte chemistry where a simple change leads to unintended consequences. The geometry of the ether linkage versus the methylene linkage will change the way that the polymer chains will organize and entangle in ways that are not currently predictable. To probe the mechanical, chemical and morphological difference between these two polymers we will fully characterize and contrast both polymers physical chemical properties including water uptake, ionic conductivity, DSC, TGA, tensile strength and morphology through SAXS, WAXS and HRTEM. Data for the two polymer membranes will also be contrasted and compared in small laboratory 5 cm2 single cells for both electrolysis in dilute carbonate and H2/O2 fuel cells using conventional catalysts.

An ultra-sensitive electrochemical biosensor for circulating tumor DNA utilizing dual enzyme-assisted target recycle and hybridization chain reaction amplification strategies

Circulating tumor DNA (ctDNA) has emerged as a pivotal biomarker for cancers, offering a non-invasive means of detection through liquid biopsies. However, the current methodologies for ctDNA detection often struggle with sensitivity, especially when confronted with ultra-low concentrations. To address this challenge, we have engineered a remarkably sensitive electrochemical biosensor that can detect low concentration of ctDNA. This breakthrough is achieved by integrating a dual enzyme-assisted amplification mechanism with hybridization chain reaction (HCR). In the initial phase, the presence of ctDNA triggers the unfolding of the H2 hairpin structure, resulting in a segment of double-stranded DNA. The subsequent introduction of Klenow (3′→5′ exo-) and nicking endonuclease (Nb.BbvCI) enzymes leads to the abundant production of extended DNA (EXTDNA). This step critically enhances the initial amplification of the target DNA, ensuring superior specificity and selectivity thanks to the synergistic enzymatic activity. EXTDNA efficiently unfolds the H1 hairpin structure immobilized on the gold electrode, which acts as the initiation point for the HCR. Further amplification of the trace target DNA is achieved through an additional H3 and H4 hybrid-mediated HCR. Finally, the differential pulse voltammetry signal of methylene blue is increased significantly. Our results reveal that the developed electrochemical biosensor displays an exceptional linear correlation with ctDNA across concentrations ranging from 10 fM to 20 pM, with an unprecedented detection limit of 2.3 fM (3 s/k). This innovative approach shows immense potential for the ultrasensitive detection of ctDNA, promising broad applications in early cancer detection and monitoring.

Synthetic Design of Dual Polar Side Chain Polymers for Enhancing Electrochromic Performance

Synthetic Design of Dual Polar Side Chain Polymers for Enhancing Electrochromic Performance

Research on the "Agricultural and Tourism Dual Chain" Model of Leisure Agriculture from the Perspective of Circular Economy

Research on the "Agricultural and Tourism Dual Chain" Model of Leisure Agriculture from the Perspective of Circular Economy

Establishment of dual reverse transcriptase-polymerase chain reaction for detection system for Areca palm velarivirus 1.

Areca palm velarivirus 1 (APV1) is one of the main pathogen causing yellow leaf disease, and leading to considerable losses in the Areca palm industry. The detection methods for APV1 are primarily based on phenotype determination and molecular techniques, such as polymerase chain reaction (PCR). However, a single PCR has limitations in accuracy and sensitivity. Therefore, in the present study, we established a dual RT-PCR APV1-detection system with enhanced accuracy and sensitivity using two pairs of specific primers, YLDV2-F/YLDV2-R and YLDV4-F/YLDV4-R. Moreover, two cDNA fragments covering different regions of the viral genome were simultaneously amplified, with PCR amplicon of 311 and 499 bp, respectively. The dual RT-PCR detection system successfully amplified the two target regions of the APV1, demonstrating high specificity and sensitivity and compensating for the limitations of single-primer detection methods. We tested 60 Areca palm samples from different geographical regions, highlighting its advantages in that the dual RT-PCR system efficiently and accurately detected APV1 in samples across diverse areas. The dual RT-PCR APV1 detection system provides a rapid, accurate, and sensitive method for detecting the virus and offers valuable technical support for research in preventing and managing yellow leaf diseases caused by APV1 in Areca palms. Moreover, the findings of this study can serve as a reference for establishing similar plants viral detection systems in the future.

The Application of CRISPR/Cas9 Technology in Neurological Diseases

Neurological disease refers to the functional disorders of the central nervous system, peripheral nervous system or plant nervous system caused by a variety of causes such as bacterial infection or genetic. Patients usually show problems such as conscious disorder, sensory disorders, and motor disorder. Common neurological diseases such as Huntington, and Alzheimer's disease, have always been one of the main diseases that endanger human life because of their complex mechanisms and treatment. Gene therapy has always been considered a way to treat diseases. The discovery of Clustered Regularly Interspaced Short Palindromic Repeats(CRISPR) has improved gene editing technology and realized the application of various biological fields. CRISPR uses sgRNA to identify target sequences, so that CAS9 protein cuts DNA, and combines the guided RNA with the recognized DNA. Then the nucleic acid-cutting enzyme breaks the DNA dual chain structure, and the host cells were repaired through homologous or non-source mechanisms. CRISPR/Cas9 technology can better perform genetic treatment of neuropathy, making it possible for the development and new treatment methods of human neurodegenerative diseases. This review summarizes the basic principles of CRISPR/Cas9 technology and its application in Huntington's and Alzheimer's disease, as well as discusses the feasibility of CRISPR technology in neurological diseases in the future.

Prevalence of Helicobacter pylori infection and clarithromycin resistance rate from 2015 to 2018 using the laboratory information system of the Seegene Medical Foundation in Korea: a repeated cross-sectional study

Background: Numerous studies have examined the prevalence of Helicobacter pylori infection and clarithromycin (CLA) resistance rate of H. pylori. However, in South Korea, there is a lack of research analyzing specimens from local clinics and hospitals using molecular methods. This study aimed to assess the prevalence of H. pylori infection and CLA resistance across sex and age groups, as well as to explore regional variations in CLA resistance and its characteristics. Methods: Data from a laboratory information system from 2015 to 2018 were retrospectively analyzed to determine the prevalence of H. pylori infection and CLA resistance rate. The 23S ribosomal RNA genes of H. pylori were analyzed using a dual priming oligonucleotide-based multiplex polymerase chain reaction method. Results: The overall prevalence of H. pylori infection was 50.5%(12,000/23,773), with a significantly higher prevalence among males (53.5%) than females (47.0%). The CLA resistance rate was 28.3%, with a significantly higher rate among females (34.9%) than males (23.8%). Age group analysis revealed that the highest prevalence of H. pylori infection was among individuals in their 40s, whereas the highest CLA resistance rate was observed among those in their 60s. The CLA resistance rate exhibited an upward trend and varied among patients based on their place of residence, and A2143G mutation was the most prevalent across all regions. Conclusion: The prevalence of H. pylori infection and CLA resistance rate in Korea remain high and vary according to sex, age, and region. To effectively eradicate H. pylori, it is crucial to periodically monitor regional CLA resistance patterns and conduct CLA susceptibility testing before prescription.

Disruption Risk Analysis of Substitutable Dual Product Supply Chain: A System Dynamics Framework

Uncertain events such as earthquakes, epidemics, and wars have increased the risk of supply chain disruption. Due to the needs of carbon reduction policies and environmental protection, a large number of enterprises have started to produce both traditional and green products. Studying the issue of supply chain disruption for such enterprises has significant practical significance. We have developed a system dynamics model for a substitutable dual product supply chain with two levels of supply sources. Through simulation analysis, we found that (1) supply chain disruption can cause fluctuations in the manufacturer’s inventory, and disruptions from second tier suppliers have a higher impact on the manufacturer’s inventory than that from primary suppliers. In addition, the disruption of traditional products will cause consumers to flow to the green product market, resulting in a sudden increase in order for green products and components in a short period of time, causing a delayed impact on the inventory of suppliers and manufacturers of green products. (2) The disruption of upstream suppliers in traditional products causes the highest profit losses for all traditional product suppliers, while the disruption of downstream suppliers in green products causes the highest profit losses for the manufacturer and all green product suppliers. (3) From the perspective of the service level, compared to other components, the disruption of critical components in traditional products poses the highest risk of out of stock in the supply chain, while the risk of out-of-stock in the intermediate component of green product is the smallest. (4) Common sense may suggest that the more the suppliers disrupt, the higher the damage of the supply chain. However, due to the ripple effect, this article finds that from the perspectives of profit, inventory, and service level, multisupplier disruption is not necessarily inferior to single supplier disruption.

Cross-channel influences in mobile-app-website e-commerce supply chains: When to weaken the influence?

Today, e-commerce has entered the mobile era in which consumers can shop through both mobile app (MA) and website (WS) channels. By strategically designing the linkage between the two channels based on the cross-channel influences, companies can better handle the demand uncertainty of seasonal products. In this paper, we consider a dual channel e-commerce supply chain with an e-tailer and a manufacturer selling a seasonal product. We analytically examine how the e-tailer can (i) adopt risk pooling by aggregating the demands from both the MA and WS channels and (ii) invest in forecast-enhancement technology (FET) to improve inventory management. We uncover that when the magnitude of cross-channel influences increases, the impacts on the optimal inventory decision vary greatly depending on four different “model cases”; interestingly, it does not affect the optimal FET decision. Considering the impacts of cross-channel influences on the e-tailer’s expected profit, we reveal that the optimal weakening or strengthening strategy, i.e., “creating barriers” or “enhancing linkage” between two channels, depends on the e-tailer’s channel operations models. Then, we find that the optimal weakening or strengthening strategy follows the same pattern as in the basic model when the dual channel e-commerce supply chain is coordinated under a Nash bargaining framework. Last but not least, we study the potential use of blockchain technology to improve the effectiveness of FET investment. We surprisingly find that using blockchain or not does not affect the optimal MA and WS design decisions on weakening or strengthening linkages.

Asynchronous dissipative control for nonhomogeneous Markov jump systems with dual Markovian wireless fading channels

This article is devoted to the matter of asynchronous state feedback control for a class of nonhomogeneous Markov jump systems subjected to the dual Markovian wireless fading channel. A key feature here is that dual Markov chain is employed to model the stochastically switching of channel state with nonhomogeneous Markov process, which characterize both the transition of channel mode itself and the dependence on the system mode. Meanwhile, channel state-dependent packet dropout rate is time-varying with different channel mode. In the case of that, existing methods are difficult to deal with, resulting in the degradation of system performance. To this end, hidden Markov model-based asynchronous controller is firstly presented with compensated measurements. Secondly, co-designing with the asynchronous controller, a novel dynamic compensator is constructed to handle the mismatched measurements. Then, since both the Markov process of system and channel are considered, dual mode-dependent Lyapunov functional is constructed to verify the stochastic stability of the augmented system, as well as the strictly dissipative performance, which leads to less conservatism compared to the single mode-dependent one. Finally, a boost converter model driven by pulse-width-modulation is presented to demonstrate the validation of the proposed strategies.

A colorimetric tandem combination of CRISPR/Cas12a with dual functional hybridization chain reaction for ultra-sensitive detection of Mycobacterium bovis.

Tuberculosis caused by Mycobacterium bovis poses a global infectious threat to humans and animals. Therefore, there is an urgent need to develop a sensitive, precise, and easy-to-readout strategy. Here, a novel tandem combination of a CRISPR/Cas12a system with dual HCR (denoted as CRISPR/Cas12a-D-HCR) was constructed for detecting Mycobacterium bovis. Based on the efficient trans-cleavage activity of the active CRISPR/Cas12a system, tandem-dsDNA with PAM sites was established using two flexible hairpins, providing multiple binding sites with CRISPR/Cas12a for further amplification. Furthermore, the activation of Cas12a initiated the second hybridization chain reaction (HCR), which integrated complete G-quadruplex sequences to assemble the hemin/G-quadruplex DNAzyme. With the addition of H2O2 and ABTS, a colorimetric signal readout strategy was achieved. Consequently, CRISPR/Cas12a-D-HCR achieved a satisfactory detection linear range from 20 aM to 50 fM, and the limit of detection was as low as 2.75 aM with single mismatched recognition capability, demonstrating good discrimination of different bacterial species. Notably, the practical application performance was verified via the standard addition method, with the recovery ranging from 96.0% to 105.2% and the relative standard deviations (RSD) ranging from 0.95% to 6.45%. The proposed CRISPR/Cas12a-D-HCR sensing system served as a promising application for accurate detection in food safety and agricultural fields.

Financing a dual capital-constrained supply chain: Profit enhancement and diffusion effect of default risk

Supply chain finance (SCF) benefits participants by alleviating capital constraints and generating additional profits but also brings a host of disadvantages. This study examines and compares how various SCF schemes affect participants’ profits and the contagion and diffusion effects of default risk in a dual capital-constrained supply chain. This study used a game theoretical approach to investigate a dual capital-constrained supply chain. The financially constrained manufacturer and retailer may be funded by bank credit or trade credit from their upstream participants, forming four financing structures. The findings suggest that although trade credit offered by the manufacturer brings more profits to the supply chain participants than bank credit, it increases the expected losses of the creditors and incurs both the contagion and diffusion effects of default risk. Pure bank financing cannot completely coordinate the supply chain but can control the contagion and diffusion effects of default risk. These effects are also weakened over time. The findings offer implications for participants who implement financing and operational actions to improve their performance and control the contagion and diffusion effects of default risk along a supply chain.

ASMF: Ambient social media forensics chain of custody with an intelligent digital investigation process using federated learning

Ambient Intelligence is a concept that relates to a new paradigm of pervasive computing and has the objective of automating responses from the system to humans without any human intervention. In social media forensics, gathering, analyzing, storing, and validating relevant evidence for investigation in a heterogeneous environment is still questionable. There is no hierarchy for automation, even though standardization and secure processes from data collection to validation have not yet been discussed. This poses serious issues for the current investigation procedures and future evidence chain of custody management. This paper contributes threefold. First, it proposes a framework using a blockchain network with a dual chain of data transmission for privacy protection, such as on-chain and off-chain. Second, a protocol is designed to detect and separate local and global cyber threats and undermine multiple federated principles to personalize search space broadly. Third, this study manages personalized updates by means of optimizing backtracking parameters and automating replacements, which directly affects the reduction of negative influence on the social networking environment in terms of imbalanced and distributed data issues. This proposed framework enhances stability in digital investigation. In addition, the simulation uses an extensive social media dataset in different cyberspaces with a variety of cyber threats to investigate. The proposed work outperformed as compared to traditional single-level personalized search and other state-of-the-art schemes.

Confinement in Dual-Chain-Locked DNA Origami Nanocages Programs Marker-Responsive Delivery of CRISPR/Cas9 Ribonucleoproteins.

Delivery of CRISPR/Cas9 ribonucleoproteins (RNPs) offers a powerful tool for therapeutic genome editing. However, precise manipulation of CRISPR/Cas9 RNPs to switch the machinery on and off according to diverse disease microenvironments remains challenging. Here, we present dual-chain-locked DNA origami nanocages (DL-DONCs) that can confine Cas9 RNPs in the inner cavity for efficient cargo delivery and dual-marker-responsive genome editing in the specified pathological states. By engineering of ATP or miRNA-21-responsive dsDNAs as chain locks on the DONCs, the permeability of nanocages and accessibility of encapsulated Cas9 RNPs can be finely regulated. The resulting DL-DONCs enabled steric protection of bioactive Cas9 RNPs from premature release and deactivation during transportation while dismounting the dual chain locks in response to molecular triggers after internalization into tumor cells, facilitating the escape of Cas9 RNPs from the confinement for gene editing. Due to the dual-marker-dominated uncaging mechanism, the gene editing efficiency could be exclusively determined by the combined level of ATP and miRNA-21 in the target cellular environment. By targeting the tumor-associated PLK-1 gene, the DL-DONCs-enveloped Cas9 RNPs have demonstrated superior inhibitory effects on the proliferation of tumor cells in vitro and in vivo. The developed DL-DONCs provide a custom-made platform for the precise manipulation of Cas9 RNPs, which can be potentially applied to on-demand gene editing for classified therapy in response to arbitrary disease-associated biomolecules.

Dual carbon oriented optimization method for manufacturing industry chain based on BP neural network and clonal selection algorithm

Global economic growth and increasing carbon emissions pose significant challenges to managing and optimizing industry chains. Against the backdrop of carbon peak and carbon neutrality goals, manufacturing enterprises forgo economic efficiency to achieve low-carbon goals. Therefore, balancing the economic efficiency and carbon emissions of the entire industrial chain has become a vital issue for manufacturing enterprises. Based on the existing research, "a dual carbon industrial chain" is proposed in this study to reveal the characteristics of the industrial chain under the dual carbon goals. A collaborative optimization model under the "dual carbon industrial chain" was constructed by combining complex networks, back-propagation (BP) neural networks, and clonal selection algorithm to optimize the economic efficiency and carbon emissions of the entire industrial chain. Using a chip industry chain as an example, an optimization solution from the perspective of the overall industry chain is proposed. The results show that the proposed method can optimize the economic benefits and carbon emissions of the entire industrial chain, which has specific theoretical and practical significance for developing modern industrial chains with a dual carbon background.

A cooperative adaptive genetic algorithm for reentrant hybrid flow shop scheduling with sequence-dependent setup time and limited buffers

This paper deals with a reentrant hybrid flow shop problem with sequence-dependent setup time and limited buffers where there are multiple unrelated parallel machines at each stage. A mathematical model with the minimization of total weighted completion time is constructed for this problem. Considering the complexity of the problem at hand, an effective cooperative adaptive genetic algorithm (CAGA) is proposed. In the algorithm, a dual chain coding scheme and a staged-hierarchical decoding approach are, respectively, designed to encode and decode each solution. Six dispatch heuristics and a dynamic adjustment method are introduced to define initial population. To balance the exploration and exploitation abilities, three effective operations are implemented: (1) two new crossover and mutation operators with collaborative mechanism are imposed on genetic algorithm; (2) an adaptive adjustment strategy is introduced to re-optimize better solutions after mutation operations, where ant colony search algorithm and modified greedy heuristic are intelligently switched; (3) a reset strategy with dynamic variable step strategy is embedded to re-generate some non-improved solutions. A Taguchi method of design of experiment is adopted to calibrate the parameter values in the presented algorithm. Comparison experiments are executed on test instances with different scale problems. Computational results show that the proposed CAGA is more effective and efficient than several well-known algorithms in solving the studied problem.