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Data temperature is a response to the ever-growing amount of data. These data have to be stored, but they have been observed that only a small portion of the data are accessed more frequently at any one time. This leads to the concept of hot and cold data. Cold data can be migrated away from high-performance nodes to free up performance for higher priority data. Existing studies classify hot and cold data primarily on the basis of data age and usage frequency. We present this as a limitation in the current implementation of data temperature. This is due to the fact that age automatically assumes that all new data have priority and that usage is purely reactive. We propose new variables and conditions that influence smarter decision-making on what are hot or cold data and allow greater user control over data location and their movement. We identify new metadata variables and user-defined variables to extend the current data temperature value. We further establish rules and conditions for limiting unnecessary movement of the data, which helps to prevent wasted input output (I/O) costs. We also propose a hybrid algorithm that combines existing variables and new variables and conditions into a single data temperature. The proposed system provides higher accuracy, increases performance, and gives greater user control for optimal positioning of data within multi-tiered storage solutions.

Little is known about how older adults with a current or recent experience of homelessness navigated the switch to telehealth during the COVID-19 pandemic. We examined the perceptions and use of telehealth in a purposive sample of 37 homeless-experienced older adults in mid-late 2020 through semi-structured qualitative interviews. We purposively recruited participants from a larger longitudinal study on homeless-experienced older adults in Oakland, CA. We subjected the data to content analysis. We found that most participants who used telehealth used audio-only phone calls for care. We found that (1) participants experienced challenges accessing the necessary technologies for telehealth, (2) perceptions of telehealth for physical health differed based on the modality (video vs. audio-only), and (3) participants had generally positive perceptions of telehealth for mental healthcare. Our findings suggest that clinicians interacting with homeless-experienced older adults should address the potential skepticism of audio-only telehealth patients, and assess their access to, and knowledge of, video conferencing technology.

Summary: Plants offer a promising chassis for the large‐scale, cost‐effective production of diverse therapeutics, including antimicrobial peptides (AMPs). However, key advances will reduce production costs, including simplifying the downstream processing and purification steps. Here, using Nicotiana benthamiana plants, we present an improved modular design that enables AMPs to be secreted via the endomembrane system and sequestered in an extracellular compartment, the apoplast. Additionally, we translationally fused an AMP to a mutated small ubiquitin‐like modifier sequence, thereby enhancing peptide yield and solubilizing the peptide with minimal aggregation and reduced occurrence of necrotic lesions in the plant. This strategy resulted in substantial peptide accumulation, reaching around 2.9 mg AMP per 20 g fresh weight of leaf tissue. Furthermore, the purified AMP demonstrated low collateral toxicity in primary human skin cells, killed pathogenic bacteria by permeabilizing the membrane and exhibited anti‐infective efficacy in a preclinical mouse (Mus musculus) model system, reducing bacterial loads by up to three orders of magnitude. A base‐case techno‐economic analysis demonstrated the economic advantages and scalability of our plant‐based platform. We envision that our work can establish plants as efficient bioreactors for producing preclinical‐grade AMPs at a commercial scale, with the potential for clinical applications. [ABSTRACT FROM AUTHOR]

BackgroundCRISPR/Cas systems confer immunity against invading nucleic acids and phages in bacteria and archaea. CRISPR/Cas13a (known previously as C2c2) is a class 2 type VI-A ribonuclease capable of targeting and cleaving single-stranded RNA (ssRNA) molecules of the phage genome. Here, we employ CRISPR/Cas13a to engineer interference with an RNA virus, Turnip Mosaic Virus (TuMV), in plants.ResultsCRISPR/Cas13a produces interference against green fluorescent protein (GFP)-expressing TuMV in transient assays and stable overexpression lines of Nicotiana benthamiana. CRISPR RNA (crRNAs) targeting the HC-Pro and GFP sequences exhibit better interference than those targeting other regions such as coat protein (CP) sequence. Cas13a can also process pre-crRNAs into functional crRNAs.ConclusionsOur data indicate that CRISPR/Cas13a can be used for engineering interference against RNA viruses, providing a potential novel mechanism for RNA-guided immunity against RNA viruses and for other RNA manipulations in plants.

Summary: Antimicrobial peptides (AMPs) are emerging as next‐generation therapeutics due to their broad‐spectrum activity against drug‐resistant bacterial strains and their ability to eradicate biofilms, modulate immune responses, exert anti‐inflammatory effects and improve disease management. They are produced through solid‐phase peptide synthesis or in bacterial or yeast cells. Molecular farming, i.e. the production of biologics in plants, offers a low‐cost, non‐toxic, scalable and simple alternative platform to produce AMPs at a sustainable cost. In this review, we discuss the advantages of molecular farming for producing clinical‐grade AMPs, advances in expression and purification systems and the cost advantage for industrial‐scale production. We further review how 'green' production is filling the sustainability gap, streamlining patent and regulatory approvals and enabling successful clinical translations that demonstrate the future potential of AMPs produced by molecular farming. Finally, we discuss the regulatory challenges that need to be addressed to fully realize the potential of molecular farming‐based AMP production for therapeutics. [ABSTRACT FROM AUTHOR]

Text detection in natural scene images for content analysis is an interesting task. The research community has seen some great developments for English/Mandarin text detection. However, Urdu text extraction in natural scene images is a task not well addressed. In this work, firstly, a new dataset is introduced for Urdu text in natural scene images. The dataset comprises of 500 standalone images acquired from real scenes. Secondly, the channel enhanced Maximally Stable Extremal Region (MSER) method is applied to extract Urdu text regions as candidates in an image. Two-stage filtering mechanism is applied to eliminate non-candidate regions. In the first stage, text and noise are classified based on their geometric properties. In the second stage, a support vector machine classifier is trained to discard non-text candidate regions. After this, text candidate regions are linked using centroid-based vertical and horizontal distances. Text lines are further analyzed by a different classifier based on HOG features to remove non-text regions. Extensive experimentation is performed on the locally developed dataset to evaluate the performance. The experimental results show good performance on test set images. The dataset will be made available for research use. To the best of our knowledge, the work is the first of its kind for the Urdu language and would provide a good dataset for free research use and serve as a baseline performance on the task of Urdu text extraction.

Rapid urban growth necessitates focused attention regarding its policy and governance to ensure affordable housing, transparent and efficient real-world systems, reduce social inequalities, and promote sustainable development. This study delves into the semantics and ontology for developing a Land Administration Domain Model (LADM) profile in the context of Pakistan's Land Administration Systems (LASs), which currently face issues due to manual record-keeping, lack of transparency, frauds, and disintegration. Establishing a baseline through Record of Rights (RoR) and Property Information Report (PIR), alongside surveying and mapping procedures defined by laws and rules, forms the foundation for LADM profile development. This study explores the transition from manual LAS to 2D/3D representation, using LADM as a conceptual guideline. The LADM profile's three key packages—PK_Party, PK_Administrative, and PK_SpatialUnit—a sub-package, and external classes are examined, with proposals for digitalisation and modernisation. Additionally, the study includes expert consultation, and highlights the significant support that the LADM implementation offers to achieve Sustainable Development Goals (SDGs) in Pakistan. In conclusion, the study underscores the need for a comprehensive and inclusive approach to address organisational overlaps and ambiguities within LAS, positioning PK LADM as a transformative force for sustainable urban LAS in Pakistan, aligning with broader SDGs. Recommendations include exploring realistic land valuation, integrated ownership and location verification systems, addressing historical survey data challenges, and promoting wider stakeholder adoption for sustainable 2D/3D urban LAS using LADM and its edition II as a way forward towards the creation of a smart city and digital twin. [ABSTRACT FROM AUTHOR]

We concentrate on Molecular-FET as a device and present a new modular framework based on VHDL-AMS. We have implemented different Molecular-FET models within the framework. The framework allows comparison between the models in terms of the capability to calculate accurate I-V characteristics. It also provides the option to analyze the impact of Molecular-FET and its implementation in the circuit with the extension of its use in an architecture based on the crossbar configuration. This analysis evidences the effect of choices of technological parameters, the ability of models to capture the impact of physical quantities, and the importance of considering defects at circuit fabrication level. The comparison tackles the computational efforts of different models and techniques and discusses the trade-off between accuracy and performance as a function of the circuit analysis final requirements. We prove this methodology using three different models and test them on a 16-bit tree adder included in Pentium 4 that, to the best of our knowledge, is the biggest circuits based on molecular device ever designed and analyzed.

Spatial data is one of the core components in all information retrieval processes for decision-making. Spatial data acquisition consumes enormous monetary resources and time. The Integrated Geospatial Information Framework (IGIF) provides a basis and guide for developing, integrating, strengthening, and maximizing geospatial information management and related resources in all countries. To this, governments all over the world are establishing national spatial data infrastructures (SDIs). However, such initiatives face a considerable amount of resistance as organizations often do not want to share their data assets. The present study investigates these barriers in the establishment of national SDI in Pakistan. The constraints studied through the IGIF pathways and past studies were adapted via a pilot study and conceptualized in a hypothesized model. We collected primary data via the administration of 520 questionnaire surveys to 280 public and private organizations. Partial least squares structural equation modeling (PLS-SEM) was applied to statistically confirm the conceptual model of the barriers to disseminating spatial data. The results indicate institutional barriers from the absence of national data policy, lack of specified roles of stakeholders, poor inter-organizational coordination, missing data-sharing policy, and weak organizational partnerships, with coefficients 0.26, 1.555, 1.305, 8.288, and 0.136, respectively, at the p < 0.001 significance level. The PLS-SEM R2 0.65 indicates a good explanatory power of the model. The methodology developed in the present study will allow devising more sustainable policies for spatial data management and dissemination in Pakistan and beyond. [ABSTRACT FROM AUTHOR]