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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Calcium and signal transduction in plants

Environmental and hormonal signals control diverse physiological processes in plants. The mechanisms by which plant cells perceive and transduce these signals are poorly understood. Understanding biochemical and molecular events involved in signal transduction pathways has become one of the most active areas of plant research. Research during the last 15 years has established that Ca2+ acts as a messenger in transducing external signals. The evidence in support of Ca2+ as a messenger is unequivocal and fulfills all the requirements of a messenger. The role of Ca2+ becomes even more important because it is the only messenger known so far in plants. Since our last review on the Ca2+ messenger system in 1987, there has been tremendous progress in elucidating various aspects of Ca(2+) -signaling pathways in plants. These include demonstration of signal-induced changes in cytosolic Ca2+, calmodulin and calmodulin-like proteins, identification of different Ca2+ channels, characterization of Ca(2+) -dependent protein kinases (CDPKs) both at the biochemical and molecular levels, evidence for the presence of calmodulin-dependent protein kinases, and increased evidence in support of the role of inositol phospholipids in the Ca(2+) -signaling system. Despite the progress in Ca2+ research in plants, it is still in its infancy and much more needs to be done to understand the precise mechanisms by which Ca2+ regulates a wide variety of physiological processes. The purpose of this review is to summarize some of these recent developments in Ca2+ research as it relates to signal transduction in plants.

NASA Program Space Biology↗
NASA NTRS2004

The AstroBiology Explorer (ABE) Mission Concept

Infrared spectroscopy in the 2.5-16 micron range is a principle means by which organic compounds can be detected and identified in space via their vibrational transitions. Ground-based, airborne, and spaceborne IR spectral studies have already demonstrated that a significant fraction of the carbon in the interstellar medium (ISM) resides in the form of complex organic molecular species. Unfortunately, neither the distribution of these materials nor their genetic and evolutionary relationships with each other or their environments are well understood. The Astrobiology Explorer (ABE) is a MIDEX mission concept currently under study by a team of partners: NASA's Ames Research Center, Ball Aerospace and Technologies Corporation, and the Jet Propulsion Laboratory. ABE will conduct IR spectroscopic observations to address outstanding important problems in astrobiology, astrochemistry, and astrophysics. The core observational program would make fundamental scientific progress in understanding (1) The evolution of ices and organic matter in dense molecular clouds and young forming stellar systems, (2) The chemical evolution of organic molecules in the ISM as they transition from AGB outflows to planetary nebulae to the general diffuse ISM to HII regions and dense clouds, (3) The distribution of organics in the diffuse ISM, (4) The nature of organics in the Solar System (in comets, asteroids, satellites), and (5) The nature and distribution of organics in local galaxies. The technical considerations of achieving these science objectives in a MIDEX-sized mission will be presented.

Sandford, Scott A.↗
NASA NTRS1992

Origin and early evolution of photosynthesis

Photosynthesis was well-established on the earth at least 3.5 thousand million years ago, and it is widely believed that these ancient organisms had similar metabolic capabilities to modern cyanobacteria. This requires that development of two photosystems and the oxygen evolution capability occurred very early in the earth's history, and that a presumed phase of evolution involving non-oxygen evolving photosynthetic organisms took place even earlier. The evolutionary relationships of the reaction center complexes found in all the classes of currently existing organisms have been analyzed using sequence analysis and biophysical measurements. The results indicate that all reaction centers fall into two basic groups, those with pheophytin and a pair of quinones as early acceptors, and those with iron sulfur clusters as early acceptors. No simple linear branching evolutionary scheme can account for the distribution patterns of reaction centers in existing photosynthetic organisms, and lateral transfer of genetic information is considered as a likely possibility. Possible scenarios for the development of primitive reaction centers into the heterodimeric protein structures found in existing reaction centers and for the development of organisms with two linked photosystems are presented.

NASA Program Exobiology↗
DOE OSTI2026

A haplotype-resolved, chromosome-scale genome assembly for the southern live oak, Quercus virginiana

Hybridization is a major force driving diversification, migration, and adaptation in Quercus species. While population genetics and phylogenetics have traditionally been used for studying these processes, advances in sequencing technology now enable us to incorporate comparative and pan-genomic approaches as well. Here, we present a highly contiguous, chromosome-scale and haplotype-resolved genome assembly for the southern live oak, Quercus virginiana, the first reference genome for section Virentes, as part of the American Campus Tree Genomes program. Originating from a clone of Auburn University's historic “Toomer's Oak,” this assembly contributes to the pool of genomic resources for investigating recombination, haplotype variation, and structural genomic changes influencing hybridization potential in this clade and across Quercus. It also provides insights into the architecture of the putative centromeric regions within the genus. Alongside other oak references, the Q. virginiana genome will support research into the evolution and adaptation of the Quercus genus.

Quercus virginiana↗
NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗
NASA NTRSDate not supplied

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗
NASA NTRS2024

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June to October 2020)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June to October 2020 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 30 cm depth below surface to just above the cobble layer (~190-250 cm depth) at discrete depths every 40 cm for microbial analyses. A total of 35 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2848 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Phylogenetic relationships of the Fox (Forkhead) gene family in the Bilateria

The Forkhead or Fox gene family encodes putative transcription factors. There are at least four Fox genes in yeast, 16 in Drosophila melanogaster (Dm) and 42 in humans. Recently, vertebrate Fox genes have been classified into 17 groups named FoxA to FoxQ. Here, we extend this analysis to invertebrates, using available sequences from D. melanogaster, Anopheles gambiae (Ag), Caenorhabditis elegans (Ce), the sea squirt Ciona intestinalis (Ci) and amphioxus Branchiostoma floridae (Bf), from which we also cloned several Fox genes. Phylogenetic analyses lend support to the previous overall subclassification of vertebrate genes, but suggest that four subclasses (FoxJ, L, N and Q) could be further subdivided to reflect their relationships to invertebrate genes. We were unable to identify orthologs of Fox subclasses E, H, I, J, M and Q1 in D. melanogaster, A. gambiae or C. elegans, suggesting either considerable loss in ecdysozoans or the evolution of these subclasses in the deuterostome lineage. Our analyses suggest that the common ancestor of protostomes and deuterostomes had a minimum complement of 14 Fox genes.

NASA Program Fundamental Space Biology↗
NASA NTRS1993

Evolution of catalytic function

An RNA-based evolution system was constructed in the laboratory and used to develop RNA enzymes with novel catalytic function. By controlling the nature of the catalytic task that the molecules must perform in order to survive, it is possible to direct the evolving population toward the expression of some desired catalytic behavior. More recently, this system has been coupled to an in vitro translation procedure, raising the possibility of evolving protein enzymes in the laboratory to produce novel proteins with desired catalytic properties. The aim of this line of research is to reduce darwinian evolution, the fundamental process of biology, to a laboratory procedure that can be made to operate in the service of organic synthesis.

NASA Program Exobiology↗
NASA NTRS1998

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗
NASA NTRS1993

Structure and function of the homeotic gene complex (HOM-C) in the beetle, Tribolium castaneum

The powerful combination of genetic, developmental and molecular approaches possible with the fruit fly, Drosophila melanogaster, has led to a profound understanding of the genetic control of early developmental events. However, Drosophila is a highly specialized long germ insect, and the mechanisms controlling its early development may not be typical of insects or Arthropods in general. The beetle, Tribolium castaneum, offers a similar opportunity to integrate high resolution genetic analysis with the developmental/molecular approaches currently used in other organisms. Early results document significant differences between insect orders in the functions of genes responsible for establishing developmental commitments.

NASA Program NSCORT↗
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗
NASA NTRS1992

On the nature of global classification

Molecular sequencing technology has brought biology into the era of global (universal) classification. Methodologically and philosophically, global classification differs significantly from traditional, local classification. The need for uniformity requires that higher level taxa be defined on the molecular level in terms of universally homologous functions. A global classification should reflect both principal dimensions of the evolutionary process: genealogical relationship and quality and extent of divergence within a group. The ultimate purpose of a global classification is not simply information storage and retrieval; such a system should also function as an heuristic representation of the evolutionary paradigm that exerts a directing influence on the course of biology. The global system envisioned allows paraphyletic taxa. To retain maximal phylogenetic information in these cases, minor notational amendments in existing taxonomic conventions should be adopted.

NASA Program Exobiology↗
NASA NTRSDate not supplied

From Source to Surface: An Investigation of Magmatic Lunar Volatiles

Lunar missions led by NASA discovered water ice on the Moon’s surface [1-3], revolutionizing views of the abundance, distribution, and potential sources of H2O and other volatiles. Volatiles play an important role in affecting the rheological properties of minerals and melts and influencing magma eruption processes. In order to determine the indigenous volatile inventory of the Moon, it is vital to identify the magmatic and secondary processes that may have affected the volatile contents in lunar minerals [4]. As part of the Apollo Next Generation Sample Analysis (ANGSA) program we are investigating the petrogenesis of a set of four Apollo lunar basalts collected from the rim of Steno Crater 71035, 71037, 71055, and specially curated sample 71036. Our team is studying the petrology in 2D and 3D (this work), chronology (Pomeroy et al., LPSC 2022), oxidation state of sulfur in apatite (Brounce et al., LPSC 2022), and volatile inventory of the sample set in order to understand the age and genetic relationships among the basalts, their magma ascent conditions and eruptive signatures, and their degassing and surface histories. Here we present the first detailed study of the 2D and 3D mineralogy, textures, 3D vesiculation, and chemistry of these basalts to shed light on their magmatic, volcanic, and post-eruptive histories. Note: Extended abstract on document.

Z. E. Wilbur↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (August 2015)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken August 29, 2015 at a location (KB1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples from a deep soil pit were collected from 0 to 234 cm depth below surface at discrete depths every ~10-20 cm for microbial analyses. 13 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores).This dataset includes a zip file of 2216 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗