P-T conditions of Pan-African orogeny in southeastern Nigeria

Abstract Different rock types from the area northeast of Obudu, southeastern Nigeria were investigated in order to place constraints on their metamorphic conditions. Detailed petrographic studies indicate four main rock groups in the studied area, namely migmatitic gneiss, migmatitic schist, granite gneiss and a minor amount of amphibolite, metagabbro and dolerite. The chemistry of minerals in these rocks is used to estimate metamorphic pressure and temperature (P-T) using appropriate geothermometers and geobarometers. The estimated temperature for migmatitic gneiss of the area is ∼600–625 °C and 600–650 °C for migmatitic schist; the pressure is ∼ 8 kbar. For amphibolite the temperature is ∼600–700 °C and pressure is 8–12 kbar. The estimated pressures and temperatures for the northeast Obudu rocks correspond to upper amphibolite to lower granulite facies metamorphism. The metamorphism occurred due to continent-continent collision during the Pan-African orogeny, most likely during the D1 deformational phase of the area. The recorded high pressures possibly resulted from crustal thickening in the area. P-T conditions for Pan-African orogeny in northeast Obudu area are in good agreement with P-T estimations for the Pan-African event in adjacent areas

Efam: an expanded, metaproteome-supported HMM profile database of viral protein families

Motivation: Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Results: Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from 'conservative' to 'eXtremely Conservative' resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem

Using Optimized Three-Band Spectral Indices and a Machine Learning Model to Assess Squash Characteristics under Moisture and Potassium Deficiency Stress

Moisture and potassium deficiency are two of the main limiting variables for squash crop performance in many water-stressed places worldwide. If major output decreases are to be avoided, it is critical to detect signs of crop stress as early as possible in the growth cycle. Proximal remote sensing can be a reliable technique for offering a rapid and precise instrument and localized management tool. This study tested the ability of proximal hyperspectral remotely sensed data to predict squash traits in two successive seasons (spring and fall) with varying moisture and potassium rates. Spectral data were collected from drip-irrigated squash that had been treated to varied rates of irrigation and potassium fertilization over both investigated seasons. To forecast potassium-use efficiency (KUE), chlorophyll meter (Chlm), water-use efficiency (WUE), and seed yield (SY) of squash, different commonly used and newly-introduced spectral index values for three bands (3D-SRIs), as well as a Decision Tree (DT) model, were evaluated. The results revealed that the newly constructed three-band SRIs based on the wavelengths of the visible (VIS), near-infrared (NIR), and red-edge regions were sensitive enough to measure the four tested parameters of squash in this study. For instance, NDI558,646,708 presented the highest R2 of 0.75 for KUE, NDI744,746,738 presented the highest R2 of 0.65 for Chlm, and NDI670,628,392 presented the highest R2 of 0.64 for SY of squash. The results further demonstrated that the principal component analysis (PCA) demonstrated the ability to distinguish moisture stress from potassium deficiency stress at the flowering stage onwards. Combining 3D-SRIs, DT-based bands (DT-b), and the aggregate of all spectral characteristics (ASF) with DT models would be an effective strategy for estimating four observed parameters with appropriate accuracy. For example, the model’s approximately 30 spectral characteristics were extremely important for predicting KUE. Its outputs with R2 were, for the training and validation datasets, 0.967 (RMSE = 0.175) and 0.818 (RMSE = 0.284), respectively. For measuring Chlm, the DT-DT-b-20 model demonstrated the best. In the training and validation datasets, the R2 value was 0.993 (RMSE = 0.522) and 0.692 (RMSE = 2.321), respectively. The overall outcomes showed that proximal-reflectance-sensing-based 3D-SRIs and DT models based on 3D-SRIs, DT-b, and ASF could be used to evaluate the four tested parameters of squash under different levels of irrigation regimes and potassium fertilizer

efam: an expanded, metaproteome-supported HMM profile database of viral protein families.

MotivationViruses infect, reprogram, and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases.ResultsHere we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240,311 HMM profiles, each with at least 2 protein sequences, making efam &gt;7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from "conservative" to "eXtremely Conservative" resulted in 37,841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs (&lt;5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem.AvailabilityThe resources are available on the iVirus platform at (doi.org/10.25739/9vze-4143).Supplementary informationSupplementary data are available at Bioinformatics online

International Journal of Sustainable Development and Planning.

The International Journal of Sustainable Development and Planning is an interdisciplinary journal covering the subjects of environmental design and planning, environmental management, spatial planning, environmental planning, environmental management and sustainable development in an integrated way as well as in accordance with the principles of sustainability. In the beginning of the 21st century, despite major scientific and technological accomplishments, the struggle for a cleaner environment as well as for rational organization of space is not settled. It is clear to us that environmentalists, planners, policy makers, engineers and economists have to work together in order to ensure that environmental protection, spatial co-ordination and economic development could all be achieved without compromising the ability of future generations to meet their own requirements. In recent years, an increase in spatial and environmental problems in many countries has led to a crisis in environmental planning and management. The increasing urbanization of the world coupled with the issues of environmental pollution, resource shortages and economic restructuring demand that a lot of effort will be required in order to make our cities sustainable. Moreover, problems of sustainable planning and management are not restricted to urban areas, since rural areas face serious environmental challenges. The aim of the International Journal of Sustainable Development and Planning is to inform its readers about all aspects of environmental planning and management. The journal includes subjects ranging from social to technical environmental management issues, having always as an axis the concept of sustainable planning and development