Land Use Land Cover Dynamics of Oba Hills Forest Reserve, Nigeria, Employing Multispectral Imagery and GIS

Land use Land cover (LULC) has undergone progressive changes worldwide over the years. However, there is limited information available about these changes in Oba Hills Forest Reserve, Nigeria. The existing spatial analysis of the forest excluded important land use classes like settlements. Therefore, this study aimed at assessing the dynamics of LULC in Oba Hills Forest Reserve between 1987 and 2019. Images from Landsat 5, Landsat 7, and Landsat 8 for the years 1987, 2001, 2013, and 2019 were obtained and subjected to preprocessing and classification using the maximum likelihood algorithm, change detection, and Normalized Differential Vegetation Index (NDVI). The coordinates of specific benchmark locations and other points were acquired for ground-truthing and developing Digital Elevation Model (DEM). Three distinct LULC classes were identified: forest, bare land (including open spaces, agriculture, rocks, and grasslands), and built-up areas. The forest cover in the reserve gradually decreased from 56% in 1987 to 47% in 2019, resulting in a total area loss of 455.4 hectares. Correspondingly, the other LULC classes experienced exponential expansion. Bare land increased from 44% in 1987 to 52% in 2019, while the built-up area expanded by 57.28 hectares. These changes are attributed to prevalent anthropogenic activities such as agriculture, grazing, logging, firewood collection, and population growth within the catchment area. The declining NDVI values in the forest reserve, from 0.52 to 0.44 within the years of assessment, further substantiated the substantial loss of forest cover. The DEM and topographical map highlighted notable steep slopes and elevations of up to over 550 m above sea level (asl) within the reserve, which have implications for forest growth and dynamics. In conclusion, this study reveals extensive rates of forest cover changes into bare land, primarily for agriculture, and settlements, and offers further recommendations to reverse the trend.

Genetic Diversity in Cultivated Groundnut Based on SSR Markers

Peanut （Arachis hypogaea L.） is an important source crop for edible oil and protein. It is important to identify the genetic diversity of peanut genetic resources for cultivar development and evaluation of peanut accessions. Thirty-four SSR markers were used to assess the genetic variation of four sets of twenty-four accessions each from the four botanical varieties of the cultivated peanut. Among the tested accessions, ten to sixteen pairs of SSR primers showed polymorphisms. The maximum differentiation index, which was defined as the degree of genetic differentiation, was as high as 0.992 in the tested accessions. Each accession could be discriminated by a specific set of polymorphic SSR primers, and the intra-variety genetic distance was determined among accessions, with an average of 0.59 in var. fastigiata, 0.46 in var. hypogaea, 0.38 in var. vulgaris, and 0.17 in var. hirsuta. Dendrogrames based on genetic distances were constructed for the four botanical varieties, which revealed the existence of different clusters. It was concluded that there was abundant intra-variety SSR polymorphism, and with more and more SSR markers being developed, the intrinsic genetic diversity would be detected and the development of genetic map and marker-assisted selection for cultivated peanut would be feasible.

Monitoring Soil Salt Content Using HJ-1A Hyperspectral Data: A Case Study of Coastal Areas in Rudong County, Eastern China

Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.

High Differential Group Index of Dispersion Compensating Fibers for OCDMA Encoder/Decoder

We report the LPG pair device that can be used as a pulse duplicator or an OCDMA encoder/decoder. Due to the ring core region of dispersion compensating fiber (DCF), we can shorten the device length by a third and obtain surrounding insensitive LPG devices.

Normalization of Indexed Differentials by Extending Grobner Basis Theory

It is a fundamental problem to determine the equivalence of indexed differential polynomials in both computer algebra and differential geometry.However,in the literature,there are no general computational theories for this problem.The main reasons are that the ideal generated by the basic syzygies cannot be finitely generated,and it involves eliminations of dummy indices and functions.This paper solves the problem by extending Grobner basis theory.The authors first present a division of the set of elementary indexed differential monomials E■ into disjoint subsets,by defining an equivalence relation on E■ based on Leibniz expansions of monomials.The equivalence relation on E■also induces a division of a Grobner basis of basic syzygies into disjoint subsets.Furthermore,the authors prove that the dummy index numbers of the sim-monomials of the elements in each equivalence class of E■ have upper bounds,and use the upper bounds to construct fundamental restricted rings.Finally,the canonical form of an indexed differential polynomial proves to be the normal form with respect to a subset of the Grobner basis in the fundamental restricted ring.

DynamicRetriever:A Pre-trained Model-based IR System Without an Explicit Index

Web search provides a promising way for people to obtain information and has been extensively studied.With the surge of deep learning and large-scale pre-training techniques,various neural information retrieval models are proposed,and they have demonstrated the power for improving search(especially,the ranking)quality.All these existing search methods follow a common paradigm,i.e.,index-retrieve-rerank,where they first build an index of all documents based on document terms(i.e.,sparse inverted index)or representation vectors(i.e.,dense vector index),then retrieve and rerank retrieved documents based on the similarity between the query and documents via ranking models.In this paper,we explore a new paradigm of information retrieval without an explicit index but only with a pre-trained model.Instead,all of the knowledge of the documents is encoded into model parameters,which can be regarded as a differentiable indexer and optimized in an end-to-end manner.Specifically,we propose a pre-trained model-based information retrieval(IR)system called DynamicRetriever,which directly returns document identifiers for a given query.Under such a framework,we implement two variants to explore how to train the model from scratch and how to combine the advantages of dense retrieval models.Compared with existing search methods,the model-based IR system parameterizes the traditional static index with a pre-training model,which converts the document semantic mapping into a dynamic and updatable process.Extensive experiments conducted on the public search benchmark Microsoft machine reading comprehension(MS MARCO)verify the effectiveness and potential of our proposed new paradigm for information retrieval.

Computational Insights into Interactions between Ca Species and α-Fe_2O_3(001)

CaC12 can be sprayed onto sinter surface, which can improve the low temperature reduction degradation index （RDI＋3.15） of sinter. This has been recognized; however, there are various opinions on the inhibition mechanism of it. At the same time, the corrosion of C1 element on equipment is very serious. First-principle calculations based on density functional theory were performed to investigate the binding mechanisms of calcium species on a a-Fe2 03 （0 0 1） surface. This is crucial in demonstrating the role of the CaC12 on improving the low temperature reduction degrada tion index. It has been determined that C1 could greatly increase the adsorption of the vacuum layer for the Ca/Fe2 03 system and the relaxation produced by adsorption made bond length decrease, bond energies increase and structure compact. Those are the main reasons that inhibiting the reduction disintegration of sinter.

Finding neoepitopes in mouse models of personalized cancer immunotherapy

BACKGROUND： Cancer immunotherapy uses one＇s own immune system to fight cancerous cells. As immune system is hard- wired to distinguish self and non-self, cancer immunotherapy is predicted to target cancerous cells specifically, therefore is less toxic than chemotherapy and radiation therapy, two major treatments for cancer. Cancer immunologists have spent decades to search for the specific targets in cancerous cells. METHODS： Due to the recent advances in high throughput sequencing and bioinformatics, evidence has merged that the neoantigens in cancerous cells are probably the cancer-specific targets that lead to the destruction of cancer. We will review the transplantable murine tumor models for cancer immunotherapy and the bioinformatics tools used to navigate mouse genome to identify tumor-rejecting neoantigens. RESULTS： Several groups have independently identified point mutations that can be recognized by T cells of host immune system. It is consistent with the note that the formation ofpeptide-MHC I-TCR complex is critical to activate T cells. Both anchor residue and TCR-facing residue mutations have been reported. While TCR-facing residue mutations may directly activate specific T cells, anchor residue mutations improve the binding of peptides to MHC I molecules, which increases the presentation of peptides and the T cell activation indirectly. CONCLUSIONS： Our work indicates that the affinity of neoepitopes for MHC I is not a predictor for anti-tumor immune responses in mice. Instead differential agretopic index （DAI）, the numerical difference of epitope-MHC I affinities between the mutated and un-mutated sequences is a significant predictor. A similar bioinformatics pipeline has been developed to generate personalized vaccines to treat human ovarian cancer in a Phase I clinical trial.

Rapid detection of chlorophyll content and distribution in citrus orchards based on low-altitude remote sensing and bio-sensors

The accuracy of detecting the chlorophyll content in the canopy and leaves of citrus plants based on sensors with different scales and prediction models was investigated for the establishment of an easy and highly-efficient real-time nutrition diagnosis technology in citrus orchards.The fluorescent values of leaves and canopy based on the Multiplex 3.6 sensor,canopy hyperspectral reflectance data based on the FieldSpec4 radiometer and spectral reflectance based on low-altitude multispectral remote sensing were collected from leaves of Shatang mandarin and then analyzed.Additionally,the associations of the leaf SPAD(soil and plant analyzer development)value with the ratio vegetation index(RVI)and normalized differential vegetation index(NDVI)were analyzed.The leaf SPAD value predictive model was established by means of univariate and multiple linear regressions and the partial least squares method.Variable distribution maps of the relative canopy chlorophyll content based on spectral reflectance in the orchard were automatically created.The results showed that the correlations of the SPAD values obtained from the Multiplex 3.6 sensor,FieldSpec4 radiometer and low-altitude multispectral remote sensing were highly significant.The measures of goodness of fit of the predictive models were R^(2)=0.7063,RMSECV=3.7892,RE=5.96%,and RMSEP=3.7760 based on RVI_((570/800)) and R^(2)=0.7343,RMSECV=3.6535,RE=5.49%,and RMSEP=3.3578 based on NDVI[(570,800)(570,950)(700,840)].The technique to create spatial distribution maps of the relative canopy chlorophyll content in the orchard was established based on sensor information that directly reflected the chlorophyll content of the plants in different parts of the orchard,which in turn provides evidence for implementation of orchard productivity evaluation and precision in fertilization management.