Background Selection Research Articles

MaxEnt brings comparable results when the input data are being completed; Model parameterization of four species distribution models.

Species distribution models (SDMs) are practical tools to assess the habitat suitability of species with numerous applications in environmental management and conservation planning. The manipulation of the input data to deal with their spatial bias is one of the advantageous methods to enhance the performance of SDMs. However, the development of a model parameterization approach covering different SDMs to achieve well-performing models has rarely been implemented. We integrated input data manipulation and model tuning for four commonly-used SDMs: generalized linear model (GLM), gradient boosted model (GBM), random forest (RF), and maximum entropy (MaxEnt), and compared their predictive performance to model geographically imbalanced-biased data of a rare species complex of mountain vipers. Models were tuned up based on a range of model-specific parameters considering two background selection methods: random and background weighting schemes. The performance of the fine-tuned models was assessed based on recently identified localities of the species. The results indicated that although the fine-tuned version of all models shows great performance in predicting training data (AUC > 0.9 and TSS > 0.5), they produce different results in classifying out-of-bag data. The GBM and RF with higher sensitivity of training data showed more different performances. The GLM, despite having high predictive performance for test data, showed lower specificity. It was only the MaxEnt model that showed high predictive performance and comparable results for identifying test data in both random and background weighting procedures. Our results highlight that while GBM and RF are prone to overfitting training data and GLM over-predict nonsampled areas MaxEnt is capable of producing results that are both predictable (extrapolative) and complex (interpolative). We discuss the assumptions of each model and conclude that MaxEnt could be considered as a practical method to cope with imbalanced-biased data in species distribution modeling approaches.

Inter- and intrafractional 4D dose accumulation for evaluating ΔNTCP robustness in lung cancer

Background and purposeModel-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, but NTCP can be affected when the delivered treatment deviates from the plan due to delivery inaccuracies. Especially for proton therapy of lung cancer, this can be important because of tissue density changes and, with pencil beam scanning, the interplay effect between the proton beam and breathing motion. Materials and methodsIn this work, we verified whether the expected benefit of proton therapy is retained despite delivery inaccuracies by reconstructing the delivered treatment using log-file based dose reconstruction and inter- and intrafractional accumulation. Additionally, the importance of two uncertain parameters for treatment reconstruction, namely deformable image registration (DIR) algorithm and α/β ratio, was assessed. ResultsThe expected benefit or proton therapy was confirmed in 97% of all studied cases, despite regular differences up to 2 percent point (p.p.) NTCP between the delivered and planned treatments. The choice of DIR algorithm affected NTCP up to 1.6 p.p., an order of magnitude higher than the effect of α/β ratio. ConclusionFor the patient population and treatment technique employed, the predicted clinical benefit for patients selected for proton therapy was confirmed for 97.0% percent of all cases, although the NTCP based proton selection was subject to 2 p.p. variations due to delivery inaccuracies.

Conditions for maintaining and eroding pseudo-overdominance and its contribution to inbreeding depression

Classical models that ignore linkage predict that deleterious recessive mutations should purge or fix within inbred populations, yet inbred populations often retain moderate to high segregating load. True overdominance could generate balancing selection strong enough to sustain inbreeding depression even within inbred populations, but this is considered rare. However, arrays of deleterious recessives linked in repulsion could generate appreciable pseudo-overdominance that would also sustain segregating load. We used simulations to explore how long pseudo-overdominant (POD) zones persist once created (e.g., by hybridization between populations fixed for alternative mildly deleterious mutations). Balanced haplotype loads, tight linkage, and moderate to strong cumulative selective effects all serve to maintain POD zones. Tight linkage is key, suggesting that such regions are most likely to arise and persist in low recombination regions (like inversions). Selection and drift unbalance the load, eventually eliminating POD zones, but this process is quite slow under strong pseudo-overdominance. Background selection accelerates the loss of weak POD zones but reinforces strong ones in inbred populations by disfavoring homozygotes. Models and empirical studies of POD dynamics within populations help us understand how POD zones may allow the load to persist, greatly affecting load dynamics and mating systems evolution

Marker-Assisted Introgression of the Salinity Tolerance Locus Saltol in Temperate Japonica Rice

BackgroundRice is one of the most salt sensitive crops at seedling, early vegetative and reproductive stages. Varieties with salinity tolerance at seedling stage promote an efficient growth at early stages in salt affected soils, leading to healthy vegetative growth that protects crop yield. Saltol major QTL confers capacity to young rice plants growing under salt condition by maintaining a low Na+/K+ molar ratio in the shoots.ResultsMarker-assisted backcross (MABC) procedure was adopted to transfer Saltol locus conferring salt tolerance at seedling stage from donor indica IR64-Saltol to two temperate japonica varieties, Vialone Nano and Onice. Forward and background selections were accomplished using polymorphic KASP markers and a final evaluation of genetic background recovery of the selected lines was conducted using 15,580 SNP markers obtained from Genotyping by Sequencing. Three MABC generations followed by two selfing, allowed the identification of introgression lines achieving a recovery of the recurrent parent (RP) genome up to 100% (based on KASP markers) or 98.97% (based on GBS). Lines with highest RP genome recovery (RPGR) were evaluated for agronomical-phenological traits in field under non-salinized conditions. VN1, VN4, O1 lines were selected considering the agronomic evaluations and the RPGR% results as the most interesting for commercial exploitation. A physiological characterization was conducted by evaluating salt tolerance under hydroponic conditions. The selected lines showed lower standard evaluation system (SES) scores: 62% of VN4, and 57% of O1 plants reaching SES 3 or SES 5 respectively, while only 40% of Vialone Nano and 25% of Onice plants recorded scores from 3 to 5, respectively. VN1, VN4 and O1 showed a reduced electrolyte leakage values, and limited negative effects on relative water content and shoot/root fresh weight ratio.ConclusionThe Saltol locus was successfully transferred to two elite varieties by MABC in a time frame of three years. The application of background selection until BC3F3 allowed the selection of lines with a RPGR up to 98.97%. Physiological evaluations for the selected lines indicate an improved salinity tolerance at seedling stage. The results supported the effectiveness of the Saltol locus in temperate japonica and of the MABC procedure for recovering of the RP favorable traits.

MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations.

Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for introgressed genomic regions. Although widely used, approaches intersecting outliers are vulnerable to a high false-negative rate as the power of different methods varies, especially for complex introgression events. Moreover, population genetic processes unrelated to AI, such as background selection or heterosis, may create similar genomic signals to AI, compromising the reliability of methods that rely on neutral null distributions. In recent years, machine learning (ML) methods have been increasingly applied to population genetic questions. Here, we present a ML-based method called MaLAdapt for identifying AI loci from genome-wide sequencing data. Using an Extra-Trees Classifier algorithm, our method combines information from a large number of biologically meaningful summary statistics to capture a powerful composite signature of AI across the genome. In contrast to existing methods, MaLAdapt is especially well-powered to detect AI with mild beneficial effects, including selection on standing archaic variation, and is robust to non-AI selective sweeps, heterosis from deleterious mutations, and demographic misspecification. Furthermore, MaLAdapt outperforms existing methods for detecting AI based on the analysis of simulated data and the validation of empirical signals through visual inspection of haplotype patterns. We apply MaLAdapt to the 1000 Genomes Project human genomic data and discover novel AI candidate regions in non-African populations, including genes that are enriched in functionally important biological pathways regulating metabolism and immune responses.

Introgression of Drought Tolerance into Elite Basmati Rice Variety through Marker-Assisted Backcrossing

Drought is one of the major abiotic threat to rice production in the context of climate change. Super Basmati is an elite, fine grain basmati rice variety grown in Punjab, Pakistan. Due to drought sensitive in nature, its yield has been facing an alarming situation in production because of gradual decrease in irrigated water for a couple of years. Three reported novel QTLs for drought tolerance were selected for incorporation into Super Basmati by employing marker assisted selection strategy. IR55419-04 with novel QTLs was used as a donor parent. Foreground selection was performed by applying PCR based QTL linked SSR markers followed by recombinant selection by using 2–4 flanking markers. Background selection was exercised by using polymorphic SSR markers for maximum genome recovery of the Super Basmati. The individuals homozygous at the target QTLs and with maximum background of Super Basmati at the rest of the non-target genome was selected for evaluation of drought tolerance. Under drought stress conditions, the yields of all introgressed lines (ILs) were 44.2%–125.7% higher than recurrent parent. Six superior ILs that are drought tolerant and very similar to Super Basmati in terms of agronomic and grain quality traits are marked for release as drought-tolerant varieties in arid regions or for use in breeding programs of high grain quality and drought-tolerant parents.

Development of low-phytate maize inbred lines through marker-assisted introgression of lpa1

Context Phytic acid is the major storage form of phosphorus in cereals and is considered an anti-nutritional factor because it chelates major mineral micronutrient cations, resulting in micronutrient malnutrition in humans. For monogastric animals fed maize (Zea mays L.) grains, the stored phosphorus does not release into the digestive tract, leading to phosphorus deficiency and environmental pollution. Aims The aim of the study was to develop maize lines with a lower level of phytic acid that might substantially enhance the nutritional value of maize. Methods The lpa1 mutant allele conferring low phytic acid was transferred into the parental lines of popular maize hybrid DMH 121 (i.e. BML 6 and BML 45) through marker-assisted backcross breeding. Foreground selection was performed using a co-dominant single nucleotide polymorphism marker through a high-resolution melting approach, and background selection was undertaken using 50–55 polymorphic sequence-tagged microsatellite site markers. Key results Near-isogeneic lines were produced with >90% recurrent parental genome and reduction of phytic acid content by up to 44–56% compared with the original lines. Conclusions The near-isogeneic lines carrying lpa1 can be used to reconstitute DHM 121 with low phytate content. Implications The low-phytate maize hybrids produced can be useful in reducing micronutrient malnutrition in humans, as well as environmental pollution.

Ugradnja Ga1-S gena u roditeljske linije hibrida kukuruza belog zrna pomoću molekularnih markera

Maize Research Institute Zemun Polje has a marker-assisted backcross breeding (MABB) program aimed to incorporate the strong allele of incompatibility gene Ga1 into parental components of the hybrids with specific traits (white kernel). The main objective of this research was marker-assisted development of the white maize hybrid's parental lines with complete cross-incompatibility to foreign pollens. Ga1-S-tightly-linked molecular markers successfully identified heterozygous plants with a percentage of approximately 50% after all three backcrossings. Regarding the background selection, 69% of progenies had recurrent parent's genome (RPG) above the theoretical value for BC3 generation. Also, a few individuals even had 99%, the value theoretically achieved in the BC6 generation, showing that MABB made a genetic gain in RPG recovery. Foreground selection in this generation aimed to identify homozygous dominant individuals. Out of 264 BC3 F2 plants, 70 (26.5%) were dominant homozygotes, which is in accordance with the expected Mendelian ratio. Progenies of the BC3 F2 homozygous dominant plants were planted alternatively with yellow-kernel maize of the same maturity to check cross-incompatibility. Unfortunately, none of the dominant progenies had a 100% white kernel, most likely due to the presence of modifier genes that increase/decrease the effectiveness of pollen exclusion or that, alternatively, modifiers are lost during the backcrossing. It could be expected that successfully employed functional markers (developed from the sequence polymorphisms present within a functional gene(s) associated with phenotypic trait variations) would outbalance the noted impediments and enhance MABB efficiency to transfer the desired gene(s) controlling simple or complex trait(s) into cultivated varieties.

Hyperspectral Target Detection via Spectral Aggregation and Separation Network With Target Band Random Mask

Hyperspectral target detection (HTD) is a pixel-wise detection method based on limited prior targets and spectral differences, which has been widely studied and applied in many fields. Recently, deep learning (DL) plays an important role in hyperspectral imagery (HSI) processing. However, for HTD, the severe lack of class-balanced training sets is an enormous challenge. Meanwhile, it is difficult to suppress backgrounds while highlighting targets through the deep network. To address these issues, we propose a spectral aggregation and separation network (SASN) with a target band random mask (TBRM) for HTD in this paper. For the training sets of SASN, a multifarious representative background selection strategy (MRBS) is first proposed to obtain a multifarious and representative background training set. Next, aiming at the notorious class imbalance, a data augmentation (DA) method, TBRM, is proposed to generate adequate target training set by repeating randomly zero-masking the spectral bands of a prior target. Subsequently, in the training of SASN, residual connection and squeeze-and-excitation (SE) channel attention mechanism are applied to fully extract high discriminative features and nonlinear ones in the spectra. Besides, to better separate the targets and backgrounds, a triplet-soft loss function is presented, which makes the training in the direction of spectral separation of background samples from both the prior target and target samples. During testing, the trained SASN distinguishes the spectral similarities and differences simultaneously for highlighting targets and suppressing backgrounds. Moreover, extensive experimental results validate that the proposed method has superior detection performances, background suppression capacity, and separability compared with ten cutting-edge HTD algorithms on six benchmark HSI datasets.

DEVELOPMENT OF NON-TIDAL ADAPTIVE RICE VARIETIES: MOLECULAR MARKER ASSISTED SELECTION OF BC2F1 PROGENIES

Submergence stress and drought stress are main abiotic constraints encountered in South Sumatra swampland rice cultivation area. The development of new abiotic stress tolerant varieties through the introgresion of tolerance genes, such as the Sub1 gene (submergence tolerance) by using Marker-assisted Backcrossing (MABC method) is one of an ideal solution to obtain an adaptive rice variety for those conditions. The study was carried out at Faculty of Agriculture, Sriwijaya University, Indonesia. In this study, BC2F1 used as the plant materials derived from backcross performed in BC1F1 and the recipient parent, Inpago 5. Previously, BC1F1 obtained from backcrossed progenies from Inpara 8 (inherited Sub1A gene) and Inpago 5 as recipient parent, a drought tolerant variety. The main objective of this study was to analyze the Sub1 introgressed plants in backcrossed progeny BC2F1 that closest similarity to recipient parent. The result showed that Sub1 introgression was confirmed by a tightly linked Sub1 gene marker, SUB1C173 marker. Out of 47 plants, 20 plants were selected based on foreground selection. Those plants were further analyzed on background selection by using 13 SSR markers. Based on the foreground and background selection, two plants, viz, plant no. 41 and 44, were selected and will be used for further study.

Screening microsatellite markers for establishing parental polymorphism in Indian rice (Oryza sativa L.)

The experiment was conducted to investigate the parental diversity along the rice genome and to understand and screen out the SSR markers-indicated polymorphism between two indica rice (Oryza sativa L.) cultivars. Namely K343, the most well-liked rice variety in the hill zone of the Jammu Region, and RML22, a rice line created at IRRI, Philippines. The study is to select polymorphic markers (Simple Sequence Repeat- SSR) associated with hill ecologies rice cultivars and additional research projects like gene pyramiding and background selection to recover the recurrent parent genome (RPG) in blast gene introgression in elite lines. 450 SSR markers, evenly distributed throughout the rice genome, were used to assess the parental polymorphism between these genotypes. Of these two cultivars, 51 markers (11.33%) showed polymorphism with bands in different spectrums throughout the genome. The study has been used to Marker Assisted Backcross (MAB) breeding to integrate rice blast resistance genes in the parental genotype. The pool of polymorphic markers has the potential to use in similar studies and work, with a high probability of polymorphism for the cultivars of hill ecologies, and thus increase the chance of selection of probability in marker selection.

The resurrection of sweet corn inbred SC11-2 using marker aided breeding for β-carotene

Sweet corn has dominated the urban market due to its sweetness, tenderness, and ease of digestibility. It's import and export values have dramatically increased during the past 10 years as a fresh, processed, and preserved commodity. However, the commercially available sweet corns are deficient in β-carotene. In our study, we introgressed the favorable allele of crtRB1 (responsible for high β-carotene) into the recurrent sweet corn inbred SC11-2 from maize donor parent UMI1230β1+ to develop the β-carotene-rich sweet corn genotype by marker aided breeding. The crtRB1 3′TE InDel marker was utilized for foreground selection of favorable genotype. A total of 103 polymorphic SSR markers were employed for background selection, resulting in a 96% recovery of recurrent parent genome (RPG). We recorded high β-carotene content (9.878–10.645 μg/g) in the introgressed lines compared to the recurrent parent, SC11-2 (0.989 μg/g). The sugar content ranged from 18 to 19.10% and was on par with the recurrent parent (20.40%). These biofortified inbreds can be used as a donor in maize breeding programs to develop sweet corn genotypes with high β-carotene content.

Marker-assisted backcross breeding for heat tolerance in bread wheat (Triticum aestivum L.).

Manipulation of flowering time for adaptation through natural or genetic approaches may combat heat-stress damage that occurs at the reproductive stages in production conditions. HD2733, a popular wheat variety of the eastern plains of India, is largely sensitive to heat stress. Therefore, the current study aims to improve heat tolerance of HD2733 by introgression of QTLs associated with early anthesis and high kernel weight linked to markers Xbarc186 and Xgwm190, respectively, through marker-assisted backcross breeding (MABB) from a tolerant donor, WH730. A total of 124 simple sequence repeat (SSR) markers distributed evenly across the genome were used for the background selection. The alleles of Xbarc186 and Xgwm190 were fixed in BC2F1 and BC1F2 generations by selecting individual plants heterozygous for both marker loci and backcrossed with HD2733 and simultaneously selfed to generate BC2F1 and BC1F2 populations, respectively. Furthermore, the selected BC1F2 were selfed to generate the BC1F4 population. By background screening, a total of 39 BC2F3 and 21 BC1F4 families homozygous for the targeted QTLs with 90.9-97.9% and 86.8-88.3% RPG recoveries were selected. The best performing 17 BC2F3 and 10 BC1F4 lines were evaluated for various morpho-physiological traits. Phenotypic evaluation and multi-location trials of the introgressed lines under late sown conditions led to the selection of three promising lines with early anthesis and higher grain yield. The improved lines will serve as an excellent genetic material for functional genomics and expression studies to understand the molecular mechanisms and pathways underlying the stress tolerance.

Molecular Breeding of Water-Saving and Drought-Resistant Rice for Blast and Bacterial Blight Resistance.

Rice production is often affected by biotic and abiotic stressors. The breeding of resistant cultivars is a cost-cutting and environmentally friendly strategy to maintain a sustainable high production level. An elite water-saving and drought-resistant rice (WDR), Hanhui3, is susceptible to blast and bacterial blight (BB). This study was conducted to introgress three resistance genes (Pi2, xa5, and Xa23) for blast and BB into Hanhui3, using marker-assisted selection (MAS) for the foreground selection and a whole-genome single-nucleotide polymorphism (SNP) array for the background selection. As revealed by the whole-genome SNP array, the recurrent parent genome (RPG) recovery of the improved NIL was 94.2%. The resistance levels to blast and BB of the improved NIL and its derived hybrids were higher than that of the controls. In addition, the improved NIL and its derived hybrids retained the desired agronomic traits from Hanhui3, such as yield. The improved NIL could be useful to enhance resistance against biotic stressors and produce stable grain yields in Oryza sativa subspecies indica rice breeding programs.

Genetic improvement of traditional Basmati rice Ranbir Basmati for semi-dwarfism and blast resistance through molecular breeding

The traditional Basmati rices grown in north-western foothills of Himalayas in India are known world-wide for their exquisite aroma and exceptional eating and cooking qualities. These varieties are tall and suffer heavy losses due to their susceptibility to lodging as well as blast disease. In present study, we improved a popular traditional Basmati rice variety ‘Ranbir Basmati’ for semi-dwarfism and resistance to blast by incorporating the semi-dwarfing gene, sd1 and two blast resistance genes, Pi9 and Pi54 through marker-assisted backcross breeding. Combining marker-assisted background selection with stringent phenotypic selection for aroma and seed quality traits during backcrossing enabled faster recovery of recurrent parent genome and reconstitution of the genomic regions associated with Basmati quality traits in the gene pyramided lines. All pyramided lines were significantly short statured with a reduction of 23.46 to 40.26 cm in height, as compared to recurrent parent, with many of them exhibiting higher grain yield and superior quality attributes than Ranbir Basmati. The yield superiority of the pyramided lines primarily resulted from the improvement in panicle number and semi-dwarf stature conferred by sd1 gene. The gene pyramided lines showed complete resistance to five highly virulent blast races that collectively showed compatibility with 16 different resistance genes, suggesting the broad-spectrum resistance in these lines. The semi-dwarf, high yielding and blast resistant lines generated herein are potential candidates for release as cultivars for overcoming losses in Ranbir Basmati due to lodging and blast disease.

Genotypic and Phenotypic Selection of Newly Improved Putra Rice and the Correlations among Quantitative Traits

This experiment was conducted to genotypically and phenotypically select new rice lines pyramided with blast and bacterial leaf blight disease resistance genes after a marker-assisted backcross breeding programme. The inter-relationship among agro-morphological characteristics and their effect on yield was also studied. The polymorphic functional and microsatellite markers Xa21FR and pTA248 (Xa21), Xa13prom (xa13), RM21 (xa5), MP (Xa4), RM6836 (Pi2, Pi9 & Piz) and RM8225 (Piz) were first confirmed for the target genes. The selected markers were used for foreground selection of BC2F2 homozygous progenies with the target genes. Plants that had homozygous IRBB60 alleles for these markers were evaluated for their recovery of the recurrent parent genome. IRBB60 was used as the donor parent for bacterial blight resistance genes while Putra-1 served as a recipient/recurrent parent with background blast-resistance genes and high yield. After the foreground selection, 79 polymorphic simple sequence repeat markers identified from the marker polymorphism survey were used for marker-assisted background selection to determine the percentage recovery of the recurrent parent genome. In order to make a selection on a phenotypic basis, 14 agro-morphological traits were measured and recorded. The result obtained from the study showed that 16 lines received the seven resistance genes in sufficiently varied numbers and were selected. The distribution of yield per hectare showed that about 50% of the selected lines had yields as high as 5 t/ha and above. Some of the lines produced as high as 8.4 t/ha. These lines demonstrated the potential of recording uniform 8t/ha upon recombination at BC2F2. The study also indicated that the number of panicles per hill correlated strongly, significantly and positively with the number of tillers (r = 0.962 **), total grain weight per hill (r = 0.928 **) and yield per hectare (r = 0.927 **). It was concluded that the newly improved resistant lines which were selected have the capability to compete with Putra-1 in terms of its productivity and yield. The newly developed lines would be useful in future breeding programmes as donors for bacterial leaf blight and blast resistance genes. These lines are recommended for release to farmers in Malaysia and other rice-growing agro-ecologies for commercial cultivation.

Reminding staff of diligence during the medication process is not enough to ensure safety: Learning from wrong fluid product selection incidents in the care of critically ill patients

Background and objectivesWrong fluid product selection may cause harm to patients. This study aimed to describe voluntarily reported wrong fluid product selection incidents, including their consequences, the reported latent conditions and active failures leading to these and the suggested safeguards to prevent their occurrence, and to compare the suggested and literature-based safeguards to improve the fluid therapy safety within the intensive care (ICU) environment. MethodsAll voluntarily and anonymously reported wrong fluid product selection incidents in all Finnish ICUs during 2007–2017 were reviewed. The incident reports included categorized data that were analyzed quantitatively, and narratives that were analyzed qualitatively, using content analysis. The results were reported as frequencies and percentages and described by using Reason's model of human error. ResultsOver the eleven years, one wrong fluid product selection incident was reported every six days (n = 663; 584 errors, 79 near misses); most were reported to have occurred during the dispensing/preparing phase (92%). Of the 584 reported selection errors, a quarter (26%) was reported to have caused consequences to patients, and one third (35%) to have required corrective or monitoring actions. The main reported latent conditions to the incidents were Working environment and resources (e.g. workload and time pressure) (29%), Similar-looking and -sounding names or shared features of the product containers (i.e. the LASA phenomenon) (28%) and Working methods (22%); and the main reported active failures were a lack of concentration, or forgetfulness (26%). Some usable suggestions of safeguards were made, e.g. optimizing fluid storage (15%) or utilizing checking practices (21%). While requiring accuracy, i.e. reminding staff of diligence and to be more attentive to detail during the whole medication process, was emphasized in most reports (71%), involving manufacturers in redesigning labels of fluid products, utilizing technology and strengthening pharmacy services are advocated existing literature. ConclusionsWrong fluid product selection incidents with various latent conditions and active failures were reported more than once a week. To minimize the serious LASA phenomenon, multi-professional collaboration, coordinated international discussion and agreements of solutions with manufacturers, regulators and end-users, are needed. However, work is also needed to reduce the other latent factors, such as Working environment and resources as well as cognitive biases in daily work that may contribute to the occurrence of LASA related errors.

Extending the energy range of AstroSat-CZTI up to 380 keV with compton spectroscopy

ABSTRACT The CZTI (Cadmium Zinc Telluride Imager) onboard AstroSat is a high energy coded mask imager and spectrometer in the energy range of 20–100 keV. Above 100 keV, the dominance of Compton scattering cross-section in CZTI results in a significant number of 2-pixel Compton events and these have been successfully utilized for polarization analysis of Crab pulsar and nebula (and transients like Gamma-ray bursts) in 100–380 keV. These 2-pixel Compton events can also be used to extend the spectroscopic energy range of CZTI up to 380 keV for bright sources. However, unlike the spectroscopy in primary energy range, where simultaneous background measurement is available from masked pixels, Compton spectroscopy requires blank sky observation for background measurement. Background subtraction, in this case, is non-trivial because of the presence of both short-term and long-term temporal variations in the data, which depend on multiple factors like earth rotation and the effect of South Atlantic Anomaly (SAA) regions etc. We have developed a methodology of background selection and subtraction that takes into account for these effects. Here, we describe these background selection and subtraction techniques and validate them using spectroscopy of Crab in the extended energy range of 30–380 keV region, and compare the obtained spectral parameters with the INTEGRAL results. This new capability allows for the extension of the energy range of AstroSat spectroscopy and will also enable the simultaneous spectropolarimetric study of other bright sources like Cygnus X-1.

Background selection schema on deep learning-based classification of dermatological disease

Skin diseases are one of the most common ailments affecting humans. Artificial intelligence based on deep learning can significantly improve the efficiency of identifying skin disorders and alleviate the scarcity of medical resources. However, the distribution of background information in dermatological datasets is imbalanced, causing generalized deep learning models to perform poorly in skin disease classification. We propose a deep learning schema that combines data preprocessing, data augmentation, and residual networks to study the influence of color-based background selection on a deep model’s capacity to learn foreground lesion subject attributes in a skin disease classification problem. First, clinical photographs are annotated by dermatologists, and then the original background information is masked with unique colors to generate several subsets with distinct background colors. Sample-balanced training and test sets are generated using random over/undersampling and data augmentation techniques. Finally, the deep learning networks are independently trained on diverse subsets of backdrop colors to compare the performance of classifiers based on different background information. Extensive experiments demonstrate that color-based background information significantly affects the classification of skin diseases and that classifiers trained on the green subset achieve state-of-the-art performance for classifying black and red skin lesions.

DRR Dhan 58, a Seedling Stage Salinity Tolerant NIL of Improved Samba Mahsuri Shows Superior Performance in Multi-location Trials

BackgroundImproved Samba Mahsuri (ISM) is an elite, high-yielding, bacterial blight resistant, fine-grained rice variety with low glycaemic index. It is highly sensitive to salt stress, particularly at seedling stage, which significantly reduces its yield potential in coastal areas. A salinity tolerant QTL, Saltol, associated with seedling stage tolerance was previously mapped on chromosome 1 (10.6–11.5 Mb) from the Indian landrace, Pokkali and is effective in different genetic backgrounds. The objective of this study was to enhance salinity tolerance of ISM by incorporating the Saltol QTL through marker-assisted backcross breeding using the breeding line, FL478 (Pokkali/IR29).ResultsForeground selection was carried out at each generation using five Saltol-specific markers and three bacterial blight resistance genes, Xa21, xa13 and xa5. Background selection was conducted using 66 well distributed polymorphic SSR markers and at the BC3F2 generation, a single plant with maximum recurrent parent genome recovery (95.3%) was identified and advanced to the BC3F4 generation. Based on bacterial blight resistance, seedling stage salinity tolerance and resemblance to ISM, four advanced breeding lines were selected for testing in replicated experiments near Hyderabad, India. A promising near-isogenic line, DRR Dhan 58, was evaluated in multi-location trials-coastal salinity and it showed significant salinity tolerance, resistance to bacterial blight disease, high yield and excellent grain quality during the 2019 and 2020 trials. DRR Dhan 58 was 95.1% similar to ISM based on genotyping with the 90 K SNP chip. Whole genome resequencing analysis of Pokkali and FL478 which were salinity tolerant checks, ISM and DRR Dhan 58 showed a high degree of relatedness with respect to the candidate gene loci for Saltol and OsSKC1 (Shoot K+Concentration 1).ConclusionDRR Dhan 58, possessing Saltol and three bacterial blight resistance genes (Xa21, xa13 and xa5) in the genetic background of the Indian mega-variety of rice, Samba Mahsuri, was developed for potential cultivation in areas prone to seedling stage salinity, as well as areas with endemic bacterial blight disease. This entry had a 24% yield advantage over the recurrent parent ISM under coastal saline conditions in multi-location trials and was recently released for commercial cultivation in India.