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During the Assyrian rule over Northern Mesopotamia (present-day northern Iraq), complex systems of canals were built to increase the surface of cultivable land and improve the movement of people and goods across the irrigated waterscape of the hinterland of Nineveh and other major urban centres, with the aim of granting socio-economic prosperity to the empire. Nevertheless, supra-regional political instability eventually led to the rapid downfall of the Assyrian state during the late seventh century BCE, causing the swift abandonment of the canal systems. In this study, we examine the post-abandonment formation processes of the natural and anthropogenic infillings of three portions of King Sennacherib’s Khinis canal system (705–681 BCE, northwestern Kurdistan Region of Iraq) through means of archaeological, sedimentological and micromorphological analyses. We identify water lain sediments, desiccation features, colluvial gravel intake and pastoral occupation layers, anchoring the deposit to radiometric dating and contextualising it against the known regional climatic history. The interpretation of pedostratigraphic evidence highlights subsequent phases of use, abandonment, and repurposing of the canals, reflecting shifts in land-use from agriculture to pastoralism and dynamic adaptation and resilience of the local ancient communities in response to Late-Holocene climate changes and geopolitical events.

‘Candidatus Liberibacter asiaticus’ is the unculturable causative agent of citrus huanglongbing disease. Here, we report the first citrus root metagenome sequence containing the draft genome of ‘Ca. L. asiaticus’ strain AHCA17, obtained from a pummelo tree in California. The assembled genome was 1.2 Mbp and resulted in 37 contigs (N50 = 158.7 kbp) containing 1,057 predicted open reading frames and 45 RNA-coding genes. This draft genome will provide a valuable resource in further study of ‘Ca. L. asiaticus’ genome diversity and pathogen epidemiology.

Monumental funerary landscapes are paramount representations of the relationship between environment and superstructural human behavior. Their formation sometimes requires millennia and they cover wide territories, often adding up to complex palimpsests of monuments belonging to different time periods. In this regard, the funerary landscape of the semi-arid foothill region of Kassala (Eastern Sudan) represents a solid example. Therein, a comprehensive geoarchaeological investigation conducted by means of field survey and remote sensing allowed the creation of a regional geomorphological base-map and a dataset of funerary monuments. The latter comprises several thousand raised stone-built tombs spanning from the early first millennium AD clusters of tumuli (belonging to the pan-African traditions) to regionally exclusive variants of medieval Islamic funerary architecture (qubbas). Funerary monuments are found as eye-catching scatters of hundreds of elements along the foothills of the many rocky outcrops dotting the pediplain of the western periphery of the Eritrean Highlands. In this study, the two categories of monuments were not considered as separate burialscapes, but rather examined as a unique, diachronic funerary landscape in its relationship with the geological and geomorphological settings and constraints. Point Pattern Analysis (PPA) was employed to determine the main environmental drivers of their locations on a regional scale, as well as to assess the existence of superstructural factors acting on their aggregation at the local scale. Our results strongly suggest the presence of a geological/environmental/societal synthesis underlying the choice of monuments’ location: at the regional scale, the pattern follows a precise set of rules residing in the concomitant presence of stable, gently rolling slopes and available metamorphic rock slabs; at the local scale, the clustering is heavily conditioned by superstructural dynamics that most likely reside in kinship and collective social memory of local Beja people. We suggest that the creation of the funerary landscape of Eastern Sudan is the result of a repeated and well coded social behavior of the Beja people, semi-nomadic cattle breeders known to have inhabited the region since “time immemorial”. Despite their mobile lifestyle and cultural contact with other North African and Arabic cultures, the monumental palimpsest portrays how the funerary habits of this millennia-old society persisted almost undisturbed, valuing location and kinship over external influences.

We present the geomorphology of the Southern Atbai Plain (Eastern Sudan) and the western edge of the Eritrean Highlands (Western Eritrea), in the eastern Sahel. The mountainous area consists of Paleo-Proterozoic gneiss and Neo-Proterozoic igneous rocks and meta-volcanic assemblages shaped as inselbergs and whaleback landforms by weathering. Bare-rock hills emerge from a gentle glacis that oversees the Southern Atbai alluvial plain, located between the Atbara and Gash Rivers. The plain features the SSE-NNW-oriented endorheic terminal fan of the Gash River and is crossed by intricate Early to Late Pleistocene paleochannels, whose evolution was controlled by the interplay between Quaternary regional tectonics and arid to humid climatic and environmental oscillations. The map is intended to interpret the evolution of local landscape, thus representing a tool for reconstructing the spatial and temporal distribution of Late Quaternary archaeological features and their functional relationships with the fossil fluvial system and the western foothills.

‘Candidatus Phytoplasma pini’-related strain MDPP, the reference strain of subgroup 16SrXXI-B, is a pathogen associated with witches’ broom disease of Pinus spp. in North America. Here, we report the first draft genome sequence of ‘Ca. Phytoplasma pini’ strain MDPP, which consists of 474,136 bases, with a G + C content of 22.22%. This information will facilitate comparative genomics of gymnosperm-infecting phytoplasmas.

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The paper deals with the modelization and optimization of an integrated multi-component energy system. On-off operation and presence-absence of components must be described by means of binary decision variables, besides equality and inequality constraints; furthermore, the synthesis and the operation of the energy system should be optimized at the same time. In this paper a hierarchical optimization strategy is used, adopting a genetic algorithm in the higher optimization level, to choose the main binary decision variables, whilst a MILP algorithm is used in the lower level, to choose the optimal operation of the system and to supply the merit function to the genetic algorithm. The method is then applied to a distributed generation system, which has to be designed for a set of users located in the center of a small town in the North-East of Italy. The results show the advantage of distributed cogeneration, when the optimal synthesis and operation of the whole system are adopted, and significant reduction in the computing time by using the proposed two-level optimization procedure.

We present a simple strategy for multiobjective target-driven optimization and apply it to the sizing optimization of a steel girder bridge. Users or decision makers are asked to express their preferences (based on their previous experience) in terms of desired target objective values to drive the optimization towards the most preferred regions of the Pareto front. This can lead to a more efficient exploration of specific regions of the objective space and reduce the computational cost of finding desirable solutions. This strategy combines a-priori with interactive preference-handling approaches. These methods have recently received more attention in the evolutionary multiobjective optimization community. The proposed algorithm is described in detail and compared with existing methods. Benchmarks on standard mathematical test functions as well as on a realistic structural engineering sizing optimization problem are provided.

In June 2018, while conducting a survey for possible presence of phytoplasma pathogens in Pennsylvania production fields, a strawberry plant (Fragaria × ananassa) was observed with symptoms of stunting and unseasonal reddening and distortion of leaves. Only one out of 500 strawberry plants expressed the described symptoms in a farm in Perry County, PA. Several leaves and stems were collected from the symptomatic plant as well as from a few asymptomatic ones for further work. Total DNA was extracted from 100 mg of leaf midveins with a DNeasy Plant Mini Kit (Qiagen, Valencia, CA). All DNA samples were initially tested using a phytoplasma universal real-time polymerase chain reaction (PCR) assay (Hodgetts et al. 2009). Positive amplification results were obtained only with samples derived from the symptomatic strawberry plant. To detect and identify the suspected phytoplasmal pathogen strain(s), the DNA samples were used as a template in conventional PCRs for amplification of phytoplasma 16S rRNA, secY, secA, and tuf gene sequences as previously described (Dickinson and Hodgetts 2013; Lee et al. 2004, 2010; Makarova et al. 2012). All of the obtained amplicons were of expected sizes, and no amplification was observed from the asymptomatic strawberry samples. PCR products were purified with a QIAquick PCR Purification Kit (Qiagen) and sequenced. Nucleotide sequences of the PCR products were deposited in the GenBank database under accession numbers MN227133 to MN227136. The nucleotide sequences were analyzed using Geneious software (Biomatters, Auckland, NZ) for sequence alignments and using iPhyClassifier (Zhao et al. 2009) for group-subgroup and ‘Candidatus Phytoplasma’ species assignments. The classification into 16Sr groups and subgroups was established by virtual restriction fragment length polymorphism (RFLP) analysis of PCR products compared with reference strains. The phytoplasma, termed strain SRL1-PA (Strawberry Red Leaf1-PA), was found to share 99.9% similarity with that of the ‘Candidatus Phytoplasma americanum’ reference strain (GenBank accession DQ174122). The virtual RFLP pattern derived from the query 16S rDNA F2nR2 fragment is most similar to the reference group XVIII, subgroup A (GenBank accession DQ174122), with a pattern similarity coefficient of 0.98. Another sample from the same strawberry plant was independently determined positive for ‘Ca. P. americanum’ by CPHST Beltsville Lab using nucleotide sequence analysis of 16S rRNA gene sequences amplified in end point PCR. Alignments and phylogenetic analyses of secY, secA, and tuf gene sequences confirmed the close relatedness of the Pennsylvania SRL1-PA strain with the reference strains of ‘Ca. P. americanum’. ‘Ca. P. americanum’ was previously reported (Lee et al. 2006) in Texas and Nebraska on potato and associated with potato purple top wilt disease. In 2019, the Pennsylvania Department of Agriculture team revisited the same farm and collected additional samples including some from potato but was not able to detect any phytoplasma. To our knowledge, this report provides the first evidence for the presence of a ‘Ca. P. americanum’-related strain in Pennsylvania and more importantly describes strawberry (Fragaria × ananassa) as a new host for this phytoplasma. With only one single positive strawberry plant in a single year, the true extent of disease spread on strawberries remains undetermined.

The race-specific resistance gene Pi-ta has been effectively used to control blast disease, one of the most destructive plant diseases worldwide. A single amino acid change at the 918 position of the Pi-ta protein was known to determine resistance specificity. To understand the evolutionary dynamics present, we examined sequences of the Pi-ta locus and its flanking regions in 159 accessions composed of seven AA genome Oryza species: O. sativa, O. rufipogon, O. nivara, O. meridionalis, O. glaberrima, O. barthii, and O. glumaepatula. A 3364-bp fragment encoding a predicted transposon was found in the proximity of the Pi-ta promoter region associated with the resistance phenotype. Haplotype network analysis with 33 newly identified Pi-ta haplotypes and 18 newly identified Pi-ta protein variants demonstrated the evolutionary relationships of Pi-ta haplotypes between O. sativa and O. rufipogon. In O. rufipogon, the recent directional selection was found in the Pi-ta region, while significant deviation from neutral evolution was not found in all O. sativa groups. Results of sequence variation in flanking regions around Pi-ta in O. sativa suggest that the size of the resistant Pi-ta introgressed block was at least 5.4 Mb in all elite resistant cultivars but not in the cultivars without Pi-ta. These findings demonstrate that the Pi-ta region with transposon and additional plant modifiers has evolved under an extensive selection pressure during crop breeding.

The Pi-ta gene in rice (Oryza sativa L.) confers resistance to races of Magnaporthe oryzae B. Couch containing its cognate avirulence gene AVR-Pita. Pi-ta is a single-copy plant resistance (R) gene encoding a protein belonging to the nucleotide-binding site leucine-rich repeat (NBS-LRR) class. In the present study, we report alternative splicing events at the Pi-ta locus, the identification of new introns and novel differentially used splice sites associated with the Pi-ta gene. A total of 12 transcript variants were predicted with ORFs ranging from 945 to 3099 bp and encoding 11 distinct putative products between 315 and 1033 amino acids. Among them, five preserve complete NBS-LRR domains and two couple the original NBS-LRR domain of the Pi-ta protein with a C-terminal thioredoxin (TRX) domain. Gene expression analysis revealed that transcript variants encoding the TRX domain had, in a resistant Pi-ta containing rice variety, the highest level of expression in comparison to the other full length or truncated transcripts. These post-transcriptional modifications of Pi-ta produce a series of transcript isoforms that could have a significant role in the R gene regulation and/or may increase protein diversity. To our knowledge, this study represents the first report of alternative splicing of a CC-NBS-LRR gene producing truncated isoforms at both their 5′ or 3′ terminus and including transcripts with a TRX domain at their C-terminus.

The molecular mechanisms and the defense responses associated with partial resistance to Phytophthora sojae in soybean are unknown. In this study, we examined correlations between the expression of defense genes with partial resistance. First, to determine whether constitutive levels of expression of defense-related genes correlated with partial resistance to P. sojae, northern blot analysis of seven defense-related genes in 14 cultivars with low, moderate and high levels of partial resistance was performed. Pearson's correlations between mean lesion length and mean constitutive mRNA signals for defense-related genes showed no significant association to partial resistance to P. sojae. These results suggested that mechanisms linked to defense-related mRNA levels expressed during infection might better explain variations in partial resistance to P. sojae in soybean. Second, accumulation of four defense-related transcripts during infection was monitored in a spatial, time-course infection assay with two soybean cultivars, Conrad (high level of partial resistance) and OX 20-8 (Rps1a, low level of partial resistance). mRNA was isolated for Northern blot analysis from root sections harvested below, at, and above the inoculation site at 0, 6, 12, 24, 48 and 72 h after inoculation (hai) with P. sojae. P. sojae and soybean actin cDNAs were used as probes in the infected root sections to estimate relative proportions of RNA. Differential mRNA accumulation patterns for both soybean and P. sojae actin following P. sojae colonization in the three root sections of Conrad and OX 20-8 suggested that effective lesion-limiting mechanisms occurred primarily in the upper root section. Transcript levels for PR1a, matrix metalloproteinase (MMP) and basic peroxidase (IPER) at the inoculation site; and IPER above the inoculation site at 72 hai were significantly higher in Conrad with higher levels of partial resistance. Our results suggest that defense responses associated with accumulation of PR1a, MMP, IPER and β-1,3-endoglucanase (EGL) mRNAs may contribute to the partial resistance response to P. sojae in soybean.

One of the major tasks of structural engineering design optimization is the handling of uncertainties (such as variations in material properties, loading conditions, unknown environmental conditions or even uncertainties in modeling assumptions), which affect system performance in terms of robustness and reliability (or, in other words, the ability to respond to input variations with minimal alteration, loss of functionality or damage). This task is usually tackled with Optimization Under Uncertainty (OUU) methods[1], like robust design optimization and reliability-based design optimization. In most cases, the optimization has to deal with multi-objective problems (such as maximizing the performance while minimizing costs, system response variations, etc). These problems do not have a unique solution, but a set of tradeoff optimal solutions (the so-called Pareto front). The action of a decision maker (DM) is necessary for choosing the final optimal design according to some (pre-defined) preferences or criteria. Multi-Criteria Decision Making (MCDM) techniques[2] have been developed over the past years to try to make these choices objective and rational. In most MCDM methods, the preferences are usually taken into account during some a-posteriori analyses of the optimization outcomes. Here we address both OUU and MCDM problems with an approach that integrates directly the action of the DM with the optimization process. The DM is asked to express their preferences (based on their previous experience) to drive the optimization towards the most preferred regions of the Pareto front. This can lead to a more efficient exploration of specific regions of the Pareto front and reduce the computational cost of finding desirable solutions. Interactive MCDM approaches have been recently given more attention in the multi-objective optimization community [3, 4, 5]. A validation of this approach on simple test-cases is shown as well as its application to the design of a simple building structure under uncertainties with seismic hazard and snow loads.

Genetic algorithms are versatile tools that are able to tackle a wide range of real-world problems. In this paper, we propose a general-purpose genetic algorithm for black box multi-objective optimization well suited for different types of variables (continuous, discrete, and combinatorial) and constraints (linear and non- linear, equalities and inequalities) without requiring any customization, such as problem-dependent operators. The basic idea is to extract as much information as possible from the characteristics of the decision variables in order to activate the most appropriate routines automatically. We apply this strategy to a real world problem: The layout optimization of a Wireless Sensor Network (WSN). This problem can be equivalently formulated in two different ways, both presenting some critical points for an effective application of standard genetic algorithms. We show how our algorithm can learn from its structure and solve the problem more efficiently than other classical genetic approaches.

In July - October of 2013-2015, more than forty blocks of Pennsylvania apple orchards from nine PA counties were surveyed for phytoplasma. Out of 218 apple samples submitted to Pennsylvania Department of Agriculture Plant Diagnostic Lab (PDA PDL) three mature trees from two farms in Adams County PA were found to be positive for Phytoplasma. Positive trees belonging to three different varieties showed abnormally small fruits, clumps of small leaves, leaf curl and premature reddening with the best symptoms showing in August-October. PDA PDL extracted total DNA from leaf mid-veins with a DNeasy Plant Mini Kit (Qiagen, Valencia, CA) according to manufacturer's instructions. Positive results were obtained when screened for presence of phytoplasmal DNA using a real-time PCR assay (Hodgetts et al. 2009). For analysis of the 16S rDNA genomic region, nested PCR was carried out with primer pair P1/P7 followed by R16F2n/R16R2 or P1A/P7A (Lee et al. 2004). For analysis of ribosomal protein genes, DNA was amplified in...

Rhizoctonia solani is a necrotrophic fungal pathogen that causes disease on many crop-plant species. Anastomosis group 1-IA is the causal agent of sheath blight of rice (Oryza sativa L.), one of the most important rice diseases worldwide. R. solani AG1-IA produces a necrosis-inducing phytotoxin and rice cultivar's sensitivity to the toxin correlates with disease susceptibility. Unlike genetic analyses of sheath blight resistance where resistance loci have been reported as quantitative trait loci, phytotoxin sensitivity is inherited as a Mendelian trait that permits high-resolution mapping of the sensitivity genes. An F(2) mapping population derived from parent cultivars 'Cypress' (toxin sensitive) and 'Jasmine 85' (toxin insensitive) was used to map Rsn1, the necrosis-inducing locus. Initial mapping based on 176 F(2) progeny and 69 simple sequence repeat (SSR) markers located Rsn1 on the long arm of chromosome 7, with tight linkage to SSR marker RM418. A high-resolution genetic map of the region was subsequently developed using a total of 1,043 F(2) progeny, and Rsn1 was mapped to a 0.7 cM interval flanked by markers NM590 and RM418. Analysis of the corresponding 29 Kb genomic sequences from reference cultivars 'Nipponbare' and '93-11' revealed the presence of four putative genes within the interval. Two are expressed cytokinin-O-glucosyltransferases, which fit an apoptotic pathway model of toxin activity, and are individually being investigated further as potential candidates for Rsn1.

The Pi-ta gene in rice effectively prevents infection by races of Magnaporthe oryzae that contain the corresponding AVR gene, AVR-Pita. Pi-ta is a putative cytoplasmic protein with a centrally located nucleotide binding sites (NBS) and a leucine rich domain (LRD) at the carboxyl terminus. The Pi-ta gene has been deployed effectively in preventing rice blast in the southern US since 1990. AVR-Pita encodes a predicted metalloprotease, and its processed form, AVR-Pita176$, was shown to directly bind with the Pi-ta protein in triggering effective defense responses. Variants of AVR-Pita were identified in many contemporary M. oryzae races and in isolates collected during the last 30 years in the US. Sequence analysis of these AVR-Pita variants revealed that the AVR-Pita protein might be under diversified selection. Most recently, sequence analysis of the Pi-ta variants in six Oryza species (O. sativa, O. glaberrima, O. officialis, O. rufipogon, O. barthii and O. nivara) revealed that functional nucleotide polymorphism at the position of 918 (FNP918) is present among all these Oryzae species, and Pi-ta may be under balanced selection. Our results suggest that Pi-ta co-evolves with AVR-Pita, and that rice engages trench warfare with M. oryzae during the host and pathogen co-evolution.

A total of 18 paralogs of xyloglucan-specific endoglucanases (EGLs) from the glycosyl hydrolase family 12 were identified and characterized in Phytophthora sojae and Phytophthora ramorum. These genes encode predicted extracellular enzymes, with sizes ranging from 189 to 435 amino acid residues, that would be capable of hydrolyzing the xyloglucan component of the host cell wall. In two cases, four and six functional copies of these genes were found in tight succession within a region of 5 and 18 kb, respectively. The overall gene copy number and relative organization appeared well conserved between P. sojae and P. ramorum, with apparent synteny in this region of their respective genomes. Phylogenetic analyses of Phytophthora endoglucanases of family 12 and other known members of EGL 12, revealed a close relatedness with a fairly conserved gene sub-family containing, among others, sequences from the fungi Emericella desertorum and Aspergillus aculeatus. This is the first report of family 12 EGLs present in plant pathogenic eukaryotes.