3000 miles from home: a new Gastrosericus baobabicus Pulawski, 1995 (Hymenoptera, Larridae) distribution record highlights that the Sahel has a distinct entomofaunal signature

[from introduction] On October 30, 1953, an unidentified female wasp (Fig. 1) was collected from ‘Belet Uen, Somaliland’ (= Beledweyne, 4°44’N 45°12’E), situated in the valley of the Shebelle River, HiraanProvince,Somalia. It was deposited in the aculeate Hymenoptera collection of the Albany Museum, Grahamstown by D. Greathead prior to 1968. Apart from the words ‘Somaliland’ and ‘Desert Locust Survey’ the label is handwritten and the collector’snameis not recorded. Greathead’s sister, S. Gess (Albany Museum), deciphered the label and stated that he had worked for the Desert Locust Survey, investigating the natural enemies of locusts and had been in Somalia (then Somaliland) at that time (Murphy & Cock 2007). The specimen was sent in 2004 by F. Gess to W. Pulawski, who determined it as Gastrosericus baobabicus Pulawski, 1995. Gastrosericus species prey on spiders and a variety of small insects (Pulawski 1995), including Orthoptera (Krombein & Pulawski 1986), so it is likely that Greathead collected the specimen in connection with his interest in the insect enemies of Acridoidea (Orthoptera) (Greathead 1962)

Prestressed Concrete Piles Under Seismic Loading: Case History

This paper describes the performance of 14-inch prestressed concrete piles, supporting a 10-story commercial building, during the 1989 Loma-Prieta Earthquake. Excavations were performed to expose several piles. Except for one comer pile, no significant damage was observed. Several cracks, indicating possible formation of a plastic hinge, were observed at the top of this corner pile. In general, the piles performed well during the M7 earthquake

Coherent States Formulation of Polymer Field Theory

We introduce a stable and efficient complex Langevin (CL) scheme to enable the first numerical simulations of the coherent-states (CS) formulation of polymer field theory. In contrast with Edwards' well known auxiliary-field (AF) framework, the CS formulation does not contain an embedded non-linear, non-local functional of the auxiliary fields, and the action of the field theory has a fully explicit, finite-order and semi-local polynomial character. In the context of a polymer solution model, we demonstrate that the new CS-CL dynamical scheme for sampling fluctuations in the space of coherent states yields results in good agreement with now-standard AF simulations. The formalism is potentially applicable to a broad range of polymer architectures and may facilitate systematic generation of trial actions for use in coarse-graining and numerical renormalization-group studies.Comment: 14pages 8 figure

Day-case surgery for total hip and knee replacement: how safe and effective is it?

Multimodal protocols for pain control, blood loss management and thromboprophylaxis have been shown to benefit patients by being more effective and as safe (fewer iatrogenic complications) as conventional protocols. Proper patient selection and education, multimodal protocols and a well-defined clinical pathway are all key for successful day-case arthroplasty. By potentially being more effective, cheaper than and as safe as inpatient arthroplasty, day-case arthroplasty might be beneficial for patients and healthcare systems

Comparing models for predicting species' potential distributions : a case study using correlative and mechanistic predictive modelling techniques

Models used to predict species’ potential distributions have been described as either correlative or mechanistic. We attempted to determine whether correlative models could perform as well as mechanistic models for predicting species potential distributions, using a case study. We compared potential distribution predictions made for a coastal dune plant (Scaevola plumieri) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique). The profile technique was based on principal components analysis (PCA) and the group-discrimination technique was based on multiple logistic regression (LR). Kappa (κ) statistics were used to objectively assess model performance and model agreement. Model performance was calculated by measuring the levels of agreement (using κ) between a set of testing localities (distribution records not used for model building) and each of the model predictions. Using published interpretive guidelines for the kappa statistic, model performance was “excellent” for the SWB model (κ=0.852), perfect for the LR model (κ=1.000), and “very good” for the PCA model (κ=0.721). Model agreement was calculated by measuring the level of agreement between the mechanistic model and the two correlative models. There was “good” model agreement between the SWB and PCA models (κ=0.679) and “very good” agreement between the SWB and LR models (κ=0.786). The results suggest that correlative models can perform as well as or better than simple mechanistic models. The predictions generated from these three modelling designs are likely to generate different insights into the potential distribution and biology of the target organism and may be appropriate in different situations. The choice of model is likely to be influenced by the aims of the study, the biology of the target organism, the level of knowledge the target organism’s biology, and data quality

Component Microenvironments and System Biogeography Structure Microorganism Distributions in Recirculating Aquaculture and Aquaponic Systems

ABSTRACT Flowthrough and pond aquaculture system microbiome management practices aim to mitigate fish disease and stress. However, the operational success of recirculating aquaculture systems (RAS) depends directly on system microbial community activities. In RAS, each component environment is engineered for a specific microbial niche for waste management, as the water continuously flowing through the system must be processed before returning to the rearing tank. In this study, we compared waste management component microbiomes (rearing tank water, pH correction tank, solid-waste clarifier, biofilter, and degassing tower) within a commercial-scale freshwater RAS by high-throughput 16S rRNA gene sequencing. To assess consistency among freshwater RAS microbiomes, we also compared the microbial community compositions of six aquaculture and aquaponic farms. Community assemblages reflected site and source water relationships, and the presence of a hydroponic subsystem was a major community determinant. In contrast to the facility-specific community composition, some sequence variants, mainly classified into Flavobacterium, Cetobacterium, the family Sphingomonadaceae, and nitrifying guilds of ammonia-oxidizing archaea and Nitrospira, were common across all facilities. The findings of this study suggest that, independently of system design, core taxa exist across RAS rearing similar fish species but that system design informs the individual aquatic microbiome assemblages. Future RAS design would benefit from understanding the roles of these core taxa and then capitalizing on their activities to further reduce system waste/added operational controls. IMPORTANCE Recirculating aquaculture systems (RAS) are agroecosystems for intensive on-land cultivation of products of fisheries. Practitioners that incorporate edible plant production into RAS refer to these facilities as aquaponic systems (AP). RAS have the potential to offset declining production levels of wild global fisheries while reducing waste and product distance to market, but system optimization is needed to reduce costs. Both RAS and AP rely on microbial consortia for maintaining water quality and promoting fish/plant health, but little is known about the microorganisms actually present. This lack of knowledge prevents optimization of designs and operational controls to target the growth of beneficial microbial species or consortia. The significance of our research is in identifying the common microorganisms that inhabit production RAS and AP and the operational factors that influence which microorganisms colonize and become abundant. Identifying these organisms is a first step toward advanced control of microbial activities that improve reproducibility and reduce costs