The Palaeolithic archaeological record from current dryland contexts informs on activity across only a fraction of occupied Pleistocene landscapes. Now-submerged contexts, such as those preserved beneath the southern North Sea, allow past human activity to be considered at a more representative scale. Previous investigations have recovered internationally significant Middle Palaeolithic archaeology associated with submerged Pleistocene landscapes in the southern North Sea. Discovered through aggregate dredging in marine aggregate licence Area 240, the archaeology is associated with Pleistocene deposits of the Paleo-Yare river system. Subsequent studies have demonstrated that the Palaeo-Yare catchment extended across adjacent aggregate areas, leading to the implementation of a regional monitoring programme at aggregate wharfs to monitor, manage, and assimilate new archaeological data.

This paper reviews all new Palaeolithic lithic finds recovered between 2011 and 2022 from Area 240 and adjacent licence areas. Most are Middle Palaeolithic artefacts from Area 240. These new Middle Palaeolithic discoveries are related to previous finds and the combined collections placed within their wider Middle Palaeolithic British context. Middle Palaeolithic activity within the Palaeo-Yare catchment included multiple phases of occupation associated with different favoured technological repertoires, indicating that two groups of artefacts are present: Levallois artefacts likely to date to the early Middle Palaeolithic (MIS 8–7–6) and handaxes dating to the Late Middle Palaeolithic (MIS 5d–3).

Aggregates provide a concise way to express complex knowledge. The problem of selecting an appropriate formalization of aggregates for answer set programming (ASP) remains unsettled. This paper revisits it from the viewpoint of Approximation Fixpoint Theory (AFT). We introduce an AFT formalization equivalent with the Gelfond–Lifschitz reduct for basic ASP programs and we extend it to handle aggregates. We analyze how existing approaches relate to our framework. We hope this work sheds some new light on the issue of a proper formalization of aggregates.

In answer set programming, two groups of rules are considered strongly equivalent if they have the same meaning in any context. In some cases, strong equivalence of programs in the input language of the grounder gringo can be established by deriving rules of each program from rules of the other. The possibility of such proofs has been demonstrated for a subset of that language that includes comparisons, arithmetic operations, and simple choice rules, but not aggregates. This method is extended here to a class of programs in which some uses of the #count aggregate are allowed.

The input language of the answer set solver clingo is based on the definition of a stable model proposed by Paolo Ferraris. The semantics of the ASP-Core language, developed by the ASP Standardization Working Group, uses the approach to stable models due to Wolfgang Faber, Nicola Leone, and Gerald Pfeifer. The two languages are based on different versions of the stable model semantics, and the ASP-Core document requires, “for the sake of an uncontroversial semantics,” that programs avoid the use of recursion through aggregates. In this paper we prove that the absence of recursion through aggregates does indeed guarantee the equivalence between the two versions of the stable model semantics, and show how that requirement can be relaxed without violating the equivalence property.

In this paper, we propose a variant of Answer Set Programming (ASP) with evaluable functions that extends their application to sets of objects, something that allows a fully logical treatment of aggregates. Formally, we start from the syntax of First Order Logic with equality and the semantics of Quantified Equilibrium Logic with evaluable functions (${\rm QEL}^=_{\cal F}$). Then, we proceed to incorporate a new kind of logical term, intensional set (a construct commonly used to denote the set of objects characterised by a given formula), and to extend ${\rm QEL}^=_{\cal F}$ semantics for this new type of expression. In our extended approach, intensional sets can be arbitrarily used as predicate or function arguments or even nested inside other intensional sets, just as regular first-order logical terms. As a result, aggregates can be naturally formed by the application of some evaluable function (count, sum, maximum, etc) to a set of objects expressed as an intensional set. This approach has several advantages. First, while other semantics for aggregates depend on some syntactic transformation (either via a reduct or a formula translation), the ${\rm QEL}^=_{\cal F}$ interpretation treats them as regular evaluable functions, providing a compositional semantics and avoiding any kind of syntactic restriction. Second, aggregates can be explicitly defined now within the logical language by the simple addition of formulas that fix their meaning in terms of multiple applications of some (commutative and associative) binary operation. For instance, we can use recursive rules to define sum in terms of integer addition. Last, but not least, we prove that the semantics we obtain for aggregates coincides with the one defined by Gelfond and Zhang for the ${\cal A}\mathit{log}$ language, when we restrict to that syntactic fragment.

We studied the role played by temperature and rennet concentration in the coagulation process for cheese manufacture and the evaluation of their kinetics. We concluded that temperature is the main factor that determines the kinetics. The rennet concentration was unimportant probably due to the fast action of the enzyme chymosin. The Dynamic light scattering technique allowed measuring the aggregate's size and their formation kinetics. The volume fraction of solids was determined from viscosity measurements, showing profiles that are in agreement with the size profiles. The results indicate that the formation of the aggregates for rennet cheese is strongly dependent on temperature and rennet concentration. The results revealed that at 35·5 °C the volume fraction of solids has the maximum slope, indicating that at this temperature the curd is formed rapidly. The optimal temperature throughout the process was established. Second-order kinetics were obtained for the process. We observed a quadratic dependence between the rennet volume and the volume fraction of solids (curd), thereby indicating that the kinetics of the curd production should be of order two.

A very desirable Datalog extension investigated by many researchers in the last 30 years consists in allowing the use of the basic SQL aggregates min, max, count and sum in recursive rules. In this paper, we propose a simple comprehensive solution that extends the declarative least-fixpoint semantics of Horn Clauses, along with the optimization techniques used in the bottom-up implementation approach adopted by many Datalog systems. We start by identifying a large class of programs of great practical interest in which the use of min or max in recursive rules does not compromise the declarative fixpoint semantics of the programs using those rules. Then, we revisit the monotonic versions of count and sum aggregates proposed by Mazuran et al. (2013b, The VLDB Journal 22, 4, 471–493) and named, respectively, mcount and msum. Since mcount, and also msum on positive numbers, are monotonic in the lattice of set-containment, they preserve the fixpoint semantics of Horn Clauses. However, in many applications of practical interest, their use can lead to inefficiencies, that can be eliminated by combining them with max, whereby mcount and msum become the standard count and sum. Therefore, the semantics and optimization techniques of Datalog are extended to recursive programs with min, max, count and sum, making possible the advanced applications of superior performance and scalability demonstrated by BigDatalog (Shkapsky et al. 2016. In SIGMOD. ACM, 1135–1149) and Datalog-MC (Yang et al. 2017. The VLDB Journal 26, 2, 229–248).

We have built a 3D lithological model of the Netherlands, for the purpose of mapping on-land aggregate resources down to 50 m below the surface. The model consists of voxel cells (1000 ⋅ 1000 ⋅ 1 m), with lithological composition and aggregate content estimates as primary attributes. These attributes were derived from ∼350,000 borehole descriptions. Overburdens and intercalations of cohesive or otherwise non-dredgeable materials were taken into account to define geologically exploitable aggregates within the total stock. We arrive at about 520 ⋅ 109 m3 of aggregates occurring in the depth range investigated. Some 50% of this amount is considered geologically exploitable and about 25% would in principle (but largely not in reality) be accessible. Most aggregates resources (∼98%) are coarse sand, which is processed for use in concrete, masonry mortars, drains, filters, etc. The total exploitable stock of coarse sand in the depth range investigated amounts to roughly 7500 times the current annual consumption level, and is virtually indepletable. The gravel stock, estimated at some 12 ⋅ 109 m3, is small by comparison, and impels a dependency on imports.

Exploitable aggregates occur in all but the coastal provinces. In accordance with current policy changes, the future may show a shift from concentrated production along the upstream Dutch Rhine and Meuse rivers towards a more even distribution of small-sized operations over the country. Fairly large aggregate stocks, that have not yet been exploited to significant extent, are available in the northern extent of the aggregates occurrences.

Gelfond and Zhang recently proposed a new stable model semantics based on Vicious Circle Principle in order to improve the interpretation of logic programs with aggregates. The paper focuses on this proposal, and analyzes the complexity of both coherence testing and cautious reasoning under the new semantics. Some surprising results highlight similarities and differences versus mainstream stable model semantics for aggregates. Moreover, the paper reports on the design of compilation techniques for implementing the new semantics on top of existing ASP solvers, which eventually lead to realize a prototype system that allows for experimenting with Gelfond-Zhang's aggregates.

Aggregate resource assessments, derived from three subsequent generations of voxel models, were compared in a qualitative way to illustrate and discuss modelling progress. We compared the models in terms of both methodology and usability. All three models were produced by the Geological Survey of the Netherlands. Aggregate is granular mineral material used in building and construction, and in this case consists of sand and gravel. On each occasion ever-increasing computer power allowed us to model at a higher resolution and use more geological information to constrain interpolations. The two oldest models, built in 2005 and 2007, were created specifically for aggregate resource assessments, the first as proof of concept, the second for an online resource information system. The third model was derived from the ongoing multipurpose systematic 3D modelling programme GeoTOP. We used a study area of 40 × 40 km located in the central Netherlands, which encompasses a section of the Rhine-Meuse delta and adjacent glacial terrains to the north. Aggregate resource assessments rely on the extent to which the occurrence and grain size of sand and gravel are resolved, and on proper representation of clay and peat layers (overburden and intercalations) that affect exploitability. Average model properties (e.g. total aggregate content) are about the same in all three models, except for a difference resulting from converting older lithological classifications to the current one. This difference illustrates that data selection and preparation are paramount, especially when dealing with quality issues. Generally speaking the results of the aggregate resource assessments are consistent and satisfactory for all three models, provided that they are judged at the appropriate scale. However, the assessments based on GeoTOP best approach the desired scale of use for the aggregates industry; in that sense progress was significant and each model was a better fit for the purpose.

The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates. The goal is to have a language based on simple syntax and clear intuitive and mathematical semantics. We give some properties of $\mathcal{A}log$, an algorithm for computing its answer sets, and comparison with other approaches.

Aggregates of the Polychaeta Phyllochaetopterus socialis were recorded for the first time off Gemlik Bay in the Sea of Marmara, in August 2008. These were found at about 53 m depth, on the soft sediments around the sub-sea part of the North Anatoly Earthquake Fault. Samples were landed by beam trawl. Total wet weight of the mats was 58 kg. Forty-three species belonging to 10 phyla associated with P. socialis were recorded from the whole landing materials. Echinodermata and Gastropoda were the most abundant (12 and 8 species, respectively). Shannon–Wiener diversity and Margalef species richness indices were applied to analyse the structure of benthic communities. Presence and abundance lognormal distribution of the species and communities in mat habitat are shown. The hydrographic environment of the water mass is also discussed.

Prevention of the heat-induced aggregation of β-lactoglobulin (β-Lg) would improve the heat stability of whey proteins. The effects of lipoic acid (LA, or thioctic acid), in both its oxidised and reduced form (dihydrolipoic acid, DHLA), on heat-induced unfolding and aggregation of β-Lg were investigated. LA/DHLA was added to native β-Lg and the mixture was heated at 70, 75, 80 or 85 °C for up to 30 min at pH 6·8. The samples were analysed by Polyacrylamide Gel Electrophoresis (PAGE) and Size-exclusion HPLC (SE-HPLC). LA was not as effective as DHLA in reducing the formation of aggregates of heated β-Lg. Heating β-Lg with DHLA resulted in formation of more β-Lg monomers (due to dissociation of native dimers) and significantly less β-Lg aggregates, compared with heating β-Lg alone. The aggregates formed in the presence of DHLA were both covalently linked, via disulphide bonds, and non-covalently (hydrophobically) linked, but the amount of covalently linked aggregates was much less than when β-Lg was heated alone. The results suggest that DHLA was able to partially trap the reactive β-Lg monomer containing a free sulphydryl (−SH) group, by forming a ‘modified monomer’, and to prevent some sulphydryl−sulphydryl and sulphydryl−disulphide interactions that lead to the formation of covalently linked protein aggregates. The effects of DHLA were similar to those of N-ethylmaleimide (NEM) and dithio(bis)-p-nitrobenzoate (DTNB). However, the advantage of using DHLA over NEM and DTNB to lessen aggregation of β-Lg is that it is a food-grade compound which occurs naturally in milk.

Weight constraint and aggregate programs are among the most widely used logic programs with constraints. In this paper, we relate the semantics of these two classes of programs, namely, the stable model semantics for weight constraint programs and the answer set semantics based on conditional satisfaction for aggregate programs. Both classes of programs are instances of logic programs with constraints, and in particular, the answer set semantics for aggregate programs can be applied to weight constraint programs. We show that the two semantics are closely related. First, we show that for a broad class of weight constraint programs, called strongly satisfiable programs, the two semantics coincide. When they disagree, a stable model admitted by the stable model semantics may be circularly justified. We show that the gap between the two semantics can be closed by transforming a weight constraint program to a strongly satisfiable one so that no circular models may be generated under the current implementation of the stable model semantics. We further demonstrate the close relationship between the two semantics by formulating a transformation from weight constraint programs to logic programs with nested expressions, which preserves the answer set semantics. Our study on the semantics leads to an investigation of a methodological issue, namely, the possibility of compact representation of aggregate programs by weight constraint programs. We show that almost all standard aggregates can be encoded by weight constraints compactly. This makes it possible to compute the answer sets of aggregate programs using the answer set programming solvers for weight constraint programs. This approach is compared experimentally with the ones where aggregates are handled more explicitly, which show that the weight constraint encoding of aggregates enables a competitive approach to answer set computation for aggregate programs.

The properties of activated sludge systems can be characterized using image analysis procedures. When these systems operate with high biomass content, accurate sludge characterization requires samples to be diluted. Selection of the best image acquisition magnification is directly related to the amount of biomass screened. The aim of the present study was to survey the effects of dilution and magnification on the assessment of aggregated and filamentous bacterial content and structure using image analysis procedures. Assessments of biomass content and structure were affected by dilutions. Therefore, the correct operating dilution requires careful consideration. Moreover, the acquisition methodology comprising a 100× magnification allowed data on aggregated and filamentous biomass to be determined and smaller aggregates to be identified and characterized, without affecting the accuracy of lower magnifications regarding biomass representativeness.

Different approaches using microscopy image analysis procedures were employed for characterization of activated sludge systems. The approaches varied mainly on the type of visualization and acquisition method used for collection of data. In this context, this study focused on the comparison of the two most common acquisition methods: bright field and phase-contrast microscopy. Images were acquired from seven different wastewater treatment plants for a combined period of two years. Advantages and disadvantages of each acquisition technique and the results are discussed. Bright field microscopy proved to be more simple and inexpensive and provided the best overall results.

The assemblage and the temporal changes of benthic macrofauna inhabiting the Phyllochaetopterus socialis (Polychaeta: Chaetopteridae) aggregates were analysed during 2004 and May 2005 in the Mar del Plata harbour, Buenos Aires (Argentina). Species composition, abundance, richness and diversity were estimated from monthly or bimonthly samples obtained by SCUBA diving. Multivariate (MDS) and SIMPER analyses were applied to analyse the structure of benthic communities. In the mats, a total of 57 species (invertebrates and chordates) belonging to 11 phyla were associated to P. socialis: crustaceans and molluscs were the most abundant species and crustaceans and polychaetes were the most diverse groups (14 and 11 species richness, respectively). The mean abundance ranged from 79.67±57.47 ind/250 ml to 718.75 ind/250 ml (mean±SD). The amphipod Monocorophium insidiosum, the gastropod Anachis isabellei and the tanaidacean Leptognathia sp. were the most representative species in the mats. Richness and diversity in P. socialis aggregates were higher than in surrounding sediments. Results show significant differences among months in composition, abundance and feeding guilds of the macrofauna associated with the mats. The assemblage of benthic macrofauna with permanent and temporary organisms in P. socialis aggregates suggests the existence of microhabitats in the mats that provide substrate, refuges for predation and availability of food increasing richness and diversity. These results allow considering P. socialis as an autogenic ecosystem engineer in the Mar del Plata harbour.

Disjunctive logic programming (DLP) is a very expressive formalism. It allows forexpressing every property of finite structures that is decidable in thecomplexity class ΣP2(=NPNP). Despite this high expressiveness, thereare some simple properties, often arising in real-world applications, whichcannot be encoded in a simple and natural manner. Especially properties thatrequire the use of arithmetic operators (like sum, times, or count) on a set ormultiset of elements, which satisfy some conditions, cannot be naturallyexpressed in classic DLP. To overcome this deficiency, we extend DLP byaggregate functions in a conservative way. In particular, we avoid theintroduction of constructs with disputed semantics, by requiring aggregates tobe stratified. We formally define the semantics of the extended language (called ), and illustrate how it can be profitably used for representingknowledge. Furthermore, we analyze the computational complexity of , showing that the addition of aggregates does not bring a highercost in that respect. Finally, we provide an implementation of in DLV—a state-of-the-art DLP system—andreport on experiments which confirm the usefulness of the proposed extensionalso for the efficiency of computation.