Radiocarbon dating by accelerator mass spectrometry (AMS) requires transforming samples into graphite, a step that typically depends on liquid nitrogen and high-purity carrier gases, increasing both cost and operational complexity. We present μGRAPHILINE, a fully automated, modular combustion–graphitization line that removes these dependencies by combining dual-zone combustion with iron–zinc reduction. Performance was evaluated on more than 180 standards and reference materials targets measured on two independent AMS systems. The μGRAPHILINE consistently achieved >90% graphitization yields, stable backgrounds of ∼0.24 pMC (≈48,500 BP), and sample throughput of ∼3.5 hours per target. Reliable operation was demonstrated for a broad sample-size range, from routine 1 mg C down to ∼0.2 mg C, with ion currents sufficient for precise AMS analysis. The system’s automation, modularity, and low memory effect support improved laboratory throughput and operator efficiency. These results indicate that μGRAPHILINE provides a robust and efficient approach to radiocarbon sample preparation with broad potential applications.

The integration of camera and LiDAR technologies has the potential to significantly enhance construction robots’ perception capabilities by providing complementary construction information. Structured light cameras (SLCs) are a desirable alternative as they provide comprehensive information on construction defects. However, fusing these two types of information depends largely on the sensors’ relative positions, which can only be established through extrinsic calibration. This paper introduces a novel calibration algorithm considering a customized board for SLCs and repetitive LiDARs, which are designed to facilitate the automation of construction robots. The calibration board is equipped with four symmetrically distributed hemispheres, whose centers are obtained by fitting the spheres and adoption with the geometric constraints. Subsequently, the spherical centers serve as reference features to estimate the relationship between the sensors. These distinctive features enable our proposed method to only require one calibration board pose and minimize human intervention. We conducted both simulation and real-world experiments to assess the performance of our algorithm. And the results demonstrate that our method exhibits enhanced accuracy and robustness.

Automatic broiler catching machines have been developed for several reasons. Manual catching is expensive, often rough and may cause injury to the birds. Apart from animal welfare considerations, the demand for good quality meat means that rejection rates must be kept at a low level. The poor working conditions for manual catching teams are also an important factor. Only a few scientific studies on the effects of catching machines on bird health and welfare have been published. In this study, the carcase rejection rates in relation to manual and mechanical catching were compared at a poultry abattoir following a change of loading and unloading systems. The effect on the level of birds found ‘dead on arrival’ at the slaughterhouse initially varied considerably, regardless of catching method. During the last 3-month period of the study however, mechanically caught flocks showed significantly higher frequencies of dead birds on arrival than manually caught flocks. During the same last period, when running-in problems should be regarded as solved, the prevalence of bruises was also still significantly higher in the mechanically caught flocks, whereas the prevalence of fractures did not differ significantly between the two groups. This suggests that there are still opportunities for further improvements of the machine, although in Sweden it has now been accepted for commercial use in accordance with Swedish animal welfare legislation, under the supervision of the National Board of Agriculture.

Drawing upon the history of the doctrine of the old use, Professor John Mee has suggested both that the extent of the authority for a “retention” approach to “automatic” resulting trusts has been overlooked, and that while as a matter of history a “retention” approach has significant support, as a matter of principle in the modern law it is not fully satisfactory, so that it is necessary to look elsewhere for a theoretical explanation for the “automatic” resulting trust. This article examines the reasons for the inconsistency identified by Professor Mee, seeking to elucidate the relationship between uses and trusts, to contribute to the history of resulting uses and trusts, and to explain why the modern “automatic” resulting trust has become a rule in search of a rationale.

To capture the fine structure of the flare kernel during it's explosive phase, we design a real time flare onset detecting algorithm named Near Saturation Area Threshold(NSAT), And an automatic CCD parameters control algorithm for the observing software. All the data from CCD, 48f/s, could be saved to the hard disk, and the GPS time of the flare onset also be saved in the log. These methods could avoid the data overflow and grab the fine structure data of the flare kernel. The simulation experiment works well and the software will be put into use in Huairou Solar Observatory soon.

Manual error annotation of learner corpora is time-consuming and error-prone, whereas existing automatic techniques cannot reliably detect and correct all types of error. This paper shows that the two methods can successfully complement each other: automatic detection and partial correction of trivial errors relieves the human annotator from the laborious task of incessantly marking up oft-committed mistakes and enables him or her to focus on errors which cannot or cannot yet be handled mechanically, thus enabling more consistent annotation with considerably less manual time and effort expended.

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends on high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research.

A method for solving the recognition of partially occluded parts is presented. It is based on the automatic generation of features from a set of primitive features which are configurations of pairs of fixed length segments of boundary edges of the parts. The procedure that creates the recognition features assigns a number in the range (0,1) that indicates the importance of the feature in the recognition strategy. This number is referred to as the feature's saliency. The method assumes that the parts that can occur in a scene come from a known set of parts. An example illustrates how automatically generated features can be used to count the number of identical parts in a heap.

The need for fault tolerant mechanisms in flexible manufacturing systems is described and previous work on diagnosis in robotics and other areas is considered. Fundamental difficulties in the analysis of robot cell malfunctions are described and a glossary of terms useful in this area is presented. Limited observational data on the occurrence of faults in assemblies are reported. Finally a proposal for an experimental mechanism for diagnosis within a knowledge rich supervisory system is explored.

Intrusive thoughts, flashbacks, panic attacks and sudden physiologicalarousal are each experienced as involuntary, are difficult to control, andlead to considerable distress. Such observations have led to the suggestionthat anxiety disorders are associated with the operation of automaticinformation-processing biases. Clinical and experimental evidence for thisproposal is reviewed and three different classes of routes to the developmentand modification of these automatic processes are described: an innate route,repetition/habituation, and conscious appraisal. The review focuses inparticular on the third route, proposing that automatic processing biasescan be altered by accessing and modifying conscious appraisals of internaland external events. Indirect evidence is provided by selective attentionparadigms in anxiety, treatment studies and clinical observations, althoughfurther research will be necessary for a direct test of the pathway. Theimplications for the theory and practice of psychological therapy for anxiety disorders are described.