Incompatible and contradictory retrodictions in the history approach to quantum mechanics

We illustrate two simple spin examples which show that in the consistent histories approach to quantum mechanics one can retrodict with certainty incompatible or contradictory propositions corresponding to non-orthogonal or, respectively, orthogonal projections

Relativistic Spontaneous Localization: A Proposal

A new proposal for a Lorentz-invariant spontaneous localization theory is presented. It is based on the choice of a suitable set of macroscopic quantities to be stochastically induced to have definite values. Such macroscopic quantities have the meaning of a time-integrated amount of a microscopically defined quantity called stuff related to the presence of massive particles

Laser pulse annealing of ion-implanted GaAs

GaAs single-crystals wafers are implanted at room temperature with 400-keV Te + ions to a dose of 1×10^15 cm^–2 to form an amorphous surface layer. The recrystallization of this layer is investigated by backscattering spectrometry and transmission electron microscopy after transient annealing by Q-switched ruby laser irradiation. An energy density threshold of about 1.0 J/cm^2 exists above which the layer regrows epitaxially. Below the threshold the layer is polycrystalline; the grain size increases as the energy density approaches threshold. The results are analogous to those reported for the elemental semiconductors, Si and Ge. The threshold value observed is in good agreement with that predicted by the simple model successfully applied previously to Si and Ge

A Fuzzy Logic Control application to the Cement Industry

A case study on continuous process control based on fuzzy logic and supported by expert knowledge is proposed. The aim is to control the coal-grinding operations in a cement manufacturing plant. Fuzzy logic is based on linguistic variables that emulate human judgment and can solve complex modeling problems subject to uncertainty or incomplete information. Fuzzy controllers can handle control problems when an accurate model of the process is unavailable, ill-defined, or subject to excessive parameter variations. The system implementation resulted in productivity gains and energy consumption reductions of 3% and 5% respectively, in line with the literature related to similar applications

Complexity measurement in two supply chains with different competitive priorities

Complexity measurement based on the Shannon information entropy is widely used to evaluate variety and uncertainty in supply chains. However, how to use a complexity measurement to support control actions is still an open issue. This article presents a method to calculate the relative complexity, i.e., the relationship between the current and the maximum possible complexity in a Supply Chain. The method relies on unexpected information requirements to mitigate uncertainty. The article studies two real-world Supply Chains of the footwear industry, one competing by cost and quality, the other by flexibility, dependability, and innovation. The second is twice as complex as the first, showing that competitive priorities influence the complexity of the system and that lower complexity does not ensure competitivity

Effect of free range production system on chicken carcass and meat quality traits

There is a growing consumer interest towards poultry products coming from unconventional housing systems with outdoor access. A study was conducted to characterize carcass traits and chemico-physical properties of chickens labelled free-range (according to the EC Directive 1538/91) if compared with conventional ones. Free range female (FR-F) and male (FR-M) chickens were separately raised for 56 and 70 d, respectively, in order to obtain currently marketed product categories. They belonged to medium growing Isa strain and had continuous daytime access to open-air area from 28 d to slaughter age and indoors stocking density did not exceed 27.5 kg/sqm. Conventional female (C-F) and male (C-M) chickens belonged to a fast growing hybrid (Ross 708) and were separately raised for 39 and 50 d, respectively, under intensive conditions in a poultry house under controlled environmental conditions at a stocking density of 30-32 kg/sqm. Females (FR-F and C-F) and male (FR-M and C-M) birds were slaughtered into 2 separate sessions. After slaughtering, 20 carcasses for each group (FR-F, 1.2 kg; FR-M, 1.9 kg; C-F, 1.2 kg; C-M, 2.3 kg) were randomly selected for evaluating carcass cut-up yields and fifteen of them were used to assess quality properties of both breast and leg meat (skin and meat colour, ultimate pH, drip and cooking losses, AK-shear force). C birds had dramatic higher carcass and breast meat yield, whereas FR had higher wing and leg yields (P <0.001). Both meat and skin of breast and leg coming from FR birds were lighter and less red and more yellow (P <0.001). Even if no difference were found in ultimate pH, FR birds exhibited higher water-holding capacity (lower drip and cooking losses) in both breast and leg meat (P <0.01). Finally, although shear force did not differ in breast meat, leg from FR birds were tougher (P <0.001). Overall these data indicate that noticeable quality trait differences exist between free range and conventional labelled poultry products

Estimating the circularity performance of an emerging industrial symbiosis network: The case of recycled plastic fibers in reinforced concrete

In recent times, the construction industry has been handling circular economy strategies in order to face the most important challenges in the sector, namely the lack of raw materials and the environmental impacts derived from all the processes linked to the entire supply chain. The industrial symbiosis approach represents an effective strategy to improve the circularity of the construction industry. This study analyses the circularity performance of an emerging industrial symbiosis network derived from the production of a cement mortar reinforced with recycled synthetic fibers coming from artificial turf carpets. From the collection of artificial turf carpets at the end-of-life stage it is possible to recover several materials, leading to potential unusual interactions between industries belonging to different sectors. A suitable indicator, retrieved from the literature, the Industrial Symbiosis Indicator (ISI), has been used to estimate the level of industrial symbiosis associated with increasing materials recirculation inside the network. Four scenarios—ranging from perfect linearity to perfect circularity—representing growing circularity were tested. Findings demonstrate that the development of an effective industrial symbiosis network can contribute to improving the circular approach within the construction sector, reducing environmental and economic pressures

Impact of minority concentration on fundamental (H)D ICRF heating performance in JET-ILW

ITER will start its operation with non-activated hydrogen and helium plasmas at a reduced magnetic field of B-0 = 2.65 T. In hydrogen plasmas, the two ion cyclotron resonance frequency (ICRF) heating schemes available for central plasma heating (fundamental H majority and 2nd harmonic He-3 minority ICRF heating) are likely to suffer from relatively low RF wave absorption, as suggested by numerical modelling and confirmed by previous JET experiments conducted in conditions similar to those expected in ITER's initial phase. With He-4 plasmas, the commonly adopted fundamental H minority heating scheme will be used and its performance is expected to be much better. However, one important question that remains to be answered is whether increased levels of hydrogen (due to e. g. H pellet injection) jeopardize the high performance usually observed with this heating scheme, in particular in a full-metal environment. Recent JET experiments performed with the ITER-likewall shed some light onto this question and the main results concerning ICRF heating performance in L-mode discharges are summarized here

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously. In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems