A Neural Network Model for Decision-Making with Application in Sewage Sludge Management

Wastewater treatment (WWT) is a foremost challenge for maintaining the health of ecosystems and human beings; the waste products of the water-treatment process can be a problem or an opportunity. The sewage sludge (SS) produced during sewage treatment can be considered a waste to be disposed of in a landfill or as a source for obtaining raw material to be used as a fertilizer, building material, or alternative fuel source suitable for co-incineration in a high-temperature furnace. To this concern, this study's purpose consisted of developing a decision model, supported by an Artificial Neural Network (ANN model), allowing us to identify the most effective sludge management strategy in economic terms. Consistent with the aim of the work, the suitable SS treatment was identified, selecting for each phase of the SS treatment, an alternative available on the market ensuring energy and/or matter recovery, in line with the circular water value chain. Results show that the ANN model identifies the suitable SS treatments on multiple factors, thus supporting the decision-making and identifying the solution as per user requirements

An analytical framework for assessing cognitive capacity and processing speed of operators in industry 4.0

Abstract The fourth industrial revolution introduced a new paradigm in manufacturing systems. The digital network is at the basis of the smart manufacturing and the physical context is strictly related to the artificial intelligence. This new manufacturing context drastically changed the role of the operator since the increasing adoption of innovative devices in manufacturing process modified the work activities and the operator is employed in more cognitive than physical tasks. Therefore, the purpose of this paper consists in developing an analytical framework to assess the human cognitive capacity occupancy and the human processing time of correct information known as the quality performance. The analytical framework presented allows to assess the human mental workload imposed by the task and how the processing speed of correct information changes when quality performance varies

Low grade epithelial stromal tumour of the seminal vesicle

<p>Abstract</p> <p>Background</p> <p>The mixed epithelial stromal tumour is morphologically characterised by a mixture of solid and cystic areas consisting of a biphasic proliferation of glands admixed with solid areas of spindle cells with variable cellularity and growth patterns. In previous reports the seminal vesicle cystoadenoma was either considered a synonym of or misdiagnosed as mixed epithelial stromal tumour. The recent World Health Organisation Classification of Tumours considered the two lesions as two distinct neoplasms. This work is aimed to present the low-grade epithelial stromal tumour case and the review of the literature to the extent of establishing the true frequency of the neoplasm.</p> <p>Case presentation</p> <p>We describe a low-grade epithelial stromal tumour of the seminal vesicle in a 50-year-old man. Computed tomography showed a 9 × 4.5 cm pelvic mass in the side of the seminal vesicle displacing the prostate and the urinary bladder. Magnetic resonance was able to define tissue planes between the lesion and the adjacent structures and provided useful information for an accurate conservative laparotomic surgical approach. The histology revealed biphasic proliferation of benign glands admixed with stromal cellularity, with focal atypia. After 26 months after the excision the patient is still alive with no evidence of disease.</p> <p>Conclusion</p> <p>Cystoadenoma and mixed epithelial stromal tumour of seminal vesicle are two distinct pathological entities with different histological features and clinical outcome. Due to the unavailability of accurate prognostic parameters, the prediction of the potential biological evolution of mixed epithelial stromal tumour is still difficult. In our case magnetic resonance imaging was able to avoid an exploratory laparotomy and to establish an accurate conservative surgical treatment of the tumour.</p

ANN Modelling to Optimize Manufacturing Process

Neural network (NN) model is an efficient and accurate tool for simulating manufacturing processes. Various authors adopted artificial neural networks (ANNs) to optimize multiresponse parameters in manufacturing processes. In most cases the adoption of ANN allows to predict the mechanical proprieties of processed products on the basis of given technological parameters. Therefore the implementation of ANN is hugely beneficial in industrial applications in order to save cost and material resources. In this chapter, following an introduction on the application of the ANN to the manufacturing process, it will be described an important study that has been published on international journals and that has investigated the use of the ANNs for the monitoring, controlling and optimization of the process. Experimental observations were collected in order to train the network and establish numerical relationships between process-related factors and mechanical features of the welded joints. Finally, an evaluation of time-costs parameters of the process, using the control of the ANN model, is conducted in order to identify the costs and the benefits of the prediction model adopted

Power for Land, Sea and Air

ABSTRACT In this paper the experimental measurements concerning the heat transfer capabilities of several trailing edge (TE) cooling configurations that are based on the combination of enlarged pedestals and small rib turbulators are presented. The baseline geometry consists of a converging duct, reproducing the typical shape of a high pressure turbine blade TE, with two rows of enlarged pedestals. Three rows of square or semicircular turbulators were arranged in between the pedestals on the pressure side (PS) surface; the ribs height is e = 1 mm and the pitch is P/e = 10. The airflow pattern inside the test rig simulates the rotor blade cooling scheme with a 90deg turning flow from the hub inlet to the TE outlet. For each configuration heat transfer measurements were made keeping Mach number fixed at 0.3 and varying Reynolds number from 9000 to 27000 in the TE throat section. The effect of a varying tip massflow rate was tested considering 0%, 12.5% and 25% of the TE massflow. The detailed HTC maps were measured using the transient technique with TLC and a PMMA test article. As expected, by comparison with the baseline geometry, test results show that the HTC distribution and the average Nusselt number over the PS surface are affected by the presence of the ribs which promote the airstream turbulence. However, no remarkable difference between the results from different rib shapes can be highlighted. The tip massflow rate alters the HTC distribution in the radial direction over the whole TE. The results are compared with previous experiments, performed on the same geometries, but with an axial inlet

Observing planetesimal formation under streaming instability in the rings of HD 163296

We introduce a new technique to determine the gas turbulence and surface density in bright disc rings, under the assumption that dust growth is limited by turbulent fragmentation at the ring centre. We benchmark this prescription in HD 163296, showing that our measurements are consistent with available turbulence upper limits and agree with independent estimates of the gas surface density within a factor of two. We combine our results with literature measurements of the dust surface density and grain size to determine the dust-to-gas ratio and Stokes number in the 67 au and 100 au rings. Our estimates suggest that particle clumping is taking place under the effect of streaming instability (SI) in the 100 au ring. Even though in the presence of external isotropic turbulence this process might be hindered, we provide evidence that turbulence is non-isotropic in both rings and likely originating from mechanisms (such as ambipolar diffusion) that could ease particle clumping under SI. Finally, we determine the mass accretion rate under the assumption that the disc is in steady state and turbulence regulates angular momentum transport. Our results are in tension with spectroscopic measurements and suggest that other mechanisms might be responsible for accretion, in qualitative agreement with the detection of a magneto-centrifugal wind in this system. Applying our method to larger samples can be used to statistically assess if SI is a viable mechanism to form planetesimals in bright rings.Comment: 13 pages, 4 figures; accepted for publication on ApJ

Human protein C concentrate in pediatric septic patients

Severe sepsis and septic shock are leading causes of morbidity and mortality in the pediatric population. Unlike what is suggested for the adult population, recombinant human activated protein C (rhAPC) is contraindicated in children. Long before rhAPC was considered for use in pediatric patients, case reports appeared on the safe administration of protein C zymogen. Therefore, we conducted a systemic review of currently available data on protein C zymogen (PC) use among children affected by severe sepsis or septic shock. A total number of 13 case series or case reports and a dose-finding study were found on the use of PC in the pediatric intensive care unit, reporting on 118 treated children, with an overall survival of 84%. There was no bleeding complication, the only reported complication being a single mild allergic reaction. These studies show that PC is safe, not associated with bleeding and possibly useful for improving coagulation abnormalities of sepsis