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To improve the financial sustainability and business management of composting facilities, mostly small-scale and manually operated facilities, the simultaneous optimization of the process and quality of the final product must be prioritized. This study used artificial neural networks (ANNs) and particle swarm optimization (PSO) as tools to evaluate the composting of biowaste (BW) with different cosubstrates (i. star grass (SG) and ii. a SG and sugarcane filter cake (SFC) mixture). The simulation aimed to maximize product quality in the shortest processing time by varying the mixing ratio and turning frequency. The simulation showed optimal conditions with a turning frequency of twice per week with the following mixtures: (i) BW:SG (72.9:27.1), 76 days of processing; and (ii) BW:SFC:SG (60:16:24), 88 days of processing. The results showed the effect of the type of carbon source in the cosubstrates on the retention time, which may imply the need for a larger area in composting facilities. On the other hand, the findings show that a minimum time is required to achieve a product that meets quality standards, although a longer processing time reduces the agricultural value of the compost. This model can be used to define design criteria and operating conditions and select a cosubstrate that can contribute to improving the agricultural quality of the final product. [ABSTRACT FROM AUTHOR]

A novel approach to optimize the composting process of biowaste (BW) mixed with sugarcane filter cake (SFC) and the product quality was attempted in the present study by adopting Artificial Neuronal Network (ANN) and the particle swarm optimization (PSO) algorithm. The effectiveness of the co-composting process depends on operational parameters such as Mixing Ratio (MR) and Turning Frequency (TF). Using the optimization of these factors, the process time can be reduced while product quality can be maximized. This study includes the simultaneous evaluation of both operational parameters, with SFC being the amendment material (BW:SFC MR of 90:10, 80:20 and 70:30) and a TF of 1, 2 and 3 turnings per week. The simultaneous effect of the two operational parameters was evaluated using a central composite design. ANN was used to predict the behaviour of the response parameters, and the PSO algorithm was used to optimize the process and the final product quality. The results of the simulations with ANN suggest that the BW:SFC ratios of 81:19 and 75:25, with a TF of two times/week and an estimated operation time of 76–94 days, correspond to a final product with the most adequate physicochemical quality for agricultural use. The optimization with PSO showed the optimal local at a BW:SFC MR of 76.9:23.1 with a turning frequency of two times weekly. An 80-day process is recommended to optimize the final product quality. The model can be useful to define design criteria and operational conditions during biowaste composting. [ABSTRACT FROM AUTHOR]

Background: Impairments in activities of daily living (ADL) are a criterion for Alzheimer's disease (AD) dementia. However, ADL gradually decline in AD, impacting on advanced (a-ADL, complex interpersonal or social functioning), instrumental (IADL, maintaining life in community), and finally basic functions (BADL, activities related to physiological and self-maintenance needs). Information and communication technologies (ICT) have become an increasingly important aspect of daily functioning. Yet, the links of ADL, ICT, and neuropathology of AD dementia are poorly understood. Such knowledge is critical as it can provide biomarker evidence of functional decline in AD. Methods: ADL were evaluated with the Technology–Activities of Daily Living Questionnaire (T-ADLQ) in 33 patients with AD and 30 controls. ADL were divided in BADL, IADL, and a-ADL. The three domain subscores were covaried against gray matter atrophy via voxel-based morphometry. Results: Our results showed that three domain subscores of ADL correlate with several brain structures, with a varying degree of overlap between them. BADL score correlated mostly with frontal atrophy, IADL with more widespread frontal, temporal and occipital atrophy and a-ADL with occipital and temporal atrophy. Finally, ICT subscale was associated with atrophy in the precuneus. Conclusions: The association between ADL domains and neurodegeneration in AD follows a traceable neuropathological pathway which involves different neural networks. This the first evidence of ADL phenotypes in AD characterised by specific patterns of functional decline and well-defined neuropathological changes. The identification of such phenotypes can yield functional biomarkers for dementias such as AD. [ABSTRACT FROM AUTHOR]

The formation of the ophthalmic artery (OA) is a complex process with two different proposed embryological steps for its development. Several anatomical variants have been described. We present a very unusual origin of the ophthalmic artery from the basilar trunk, in a 45-year-old male with a history of pontine hemorrhagic stroke. MRI and CTA showed evidence of previous hemorrhage in the pons and several intracranial arterial dysplastic dilatations. DSA confirmed several fusiform dilatations of the basilar trunk. In the left ICA, no ophthalmic artery was seen arising from the carotid siphon. The left ophthalmic artery arises from the basilar trunk and runs lateral to the cavernous sinus through the middle cranial fossa, entering the left orbit at the superior orbital fissure. The patient was treated conservatively. Two main theories for this anomaly are known, one from Lasjaunias and the other from Paget. To our knowledge, this basilar origin of the OA has only been described three times in the literature. For its origin, we propose a partial persistence of the trigeminal artery together with a dominance of the dorsal ophthalmic artery. [ABSTRACT FROM AUTHOR]

A description of the X-ray instrument SIXE proposed for the MINISAT-02 mission is presented. The description includes the scientific goals and instrument performances. [ABSTRACT FROM AUTHOR]