Integrating Absolute Sustainability and Social Sustainability in the Digital Product Passport to Promote Industry 5.0

The establishment of the digital product passport is regarded to be a prominent tool to promote environmental and social sustainability, thus enabling the transition towards Industry 5.0. In this way, it represents a holistic tool for the decision-making process of several actors of a product’s value chain. However, its development is still ongoing and the absolute perspective of environmental sustainability and the social sustainability have been overlooked. The present work aims to fill these gaps and complement the literature currently available on the digital product passport with a threefold purpose. Firstly, by referring to social life cycle assessment methodologies, useful social indicators to include in the digital product passport are discussed and proposed. Secondly, the need for an absolute perspective of environmental sustainability that respects the natural limits of our planet is presented; based on the LCA methodology and the Planetary Boundaries framework, environmental attributes and environmental impact indicators with the corresponding threshold are proposed to be included in the passport and enable the so-called absolute environmental sustainability assessment of products. Finally, a framework based on a cyber-physical system for filling in the digital product passport throughout a product lifecycle is conceived. This work represents an example of how the hallmark technologies of Industry 4.0 can be used towards Industry 5.0

Are NSAIDs Useful to Treat Alzheimer's Disease or Mild Cognitive Impairment?

Several epidemiological studies suggest that long-term use of non-steroidal anti-inflammatory drugs (NSAIDs) may protect subjects carrying one or more ε4 allele of the apolipoprotein E (APOE ε4) against the onset of Alzheimer's disease (AD). The biological mechanism of this protection is not completely understood and may involve the anti-inflammatory properties of NSAIDs or their ability of interfering with the β-amyloid (Aβ) cascade. Unfortunately, long-term, placebo-controlled clinical trials with both non-selective and cyclooxygenase-2 (COX-2) selective inhibitors in mild-to-moderate AD patients produced negative results. A secondary prevention study with rofecoxib, a COX-2 selective inhibitor, in patients with mild cognitive impairment was also negative. A primary prevention study (ADAPT trial) of naproxen (a non-selective COX inhibitor) and celecoxib (a COX-2 selective inhibitor) in cognitively normal elderly subjects with a family history of AD was prematurely interrupted for safety reasons after a median period of treatment of 2 years. Although both drugs did not reduce the incidence of dementia after 2 years of treatment, a 4-year follow-up assessment surprisingly revealed that subjects previously exposed to naproxen were protected from the onset of AD by 67% compared to placebo. Thus, it could be hypothesized that the chronic use of NSAIDs may be beneficial only in the very early stages of the AD process in coincidence of initial Aβ deposition, microglia activation and consequent release of pro-inflammatory mediators. When the Aβ deposition process is already started, NSAIDs are no longer effective and may even be detrimental because of their inhibitory activity on chronically activated microglia that on long-term may mediate Aβ clearance. The research community should conduct long-term trials with NSAIDs in cognitively normal APOE ε4 carriers

Machine learning tool for the prediction of electrode wear effect on the quality of resistance spot welds

The quality of resistance spot welding (RSW) joints is strongly affected by the condition of the electrodes. This work develops a machine learning-based tool to automatically assess the influence of electrode wear on the quality of RSW welds. Two different experimental campaigns were performed to evaluate the effect of electrode wear on the mechanical strength of spot welds. The resulting failure load of the joints has been used to define the weld quality classes of the machine learning tool, while data from electrode displacement and electrode force sensors, embedded in the welding machine, have been processed to identify the predictors of the tool. Some machine learning algorithms have been tested. The most performing algorithm, i.e., the neural network, achieved an accuracy of 90%. This work provides important theoretical and practical contributions. First, the decreasing thermal expansion of the weld nugget as the electrode degradation advances results in a strong correlation between the difference of the maximum displacement value and the last value recorded during the welding and the relative failure load. Then, this work offers a practical decision support tool for manufacturers. In fact, the automatic detection of low-quality welds allows to reduce or eliminate unnecessary redundant welds, which are performed to compensate for the uncertainty of electrode wear. This leads to savings in time, energy, and resources for manufacturers. Finally, general recommendations for the timing of redressing or replacing the electrode are provided in the manuscript based on the company willingness to accept some non-compliant welds or not

Efficient management of industrial electric vehicles by means of static and dynamic wireless power transfer systems

Industrial companies are moving toward the electrification of equipment and processes, in line with the broader energy transition taking place across the economy. Particularly, the energy efficiency and, consequently, the reduction of environmental pollution of intralogistics activities have become a competitive element and are now an actual research and development objective. A wireless power transfer is a contactless electrical energy transmission technology based on the magnetic coupling between coils installable under the ground level and a coil mounted under the vehicle floor, and it represents an excellent solution to decrease the demand for batteries by reducing vehicle downtimes during the recharge. This work aims to define a methodology to determine the optimal positioning of wireless charging units across the warehouse, both for static and dynamic recharging. To this aim, firstly, a mathematical model of the warehouse is proposed to describe transfers and storage/retrieval operations executed by the forklifts. Then, an integer linear programming problem is applied to find the best possible layout of the charging infrastructures. The optimal solution respects the energetic requirements given by the customer and minimizes the overall system cost. The proposed approach was applied to optimize the installation in a real-size warehouse of a tire manufacturing company. Several scenarios were computer generated through discrete event simulation in order to test the optimizer in different warehouse conditions. The obtained results show that integrated dynamic and static WPT systems ensure a constant state of charge of the electric vehicles during their operations

Efficient management of industrial electric vehicles by means of static and dynamic wireless power transfer systems

Industrial companies are moving toward the electrification of equipment and processes, in line with the broader energy transition taking place across the economy. Particularly, the energy efficiency and, consequently, the reduction of environmental pollution of intralogistics activities have become a competitive element and are now an actual research and development objective. A wireless power transfer is a contactless electrical energy transmission technology based on the magnetic coupling between coils installable under the ground level and a coil mounted under the vehicle floor, and it represents an excellent solution to decrease the demand for batteries by reducing vehicle downtimes during the recharge. This work aims to define a methodology to determine the optimal positioning of wireless charging units across the warehouse, both for static and dynamic recharging. To this aim, firstly, a mathematical model of the warehouse is proposed to describe transfers and storage/retrieval operations executed by the forklifts. Then, an integer linear programming problem is applied to find the best possible layout of the charging infrastructures. The optimal solution respects the energetic requirements given by the customer and minimizes the overall system cost. The proposed approach was applied to optimize the installation in a real-size warehouse of a tire manufacturing company. Several scenarios were computer generated through discrete event simulation in order to test the optimizer in different warehouse conditions. The obtained results show that integrated dynamic and static WPT systems ensure a constant state of charge of the electric vehicles during their operations

Alternative pharmacological treatment options for agitation in Alzheimer's disease

In patients with dementia and Alzheimer's disease (AD), treatment of neuropsychiatric symptoms (NPS) is a major concern in the management of these devastating diseases. Among NPS in AD, agitation and aggression are common with earlier institutionalization, increased morbidity and mortality, and greater caregiver burden. Pharmacological treatments for AD-related agitation, specifically off-label use of atypical antipsychotics, showed only modest improvements, with increased side-effect burden and risk of mortality. Non-pharmacological treatment approaches have become the preferred firstline option. However, when such treatments fail, pharmacological options are often used. Therefore, there is an urgent need to identify effective and safe pharmacological treatments for agitation/aggression in AD and dementia. Unfortunately, progresses have been slow, with a small number of methodologically heterogeneous randomized controlled trials (RCTs), with disappointing results. However, evidence coming from recently completed RCTs on novel or repositioned drugs (mibampator, dextromethorphan/ quinidine, cannabinoids, and citalopram) showed some promise in treating agitation in AD, but still with safety concerns. Further evidence will come from ongoing Phase II and III trials on promising novel drugs for treating these distressing symptoms in patients with AD and dementia

Hybrid knowledge based system supporting Digital Twins in the Industry 5.0

Digital twins are employed to monitor, analyze, and predict the behavior of a manufacturing system. In literature, the concept of digital twin is mainly associated with simulation models, and only a few works addressed the integration between physics-based and data driven models. This work extends this definition and describes how different kinds of knowledge can be integrated in a hybrid knowledge based system supporting digital twin. Following the Industry 5.0 paradigm, the hybrid system can improve the human-centricity, sustainability, and resilience of a manufacturing system. The hybrid digital twin is structured as an enterprise information system, which can be connected to the other information systems of the company, such as ERP, MES, and PLM, as well as other platforms of total quality management and total productive maintenance. A discussion on the application of the proposed approach in fusion welding, as an example of a very complex process, is also presented

Efeito da dieta cetogênica na capacidade de endurance e na utilização de substratos energéticos no exercício

O objetivo desta revisão foi identificar e discutir evidências científicas sobre os efeitos da dieta cetogênica com severa restrição de carboidrato na capacidade de endurance e em metabólicas no exercício em indivíduos saudáveis. Realizou-se uma busca de artigos publicados entre os anos de 1975 e 2017, nas bases de dados MedLine, Scielo e Google acadêmico. Utilizou-se as palavras-chave: ketogenic diet, low-carbohydrate, high-fat diet, exercise, training, endurance, endurance capacity, performance, fuel oxidation, fat oxidation e metabolic adaptation. Foram selecionados 10 artigos, dentre os quais, nove demonstraram que a dieta cetogênica aumentou a taxa de oxidação de gordura e atenuou a taxa de utilização de glicogênio muscular durante o exercício. Contudo, oito estudos relataram efeitos negativos da dieta cetogênica em exercícios moderados ou intensos, relacionados principalmente ao tempo até a exaustão, à percepção de esforço, à produção de potência e à economia de exercício tanto em indivíduos treinados quanto em não treinados. Esta revisão concluiu que, independentemente do nível de treinamento, a dieta cetogênica ofertando <50 g de carboidrato por dia, embora possa induzir vantagens metabólicas, pode resultar em efeitos ergolíticos, quanto à capacidade de endurance, bem como a outros parâmetros de alto desempenho, onde a dependência de carboidrato é claramente predominante. ABSTRACTEffect of the ketogenic diet on exercise endurance capacity and fuel utilizationThe objective of this review was to identify and discuss scientific evidence on the effects of the ketogenic diet with severe carbohydrate restriction on endurance capacity and on metabolic responses during exercise in healthy individuals. A search of articles published between 1975 and 2017 was performed in the databases of MedLine, Scielo and Google Scholars. The following key words were used: ketogenic diet, low-carbohydrate, high-fat diet, exercise, training, endurance, endurance capacity, performance, fuel oxidation, fat oxidation, and metabolic adaptation. Ten articles were selected, of which nine showed that the ketogenic diet increased the rate of fat oxidation and attenuated the rate of glycogen utilization during exercise. However, eight studies reported negative effects of the ketogenic diet on moderate or intense exercises, mainly related to time to exhaustion, perception of effort, power output, and exercise economy both in trained and untrained subjects. This review concluded that, independently of training status, the ketogenic diet offering <50 g of carbohydrate per day, although it may induce metabolic advantages, may result in ergolytic effects on endurance capacity, as well as other high performance parameters, where the carbohydrate dependence is clearly predominant

Tau-Centric Targets and Drugs in Clinical Development for the Treatment of Alzheimer's Disease

The failure of several Phase II/III clinical trials in Alzheimer's disease (AD) with drugs targeting \u3b2-amyloid accumulation in the brain fuelled an increasing interest in alternative treatments against tau pathology, including approaches targeting tau phosphatases/kinases, active and passive immunization, and anti-tau aggregation. The most advanced tau aggregation inhibitor (TAI) is methylthioninium (MT), a drug existing in equilibrium between a reduced (leuco-methylthioninium) and oxidized form (MT+). MT chloride (methylene blue) was investigated in a 24-week Phase II clinical trial in 321 patients with mild to moderate AD that failed to show significant positive effects in mild AD patients, although long-term observations (50 weeks) and biomarker studies suggested possible benefit. The dose of 138 mg/day showed potential benefits on cognitive performance of moderately affected AD patients and cerebral blood flow in mildly affected patients. Further clinical evidence will come from the large ongoing Phase III trials for the treatment of AD and the behavioral variant of frontotemporal dementia on a new form of this TAI, more bioavailable and less toxic at higher doses, called TRx0237. More recently, inhibitors of tau acetylation are being actively pursued based on impressive results in animal studies obtained by salsalate, a clinically used derivative of salicylic acid