Optimization of an Impact-Based Frequency Up-Converted Piezoelectric Vibration Energy Harvester for Wearable Devices

This work presents a novel development of the impact-based mechanism for piezoelectric vibration energy harvesters. More precisely, the effect of an impacting mass on a cantilever piezoelectric transducer is studied both in terms of the tip mass value attached to the cantilever and impact position to find an optimal condition for power extraction. At first, the study is carried out by means of parametric analyses at varying tip mass and impact position on a unimorph MEMS cantilever, and a suitable physical interpretation of the associated electromechanical response is given. The effect of multiple impacts is also considered. From the analysis, it emerges that the most effective configuration, in terms of power output, is an impact at the cantilever tip without a tip mass. By changing the value of the tip mass, a sub-optimal impact position along the beam axis can also be identified. Moreover, the effect of a tip mass is deleterious on the power performance, contrary to the well-known case of a resonant energy harvester. A mesoscale prototype with a bimorph transducer is fabricated and tested to validate the computational models. The comparison shows a good agreement between numerical models and the experiments. The proposed approach is promising in the field of consumer electronics, such as wearable devices, in which the impact-based device moves at the frequencies of human movement and is much lower than those of microsystems

Battery modeling for microgrid design: A comparison between lithium-ion and lead acid technologies

Battery energy storage systems are fundamental components in microgrids operations, therefore it is important to adopt models suitable to properly evaluate the performance of these electrical systems. Different methodologies for battery modeling have been developed and tested in this work: (i) Empirical model, in which batteries are described by analytic expressions not based on electrochemical processes; (ii) Equivalent electrical circuit model, in which batteries are described in terms of electrical quantities. These approaches allow to adapt the model to different battery technologies: both the emerging Li-ion and the consolidated lead acid are considered in this paper. The proposed models are implemented in the software Poli. NRG, a Matlab based procedure for microgrid sizing developed by Energy Department of Politecnico di Milano. Simulations are based on a real case study relevant to a microgrid in a rural area: Ngarenanyuki Secondary School in Tanzania. The proposed methodology is used to design a new microgrid based on photovoltaic and energy storage system, comparing the results obtained adopting different modeling approaches and different technologies. Eventually, results are critically analyzed and discussed in order to compare accuracy, computational effort, costs and opportunities

Large mediastinal mass of heterotopic thyroid tissue: a case report and review of literature

Salvatore. Incidental detection of a mediastinal mass in a asymptomatic patient poses a not easy diagnostic problem. For solid masses or cysts, histology or cytology is often necessary. Although substernal extension of a cervical goiter is common, totally intrathoracic primary thyroidal mass is unusual. We describe a rare case of heterotopic accessory mediastinal thyroid in a patient completely asymptomatic both for signs of thyroid dysfunction and mechanical compression. Radiological and hormonal 6 and 12 months follow-up is reported

Differential responses of zooplankton assemblages to environmental variation in temporary and permanent ponds

Permanent and temporary wetlands in Mediterranean shrublands represent unique repositories of biodiversity, which are increasingly threatened by human-induced habitat loss. The zooplankton of a permanent (P1) and a temporary pond (T35) in the Natural Reserve of Castelporziano, a rare residual stretch of such a shrubland in Central Italy (Latium), was investigated to: (1) expand and deepen knowledge of these endangered freshwater habitats, which represent a crucial component of Mediterranean biodiversity; (2) identify environmental controls regulating the development of zooplankton communities of each environment; and (3) highlight differences in the adaptive responses of the zooplankton community in relation to the different ecological conditions experienced by permanent and temporary habitats. Despite summer desiccation in T35, the two ponds exhibited a relative homogeneity in hydrological and physico-chemical dynamics. Zooplankton assemblages contained 41 total taxa, of which 32 were found in P1 and 28 in T35. Out of the 41 taxa identified, 22 (> 50%) were exclusively present in one of the two ponds. On a yearly basis, the community dynamics of P1 seemed to be conditioned by physical and chemical factors and by hydrological cycle characteristics, while the community of T35 responded to algal blooms, food competition and predator/prey equilibria rather than correlating to abiotic factors. The main differences amongst zooplankton assemblages were observed over short time scales and occurred both within and between seasons, highlighting the role of some structural taxa that dominated the average composition of the community throughout the year, and the importance of "quick-response" taxa in determining the short-term composition and structure variation of pond zooplankton. A year-round cyclic community succession peculiar to each pond is described

Social cognition in people with schizophrenia: A cluster-analytic approach

Background The study aimed to subtype patients with schizophrenia on the basis of social cognition (SC), and to identify cut-offs that best discriminate among subtypes in 809 out-patients recruited in the context of the Italian Network for Research on Psychoses. Method A two-step cluster analysis of The Awareness of Social Inference Test (TASIT), the Facial Emotion Identification Test and Mayer-Salovey-Caruso Emotional Intelligence Test scores was performed. Classification and regression tree analysis was used to identify the cut-offs of variables that best discriminated among clusters. Results We identified three clusters, characterized by unimpaired (42%), impaired (50.4%) and very impaired (7.5%) SC. Three theory-of-mind domains were more important for the cluster definition as compared with emotion perception and emotional intelligence. Patients more able to understand simple sarcasm (14 for TASIT-SS) were very likely to belong to the unimpaired SC cluster. Compared with patients in the impaired SC cluster, those in the very impaired SC cluster performed significantly worse in lie scenes (TASIT-LI <10), but not in simple sarcasm. Moreover, functioning, neurocognition, disorganization and SC had a linear relationship across the three clusters, while positive symptoms were significantly lower in patients with unimpaired SC as compared with patients with impaired and very impaired SC. On the other hand, negative symptoms were highest in patients with impaired levels of SC. Conclusions If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person

Insight in cognitive impairment assessed with the Cognitive Assessment Interview in a large sample of patients with schizophrenia

The Cognitive Assessment Interview (CAI) is an interview-based scale measuring cognitive impairment and its impact on functioning in subjects with schizophrenia (SCZ). The present study aimed at assessing, in a large sample of SCZ (n = 601), the agreement between patients and their informants on CAI ratings, to explore patients' insight in their cognitive deficits and its relationships with clinical and functional indices. Agreement between patient- and informant-based ratings was assessed by the Gwet's agreement coefficient. Predictors of insight in cognitive deficits were explored by stepwise multiple regression analyses. Patients reported lower severity of cognitive impairment vs. informants. A substantial to almost perfect agreement was observed between patients' and informants' ratings. Lower insight in cognitive deficits was associated to greater severity of neurocognitive impairment and positive symptoms, lower severity of depressive symptoms, and older age. Worse real-life functioning was associated to lower insight in cognitive deficit, worse neurocognitive performance, and worse functional capacity. Our findings indicate that the CAI is a valid co-primary measure with the interview to patients providing a reliable assessment of their cognitive deficits. In the absence of informants with good knowledge of the subject, the interview to the patient may represent a valid alternative

Clinical Features, Cardiovascular Risk Profile, and Therapeutic Trajectories of Patients with Type 2 Diabetes Candidate for Oral Semaglutide Therapy in the Italian Specialist Care

Introduction: This study aimed to address therapeutic inertia in the management of type 2 diabetes (T2D) by investigating the potential of early treatment with oral semaglutide. Methods: A cross-sectional survey was conducted between October 2021 and April 2022 among specialists treating individuals with T2D. A scientific committee designed a data collection form covering demographics, cardiovascular risk, glucose control metrics, ongoing therapies, and physician judgments on treatment appropriateness. Participants completed anonymous patient questionnaires reflecting routine clinical encounters. The preferred therapeutic regimen for each patient was also identified. Results: The analysis was conducted on 4449 patients initiating oral semaglutide. The population had a relatively short disease duration (42%  60% of patients, and more often than sitagliptin or empagliflozin. Conclusion: The study supports the potential of early implementation of oral semaglutide as a strategy to overcome therapeutic inertia and enhance T2D management

The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients

Improving real-life functioning is the main goal of the most advanced integrated treatment programs in people with schizophrenia. The Italian Network for Research on Psychoses previously explored, by using network analysis, the interplay among illness-related variables, personal resources, context-related factors and real-life functioning in a large sample of patients with schizophrenia. The same research network has now completed a 4-year follow-up of the original sample. In the present study, we used network analysis to test whether the pattern of relationships among all variables investigated at baseline was similar at follow-up. In addition, we compared the network structure of patients who were classified as recovered at follow-up versus those who did not recover. Six hundred eighteen subjects recruited at baseline could be assessed in the follow-up study. The network structure did not change significantly from baseline to follow-up, and the overall strength of the connections among variables increased slightly, but not significantly. Functional capacity and everyday life skills had a high betweenness and closeness in the network at follow-up, as they had at baseline, while psychopathological variables remained more peripheral. The network structure and connectivity of non-recovered patients were similar to those observed in the whole sample, but very different from those in recovered subjects, in which we found few connections only. These data strongly suggest that tightly coupled symptoms/dysfunctions tend to maintain each other's activation, contributing to poor outcome in schizophrenia. Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms and dysfunctions in people with schizophrenia

The association between insight and depressive symptoms in schizophrenia: Undirected and Bayesian network analyses

Background. Greater levels of insight may be linked with depressive symptoms among patients with schizophrenia, however, it would be useful to characterize this association at symptom-level, in order to inform research on interventions. Methods. Data on depressive symptoms (Calgary Depression Scale for Schizophrenia) and insight (G12 item from the Positive and Negative Syndrome Scale) were obtained from 921 community-dwelling, clinically-stable individuals with a DSM-IV diagnosis of schizophrenia, recruited in a nationwide multicenter study. Network analysis was used to explore the most relevant connections between insight and depressive symptoms, including potential confounders in the model (neurocognitive and social-cognitive functioning, positive, negative and disorganization symptoms, extrapyramidal symptoms, hostility, internalized stigma, and perceived discrimination). Bayesian network analysis was used to estimate a directed acyclic graph (DAG) while investigating the most likely direction of the putative causal association between insight and depression. Results. After adjusting for confounders, better levels of insight were associated with greater self-depreciation, pathological guilt, morning depression and suicidal ideation. No difference in global network structure was detected for socioeconomic status, service engagement or illness severity. The DAG confirmed the presence of an association between greater insight and self-depreciation, suggesting the more probable causal direction was from insight to depressive symptoms. Conclusions. In schizophrenia, better levels of insight may cause self-depreciation and, possibly, other depressive symptoms. Person-centered and narrative psychotherapeutic approaches may be particularly fit to improve patient insight without dampening self-esteem

The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients

Improving real-life functioning is the main goal of the most advanced integrated treatment programs in people with schizophrenia. The Italian Network for Research on Psychoses previously explored, by using network analysis, the interplay among illness-related variables, personal resources, context-related factors and real-life functioning in a large sample of patients with schizophrenia. The same research network has now completed a 4-year follow-up of the original sample. In the present study, we used network analysis to test whether the pattern of relationships among all variables investigated at baseline was similar at follow-up. In addition, we compared the network structure of patients who were classified as recovered at follow-up versus those who did not recover. Six hundred eighteen subjects recruited at baseline could be assessed in the follow-up study. The network structure did not change significantly from baseline to follow-up, and the overall strength of the connections among variables increased slightly, but not significantly. Functional capacity and everyday life skills had a high betweenness and closeness in the network at follow-up, as they had at baseline, while psychopathological variables remained more peripheral. The network structure and connectivity of non-recovered patients were similar to those observed in the whole sample, but very different from those in recovered subjects, in which we found few connections only. These data strongly suggest that tightly coupled symptoms/dysfunctions tend to maintain each other's activation, contributing to poor outcome in schizophrenia. Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms and dysfunctions in people with schizophrenia