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In the context of the internet of things, and particularly within distributed measurement systems that are subject to high privacy risks, it is essential to emphasize the need for increasingly effective privacy protections. The idea presented in this work involves managing critical traffic through an architectural proposal aimed at solving the problem of communications between nodes by optimizing both the confidentiality to be guaranteed to the payload and the transmission speed. Specifically, data such as a typical sensor on/off signal could be sent via a standard encrypted channel, while a sensitive aggregate could be transmitted through a dedicated private channel. Additionally, this work emphasizes the critical importance of optimizing message sizes to 5 k-bytes (small payload messages) for transmission over the reserve channel, enhancing both privacy and system responsiveness, a mandatory requirement in distributed measurement systems. By focusing on small, encrypted payloads, the study facilitates secure, timely updates and summaries of network conditions, maintaining the integrity and privacy of communications in even the most challenging and privacy-sensitive environments. This study provides a comprehensive performance analysis of IoT networks using Dark Net technologies and MQTT protocols, with a focus on privacy and anonymity. It highlights the trade-offs between enhanced security and performance, noting increased latency, reduced bandwidth, and network instability when using TOR, particularly with cipher suites like AES256-GCM-SHA384 and DHE-RSA-CHACHA20-POLY1305. The research emphasizes the need for further exploration of alternative protocols like LWM2M in secure IoT environments and calls for optimization to balance privacy with performance in Dark-Net-based IoT deployments.

Since 2013, the olive landscapes have gradually degenerated due to the spread and establishment of Xylella fastidiosa subsp. pauca (hereafter Xf) in Apulia, southern Italy. From 2013 to 2019, a total of approximately 54,000 hectares of olive orchards in the south of this region have been seriously damaged, and their restoration will progressively regenerate the economic, social, cultural and environmental nonmarket benefits. Since there is a willingness to restore the affected landscape in the best interest of the local citizens, this research aims to predict their preference heterogeneity and willingness to pay (WTP) to improve this landscape and continue research and experimentation in relation to Olive Quick Decline Syndrome Disease by the bacterium. For this purpose, a choice experiment method is used. The social field survey includes a representative sample of 683 respondents in three major cities (Foggia, Bari and Lecce) of Apulia region. The results reveal that for the local citizens interviewed, the most appreciated olive landscape services are cultural heritage and aesthetic values. In addition, the findings revealed citizens’ positive appreciation of improving the damaged olive landscape, while respondents are not willing to pay a premium for research. The results show that the average value that Apulians are willing to pay for landscape restoration is about 5.7 million of € per year. Further, this research has implications for land use planners in the study area, which faces issues of harmful pathogen management and land revival.

The analysis of immunosuppressive drugs allows the physician to monitor, and eventually correct, immunosuppressive therapy. The panel of molecules under evaluation includes cyclosporine A (CsA), tacrolimus, sirolimus, and everolimus. Initially, assays were performed by immunometric methods, but in the past few years this methodology has been largely superseded by a more accurate and specific technique, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), which is now considered the “gold standard” for immunosuppressant analysis. Both LC-MS/MS and often also immunoassays require a preanalytical manual sample preparation, which involves time-consuming sequential operations whose traceability is often hampered and adds up to the probability of gross errors. The aim of this work was to compare an “open” LC-MS/MS with a fully automated system, consisting of LC instrumentation combined with a triple quadrupole MS, named Thermo ScientificTM CascadionTM SM Clinical Analyzer (Cascadion). Such automated systems suit the requirements of the reference method and are designed to completely eliminate all of the manual procedures. More than 2000 immunosuppressant samples were analyzed both with the open LC-MS/MS and with Cascadion. Statistics allowed the evaluation of linearity, intra- and inter-assay CV%, bias %, limit of detection and of quantitation, and Passing–Bablok and Bland–Altman plots. Results indicated a good correlation between the two methods. In both cases, methods confirmed their suitability for diagnostic settings. Cascadion could provide support when the presence of specialized personnel is lacking, and/or when great productivity and continuous workflow are required.

In modern building infrastructures, the chance to devise adaptive and unsupervised data-driven structural health monitoring (SHM) systems is gaining in popularity. This is due to the large availability of big data from low-cost sensors with communication capabilities and advanced modeling tools such as deep learning. A promising method suitable for smart SHM is the analysis of acoustic emissions (AEs), i.e., ultrasonic waves generated by internal ruptures of the concrete when it is stressed. The advantage in respect to traditional ultrasonic measurement methods is the absence of the emitter and the suitability to implement continuous monitoring. The main purpose of this paper is to combine deep neural networks with bidirectional long short term memory and advanced statistical analysis involving instantaneous frequency and spectral kurtosis to develop an accurate classification tool for tensile, shear and mixed modes originated from AE events (cracks). We investigated effective event descriptors to capture the unique characteristics from the different types of modes. Tests on experimental results confirm that this method achieves promising classification among different crack events and can impact on the design of the future of SHM technologies. This approach is effective to classify incipient damages with 92% of accuracy, which is advantageous to plan maintenance.

Human induced pluripotent stem cells (hiPSCs) have become indispensable for disease modelling. They are an important resource to access patient cells harbouring disease-causing mutations. Derivation of midbrain dopaminergic (DAergic) neurons from hiPSCs of PD patients represents the only option to model physiological processes in a cell type that is not otherwise accessible from human patients. However, differentiation does not produce a homogenous population of DA neurons and contaminant cell types may interfere with the readout of the in vitro system. Here, we use CRISPR/Cas9 to generate novel knock-in reporter lines for DA neurons, engineered with an endogenous fluorescent tyrosine hydroxylase – enhanced green fluorescent protein (TH-eGFP) reporter. We present a reproducible knock-in strategy combined with a highly specific homologous directed repair (HDR) screening approach using digital droplet PCR (ddPCR). The knock-in cell lines that we created show a functioning fluorescent reporter system for DA neurons that are identifiable by flow cytometry. Keywords: Human induced pluripotent stem cells, Dopaminergic neurons, CRISPR/Cas9, Knock-in, Digital droplet PCR, Fluorescent reporter, FACS

Chronic obstructive pulmonary disease (COPD) is characterized by long-term airflow limitation. Early-onset COPD in non-smoker subjects is ≥60 years and in the elderly is often associated with different comorbidities. Cognitive impairment is one of the most common feature in patients with COPD, and is associated with COPD severity and comorbidities. Cognitive impairment in COPD enhances the assistance requirement in different aspects of daily living, treatment adherence, and effectual self-management.This review describes various bioactive compounds of natural marine sources that modulate different targets shared by both COPD and cognitive impairment and hypothesizes a possible link between these two syndromes.

Metabolic disorder has been frequently observed in chronic obstructive pulmonary disease (COPD) patients. However, the exact correlation between obesity, which is a complex metabolic disorder, and COPD remains controversial. The current study summarizes a variety of drugs from marine sources that have anti-obesity effects and proposed potential mechanisms by which lung function can be modulated with the anti-obesity activity. Considering the similar mechanism, such as inflammation, shared between obesity and COPD, the study suggests that marine derivatives that act on the adipose tissues to reduce inflammation may provide beneficial therapeutic effects in COPD subjects with high body mass index (BMI).

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder. Current approved drugs may only ameliorate symptoms in a restricted number of patients and for a restricted period of time. Currently, there is a translational research challenge into identifying the new effective drugs and their respective new therapeutic targets in AD and other neurodegenerative disorders. In this review, selected examples of marine-derived compounds in neurodegeneration, specifically in AD field are reported. The emphasis has been done on compounds and their possible relevant biological activities. The proposed drug development paradigm and current hypotheses should be accurately investigated in the future of AD therapy directions although taking into account successful examples of such approach represented by Cytarabine, Trabectedin, Eribulin and Ziconotide. We review a complexity of the translational research for such a development of new therapies for AD. Bryostatin is a prominent candidate for the therapy of AD and other types of dementia in humans.