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Throughout Mycobacterium leprae's (M. leprae) evolutionary trajectory, nearly half of its genome was converted into pseudogenes. Despite this drastic reduction in genetic content, the genome sequence identity among M. leprae isolates worldwide is remarkably high compared to other pathogens. In this study, we investigated the genotype and morphotype of three M. leprae strains: the reference strain Thai-53 (genotype 1A), and two clinical isolates from Brazilian leprosy relapse patients, which were Br014-03 (genotypes 3I) and Br014-01(4N). We compared their genome sequences and their interaction with human Schwann cells from the ST88-14 lineage and with human primary macrophages. On the genetic level, we observed over a hundred missense mutations in the three strains, translated into significant phenotypic changes such as: prolonged doubling time, altered cytokine induction, reduced interaction rates, and decreased intracellular viability in Schwann cells. Our findings underscore the concept that despite their 99.992% identity, even small genomic disparities in M. leprae genomes can elicit substantial alterations in bacilli interaction with host cells and subsequent immune responses. Consequently, our data could lead to better comprehension of correlation between pathogen mutations and the diverse clinical manifestations observed in leprosy patients. [ABSTRACT FROM AUTHOR]

Background: Parkinson's Disease significantly impacts health-related quality of life, with the Parkinson's Disease Questionnaire-39 extensively used for its assessment. However, predicting such outcomes remains a challenge due to the subjective nature and variability in patient experiences. This study develops a machine learning model using accessible clinical data to enable predictions of life-quality outcomes in Parkinson's Disease and utilizes explainable machine learning techniques to identify key influencing factors, offering actionable insights for clinicians. Methods: Data from the Parkinson's Real-world Impact Assessment study (PRISM), involving 861 patients across six European countries, were analyzed. After excluding incomplete data, 627 complete observations were used for the analysis. An ensemble machine learning model was developed with a 90% training and 10% validation split. Results: The model demonstrated a Mean Absolute Error of 4.82, a Root Mean Squared Error of 8.09, and an R2 of 0.75 in the training set, indicating a strong model fit. In the validation set, the model achieved a Mean Absolute Error of 11.22, a Root Mean Squared Error of 13.99, and an R2 of 0.36, showcasing moderate variation. Key predictors such as age at diagnosis, patient's country, dementia, and patient's age were identified, providing insights into the model's decision-making process. Conclusions: This study presents a robust model capable of predicting the impact of Parkinson's Disease on patients' quality of life using common clinical variables. These results demonstrate the potential of machine learning to enhance clinical decision-making and patient care, suggesting directions for future research to improve model generalizability and applicability. [ABSTRACT FROM AUTHOR]

Due to the similar characteristics of chaotic systems and cryptography, public key encryption algorithms based on chaotic systems are worth in-depth research and have high value for the future. Chebyshev polynomials have good properties and are often used in the design of public key algorithms. This paper improves the Bose Multi-Chaotic Public Key Cryptographic Algorithm (BMPKC) by applying Chebyshev polynomials. The proposed algorithm (CMPKC- k i ) introduces the selective coefficient k i based on the properties of Chebyshev polynomials, allowing the special functions that need to be negotiated in the original system to be freely and randomly chosen as Chebyshev polynomials, and can also be expanded to m levels. The improved cryptographic algorithm also utilizes chaotic hash functions and logistic mapping to generate pseudo-random sequences and overcomes shortcomings of the Bose algorithm by iteratively iterating the selected Chebyshev polynomials based on the number of 0s or 1s in the pseudo-random sequence, thus providing better security. Analysis and software testing results indicate that this algorithm has strong robustness against brute force attacks, achieving a higher attack time for breaking the private key compared to the CEPKC, BMPKC, and CMPKC algorithms. Compared to the CMPKC algorithm, our proposal algorithm achieves better performance in the encryption and decryption phases. Furthermore, we combine this Multi-Chaotic System Key Exchange Protocol with the Advanced Encryption Standard (AES) algorithm, while providing a demonstration, offering more possibilities for practical applications of this system. [ABSTRACT FROM AUTHOR]

The aims of this study were to assess the impact of exclusive breastfeeding up to 6 months of age on reducing the incidence of overweight and obesity in children up to 10 years of age and to estimate the annual incidence of obesity and overweight in the study population. Our retrospective cohort analysis using electronic health records included children from zero to ten years old, born between 1 January 2006 and 31 December 2022, followed up at the Unidade Local de Saúde de Matosinhos (ULSM). Information on their comorbidity history was collected, and positive or negative control results were defined. In the first year of life, around 29% of the children on exclusive breastfeeding were obese and 20% were overweight. This trend was reversed by the age of 9. Asthma and allergic rhinitis were used as positive control outcomes and allergic dermatitis as a negative control outcome. There seems to be no relationship between exclusive and non-exclusive breastfeeding and the development of overweight or obesity at the age of 10. The results showed that breastfeeding is associated with a lower risk of asthma in the future. [ABSTRACT FROM AUTHOR]

In the evolving landscape of autonomous driving technology, Light Detection and Ranging (LiDAR) sensors have emerged as a pivotal instrument for enhancing environmental perception. They can offer precise, high-resolution, real-time 3D representations around a vehicle, and the ability for long-range measurements under low-light conditions. However, these advantages come at the cost of the large volume of data generated by the sensor, leading to several challenges in transmission, processing, and storage operations, which can be currently mitigated by employing data compression techniques to the point cloud. This article presents a survey of existing methods used to compress point cloud data for automotive LiDAR sensors. It presents a comprehensive taxonomy that categorizes these approaches into four main groups, comparing and discussing them across several important metrics. [ABSTRACT FROM AUTHOR]

Due to its very desirable properties, Chebyshev polynomials are often used in the design of public key cryptographic systems. This paper discretizes the Chebyshev mapping, generalizes the properties of Chebyshev polynomials, and proposes an improved public key encryption algorithm based on Chebyshev chaotic mapping and RSA, i.e., C R P K C − K i . This algorithm introduces alternative multiplication coefficients K i , the selection of which is determined by the size of T r T d x m o d   N = T d T r x m o d   N , and the specific value selection rules are shared secrets among participants, overcoming the shortcomings of previous schemes. In the key generation and encryption/decryption stages, more complex intermediate processes are used to achieve higher algorithm complexity, making the algorithm more robust against ordinary attacks. The algorithm is also compared with other RSA-based algorithms to demonstrate its effectiveness in terms of performance and security. [ABSTRACT FROM AUTHOR]

Evaluating the efficiency of surface treatments is a problem of paramount importance for the cork stopper industry. Generically, these treatments create coatings that aim to enhance the impermeability and lubrification of cork stoppers. Yet, current methods of surface analysis are typically time-consuming, destructive, have poor representativity or rely on indirect approaches. In this work, the use of a laser-induced breakdown spectroscopy (LIBS) imaging solution is explored for evaluating the presence of coating along the cylindrical surface and in depth. To test it, several cork stoppers with different shaped areas of untreated surface were analyzed by LIBS, making a rectangular grid of spots with multiple shots per spot, to try to identify the correspondent shape. Results show that this technique can detect the untreated area along with other features, such as leakage and holes, allowing for a high success rate of identification and for its performance at different depths, paving the way for future industry-grade quality control solutions with more complex surface analysis. [ABSTRACT FROM AUTHOR]

Older adult maltreatment (OAM) is a global problem that has attracted increasing attention due to the ageing population and its severe impact on victim health. Thus, this study aims to analyse the prevalence of certain health conditions in people ≥ 60 years old whom physicians from a local healthcare unit suspected to be victims of maltreatment. The specific objectives are to determine the prevalence rates of health-related risk factors, traumatic injuries and intoxications, mental disorders, and physical disorders. We conducted a real-world, retrospective, observational, and cross-sectional study based on secondary data analyses of electronic health records and healthcare registers of patients at the Local Healthcare Unit of Matosinhos (2001–2021). Information was obtained based on codes from the International Classification of Diseases, codes from the International Classification of Primary Care, and clinical notes (according to previously defined keywords). We identified 3092 suspected victims of OAM, representing 4.5% of the total population analysed. This prevalence is lower than the known rates. We also found that some health risk factors, traumatic injuries and intoxications, mental health disorders, and physical disorders presented higher rates in the suspected victims than among the total population. In this age group, we cannot assume that these health problems are only related to a possible current victimisation process; they could also be associated with adverse childhood experiences or intimate partner violence, among other forms of violence, all of which can lead to cumulative effects on the victim's health. This evidence increases healthcare providers' responsibility in detecting and reporting all cases of suspected maltreatment. [ABSTRACT FROM AUTHOR]

In the highly competitive injection molding industry, the ability to effectively collect information from various sensors installed in molds and machines is of the utmost relevance, enabling the development of data-based Industry 4.0 algorithms. In this work, an alternative to commercially available monitoring systems used in the industry was developed and tested in the scope of the TOOLING 4G project. The novelty of this system is its affordability, simplicity, real-time data acquisition and display in an intuitive Graphical User Interface (GUI), while being open-source firmware and software-based. These characteristics, and their combinations have been present in previous works, but, to the authors' knowledge, not all of them simultaneously. The system used an Arduino microcontroller-based data acquisition module that can be connected to any computer via a USB port. Software was developed, including a GUI, prepared to receive data from both the Arduino module and a second module. In the current state of development, data corresponding to a maximum of six sensors can be visualized, at a rate of 10 Hz, and recorded for later usage. These capabilities were verified under real-world conditions for monitoring an injection mold with the objective of creating the basis of a platform to deploy predictive maintenance. Mold temperature, cavity pressure, 3-axis acceleration, and extraction force data showed the system can successfully monitor the mold and allowed the clear distinction between normal and abnormal operating patterns. [ABSTRACT FROM AUTHOR]

Injury outcomes seem to be more severe in older than younger persons. This may make personal injury assessment (PIA) particularly difficult, mainly because of seniors' previous health frailties. To set the grounds for seniors' PIA guidelines, we compared an older with a younger adult population of trauma victims and, secondarily, identified differences between the groups regarding three-dimensional and medico-legal damage parameters assessment. Using a retrospective study of victims of road traffic accidents, we compared the groups (n = 239 each), assuring similar acute injury severity (ISS standardised difference = 0.01): G1 (older adults); G2 (younger adults). Logistic regression was used to estimate the odds ratio. G1 revealed higher negative consequences when considering the three-dimensional damage assessment, with more frequent and severe outcomes, being a cause of further difficulties in daily living activities, with a loss of independence and autonomy. Nevertheless, regarding the medico-legal damage parameters, permanent functional disability did not show significant differences. This study generates evidence that reveals the need to rethink the traditional methodology of PIA in older persons, giving more relevance to the real-life contexts of each person. It is essential to: obtain complete information about previous physiologic and health states, begin the medico-legal assessment as early as possible, make regular follow-ups, and perform a multidisciplinary evaluation. [ABSTRACT FROM AUTHOR]

The world is facing a great technological transformation towards fully autonomous vehicles, where optimists predict that by 2030 autonomous vehicles will be sufficiently reliable, affordable, and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all their surroundings, with light detection and ranging (LiDAR) sensors being a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely on accurate measurements of the environment. Thus, these intelligent sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors, with the main goal of testing both commercially available sensors and new sensor prototypes currently under development in Bosch Car Multimedia Portugal. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment in which such devices normally operate. To characterize and validate the sensor under test, the platform evaluates several parameters, such as the field of view (FoV), angular resolution, sensor's range, etc., based only on the point cloud output. This project is the result of a partnership between the University of Minho and Bosch Car Multimedia Portugal. [ABSTRACT FROM AUTHOR]

In the new Internet of Things (IoT) era, embedded Field-Programmable Gate Array (FPGA) technology is enabling the deployment of custom-tailored embedded IoT solutions for handling different application requirements and workloads. Combined with the open RISC-V Instruction Set Architecture (ISA), the FPGA technology provides endless opportunities to create reconfigurable IoT devices with different accelerators and coprocessors tightly and loosely coupled with the processor. When connecting IoT devices to the Internet, secure communications and data exchange are major concerns. However, adding security features requires extra capabilities from the already resource-constrained IoT devices. This article presents the FAC-V coprocessor, which is an FPGA-based solution for an RISC-V processor that can be deployed following two different coupling styles. FAC-V implements in hardware the Advanced Encryption Standard (AES), one of the most widely used cryptographic algorithms in IoT low-end devices, at the cost of few FPGA resources. The conducted experiments demonstrate that FAC-V can achieve performance improvements of several orders of magnitude when compared to the software-only AES implementation; e.g., encrypting a message of 16 bytes with AES-256 can reach a performance gain of around 8000× with an energy consumption of 0.1 μ J. [ABSTRACT FROM AUTHOR]

The rising prevalence of cardiovascular (CV) risk factors in Portugal has translated into more than 35,000 annual deaths due to CV diseases. We performed a multicenter observational cohort study encompassing clinical activities performed between 2000 and 2019 to characterize the CV risk profile and LDL-C management of patients in every CV risk category using electronic health records of a regional population in Portugal. We analyzed data from 14 health centers and 1 central hospital in the north of Portugal of patients between 40 and 80 years that had at least 1 family medicine appointment at these institutions. Living patients were characterized on 31 December 2019. CV risk assessment was computed according to the 2019 ESC/EAS Guidelines. Lipid-lowering therapy (LLT) and achievement of LDL-C targets were assessed. In total, the analysis included 78,459 patients. Patient proportions were 33%, 29%, 22%, and 17% for low, intermediate, high, and very high CV risk, respectively. Moderate-intensity statins were the most frequently used medication across all CV risk categories. High-intensity statins were used in 5% and 10% of high and very high CV risk patients, respectively. Ezetimibe was used in 6% and 10% of high and very high CV risk patients, respectively. LDL-C targets were achieved in 44%, 27%, 7%, and 3% of low, intermediate, high, and very high CV risk patients, respectively. For uncontrolled patients in the high and very high CV risk categories, a median LDL-C reduction of 44% and 53%, respectively, would be required to meet LDL-C targets. There are clear opportunities to optimize LDL-C management in routine clinical practice. The prescription of LLT according to CV risk represents an important missed treatment opportunity. [ABSTRACT FROM AUTHOR]

Simple Summary: Transposable elements are capable of promoting somatic mobilization, and this may potentially have biological consequences. However, the rate of somatic mobilization is poorly known. The mariner element causes somatic mobilization in Drosophila simulans. We used an assay based on sequencing of the flanking mariner region and developed a pipeline to identify new mariner insertions in D. simulans. We found that flies carrying two mariner copies (one autonomous and one non-autonomous) had approximately 300 new somatic insertions during fly development (eggs to adult). We show that the rate of somatic insertion of the mariner element in D. simulans is high. Although transposable elements (TEs) are usually silent in somatic tissues, they are sometimes mobilized in the soma and can potentially have biological consequences. The mariner element is one of the TEs involved in somatic mobilization (SM) in Drosophila and has a high rate of somatic excision. It is also known that temperature is an important factor in the increase of the mariner element SM in the fly. However, it is important to emphasize that excision is only one step of TE transposition, and the final step in this process is insertion. In the present study, we used an assay based on sequencing of the mariner flanking region and developed a pipeline to identify novel mariner insertions in Drosophila simulans at 20 and 28 °C. We found that flies carrying two mariner copies (one autonomous and one non-autonomous) had an average of 236.4 (±99.3) to 279 (±107.7) new somatic insertions at 20 °C and an average of 172.7 (±95.3) to 252.6 (±67.3) at 28 °C. In addition, we detected fragments containing mariner and others without mariner in the same regions with low-coverage long-read sequencing, indicating the process of excision and insertion. In conclusion, a low number of autonomous copies of the mariner transposon can promote a high rate of new somatic insertions during the developmental stages of Drosophila. Additionally, the developed method seems to be sensitive and adequate for the verification and estimation of somatic insertion. [ABSTRACT FROM AUTHOR]

Introduction: Type 2 diabetes mellitus (T2D) increases the risk of heart failure (HF) and chronic kidney disease (CKD). Nonetheless, evidence of cardiovascular (CV) prognosis is relatively scarce in young T2D patients. Purpose: To estimate the risk of all-cause death, CV death, and non-fatal major CV events (MACEs) in T2D patients younger than 65 years old. Methods: We designed a retrospective cohort study using incident cases of either T2D, HF, or CKD in the population aged 40–65 years, from 1st January 2000 to 31st December 2019. Each individual was followed for up to one year. The primary analysis consisted of survival analysis with Cox proportional hazards to compare one-year risk of all-cause death, CV death, and MACEs between T2D without HF or CKD (T2D), T2D with HF (T2D-HF), and T2D with CKD (T2D-CKD) groups. Results: A total of 14,986 incident adult diabetic patients from the last two decades in our institution were included with an average age at cohort inclusion of 55–58 years old. Glycemic control was similar among groups. The adjusted hazard ratio (HR) of one-year all-cause death was 2.77 (95% CI: 2.26–3.40) for T2D-HF and 3.09 (2.77–3.45) for T2D-CKD compared with the baseline T2D risk. The highest event rate (T2D-CKD) was 0.15 per person-year. The adjusted HR of one-year CV death was 2.75 (95% CI: 2.19–3.46) for T2D-CKD and 2.59 (1.72–3.91) for T2D-HF. The non-fatal MACE risk was significantly increased in T2D-HF or T2D-CKD compared with T2D (2.82 (CI95%: 2.34–3.41) for T2D-CKD vs. 1.90 (CI95%: 1.66–2.17) for T2D-CKD) with a 32% event rate in non-fatal MACEs. Conclusions: Coexistence of HF or CKD is associated with increased premature mortality as well as non-fatal CV events in T2D patients under 65 years old. [ABSTRACT FROM AUTHOR]

As additive manufacturing (AM) technologies have been gaining popularity in the plastic processing sector, it has become a major concern to establish closed-loop recycling strategies to maximize the value of the materials processed, therefore enhancing their sustainability. However, there are challenges to overcome related to the performance of recycled materials since, after mechanical recycling, the molecular degradation of thermoplastics shifts their performance and processability. In this work, it was hypothesized that the incorporation of a chain extender (CE) during the reprocessing would allow us to overcome these drawbacks. To attest this conjecture, the influence of 1,3-Bis(4,5-dihydro-2-oxazolyl)benzene (PBO), used as a CE, on mechanical, thermal, and rheological properties of polilactic acid (PLA) was studied. Furthermore, a closed-loop recycling system based on Fused Filament Fabrication (FFF) was attempted, consisting of the material preparation, filament extrusion, production of 3D components, and mechanical recycling steps. PBO partially recovered the recycled PLA mechanical performance, reflected by an increase in both tensile modulus (+13%) and tensile strength (+121%), when compared with recycled PLA without PBO. Printability tests were conducted, with the material's brittle behavior being the major constraint for successfully establishing a closed-loop recycling scheme for FFF applications. [ABSTRACT FROM AUTHOR]

With the current technological transformation in the automotive industry, autonomous vehicles are getting closer to the Society of Automative Engineers (SAE) automation level 5. This level corresponds to the full vehicle automation, where the driving system autonomously monitors and navigates the environment. With SAE-level 5, the concept of a Shared Autonomous Vehicle (SAV) will soon become a reality and mainstream. The main purpose of an SAV is to allow unrelated passengers to share an autonomous vehicle without a driver/moderator inside the shared space. However, to ensure their safety and well-being until they reach their final destination, active monitoring of all passengers is required. In this context, this article presents a microphone-based sensor system that is able to localize sound events inside an SAV. The solution is composed of a Micro-Electro-Mechanical System (MEMS) microphone array with a circular geometry connected to an embedded processing platform that resorts to Field-Programmable Gate Array (FPGA) technology to successfully process in the hardware the sound localization algorithms. [ABSTRACT FROM AUTHOR]

Undeniably, the Internet of Things (IoT) ecosystem continues to evolve at a breakneck pace, exceeding all growth expectations and ubiquity barriers. From sensor to cloud, this giant network keeps breaking technological bounds in several domains, and wireless sensor nodes (motes) are expected to be predominant as the number of IoT devices grows towards the trillions. However, their future in the IoT ecosystem still seems foggy, where several challenges, such as (i) device's connectivity, (ii) intelligence at the edge, (iii) security and privacy concerns, and (iv) growing energy needs, keep pulling in opposite directions. This prospective paper offers a succinct and forward-looking review of recent trends, challenges, and state-of-the-art solutions of low-end IoT motes, where reconfigurable computing technology plays a key role in tomorrow's IoT devices. [ABSTRACT FROM AUTHOR]