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This work presents a flexible method for the real-time estimation of human joint angles from magneto-inertial measurement technology. The method aims to enhance the accuracy and consistency of joint angle estimates by incorporating physiological joint limits and task-specific motor characteristics into the optimization process, thanks to a biomechanical model. As an explanatory example, the method was applied to shoulder and elbow joints during a prolonged writing task. The adopted upper limb model was designed following the International Society of Biomechanics guidelines and the Denavit-Hartenberg convention, ensuring anatomical relevance and computational efficiency. By comparing results with stereophotogrammetric tracking outputs, the application of constraints - leveraging a priori knowledge of the workspace boundaries for joint centers - enhanced the accuracy of shoulder and elbow angle estimations and effectively mitigated the impact of sensor orientation drift over extended periods. This method ensured that joint centers trajectories remain within task-specific workspace limits, thus preventing deviations that are not compatible with the expected kinematic behavior. The percentage decrease in the root mean square average errors amounted to about 13% in the time intervals when constraints were active, demonstrating the method’s effectiveness in reducing the errors. Computationally time-wise, joint angles were estimated with an update period of about 10 ms, allowing real-time usage. The proposed method can be easily generalized to different biomechanical models and to include information from complementary technologies, making it applicable across various contexts such as clinical assessments, rehabilitation, and ergonomics.

Abstract Background Diagnosis of acute otitis media (AOM) in children can be challenging, given that symptoms are often non-specific or absent, and that the direct observation of the tympanic membrane in its entirety through otoscopy can sometimes be difficult. The aim of this study is to assess the diagnostic concordance in detection of AOM episodes between primary care paediatricians and physicians especially trained in paediatric otoscopy, and to characterize the most misleading elements in diagnostic failure. Methods Consecutive clinical charts of children regularly followed for recurrent AOM (RAOM, i.e.: >3 episodes in 6 months or > 4 episodes in 1 year) at our Otitis Media paediatric outpatient clinic were retrospectively screened, in order to collect any diagnosis of AOM episode (and the related clinical findings/middle ear complaints) performed by primary care paediatricians/emergency room paediatricians. Diagnosis of AOM episode was validated by the same experienced physician (FF) in case of otoscopic relief of a bulging eardrum with at least one of the following: hyperaemia or yellow-like colour. The diagnostic concordance in detection of AOM episodes between primary care/emergency room paediatricians and our internal validator was expressed as the percentage of matching diagnosis. Results One hundred and thirty-four single AOM episodes occurring in 87 children (mean age: 26.9 +/- 18.9 months) were included in the analysis. Diagnostic concordance in detection of AOM episodes between primary care/emergency room paediatricians and our internal validator was reported in 72.4% of cases. The most common pitfall found in our study was the misleading diagnosis of AOM in case of hyperaemic tympanic membrane without bulging (32/37 out of non-validated diagnoses). Conclusions AOM diagnosis still represents a relevant issue among paediatricians in our country, and the presence of tympanic membrane hyperaemia without concomitant bulging can be confusing.

Abstract This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987.

The aim of this contribution is to present a segmentation method for the identification of voluntary movements from inertial data acquired through a single inertial measurement unit placed on the subject’s wrist. Inertial data were recorded from 25 healthy subjects while performing 75 consecutive reach-to-grasp movements. The approach herein presented, called DynAMoS, is based on an adaptive thresholding step on the angular velocity norm, followed by a statistics-based post-processing on the movement duration distribution. Post-processing aims at reducing the number of erroneous transitions in the movement segmentation. We assessed the segmentation quality of this method using a stereophotogrammetric system as the gold standard. Two popular methods already presented in the literature were compared to DynAMoS in terms of the number of movements identified, onset and offset mean absolute errors, and movement duration. Moreover, we analyzed the sub-phase durations of the drinking movement to further characterize the task. The results show that the proposed method performs significantly better than the two state-of-the-art approaches (i.e., percentage of erroneous movements = 3%; onset and offset mean absolute error < 0.08 s), suggesting that DynAMoS could make more effective home monitoring applications for assessing the motion improvements of patients following domicile rehabilitation protocols.

BackgroundWrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. ObjectiveThe aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back–worn inertial sensors. MethodsParticipants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back–worn inertial sensors. ResultsThe best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. ConclusionsAlgorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. Trial RegistrationISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987 International Registered Report Identifier (IRRID)RR2-10.1136/bmjopen-2021-050785

Conservation, characterization and exploitation of agrobiodiversity are key factors to guarantee food security and face future challenges such as climate changes. These issues are the subject of a series of international agreements, such as the Convention of Biological Diversity, with its Nagoya Protocol, and the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA) adopted in 2001 and entered into force in 2004. Italy ratified the Treaty in 2004 and instituted a long-lasting program, RGV-FAO, to implement it. CREA is one of the three organizations involved in the RGV-FAO Program, together with the National Research Council (CNR) and Reti Semi Rurali. CREA maintains a total of 40,186 accessions including cereals, vegetables, fruits, forages, industrial crops, forest and woody crops, medicinal and aromatic plants, and their wild relatives. Accessions are conserved using different ex situ conservation systems (seeds, in vivo plants, vegetative organs and in vitro plantlets), and characterized using genetic, morpho-phenological and/or biochemical methods. Herein, we will present the CREA long-lasting program RGV-FAO with some examples of the use of plant genetic resources in breeding programs, including molecular approaches. Some critical issues related to access and benefit sharing in PGRFA, such as the Nagoya Protocol and the Digital Sequence Information, will be discussed, highlighting their potential impact on food security and on the advancement of knowledge.

Abstract Background Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. Methods Twenty healthy older adults, 20 people with Parkinson’s disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. Results We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors

IntroductionThe use of contemporary drug-eluting stents (DES) has significantly improved outcomes of patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI). However, concerns exist regarding the long-term proinflammatory effects of durable polymer coatings used in most DES, potentially leading to long-term adverse events. First-generation polymer-free stent technologies, such as sirolimus- and probucol-eluting stents (PF-SES), have shown an excellent safety and efficacy profile. The aim of this study was to evaluate the safety and efficacy of the new ultrathin Coroflex ISAR NEO PF-SES, in a more-comers PCI population.MethodsThe CAESAR (a more-Comers populAtion trEated with an ultrathin struts polimer-free Sirolimus stent: An Italian post-maRketing study) registry is a multicenter, prospective study conducted in Italy, enrolling more-comers CAD patients undergoing PCI with the Coroflex ISAR NEO stent. Patients with left main (LM) disease, cardiogenic shock (CS), or severely reduced left-ventricular ejection fraction (LVEF) were excluded. The primary endpoint was target-lesion revascularization (TLR) at 1 year.ResultsA total of 425 patients were enrolled at 13 centers (mean age 66.9 ± 11.6 years, Diabetes mellitus 29%, acute coronary syndrome 67%, chronic total occlusion 9%). Of these, 40.9% had multivessel disease (MVD) and in 3.3% cases, the target lesion was in-stent restenosis (ISR). Clinical device success was reached in 422 (99.6%) cases. At 1 year, only two (0.5%) subjects presented ischemia-driven TLR. The 1-year rates of target vessel revascularization and MACE were 0.5% and 5.1%, respectively. Major bleeding was observed in four (1.0%) patients.ConclusionIn this multicenter, prospective registry, the use of a new ultrathin Coroflex ISAR NEO PF-SES in a more-comers PCI population showed good safety and efficacy at 1 year.

A central debate is the improvement in the mechanical and water resistance of sustainable earthen architecture without additives or stabilizers. This innovative work aims to test the effects of a graphene-based additive, optimized for the improvement in concrete properties, on the strength and water resistance of raw-earth plasters without any stabilizer other than sand. Given the heterogeneous nature of raw earth, three different soils were tested by adding three increasing graphene-based additive contents (0.01, 0.05 and 0.1 wt% of the earth–sand proportion). The link between soil intrinsic properties, i.e., geotechnical and mineralogical properties, and their interaction with the additive were investigated through geotechnical characterization, as well as mineralogical characterization, by XRD and ATR-FTIR analyses. The experimental tests carried out focused on the adhesion properties of the twelve different plasters on standard hollow bricks and on their interaction with water through capillary rise tests and erosion resistance tests. Conclusion from the experimental tests suggests that the graphene-based additive in earth plasters, by increasing the cohesion of the mixture, improves their adhesion performance.

IntroductionThe clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings.MethodsHere, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data.Results and discussionThe results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of −0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, −0.07, and

Failures that occurred in the last few decades highlighted the need to raise awareness about the emergent risk related to the impact localised degradation phenomena have on embankments. Common interventions aimed to improve embankments, such as the reconstruction of the damaged area or the injection of low-pressure grouts to fill fractures and burrows, may cause the weakening of the structure due to discontinuities between natural and treated zones. Moreover, since such repair techniques require huge volumes of materials, more sustainable solutions are encouraged. At the same time, the textile and fashion industries are looking for sustainable waste management and disposal strategies to face environmental problems concerned with the voluminous textile waste dispatched to landfills or incinerators. The use of soil mixed with textile waste in embankment improvement has been investigated to identify an effective engineering practice and to provide a strategy for the circular economy of textiles. Preliminary laboratory tests have been conducted on soil specimens collected from the Secchia River embankment, Northern Italy, to define the appropriate mixture proportions and to compare physical properties and hydro-mechanical behaviour of natural and treated soils. The results show that an appropriate fibre content offers manageable and relatively homogeneous mixtures. The indluence on soil consistency is mainly due to the textile fibre hydrophilic nature. The addition of fibres reduces the maximum dry density and increases the optimum water content. At low stress levels, the compressibility and hydraulic conductivity appear higher, however macro voids produced during sample preparation may alter the findings.

Abstract Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual’s mobility. Still, heterogeneity in protocols, sensor characteristics, data formats, and gold standards represent a barrier for data sharing, reproducibility, and external validation. In this study, we aim at providing an example of how movement data (from the real-world and the laboratory) recorded from different wearables and gold standard technologies can be organized, integrated, and stored. We leveraged on our experience from a large multi-centric study (Mobilise-D) to provide guidelines that can prove useful to access, understand, and re-use the data that will be made available from the study. These guidelines highlight the encountered challenges and the adopted solutions with the final aim of supporting standardization and integration of data in other studies and, in turn, to increase and facilitate comparison of data recorded in the scientific community. We also provide samples of standardized data, so that both the structure of the data and the procedure can be easily understood and reproduced.

Abstract Background Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety. Methods The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants’ strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson’s disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks. Results The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life. Conclusions The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy. Trial registration: ISRCTN—12246987.

Introduction: Accurately assessing people’s gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors).Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity.Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72–4.87 steps/min, stride length 0.04–0.06 m, walking speed 0.03–0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

CRISPR/Cas9 genome editing is a modern biotechnological approach used to improve plant varieties, modifying only one or a few traits of a specific variety. However, this technology cannot be easily used to improve fruit quality traits in citrus, due to the lack of knowledge of key genes, long juvenile stage, and the difficulty regenerating whole plants of specific varieties. Here, we introduce a genome editing approach with the aim of producing citrus plantlets whose fruits contain both lycopene and anthocyanins. Our method employs a dual single guide RNA (sgRNA)-directed genome editing approach to knockout the fruit-specific β-cyclase 2 gene, responsible for the conversion of lycopene to beta-carotene. The gene is targeted by two sgRNAs simultaneously to create a large deletion, as well as to induce point mutations in both sgRNA targets. The EHA105 strain of Agrobacterium tumefaciens was used to transform five different anthocyanin-pigmented sweet oranges, belonging to the Tarocco and Sanguigno varietal groups, and ‘Carrizo’ citrange, a citrus rootstock as a model for citrus transformation. Among 58 plantlets sequenced in the target region, 86% of them were successfully edited. The most frequent mutations were deletions (from -1 to -74 nucleotides) and insertions (+1 nucleotide). Moreover, a novel event was identified in six plantlets, consisting of the inversion of the region between the two sgRNAs. For 20 plantlets in which a single mutation occurred, we excluded chimeric events. Plantlets did not show an altered phenotype in vegetative tissues. To the best of our knowledge, this work represents the first example of the use of a genome editing approach to potentially improve qualitative traits of citrus fruit.

There is growing interest in the quantification of gait as part of complex motor tasks. This requires gait events (GEs) to be detected under conditions different from straight walking. This study aimed to propose and validate a new marker-based GE detection method, which is also suitable for curvilinear walking and step negotiation. The method was first tested against existing algorithms using data from healthy young adults (YA, n = 20) and then assessed in data from 10 individuals from the following five cohorts: older adults, chronic obstructive pulmonary disease, multiple sclerosis, Parkinson’s disease, and proximal femur fracture. The propagation of the errors associated with GE detection on the calculation of stride length, duration, speed, and stance/swing durations was investigated. All participants performed a variety of motor tasks including curvilinear walking and step negotiation, while reference GEs were identified using a validated methodology exploiting pressure insole signals. Sensitivity, positive predictive values (PPV), F1-score, bias, precision, and accuracy were calculated. Absolute agreement [intraclass correlation coefficient (ICC2,1)] between marker-based and pressure insole stride parameters was also tested. In the YA cohort, the proposed method outperformed the existing ones, with sensitivity, PPV, and F1 scores ≥ 99% for both GEs and conditions, with a virtually null bias (

The analysis of the stability of human gait may be effectively performed when estimates of the base of support are available. The base of support area is defined by the relative position of the feet when they are in contact with the ground and it is closely related to additional parameters such as step length and stride width. These parameters may be determined in the laboratory using either a stereophotogrammetric system or an instrumented mat. Unfortunately, their estimation in the real world is still an unaccomplished goal. This study aims at proposing a novel, compact wearable system, including a magneto-inertial measurement unit and two time-of-flight proximity sensors, suitable for the estimation of the base of support parameters. The wearable system was tested and validated on thirteen healthy adults walking at three self-selected speeds (slow, comfortable, and fast). Results were compared with the concurrent stereophotogrammetric data, used as the gold standard. The root mean square errors for the step length, stride width and base of support area varied from slow to high speed between 10–46 mm, 14–18 mm, and 39–52 cm2, respectively. The mean overlap of the base of support area as obtained with the wearable system and with the stereophotogrammetric system ranged between 70% and 89%. Thus, this study suggested that the proposed wearable solution is a valid tool for the estimation of the base of support parameters out of the laboratory.

Among Citrus species, the sweet orange (Citrus sinensis (L.) Osbeck) is the most important in terms of production volumes and cultivated areas. Oranges are particularly appreciated for the organoleptic characteristics and the high nutraceutical value of the fruits (thanks especially to their high content of antioxidants). Recent advances in citrus genetic and genomic resources, such as the release of the reference genomes of several sweet orange cultivars, have contributed to (i) understanding the diversification of C. sinensis and its relation with other citrus species, (ii) assessing the molecular mechanisms underlying traits of interest, (iii) identifying and characterizing the candidate genes responsible for important phenotypic traits, and (iv) developing biotechnological methods to incorporate these traits into different citrus genotypes. It has been clarified that all the genetic diversity within the sweet orange species was derived from subsequent mutations starting from a single ancestor and was derived from complex cycles of hybridization and backcrossing between the mandarin (Citrus reticulata Blanco) and the pummelo (Citrus maxima (Burm.) Merr.). This paper provides an overview of the varietal panorama together with a description of the main driving forces in present and future sweet orange breeding. In fact, for the sweet orange, as well as for other citrus species, the release of novel varieties with improved characteristics is being pursued thanks to the employment of conventional and/or innovative (molecular-based) methods. The state of the art methods together with the innovations in genomics and biotechnological tools leading to the so-called new plant breeding technologies were also reviewed and discussed.

The mechanical behaviour of a quasi-brittle material, i.e. Pietra Serena sandstone, was investigated both numerically and experimentally in order to build a reliable numerical modelling system applicable to more complex cases. The Karagozian and Case concrete (KCC) model was exploited as the material constitutive law and a new method to utilise this model for efficient and accurate simulation of quasi-brittle materials is discussed. The capability of this model is evaluated by comparing the results of the numerical simulations with the corresponding experimental results, and the method itself is critically assessed. Keywords: Finite element method (FEM), Triaxial compression test, Brazilian disc test, Quasi-brittle behaviour, Karagozian and Case concrete (KCC) model

Interest towards cellulose nanofibers obtained from virgin and waste sources has seen a significant growth, mainly thanks to the increasing sensitivity towards the concept of circular economy and the high levels of paper recycling achieved in recent years. Inspired by the guidelines of the green building industry, this study proposes the production and characterization of TEMPO-oxidized and homogenized cellulose nanofibers (TOHO CNF) from different sources and their use as additives for earth plasters on two different raw earth samples, characterized by geotechnical laboratory tests and mineralogical analysis: a high-plasticity clay (T2) and a medium-compressibility silt (ABS). Original sources, including those derived from waste (recycled cardboard and paper mill sludge), were characterized by determining chemical content (cellulose versus ashes and lignin) and fiber morphology. TOHO CNF derived from the different sources were compared in terms of nanofibers medium diameter, crystallinity degree, thermal decomposition and oxidation degree, that is the content of carboxylic groups per gram of sample. Then, a preliminary analysis of the influence of CNF on earth plasters is examined. Adhesion and capillary absorption tests highlighted the effect of such nanofibers on blends in function of two factors, namely the cellulose original source and the oxidation degree of the fibers. In particular, for both earth samples, T2 and ABS, a significant increase in adhesion strength was observed in the presence of some TOHO CNF additives. As far as capillary sorption tests, while an undesired increase in water adsorption was detected for T2 compared to the control, in the case of ABS, a significant reduction in water content was measured by adding TOHO CNF derived from recycled sources. These results pave the way for further in-depth investigation on the role of TOHO CNF as additives for earth plasters.

Low-molecular-weight, aspartic-acid-rich proteins (ASP-RICH) have been assumed to be involved in the self-incompatibility process of clementine. The role of ASP-RICH is not known, but hypothetically they could sequester calcium ions (Ca2+) and affect Ca2+-dependent mechanisms. In this article, we analyzed the effects induced by clementine ASP-RICH proteins (CcASP-RICH) when expressed in the tobacco heterologous system, focusing on the male gametophyte. The aim was to gain insight into the mechanism of action of ASP-RICH in a well-known cellular system, i.e., the pollen tube. Pollen tubes of tobacco transgenic lines expressing CcASP-RICH were analyzed for Ca2+ distribution, ROS, proton gradient, as well as cytoskeleton and cell wall. CcASP-RICH modulated Ca2+ content and consequently affected cytoskeleton organization and the deposition of cell wall components. In turn, this affected the growth pattern of pollen tubes. Although the expression of CcASP-RICH did not exert a remarkable effect on the growth rate of pollen tubes, effects at the level of growth pattern suggest that the expression of ASP-RICH may exert a regulatory action on the mechanism of plant cell growth.

The causal agent of mal secco disease is the fungus Plenodomus tracheiphilus, mainly affecting lemon tree survival in the Mediterranean area. Using a fully compatible host-pathogen interaction, the aim of our work was to retrieve the fungus transcriptome by an RNA seq approach during infection of rough lemon (Citrus jambhiri Lush.) to identify crucial transcripts for pathogenesis establishment and progression. A total of 2438 clusters belonging to P. tracheiphilus were retrieved and classified into the GO and KEGG categories. Transcripts were categorized mainly within the “membrane”, “catalytic activity”, and “primary metabolic process” GO terms. Moreover, most of the transcripts are included in the “ribosome”, “carbon metabolism”, and “oxidative phosphorylation” KEGG categories. By focusing our attention on transcripts with FPKM values higher than the median, we were able to identify four main transcript groups functioning in (a) fungus cell wall remodeling and protection, (b) destroying plant defensive secondary metabolites, (c) optimizing fungus development and pathogenesis, and (d) toxin biosynthesis, thus indicating that a multifaceted strategy to subdue the host was executed.

This study aims to check the compatibility of a selection of waste and recycled biopolymers for rammed earth applications in order to replace the more common cement-based stabilization. Five formulations of stabilized rammed earth were prepared with different biopolymers: lignin sulfonate, tannin, sheep wool fibers, citrus pomace and grape-seed flour. The microstructure of the different formulations was characterized by investigating the interactions between earth and stabilizers through mercury intrusion porosimetry (MIP), nitrogen soprtion isotherm, powder X-ray diffraction (XRD) and scanning electron microscopy (SEM). The unconfined compressive strength (UCS) was also evaluated for all stabilized specimens. Three out of five biopolymers were considered suitable as rammed earth stabilizers. The use of wool increased the UCS by 6%, probably thanks to the combined effect of the length of the fibers and the roughness of their surfaces, which gives a contribution in binding clay particles higher than citrus and grape-seed flour. Lignin sulfonate and tannin increased the UCS by 38% and 13%, respectively, suggesting the additives’ ability to fill pores, coat soil grains and form aggregates; this capability is confirmed by the reduction in the specific surface area and the pore volume in the nano- and micropore zones.

Nowadays, the installation of efficient lighting sources and Information and Communications Technologies can provide economic benefits, energy efficiency, and visual comfort requirements. More advantages can be derived if the public lighting infrastructure integrates a smart grid. This study presents an experimental multifunctional infrastructure for public lighting, installed in Palermo. The system is able to provide smart lighting functions (hotspot Wi-Fi, video-surveillances, car and pedestrian access control, car parking monitoring and support for environmental monitoring). A remote control and monitoring platform called “Centro Servizi” processes the information coming from different installations as well as their status in real time, and sends commands to the devices (e.g. to control the luminous flux), each one provided with a machine to machine interface. Data can be reported either on the web or on a customised app. The study has shown the efficient operation of such new infrastructure and its capability to provide new functions and benefits to citizens, tourists, and public administration. Thus, this system represents a starting point for the implementation of many other lighting infrastructure features typical of a “smart city.”

The orientation of a magneto-inertial measurement unit can be estimated using a sensor fusion algorithm (SFA). However, orientation accuracy is greatly affected by the choice of the SFA parameter values which represents one of the most critical steps. A commonly adopted approach is to fine-tune parameter values to minimize the difference between estimated and true orientation. However, this can only be implemented within the laboratory setting by requiring the use of a concurrent gold-standard technology. To overcome this limitation, a Rigid-Constraint Method (RCM) was proposed to estimate suboptimal parameter values without relying on any orientation reference. The RCM method effectiveness was successfully tested on a single-parameter SFA, with an average error increase with respect to the optimal of 1.5 deg. In this work, the applicability of the RCM was evaluated on 10 popular SFAs with multiple parameters under different experimental scenarios. The average residual between the optimal and suboptimal errors amounted to 0.6 deg with a maximum of 3.7 deg. These encouraging results suggest the possibility to properly tune a generic SFA on different scenarios without using any reference. The synchronized dataset also including the optical data and the SFA codes are available online.

Sweet oranges are an important source of ascorbic acid (AsA). In this study, the content of AsA in the juice and leaves of four orange clonal selections, different in terms of maturity time and the presence/absence of anthocyanins, was correlated with the transcription levels of the main genes involved in the biosynthesis, recycling, and degradation pathways. Within each variety, differences in the above pathways and the AsA amount were found between the analysed tissues. Variations were also observed at different stages of fruit development and maturation. At the beginning of fruit development, AsA accumulation was attributable to the synergic action of l-galactose and Myo-inositol, while the l-gulose pathway was predominant between the end of fruit development and the beginning of ripening. In leaves, the l-galactose pathway appeared to play a major role in AsA accumulation, even though higher GalUr isoform expression suggests a synergistic contribution of both pathways in this tissue. In juice, the trend of the AsA content may be related to the decrease in the transcription levels of the GME, GDH, MyoOx, and GalUr12 genes. Newhall was the genotype that accumulated the most AsA. The difference between Newhall and the other varieties seems to be attributable to the GLDH, GalUr12, APX2, and DHAR3 genes.

Inertial measurement units (IMUs) enable orientation, velocity, and position estimation in several application domains ranging from robotics and autonomous vehicles to human motion capture and rehabilitation engineering. Errors in orientation estimation greatly affect any of those motion parameters. The present work explains the main challenges in inertial orientation estimation (IOE) and presents an extensive benchmark dataset that includes 3D inertial and magnetic data with synchronized optical marker-based ground truth measurements, the Berlin Robust Orientation Estimation Assessment Dataset (BROAD). The BROAD dataset consists of 39 trials that are conducted at different speeds and include various types of movement. Thereof, 23 trials are performed in an undisturbed indoor environment, and 16 trials are recorded with deliberate magnetometer and accelerometer disturbances. We furthermore propose error metrics that allow for IOE accuracy evaluation while separating the heading and inclination portions of the error and introduce well-defined benchmark metrics. Based on the proposed benchmark, we perform an exemplary case study on two widely used openly available IOE algorithms. Due to the broad range of motion and disturbance scenarios, the proposed benchmark is expected to provide valuable insight and useful tools for the assessment, selection, and further development of inertial sensor fusion methods and IMU-based application systems.

Among Citrus species, lemon is one of the most susceptible to mal secco disease, a tracheomycosis caused by the mitosporic fungus Plenodomus tracheiphilus, which induces chlorosis followed by leaf drop and progressive desiccation of twigs and branches. Severe infection can cause the death of the plant. Since no effective control strategies are available to efficiently control the pathogen spread, host tolerance is the most desirable goal in the struggle against mal secco disease. To date, both traditional breeding programs and biotechnological techniques were not efficient in developing novel varieties coupling tolerance to mal secco with optimal fruit quality. Furthermore, the genetic basis of host resistance has not been fully deciphered yet, hampering the set-up of marker-assisted selection (MAS) schemes. This paper provides an overview of the biotechnological approaches adopted so far for the selection of mal secco tolerant lemon varieties and emphasizes the promising contribution of marker-trait association analysis techniques for both unraveling the genetic determinism of the resistance to mal secco and detecting molecular markers that can be readily used for MAS. Such an approach has already proved its efficiency in several crops and could represent a valuable tool to select novel lemon varieties coupling superior fruit quality traits and resistance to mal secco.

The orientation of a magneto and inertial measurement unit (MIMU) is estimated by means of sensor fusion algorithms (SFAs) thus enabling human motion tracking. However, despite several SFAs implementations proposed over the last decades, there is still a lack of consensus about the best performing SFAs and their accuracy. As suggested by recent literature, the filter parameters play a central role in determining the orientation errors. The aim of this work is to analyze the accuracy of ten SFAs while running under the best possible conditions (i.e., their parameter values are set using the orientation reference) in nine experimental scenarios including three rotation rates and three commercial products. The main finding is that parameter values must be specific for each SFA according to the experimental scenario to avoid errors comparable to those obtained when the default parameter values are used. Overall, when optimally tuned, no statistically significant differences are observed among the different SFAs in all tested experimental scenarios and the absolute errors are included between 3.8 deg and 7.1 deg. Increasing the rotation rate generally leads to a significant performance worsening. Errors are also influenced by the MIMU commercial model. SFA MATLAB implementations have been made available online.

Mal secco is one of the most severe diseases of citrus, caused by the necrotrophic fungus Plenodomus tracheiphilus. With the main aim of identifying candidate genes involved in the response of citrus plants to “Mal secco”, we performed a de novo transcriptome analysis of rough lemon seedlings subjected to inoculation of P. tracheiphilus. The analysis of differential expressed genes (DEGs) highlighted a sharp response triggered by the pathogen as a total of 4986 significant DEGs (2865 genes up-regulated and 2121 down-regulated) have been revealed. The analysis of the most significantly enriched KEGG pathways indicated that a crucial role is played by genes involved in “Plant hormone signal transduction”, “Phenylpropanoid biosynthesis”, and “Carbon metabolism”. The main findings of this work are that under fungus challenge, the rough lemon genes involved both in the light harvesting and the photosynthetic electron flow were significantly down-regulated, thus probably inducing a shortage of energy for cellular functions. Moreover, the systemic acquired resistance (SAR) was activated through the induced salicylic acid cascade. Interestingly, RPM1 interacting protein 4, an essential positive regulator of plant defense, and BIR2, which is a negative regulator of basal level of immunity, have been identified thus representing useful targets for molecular breeding.

Mal secco is a tracheomycotic disease caused by the fungus Plenodomus tracheiphilus (Petri) Gruyter, Aveskamp, and Verkley that has caused severe damage and loss of yield in the citrus industry in the Mediterranean area, for 100 years. While the disease can affect different cultivated citrus species, lemon (C. × limon var. limon (L.) Burm. f.) and citron are the most susceptible. The identification of resistant or field-tolerant clones and hybrids is a major goal for lemon growers and breeders. To identify sources of resistance or tolerance to the disease, we performed a phenotypic survey on a lemon and lemon-like open-field germplasm planted at CREA (Research Centre for Olive, Fruit and Citrus Crops), Italy, in an area with high pathogen pressure. Phenotyping was performed visually, four times, for three consecutive years, on a total of 50 accessions, with two or three replicate trees per accession. Moreover, molecular screening based on real-time PCR was performed, for two consecutive years, on twigs, young leaves, and mature leaves of all plants, to detect the pathogen in the absence of clear symptoms. The accessions were categorized into seven groups based on the presence of visual symptoms, real-time PCR pathogen detection, and canopy volume. The results revealed sources of tolerance in lemon and citron hybrids. The molecular screening identified P. tracheiphilus in all lemon clones, with mean Ct values ranging from 17 to 39. The screening also identified P. tracheiphilus in clones without clear symptoms, indicating their ability to tolerate the disease. Moreover, a strong negative correlation was found between the Ct values in twigs and symptom severity (r = −0.72). This indicates that the DNA from twigs is the most appropriate for use in performing reliable phenotyping of mal secco susceptibility in adult plants. An autotetraploid lemon (Doppio Lentini) seems to be immune to the disease, under natural pressure, since P. tracheiphilus was not detected by real-time PCR and visual screening. Overall, the data obtained are a valuable resource for identifying both the most tolerant lemon varieties suitable for areas with high pathogen pressure and the best breeding parents for the introgression of resistance genes into lemon genotypes.

Citrus fruit quality and scion productivity are influenced by the choice of rootstock. We aimed to evaluate the effect of rootstocks on yield and fruit quality of Mandared, a triploid pigmented mandarin. To do so, we established a rootstock field trial on a high pH soil (8.6) in which Mandared was grafted onto 11 rootstocks. These included some standard rootstocks, such as trifoliate orange ((Poncirus trifoliata (L.) Raf.), Troyer citrange (Citrus sinensis (L.) Osb. × P. trifoliata), Swingle citrumelo (Citrus paradisi Macf. × P. trifoliata), and C35 citrange (C. sinensis × P. trifoliata), as well as new releases from the Council for Agricultural Research and Economics (CREA, Acireale, Italy) and the University of California Riverside (UCR). The cumulative yield was measured over five consecutive years, while fruit quality was analyzed for two years. The trees on C35, C57 (Citrus sunki Hort. ex. Tan. × P. trifoliata), and C22 (C. sunki × P. trifoliata), started to set fruits one year earlier than the others. The trees on C57 provided some of the highest cumulative yields and canopy volumes. The production of Mandared grafted onto C57 was double that of Mandared grafted onto Troyer, while Mandared grafted onto C35 and C22 resulted in the best yield efficiency. The trees on Swingle and C57 significantly reduced the pre-harvest fruit drop, to which Mandared is particularly sensitive. However, grafting Mandared onto Swingle resulted in the highest variation among replicates, probably due to its high sensitivity to iron chlorosis. Most of the fruit quality parameters, such as fruit size, total soluble solids (TSS), and acidity were not significantly different among the rootstock treatments. However, fruits produced by Mandared grafted onto C22 had one of the highest rates of anthocyanin accumulation. The results indicate that C57, C35, and C22 were the most suitable rootstocks for Mandared in South-Eastern Sicily.

Alternaria alternata is a fungus that causes a serious disease in susceptible genotypes of citrus, particularly in mandarins. The Alternaria citri toxin (ACT) produced by the pathogen induces necrotic lesions on young leaves and fruits, defoliation and fruit drop. Here, we describe two methods of marker-assisted selection (MAS) that could be used for the early identification of Alternaria brown spot (ABS)-resistant mandarin hybrids. The first method is based on a nested PCR coupled to high resolution melting (HRM) analysis at the SNP08 locus, which is located at 0.4 cM from the ABS resistance locus, and was previously indicated as the most suitable for the selection of ABS-resistant hybrids. The method was validated on 41 mandarin hybrids of the CREA germplasm collection, and on 862 progenies generated from five crosses involving different susceptible parents. Four out of five populations showed Mendelian segregation at the analyzed locus, while a population involving Murcott tangor as male parent showed distorted segregation toward the susceptible hybrids. The second method is based on a cleaved amplified polymorphic sequences (CAPS) marker that was developed using the same primers as the nested PCR at the SNP08 locus, coupled with BccI restriction enzyme digestion. To verify the reliability of the two genotyping methods, in vitro leaf phenotyping was carried out by inoculating A. alternata spores onto young leaves of 101 hybrids, randomly chosen among the susceptible and resistant progenies. The phenotyping confirmed the SNP08 genotyping results, so the proposed method of selection based on HRM or CAPS genotyping could be routinely used as an alternative to KBioscience competitive allele specific polymerase chain reaction (KASPar) single nucleotide polymorphism (SNP) genotyping system to improve citrus breeding programs. While the study confirmed that the SNP08 marker is a reliable tool for MAS of new citrus hybrids with different genetic backgrounds, it also identified a small group of genotypes where the resistance mechanism requires further investigation.

Congenital anomalies of the coronary arteries, although uncommon, have the potential to cause serious myocardial damage, ischemic cardiomyopathy, and sudden cardiac death. We report a rare case of origin of all three coronaries from the right sinus of Valsalva.

High resolution melting curve analysis (HRM) has been used as an efficient, accurate and cost-effective tool to detect single nucleotide polymorphisms (SNPs) or insertions or deletions (INDELs). However, its efficiency, accuracy and applicability to discriminate microsatellite polymorphism have not been extensively assessed. The traditional protocols used for SSR genotyping include PCR amplification of the DNA fragment and the separation of the fragments on electrophoresis-based platform. However, post-PCR handling processes are laborious and costly. Furthermore, SNPs present in the sequences flanking repeat motif cannot be detected by polyacrylamide-gel-electrophoresis based methods. In the present study, we compared the discriminating power of HRM with the traditional electrophoresis-based methods and provided a panel of primers for HRM genotyping in Citrus. The results showed that sixteen SSR markers produced distinct polymorphic melting curves among the Citrus spp investigated through HRM analysis. Among those, 10 showed more genotypes by HRM analysis than capillary electrophoresis owing to the presence of SNPs in the amplicons. For the SSR markers without SNPs present in the flanking region, HRM also gave distinct melting curves which detected same genotypes as were shown in capillary electrophoresis (CE) analysis. Moreover, HRM analysis allowed the discrimination of most of the 15 citrus genotypes and the resulting genetic distance analysis clustered them into three main branches. In conclusion, it has been approved that HRM is not only an efficient and cost-effective alternative of electrophoresis-based method for SSR markers, but also a method to uncover more polymorphisms contributed by SNPs present in SSRs. It was therefore suggested that the panel of SSR markers could be used in a variety of applications in the citrus biodiversity and breeding programs using HRM analysis. Furthermore, we speculate that the HRM analysis can be employed to analyse SSR markers in a wide range of applications in all other species.