HOLLOWS: A Power-Aware Task Scheduler for Energy Harvesting Sensor Nodes

Energy-harvesting sensor nodes (EHSNs) have stringent low-energy consumption requirements, but they need to concurrently execute several types of tasks (processing, sensing, actuation, etc). Furthermore, no accurate models exist to predict the energy harvesting income in order to adapt at run-time the executing set of prioritized tasks. In this paper, we propose a novel power-aware task scheduler for EHSNs, namely, HOLLOWS: Head-of-Line Low-Overhead Wide-priority Service. HOLLOWS uses an energy-constrained prioritized queue model to describe the residence time of tasks entering the system and dynamically selects the set of tasks to execute, according to system accuracy requirements and expected energy. Moreover, HOLLOWS includes a new energy harvesting prediction algorithm, i.e., Weather-Conditioned Moving Average (WCMA), which we have developed to estimate the solar panel energy income. We have tested HOLLOWS using the real-life working conditions of Shimmer, a sensor node for structural health monitoring. Our results indicate that HOLLOWS accurately predicts the energy available in Shimmer to guarantee a certain damage monitoring quality for long-term autonomous scenarios. Also, HOLLOWS is able to adjust the use of the incoming energy harvesting to achieve high accuracy for rapid event damage assessment (after earthquakes, fires, etc.)

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Prediction and Management in Energy Harvested Wireless Sensor Nodes

Abstract—Solar panels are frequently used in wireless sensor nodes because they can theoretically provide quite a bit of harvested energy. However, they are not a reliable, consistent source of energy because of the Sun’s cycles and the everchanging weather conditions. Thus, in this paper we present a fast, efficient and reliable solar prediction algorithm, namely, Weather-Conditioned Moving Average (WCMA) that is capable of exploiting the solar energy more efficiently than state-of-the-art energy prediction algorithms (e.g. Exponential Weighted Moving Average EWMA). In particular, WCMA is able to effectively take into account both the current and past-days weather conditions, obtaining a relative mean error of only 10%. When coupled with energy management algorithm, it can achieve gains of more than 90 % in energy utilization with respect to EWMA under the real working conditions of the Shimmer node, an active sensing platform for structural health monitoring. I

SUNCT/SUNA in Pediatric Age: A Review of Pathophysiology and Therapeutic Options

The International Classification of Headache Disorders, 3rd edition (ICHD3) defines Shortlasting Unilateral Neuralgiform Headache Attacks (SUNHA) as attacks of moderate or severe, strictly unilateral head pain lasting from seconds to minutes, occurring at least once a day and usually associated with prominent lacrimation and redness of the ipsilateral eye. Two subtypes of SUNHA are identified: Short-lasting Unilateral Neuralgiform headache attacks with Conjunctival injection and Tearing (SUNCT) and Short-lasting Unilateral Neuralgiform headache attacks with cranial Autonomic symptoms (SUNA). These pathologies are infrequent in children and difficult to diagnose. The authors reviewed the existing literature on SUNCT and SUNA, especially in the developmental age, which describes the pathophysiology in detail and focuses on the therapeutic options available to date. SUNHA-type headaches must be considered on the one hand, for the possibility of the onset of forms secondary to underlying pathologies even of a neoplastic nature, and on the other hand, for the negative impact they can have on an individual\u2019s quality of life, particularly in young patients. Until now, published cases suggest that no chronic variants occur in childhood and adolescents. In light of this evidence, the authors offer a review that may serve as a source to be drawn upon in the implementation of suitable treatments in children and adolescents suffering from these headaches, focusing on therapies that are non-invasive and as risk-free as possible for pediatric patients

Infantile neuroaxonal dystrophy and PLA2G6-associated neurodegeneration: An update for the diagnosis

Infantile neuroaxonal dystrophy is a rare neurodegenerative disorder characterized by infantile onset of rapid motor and cognitive regression and hypotonia evolving into spasticity. Recessively inherited mutations of the PLA2G6 gene are causative of infantile neuroaxonal dystrophy and other PLA2G6-associated neurodegeneration, which includes conditions known as atypical neuroaxonal dystrophy, Karak syndrome and early-onset dystonia-parkinsonism with cognitive impairment. Phenotypic spectrum continues to evolve and genotype-phenotype correlations are currently limited. Due to the overlapping phenotypes and heterogeneity of clinical findings characterization of the syndrome is not always achievable. We reviewed the most recent clinical and neuroradiological information in the way to make easier differential diagnosis with other degenerative disorders in the paediatric age. Recognizing subtle signs and symptoms is a fascinating challenge to drive towards better diagnostic and genetic investigations

Further delineation of PIGB-related early infantile epileptic encephalopathy

Pathogenic variants in phosphatidylinositol glycan anchor biosynthesis class B (PIGB) gene have been first described as the cause of early infantile epileptic encephalopathy 80 (EIEE-80) in 2019. This disorder, an inherited glycosylphosphatidylinositol deficiency, is associated with a complex neurologic phenotype, including developmental delay, early-onset epilepsy and peripheral neuropathy. We report on a 5 year-old girl born from consanguineous parents, manifesting severe global developmental delay with absent speech, mixed peripheral polyneuropathy, hypotonia, bilateral equino-varo-supinated-cavus foot, early-onset scoliosis, elevated serum alkaline phosphatase and a single episode of febrile status epilepticus. Hypomyelination was documented on brain MRI. Whole-exome sequencing (WES) disclosed the likely pathogenic biallelic PIGB NM_004855.4: c.463G > C, p.(Asp155His) missense variant. In our patient, while other characteristic clinical, neuroimaging and laboratory findings (as described in the first research paper) were present, seizures were not a major clinical issue, thus contributing to our knowledge on this ultra-rare disorder

Aromatic L-Amino-Acid Decarboxylase Deficiency Screening by Analysis of 3-O-Methyldopa in Dried Blood Spots: Results of a Multicentric Study in Neurodevelopmental Disorders

Aromatic L-amino acid decarboxylase deficiency (AADCd) is a rare recessive metabolic disorder caused by pathogenic homozygous or compound heterozygous variants in the dopa decarboxylase (DDC) gene. Adeno-associated viral vector-mediated gene transfer of the human DDC gene injected into the putamen is available. The typical presentation is characterized by early-onset hypotonia, severe developmental delay, movement disorders, and dysautonomia. Recently, mild and even atypical phenotypes have been reported, increasing the diagnostic challenge. The aim of this multicentric study is to identify the prevalence of AADCd in a population of patients with phenotypic clusters characterized by neurodevelopmental disorders (developmental delay/intellectual disability, and/or autism) by 3-O-methyldopa (3-OMD) detection in dried blood spots (DBS). It is essential to identify AADCd promptly, especially within non-typical phenotypic clusters, because better results are obtained when therapy is quickly started in mild-moderate phenotypes. Between 2021 and 2023, 390 patients with non-specific phenotypes possibly associated with AADCd were tested; none resulted in a positive result. This result highlights that the population to be investigated for AADCd should have more defined clinical characteristics: association with common signs (hypotonia) and/or pathognomonic symptoms (oculogyric crisis and dysautonomia). It is necessary to continue to screen selected clusters for reaching diagnosis and improving long-term outcomes through treatment initiation. This underscores the role of newborn screening in identifying AADCd