Calibration of pipeline ADC with pruned Volterra kernels

A Volterra model is used to calibrate a pipeline ADC simulated in Cadence Virtuoso using the STMicroelectronics CMOS 45 nm process. The ADC was designed to work at 50 MSps, but it is simulated at up to 125 MSps, proving that calibration using a Volterra model can significantly increase sampling frequency. Equivalent number of bits (ENOB) improves by 1-2.5 bits (6-15 dB) with 37101 model parameters. The complexity of the calibration algorithm is reduced using different lengths for each Volterra kernels and performing iterative pruning. System identification is performed by least squares techniques with a set of sinusoids at different frequencies spanning the whole Nyquist band. A comparison with simplified Volterra models proposed in the literature shows better performance for the pruned Volterra model with comparable complexity, improving linearity by as much as 1.5 bits more than the other techniques

Analysis and design of low-power data converters

In a large number of applications the signal processing is done exploiting both analog and digital signal processing techniques. In the past digital and analog circuits were made on separate chip in order to limit the interference and other side effects, but the actual trend is to realize the whole elaboration chain on a single System on Chip (SoC). This choice is driven by different reasons such as the reduction of power consumption, less silicon area occupation on the chip and also reliability and repeatability. Commonly a large area in a SoC is occupied by digital circuits, then, usually a CMOS short-channel technological processes optimized to realize digital circuits is chosen to maximize the performance of the Digital Signal Proccessor (DSP). Opposite, the short-channel technology nodes do not represent the best choice for analog circuits. But in a large number of applications, the signals which are treated have analog nature (microphone, speaker, antenna, accelerometers, biopotential, etc.), then the input and output interfaces of the processing chip are analog/mixed-signal conversion circuits. Therefore in a single integrated circuit (IC) both digital and analog circuits can be found. This gives advantages in term of total size, cost and power consumption of the SoC. The specific characteristics of CMOS short-channel processes such as: • Low breakdown voltage (BV) gives a power supply limit (about 1.2 V). • High threshold voltage VTH (compared with the available voltage supply) fixed in order to limit the leakage power consumption in digital applications (of the order of 0.35 / 0.4V), puts a limit on the voltage dynamic, and creates many problems with the stacked topologies. • Threshold voltage dependent on the channel length VTH = f(L) (short channel effects). • Low value of the output resistance of the MOS (r0) and gm limited by speed saturation, both causes contribute to achieving a low intrinsic gain gmr0 = 20 to 26dB. • Mismatch which brings offset effects on analog circuits. make the design of high performance analog circuits very difficult. Realizing lowpower circuits is fundamental in different contexts, and for different reasons: lowering the power dissipation gives the capability to reduce the batteries size in mobile devices (laptops, smartphones, cameras, measuring instruments, etc.), increase the life of remote sensing devices, satellites, space probes, also allows the reduction of the size and weight of the heat sink. The reduction of power dissipation allows the realization of implantable biomedical devices that do not damage biological tissue. For this reason, the analysis and design of low power and high precision analog circuits is important in order to obtain high performance in technological processes that are not optimized for such applications. Different ways can be taken to reduce the effect of the problems related to the technology: • Circuital level: a circuit-level intervention is possible to solve a specific problem of the circuit (i.e. Techniques for bandwidth expansion, increase the gain, power reduction, etc.). • Digital calibration: it is the highest level to intervene, and generally going to correct the non-ideal structure through a digital processing, these aims are based on models of specific errors of the structure. • Definition of new paradigms. This work has focused the attention on a very useful mixed-signal circuit: the pipeline ADC. The pipeline ADCs are widely used for their energy efficiency in high-precision applications where a resolution of about 10-16 bits and sampling rates above hundreds of Mega-samples per second (telecommunication, radar, etc.) are needed. An introduction on the theory of pipeline ADC, its state of the art and the principal non-idealities that affect the energy efficiency and the accuracy of this kind of data converters are reported in Chapter 1. Special consideration is put on low-voltage low-power ADCs. In particular, for ADCs implemented in deep submicron technology nodes side effects called short channel effects exist opposed to older technology nodes where undesired effects are not present. An overview of the short channel effects and their consequences on design, and also power consuption reduction techniques, with particular emphasis on the specific techniques adopted in pipelined ADC are reported in Chapter 2. Moreover, another way may be undertaken to increase the accuracy and the efficiency of an ADC, this way is the digital calibration. In Chapter 3 an overview on digital calibration techniques, and furthermore a new calibration technique based on Volterra kernels are reported. In some specific applications, such as software defined radios or micropower sensor, some circuits should be reconfigurable to be suitable for different radio standard or process signals with different charateristics. One of this building blocks is the ADC that should be able to reconfigure the resolution and conversion frequency. A reconfigurable voltage-scalable ADC pipeline capable to adapt its voltage supply starting from the required conversion frequency was developed, and the results are reported in Chapter 4. In Chapter 5, a pipeline ADC based on a novel paradigm for the feedback loop and its theory is described

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

The Sex-Specific Detrimental Effect of Diabetes and Gender-Related Factors on Pre-admission Medication Adherence Among Patients Hospitalized for Ischemic Heart Disease: Insights From EVA Study

Background: Sex and gender-related factors have been under-investigated as relevant determinants of health outcomes across non-communicable chronic diseases. Poor medication adherence results in adverse clinical outcomes and sex differences have been reported among patients at high cardiovascular risk, such as diabetics. The effect of diabetes and gender-related factors on medication adherence among women and men at high risk for ischemic heart disease (IHD) has not yet been fully investigated.Aim: To explore the role of sex, gender-related factors, and diabetes in pre-admission medication adherence among patients hospitalized for IHD.Materials and Methods: Data were obtained from the Endocrine Vascular disease Approach (EVA) (ClinicalTrials.gov Identifier: NCT02737982), a prospective cohort of patients admitted for IHD. We selected patients with baseline information regarding the presence of diabetes, cardiovascular risk factors, and gender-related variables (i.e., gender identity, gender role, gender relations, institutionalized gender). Our primary outcome was the proportion of pre-admission medication adherence defined through a self-reported questionnaire. We performed a sex-stratified analysis of clinical and gender-related factors associated with pre-admission medication adherence.Results: Two-hundred eighty patients admitted for IHD (35% women, mean age 70), were included. Around one-fourth of the patients were low-adherent to therapy before hospitalization, regardless of sex. Low-adherent patients were more likely diabetic (40%) and employed (40%). Sex-stratified analysis showed that low-adherent men were more likely to be employed (58 vs. 33%) and not primary earners (73 vs. 54%), with more masculine traits of personality, as compared with medium-high adherent men. Interestingly, women reporting medication low-adherence were similar for clinical and gender-related factors to those with medium-high adherence, except for diabetes (42 vs. 20%, p = 0.004). In a multivariate adjusted model only employed status was associated with poor medication adherence (OR 0.55, 95%CI 0.31–0.97). However, in the sex-stratified analysis, diabetes was independently associated with medication adherence only in women (OR 0.36; 95%CI 0.13–0.96), whereas a higher masculine BSRI was the only factor associated with medication adherence in men (OR 0.59, 95%CI 0.35–0.99).Conclusion: Pre-admission medication adherence is common in patients hospitalized for IHD, regardless of sex. However, patient-related factors such as diabetes, employment, and personality traits are associated with adherence in a sex-specific manner

A new class-AB Flipped Voltage Follower using a common-gate auxiliary amplifier

A novel class-AB Flipped Voltage Follower is proposed, suitable for low-voltage low-power CMOS implementation in advanced technology nodes. Simulations have been performed using STMicroelectronics models for the 45nm technology. The Flipped Voltage Follower allows low output impedance and high linearity by means of a feedback loop. However, like the conventional common-drain voltage follower, it has class-A behavior. Class-AB behavior enables faster settling with large capacitive loads and/or lower power consumption

Calibrating sample and hold stages with pruned Volterra kernels

Switched capacitor sample and hold (SHA) stages in deep submicron technologies can achieve hundreds of mega samples per second of sampling frequency, but are affected by several nonlinear effects which reduce their signal-to-noise-and-distortion ratio (SNDR): CMOS switch non-idealities, amplifier nonlinearity, and incomplete settling. It is possible to model and correct distortions using Volterra kernels, which can be rather resource-consuming as the number of parameters to estimate rapid increases with the order and length of the kernels. In this reported work, it is shown that a switched capacitor SHA, simulated using the 45 nm process by STMicroelectronics, can be calibrated to achieve a 10-24 dB improvement in SNDR. Computational costs are kept low using a different lag value for each kernel, and iteratively pruning the elements of the Volterra kernels which affect linearity the least. A technique for estimation and out-of- sample validation is presented and robustness checks are performed. A performance gain of 8.5 dB can be achieved with as few as 17 correction parameters, while 21 coefficients are enough to gain 12.2 dB, and 36 to gain 18.4 dB

Simple versus reinforced cruroplasty in patients submitted to concomitant laparoscopic sleeve gastrectomy. Prospective evaluation in a bariatric center of excellence

Crural closure in addition to laparoscopic sleeve gastrectomy (LSG) represents a valuable option for the synchronous management of morbid obesity and hiatal defects, providing good outcomes in terms of weight loss and gastroesophageal reflux disease (GERD) symptoms control. The aim of this prospective study was to evaluate the safety and effectiveness of the reinforced cruroplasty during LSG compared with a concurrent group of simple cruroplasty

Frequency and characterization of cognitive impairments in patients diagnosed with paediatric central nervous system tumours: a systematic review

Background: This systematic review has been conducted with the aim of characterizing cognitive deficits and analyzing their frequency in survivors of paediatric Central Nervous System tumours. Materials and methods: All literature published up to January 2023 was retrieved searching the databases "PubMed", "Cochrane", "APA PsycInfo" and "CINAHL". The following set of pre-defined inclusion criteria were then individually applied to the selected articles in their full-text version: i) Retrospective/prospective longitudinal observational studies including only patients diagnosed with primary cerebral tumours at ≤ 21 years (range 0-21); ii) Studies including patients evaluated for neuro-cognitive and neuro-psychological deficits from their diagnosis and/or from anti-tumoral therapies; iii) Studies reporting standardized tests evaluating patients' neuro-cognitive and neuro-psychological performances; iv) Patients with follow-ups ≥ 2 years from the end of their anti-tumoral therapies; v) Studies reporting frequencies of cognitive deficits. Results: 39 studies were included in the analysis. Of these, 35 assessed intellectual functioning, 30 examined memory domains, 24 assessed executive functions, 22 assessed attention, 16 examined visuo-spatial skills, and 15 explored language. A total of 34 studies assessed more than one cognitive function, only 5 studies limited their analysis on a single cognitive domain. Attention impairments were the most recurrent in this population, with a mean frequency of 52.3% after a median period post-treatment of 11.5 years. The other cognitive functions investigated in the studies showed a similar frequency of impairments, with executive functions, language, visuospatial skills and memory deficits occurring in about 40% of survivors after a similar post-treatment period. Longitudinal studies included in the systematic review showed a frequent decline over time of intellectual functioning. Conclusions: Survivors of paediatric Central Nervous System tumours experience cognitive sequelae characterized by significant impairments in the attention domain (52.3%), but also in the other cognitive functions. Future studies in this research field need to implement more cognitive interventions and effective, but less neurotoxic, tumour therapies to preserve or improve neurocognitive functioning and quality of life of this population

Frequency and characterization of cognitive impairments in patients diagnosed with paediatric central nervous system tumours: a systematic review

BackgroundThis systematic review has been conducted with the aim of characterizing cognitive deficits and analyzing their frequency in survivors of paediatric Central Nervous System tumours.Materials and methodsAll literature published up to January 2023 was retrieved searching the databases “PubMed”, “Cochrane”, “APA PsycInfo” and “CINAHL”. The following set of pre-defined inclusion criteria were then individually applied to the selected articles in their full-text version: i) Retrospective/prospective longitudinal observational studies including only patients diagnosed with primary cerebral tumours at ≤ 21 years (range 0-21); ii) Studies including patients evaluated for neuro-cognitive and neuro-psychological deficits from their diagnosis and/or from anti-tumoral therapies; iii) Studies reporting standardized tests evaluating patients’ neuro-cognitive and neuro-psychological performances; iv) Patients with follow-ups ≥ 2 years from the end of their anti-tumoral therapies; v) Studies reporting frequencies of cognitive deficits.Results39 studies were included in the analysis. Of these, 35 assessed intellectual functioning, 30 examined memory domains, 24 assessed executive functions, 22 assessed attention, 16 examined visuo-spatial skills, and 15 explored language. A total of 34 studies assessed more than one cognitive function, only 5 studies limited their analysis on a single cognitive domain. Attention impairments were the most recurrent in this population, with a mean frequency of 52.3% after a median period post-treatment of 11.5 years. The other cognitive functions investigated in the studies showed a similar frequency of impairments, with executive functions, language, visuospatial skills and memory deficits occurring in about 40% of survivors after a similar post-treatment period. Longitudinal studies included in the systematic review showed a frequent decline over time of intellectual functioning.ConclusionsSurvivors of paediatric Central Nervous System tumours experience cognitive sequelae characterized by significant impairments in the attention domain (52.3%), but also in the other cognitive functions. Future studies in this research field need to implement more cognitive interventions and effective, but less neurotoxic, tumour therapies to preserve or improve neurocognitive functioning and quality of life of this population