A novel stepwise micro-TESE approach in non obstructive azoospermia

Background: The purpose of the study was to investigate whether micro-TESE can improve sperm retrieval rate (SRR) compared to conventional single TESE biopsy on the same testicle or to contralateral multiple TESE, by employing a novel stepwise micro-TESE approach in a population of poor prognosis patients with non-obstructive azoospermia (NOA). Methods: Sixty-four poor prognosis NOA men undergoing surgical testicular sperm retrieval for ICSI, from March 2007 to April 2013, were included in this study. Patients inclusion criteria were a) previous unsuccessful TESE, b) unfavorable histology (SCOS, MA, sclerahyalinosis), c) Klinefelter syndrome. We employed a stepwise micro-TESE consisting three-steps: 1) single conventional TESE biopsy; 2) micro-TESE on the same testis; 3) contralateral multiple TESE. Results: SRR was 28.1 % (18/64). Sperm was obtained in both the initial single conventional TESE and in the following micro-TESE. The positive or negative sperm retrieval was further confirmed by a contralateral multiple TESE, when performed. No significant pre-operative predictors of sperm retrieval, including patients’ age, previous negative TESE or serological markers (LH, FSH, inhibin B), were observed at univariate or multivariate analysis. Micro-TESE (step 2) did not improve sperm retrieval as compared to single TESE biopsy on the same testicle (step 1) or multiple contralateral TESE (step 3). Conclusions: Stepwise micro-TESE could represent an optimal approach for sperm retrieval in NOA men. In our view, it should be offered to NOA patients in order to gradually increase surgical invasiveness, when necessary. Stepwise micro-TESE might also reduce the costs, time and efforts involved in surgery

Testicular histopathology, semen analysis and FSH, predictive value of sperm retrieval: supportive counseling in case of reoperation after testicular sperm extraction (TESE)

Background: To provide indicators for the likelihood of sperm retrieval in patients undergoing testicular sperm extraction is a major issue in the management of male infertility by TESE. The aim of our study was to determine the impact of different parameters, including testicular histopathology, on sperm retrieval in case of reoperation in patients undergoing testicular sperm extraction. Methods: We retrospectively analyzed 486 patients who underwent sperm extraction for intracytoplasmic sperm injection and testicular biopsy. Histology was classified into: normal spermatogenesis; hypospermatogenesis (reduction in the number of normal spermatogenetic cells); maturation arrest (absence of the later stages of spermatogenesis); and Sertoli cell only (absence of germ cells). Semen analysis and serum FSH, LH and testosterone were measured. Results: Four hundred thirty patients had non obstructive azoospermia, 53 severe oligozoospermia and 3 necrozoospermia. There were 307 (63%) successful sperm retrieval. Higher testicular volume, lower levels of FSH, and better histological features were predictive for sperm retrieval. The same parameters and younger age were predictive factors for shorter time for sperm recovery. After multivariable analysis, younger age, better semen parameters, better histological features and lower values of FSH remained predictive for shorter time for sperm retrieval while better semen and histology remained predictive factors for successful sperm retrieval. The predictive capacity of a score obtained by summing the points assigned for selected predictors (1 point for Sertoli cell only, 0.33 points for azoospermia, 0.004 points for each FSH mIU/ml) gave an area under the ROC curve of 0.843. Conclusions: This model can help the practitioner with counseling infertile men by reliably predicting the chance of obtaining spermatozoa with testicular sperm extraction when a repeat attempt is planne

PV Cell Characteristic Extraction to Verify Power Transfer Efficiency in Indoor Harvesting System

A method is proposed to verify the efficiency of low-power harvesting systems based on Photovoltaic (PV) cells for indoor applications and a Fractional Open-Circuit Voltage (FOCV) technique to track the Maximum Power Point (MPP). It relies on an algorithm to reconstruct the PV cell Power versus Voltage (P-V) characteristic measuring the open circuit voltage and the voltage/current operating point but not the short-circuit current as required by state-of-the-art algorithms. This way the characteristic is reconstructed starting from the two values corresponding to standard operation modes of dc-dc converters implementing the FOCV Maximum Power Point Tracking (MPPT) technique. The method is applied to a prototype system: an external board is connected between the transducer and the dc-dc converter to measure the open circuit voltage and the voltage/current operating values. Experimental comparisons between the reconstructed and the measured P-V characteristics validate the reconstruction algorithm. Experimental results show the method is able to clearly identify the error between the transducer operating point and the one corresponding to the maximum power transfer, whilst also suggesting corrective action on the programmable factor of the FOCV technique. The proposed technique therefore provides a possible way of estimating MPPT efficiency without sampling the full P-V characteristic

An 8 bit current steering DAC for offset compensation purposes in sensor arrays

Abstract. An 8 bit segmented current steering DAC is presented for the compensation of mismatch of sensors with current output arranged in a large arrays. The DAC is implemented in a 1.8 V supply voltage 180 nm standard CMOS technology. Post layout simulations reveal that the design target concerning a sampling frequency of 2.6 MHz is exceeded, worst-case settling time equals 60.6 ns. The output current range is 0–10 μA, which translates into an LSB of 40 nA. Good linearity is achieved, INL < 0.5 LSB and DNL < 0.4 LSB, respectively. Static power consumption with the outputs operated at a voltage of 0.9 V is approximately 10 μW. Dynamic power, mainly consumed by switching activity of the digital circuit parts, amounts to 100 μW at 2.6 MHz operation frequency. Total area is 38.6 × 2933.0 μm2

Design and Experimental Characterization of a Niti-Based, High-Frequency, Centripetal Peristaltic Actuator

Development and experimental testing of a peristaltic device actuated by a single shape-memory NiTi wire are described. The actuator is designed to radially shrink a compliant silicone pipe, and must work on a sustained basis at an actuation frequency that is higher than those typical of NiTi actuators. Four rigid, aluminum-made circular sectors are sitting along the pipe circumference and provide the required NiTi wire housing. The aluminum assembly acts as geometrical amplifier of the wire contraction and as heat sink required to dissipate the thermal energy of the wire during the cooling phase. We present and discuss the full experimental investigation of the actuator performance, measured in terms of its ability to reduce the pipe diameter, at a sustained frequency of 1.5 Hz. Moreover, we investigate how the diameter contraction is affected by various design parameters as well as actuation frequencies up to 4 Hz. We manage to make the NiTi wire work at 3% in strain, cyclically providing the designed pipe wall displacement. The actuator performance is found to decay approximately linearly with actuation frequencies up to 4 Hz. Also, the interface between the wire and the aluminum parts is found to be essential in defining the functional performance of the actuator

Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network

The application of deep learning to symbolic domains remains an active research endeavour. Graph neural networks (GNN), consisting of trained neural modules which can be arranged in different topologies at run time, are sound alternatives to tackle relational problems which lend themselves to graph representations. In this paper, we show that GNNs are capable of multitask learning, which can be naturally enforced by training the model to refine a single set of multidimensional embeddings $\in \mathbb{R}^d$ and decode them into multiple outputs by connecting MLPs at the end of the pipeline. We demonstrate the multitask learning capability of the model in the relevant relational problem of estimating network centrality measures, focusing primarily on producing rankings based on these measures, i.e. is vertex $v_1$ more central than vertex $v_2$ given centrality $c$?. We then show that a GNN can be trained to develop a \emph{lingua franca} of vertex embeddings from which all relevant information about any of the trained centrality measures can be decoded. The proposed model achieves $89\%$ accuracy on a test dataset of random instances with up to 128 vertices and is shown to generalise to larger problem sizes. The model is also shown to obtain reasonable accuracy on a dataset of real world instances with up to 4k vertices, vastly surpassing the sizes of the largest instances with which the model was trained ($n=128$). Finally, we believe that our contributions attest to the potential of GNNs in symbolic domains in general and in relational learning in particular.Comment: Published at ICANN2019. 10 pages, 3 Figure

A gated oscillator clock and data recovery circuit for nanowatt wake-up and data receivers

This article presents a data-startable baseband logic featuring a gated oscillator clock and data recovery (GO-CDR) circuit for nanowatt wake-up and data receivers (WuRxs). At each data transition, the phase misalignment between the data coming from the analog front-end (AFE) and the clock is cleared by the GO-CDR circuit, thus allowing the reception of long data streams. Any free-running frequency mismatch between the GO and the bitrate does not limit the number of receivable bits, but only the maximum number of equal consecutive bits (Nm). To overcome this limitation, the proposed system includes a frequency calibration circuit, which reduces the frequency mismatch to ±0.5%, thus enabling the WuRx to be used with different encoding techniques up to Nm = 100. A full WuRx prototype, including an always-on clockless AFE operating in subthreshold, was fabricated with STMicroelectronics 90 nm BCD technology. The WuRx is supplied with 0.6 V, and the power consumption, excluding the calibration circuit, is 12.8 nW during the rest state and 17 nW at a 1 kbps data rate. With a 1 kbps On-Off Keying (OOK) modulated input and −35 dBm of input RF power after the input matching network (IMN), a 10^(−3) missed detection rate with a 0 bit error tolerance is measured, transmitting 63 bit packets with the Nm ranging from 1 to 63. The total sensitivity, including the estimated IMN gain at 100 MHz and 433 MHz, is −59.8 dBm and −52.3 dBm, respectively. In comparison with an ideal CDR, the degradation of the sensitivity due to the GO-CDR is 1.25 dBm. False alarm rate measurements lasting 24 h revealed zero overall false wake-ups

Photoresponse from noble metal nanoparticles-multi walled carbon nanotube composites

In this Letter, we investigated the photo-response of multi wall carbon nanotube-based composites obtained from in situ thermal evaporation of noble metals (Au, Ag, and Cu) on the nanotube films. The metal deposition process produced discrete nanoparticles on the nanotube outer walls. The nanoparticle-carbon nanotube films were characterized by photo-electrochemical measurements in a standard three electrode cell. The photocurrent from the decorated carbon nanotubes remarkably increased with respect to that of bare multiwall tubes. With the aid of first-principle calculations, these results are discussed in terms of metal nanoparticle–nanotube interactions and electronic charge transfer at the interface.VC 2012 American Institute of Physics

Applications of three-dimensional carbon nanotube

In this paper, we show that it is possible to synthesize carbon-based three-dimensional networks by adding sulfur, as growth enhancer, during the synthesis process. The obtained material is self-supporting and consists of curved and interconnected carbon nanotubes and to lesser extent of carbon fibers. Studies on the microstructure indicate that the assembly presents a marked variability in the tube external diameter and in the inner structure. We study the relationship between the observed microscopic properties and some potential applications. In particular, we show that the porous nature of the network is directly responsible for the hydrophobic and the lipophilic behavior. Moreover, we used a cut piece of the produced carbon material as working electrode in a standard electrochemical cell and, thus, demonstrating the capability of the system to respond to incident light in the visible and near-ultraviolet region and to generate a photocurrent