Static analysis of logic programs by abstract interpretation requires designing abstract operators which mimic the concrete ones, such as unification, renaming, and projection. In the case of goal-driven analysis, where goal-dependent semantics are used, we also need a backward-unification operator, typically implemented through matching. In this paper, we study the problem of deriving optimal abstract matching operators for sharing and linearity properties. We provide an optimal operator for matching in the domain $\mathtt{ShLin}^{\omega }$, which can be easily instantiated to derive optimal operators for the domains $\mathtt{ShLin}^2$ by Andy King and the reduced product $\mathtt{Sharing} \times \mathtt{Lin}$.

In medical research, continuous variables are often categorised into two or more groups before being included in the analysis; this practice often comes with a cost, such as loss of power in analysis, less reliable estimates, and can often leave residual confounding in the results. In this research report, we show this by way of estimates from a regression analysis looking at the association between acute kidney injury and post-operative mortality in a sample of 194 neonates who underwent the Norwood operation. Two models were developed, one using a continuous measure of renal function as the main explanatory variable and second using a categorised version of the same variable. A continuous measure of renal function is more likely to yield reliable estimates and also maintains more statistical power in the analysis to detect a relation between the exposure and outcome. It also reveals the true biological relationship between the exposure and outcome. Categorising a continuous variable may not only miss an important message, it can also get it wrong. Additionally, given a non-linear relationship is commonly encountered between the exposure and outcome variable, investigators are advised to retain a predictor with a linear term only when supported by data. All of this is particularly important in small data sets which account for the majority of clinical research studies.

We present a self-biased three-stage GaN-based monolithic microwave integrated circuit low-noise amplifier (LNA) operating between 26 and 29 GHz for 5G mobile communications. The self-biasing circuit, common-source topology with inductive source feedback, and RLC negative feedback loops between gate and drain of the third transistor were implemented to achieve low noise, good port match, high stability, high gain, and compact size. Measurement results show that the LNA has a high and flat gain of 30.5 ± 0.4 dB with noise figure (NF) of 1.65–1.8 dB across the band. The three-stage topology also achieves high linearity, providing the 1 dB compression point output power (P1dB) of 21 dBm in the band. To our knowledge, this combination of NF, gain, and linearity performance represents the state of art of self-biased LNA in this frequency band.

Sharing analysis is used to statically discover data structures which may overlap in object-oriented programs. Using the abstract interpretation framework, we show that sharing analysis greatly benefits from linearity information. A variable is linear in a program state when different field paths starting from it always reach different objects. We propose a graph-based abstract domain which can represent aliasing, linearity, and sharing information and define all the necessary abstract operators for the analysis of a Java-like language.

In this study, we design a differential CMOS power amplifier using a 180-nm SOI RFCMOS process for 802.11n (64-QAM, 20 MHz bandwidth, 9.6 dB peak to average power ratio (PAPR)) applications. To minimize the chip area and mismatch in differential signals, we propose a layout method with an inter-stage matching network using a split inductor. By virtue of the symmetrical layout of the proposed split inductor, the mismatch in the differential signals is minimized, while the interconnection lines between the driver and power stages are shortened to minimize the overall chip area and the loss induced by the resistive parasitic components. The designed power amplifier is measured using a wireless local area network (WLAN) 802.11n signal to verify the feasibility of the proposed layout technique. The power amplifier achieved 20.34 dBm output power, while the measured EVM for the 802.11n applications is satisfied. From the measured results, we successfully prove the feasibility of the proposed power amplifier.

If $f,\,g:\,{{\mathbb{R}}^{n}}\,\to \,{{\mathbb{R}}_{\ge 0}}$ are non-negative measurable functions, then the Prékopa–Leindler inequality asserts that the integral of the Asplund sum (provided that it is measurable) is greater than or equal to the 0-mean of the integrals of $f$ and $g$. In this paper we prove that under the sole assumption that $f$ and $g$ have a common projection onto a hyperplane, the Prékopa–Leindler inequality admits a linear refinement. Moreover, the same inequality can be obtained when assuming that both projections (not necessarily equal as functions) have the same integral. An analogous approach may be also carried out for the so-called Borell-Brascamp-Lieb inequality.

In the analysis of logic programs, abstract domains for detecting sharing properties are widely used. Recently, the new domain ${\mathtt{ShLin}^{\omega}}$ has been introduced to generalize both sharing and linearity information. This domain is endowed with an optimal abstract operator for single-binding unification. The authors claim that the repeated application of this operator is also optimal for multibinding unification. This is the proof of such a claim.

LInear amplification using Non-linear Components (LINC) is an architecture that achieves linear power amplification for radio-frequency (RF) transmitters. This paper describes the impact of RF power amplifiers (PAs) class on the overall system performances. The linearity and efficiency of the LINC transmitter with different PA classes (AB, B, C, D, E, F, F−1, and J) are evaluated and compared, in terms of error vector magnitude (EVM), adjacent channel leakage ratio (ACLR), and power added efficiency (PAE), for a 16QAM modulation having 5.6 dB peak to average power ratio. Simulations are performed using a gallium-nitride high electron mobility transistor (GaN HEMT) for a power amplifier with an output power of 10 W at 900 MHz.

Burst mode operation is proposed as an efficiency improving technique for power amplifiers. The core idea is to modulate the amplitude of the envelope signal into a series of square-wave pulses such that the width of the signal burst or the total amount of pulses are varied according to the envelope. The phase information is still contained by the timing of the pulses. This work presents the efficiency and linearity analysis of burst mode radio frequency (RF)/power amplifier (PA). In addition, the efficiency performance is compared when the burst mode RF power amplifiers (PA) is connected to a wideband load or a narrowband filter. It is shown that burst mode PAs are more efficient than the conventional Class B PAs. To achieve an even more favorable efficiency, a transmission line is inserted between the output of the switching RF PA and the filter to improve the filter's impedance characteristic. Additionally, the efficiency and linearity of the burst mode PA with and without transmission line has been studied and simulated thoroughly. To demonstrate the validity of the efficiency formulas and linearity considerations, a printed circuit board (PCB)-mounted burst mode PA using a laterally diffused metal oxide semiconductor (LDMOS) transistor was fabricated. Measurements show a peak efficiency of 78% and 28.8 dBm of output power.

This paper demonstrates a highly efficient 3-stage Doherty power amplifier (PA) employing an envelope tracking (ET) technique. The ‘3-stage’ Doherty PA is the most efficient architecture for a high peak-to-average power ratio (PAPR) signal among the various Doherty PAs. However, because of the lower peaking biases than those of the ‘N-way’ Doherty PA, the proper load modulation is hard to be achieved. To get proper modulation, the peaking PAs' gate biases have been adaptively controlled using the ET technique, and the peak power and maximum efficiency characteristic along the backed-off output power region is successfully achieved. By ADS and Matlab simulations, the overall behavior of the 3-stage Doherty PA employing the ET technique has been fully analyzed. To maximize the overall efficiency of the proposed 3-stage Doherty PA, the unit PA has been designed using class F−1 PA. For verification, the amplifier is implemented using 5 W and 10 W PEP LDMOSFETs for the 802.16e mobile world interoperability for microwave access (WiMAX) at 1 GHz with a 8.5 dB PAPR. The measured drain efficiency of the proposed 3-stage Doherty PA is 55.5% at an average output power of 37 dBm, which is a 7.54 dB backed-off output power. The digital feedback predistortion (DFBPD) algorithm has been used to linearize the proposed PA considering the ET technique. After linearization, the −33.15 dB of relative constellation error (RCE) performance is achieved, satisfying the system specification. These results show that the 3-stage Doherty employing the ET technique and saturated PA is the most suitable PA for the highly efficient and linear transmitter.

Retinal ganglion cells (RGCs) are highly sensitive to changes in contrast, which is crucial for the detection of edges in a visual scene. However, in the natural environment, edges do not just vary in contrast, but edges also vary in the degree of blur, which can be caused by distance from the plane of fixation, motion, and shadows. Hence, blur is as much a characteristic of an edge as luminance contrast, yet its effects on the responses of RGCs are largely unexplored.

We examined the responses of rabbit RGCs to sharp edges varying by contrast and also to high-contrast edges varying by blur. The width of the blur profile ranged from 0.73 to 13.05 deg of visual angle. For most RGCs, blurring a high-contrast edge produced the same pattern of reduction of response strength and increase in latency as decreasing the contrast of a sharp edge. In support of this, we found a significant correlation between the amount of blur required to reduce the response by 50% and the size of the receptive fields, suggesting that blur may operate by reducing the range of luminance values within the receptive field. These RGCs cannot individually encode for blur, and blur could only be estimated by comparing the responses of populations of neurons with different receptive field sizes. However, some RGCs showed a different pattern of changes in latency and magnitude with changes in contrast and blur; these neurons could encode blur directly.

We also tested whether the response of a RGC to a blurred edge was linear, that is, whether the response of a neuron to a sharp edge was equal to the response to a blurred edge plus the response to the missing spatial components that were the difference between a sharp and blurred edge. Brisk-sustained cells were more linear; however, brisk-transient cells exhibited both linear and nonlinear behavior.

In the analysis of logic programs, abstract domains for detecting sharing and linearity information are widely used. Devising abstract unification algorithms for such domains has proved to be rather hard. At the moment, the available algorithms are correct but not optimal; i.e., they cannot fully exploit the information conveyed by the abstract domains. In this paper, we define a new (infinite) domain ShLinω which can be thought of as a general framework from which other domains can be easily derived by abstraction. ShLinω makes the interaction between sharing and linearity explicit. We provide a constructive characterization of the optimal abstract unification operator on ShLinω, and we lift it to two well-known abstractions of ShLinω, namely, to the classical Sharing × Lin abstract domain and to the more precise ShLin2 abstract domain by Andy King. In the case of single-binding substitutions, we obtain optimal abstract unification algorithms for such domains.