Urocortin-3 neurons in the mouse perifornical area promote infant-directed neglect and aggression

While recent studies have uncovered dedicated neural pathways mediating the positive control of parenting, the regulation of infant-directed aggression and how it relates to adult-adult aggression is poorly understood. Here we show that urocortin-3 (Ucn3)-expressing neurons in the hypothalamic perifornical area (PeFAUcn3) are activated during infant-directed attacks in males and females, but not other behaviors. Functional manipulations of PeFAUcn3 neurons demonstrate the role of this population in the negative control of parenting in both sexes. PeFAUcn3 neurons receive input from areas associated with vomeronasal sensing, stress, and parenting, and send projections to hypothalamic and limbic areas. Optogenetic activation of PeFAUcn3 axon terminals in these regions triggers various aspects of infant-directed agonistic responses, such as neglect, repulsion, and aggression. Thus, PeFAUcn3 neurons emerge as a dedicated circuit component controlling infant-directed neglect and aggression, providing a new framework to understand the positive and negative regulation of parenting in health and disease.

Dual-mode multifunction filter realized with a single voltage differencing gain amplifier (VDGA)

This article presents the dual-mode multifunction biquad filter realized employing only a single voltage differencing gain amplifier (VDGA), one resistor and three capacitors. The proposed filterwith one input and three outputs can configure as voltage-mode or current-mode filter circuit with the appropriate input injection choice. It can also synthesis the three standard filter functions, which are highpass, bandpass, and lowpass responses without modifying the circuit configuration. Orthogonal adjustment between the natural angular frequency (o) and the quality factor (Q) of the filter is achieved. Detail analysis of non-ideal VDGA effects and circuit component sensitivity are included. The circuit principle is verified by means of simulation results with TSMC 0.35-m CMOS process parameters.

Freehand to Digital Circuit Reconstruction Using HOG and SVM

Sketches are commonly used in the fields of engineering and architecture, especially for the early design phases. Engineers spend considerable time setting up initial designs using pencil and paper, and then redrawing them to any software. This problem can be solved by using the idea to scan the circuit sketch with android device which is drawn on the paper and translate it into standard layouts and run circuit simulations. The scanned image will be pre-processed and further segmented. The segmented image will be used to extract the features which are in turn given for classification. Recognizing sketches may seem so quick and intuitive to humans but it is really a big challenge for the machine. In this proposed work the aim is to achieve high precision trainable electronic circuit component recognizer for sketched circuits with fast response time and simple extensibility to new components.

A Non-Dissipative Equalizer with Fast Energy Transfer Based on Adaptive Balancing Current Control

In this study, an active inductive equalizer with fast energy transfer based on adaptive balancing current control is proposed to rapidly equilibrate lithium-ion battery packs. A multiphase structure of equalizer formed by many specific parallel converter legs (PCLs) with bidirectional energy conversion serves as the power transfer stage to make the charge shuttle back and forth between the cell and sub-pack or sub-pack and sub-pack more flexible and efficient. This article focuses on dealing with the problem of slow balancing rate, which inherently arises from the reduction of balancing current as the voltage difference between the cells or sub-packs decreases, especially in the later period of equalization. An adaptive varied-duty-cycle (AVDC) algorithm is put forward here to accelerate the balance process. The devised method has taken the battery nonlinear behavior and the nonideality of circuit component into consideration and can adaptively modulate the duty cycle with the change of voltage differences to maintain balancing current nearly constant in the whole equilibrating procedure. Test results derived from simulations and experiments are provided to demonstrate the validity and effectiveness of the equalizer prototype constructed. Comparing with the conventional fixed duty cycle (FDC) method, the improvements of 68.3% and 8.3% in terms of balance time and efficiency have been achieved.

Development of Heavy Metal Potentiostat for Batik Industry

The consumption of reactive dyes in the batik industry has led to a severe concern in monitoring the heavy metal level in wastewater. Due to the necessity of implementing a wastewater monitoring system in the batik factory, a Heavy Metal potentiostat (HMstat) was designed. The main goal of this study is to understand the optimal design concept of the potentiostat function in order to investigate the losses of accuracy in measurement using off-the-shelf devices. Through lab-scale design, the HMstat comprises of an analog potentiostat read-out circuit component (PRCC) and a digital control signal component (CSC). The PRCC is based on easy to use components integrated with a NI-myRIO controller in a CSC. Here, the myRIO was equipped with built-in analog to digital converter (ADC) and digital to analog converter (DAC) components. In this paper, the accuracy test and detection of cadmium(II) (Cd2+) and lead(II) (Pb2+) were conducted using the HMstat. The results were compared with the Rodeostat (an open source potentiostat available on the online market). The accuracy of the HMStat was higher than 95% and within the precision rate of the components used. The HMstat was able to detect Cd2+ and Pb2+ at −0.25 and −0.3 V, respectively. Similar potential peaks were obtained using Rodeostat (Cd2+ at −0.25 V and Pb2+ at −0.3 V).

Unexpected Behaviors in a Single Mesh Josephson Junction Based Self-Reproducing Autonomous System

In the literature, existing Josephson junction based oscillators are mostly driven by external sources. Knowing the different limits of the external driven systems, we propose in this work a new autonomous one that exhibits the unusual and striking multiple phenomena among which coexist the multiple hidden attractors in self-reproducing process under the effect of initial conditions. The eight-term autonomous chaotic system has a single nonlinearity of sinusoidal type acting on only one of the state variables. A priori, the simplicity of the system does not predict the richness of its dynamics. We also find that a limit cycle attractor widens to a parameter controlling coexisting multiple-scroll attractors through the splitting and the inverse splitting of periods. Multiple types of bifurcations are found including period-doubling and period-splitting (antimonotonicity) sequences to chaos, crisis and Hopf type bifurcation. To the best of our knowledge, some of these interesting phenomena have not yet been reported in similar class of autonomous Josephson junction based circuits. Moreover, analytical investigations based on the Hopf theory analysis lead to the expressions that determine the direction of appearance of the Hopf bifurcation, confirming the existence and determining the stability of bifurcating periodic solutions. To observe this latter bifurcation and to illustrate the theoretical analysis, numerical simulations are performed. Chaos can be easily controlled by the frequency of the linear oscillator, the superconducting junction current, as well as the gain of the amplifier or circuit component values. The circuit and Field Programmable Gate Arrays (FPGA)-based implementation of the system are presented as well.

Accurate prediction of genetic circuit behavior requires multidimensional characterization of parts

Mathematical models can aid the design of genetic circuits, but may yield inaccurate results if individual parts are not modeled at the appropriate resolution. To illustrate the importance of this concept, we study transcriptional cascades consisting of two inducible synthetic transcription factors connected in series. Despite the simplicity of this design, we find that accurate prediction of circuit behavior requires mapping the dose responses of each circuit component along the dimensions of both its expression level and its inducer concentration. With such multidimensional characterizations, we were able to computationally explore the behavior of 16 different circuit designs. We experimentally verified a subset of these predictions and found substantial agreement. This method of biological part characterization enables the use of models to identify (un)desired circuit behaviors prior to experimental implementation, thus shortening the design-build-test cycle for more complex circuits.