bluuebunny/crossref_metadata_2025_split huggingface dataset:
A neural circadian signal essential for ovulation is generated in the suprachiasmatic nucleus during each stage of the oestrous cycle
Authors: Silva Carlos‐Camilo , Cortés Georgina Daniela , Javier Cintia Yolanda , Flores Angélica , Domínguez Roberto 
Published: November 2019

New Findings
What is the central question of this study?
Is the suprachiasmatic nucleus the structure that generates the neural circadian signals that occur during every stage of the oestrous cycle, not only pro‐oestrus, and are these signals essential for proper regulation of ovulation?

What is the main finding and its importance?
Transient inhibition of Na+‐dependent action potentials in the suprachiasmatic nucleus by tetrodotoxin microinjection at 14.00 h inhibits ovulation irrespective of the stage of the oestrous cycle at which the procedure is performed. Microinjection of saline solution into the suprachiasmatic nucleus has a disruptive effect on ovulation that depends on the stage of the cycle at which it is administered.

AbstractReproduction is a highly timed process that depends on both the reproductive and circadian systems. The core oscillator of the latter resides at the suprachiasmatic nuclei (SCN) and it is pivotal for the regulation of the pro‐oestrus pre‐ovulatory surge of gonadotropins in females. There is evidence to suggest that this system may be involved in the regulation of neuroendocrine events that are essential for ovulation and that occur prior to pro‐oestrus. We explored this possibility by transiently inactivating the SCN. Female rats were implanted with guide cannulas aimed at the SCN. After recovery of the oestrous cycle, animals were injected with tetrodotoxin (TTX), artificial cerebrospinal fluid (ACSF) or saline solution while freely moving. Injections were performed at 14.00 h of each stage of the oestrous cycle. Animals were killed on the next predicted oestrus day, the number of ova shed was counted and intact rats at oestrus stage were used as absolute control. ACSF did not modify ovulation. Saline solution blocked ovulation in oestrus‐ and dioestrus‐injected rats. Irrespectively of the stage of the oestrous cycle, TTX blocked ovulation. These results lead us to suggest that a neural circadian signal, pivotal for triggering the gonadotropin pre‐ovulatory surge, arises from the SCN during the critical window of pro‐oestrus. We also suggest that a similar signal, needed for the regulation of other events that are indispensable for proper regulation of ovulation, is also generated in this nucleus during the other stages of the cycle at a similar time.
Intracranial pressure modulates aqueous humour dynamics of the eye
Authors: Ficarrotta Kayla R. , Passaglia Christopher L. 
Published: November 2019

Key pointsAn elevation in intracranial pressure (ICP) lowers conventional outflow facility (increases aqueous outflow resistance) of rat eyes.The reduction in outflow facility correlates with an increase in intraocular pressure (IOP).The effect of ICP elevation on outflow facility and IOP is blocked by TTX.The results indicate that aqueous humour dynamics is modulated by ICP‐driven neural feedback from the brain.This feedback mechanism may act to stabilize translaminar pressure across the optic nerve head and may provide a new avenue for glaucoma therapy.AbstractWhile intraocular pressure (IOP) is a well‐known risk factor for glaucoma, intracranial pressure (ICP) is attracting heightened interest because of its influence on optic nerve head biomechanics. Studies have shown that ICP can have marked impacts on posterior eye health by modifying the translaminar pressure gradient across the optic nerve. There is also growing evidence that IOP and ICP may be interconnected, although the mechanism of their putative interaction is unknown. We sought to test the hypothesis that ICP modulates IOP by altering aqueous humour dynamics. The anterior chamber and lateral ventricle of anaesthetized Brown‐Norway rats were cannulated with fine‐gauge needles connected to a programmable pump and saline reservoir, respectively. ICP was manipulated by varying reservoir height, and eye outflow facility (C) was determined from the pump flow rate required to hold IOP at different levels.Cwas 22 ± 4 nl/min/mmHg at resting ICP and 13 ± 3 nl/min/mmHg when ICP was raised 15 mmHg, a reduction of 41 ± 13% (n = 18). The decrease in outflow facility was independent of blood pressure, reversible, scaled with ICP elevation and correlated with increases in resting IOP. It was physiological in origin becauseCreturned to baseline values after the rats were killed and corneal application of TTX though ICP remained elevated. These results indicate that a neural feedback mechanism driven by ICP regulates conventional outflow facility in rats. The mechanism may protect the eye from translaminar pressure swings and may offer a new target for glaucoma treatment.
Heat Transfer and Pressure Drop Measurements in a High Aspect Ratio Channel With Circular Pins and Strip Fins
Authors: Nuntakulamarat Metapun , Shiau Chao-Cheng , Han Je-Chin 
Published: November 2019

Abstract
This paper focuses on the measurements of heat transfer enhancement and pressure drop of different pin or fin configurations in a high aspect ratio (AR = 9.57/1.2) channel. Two different pin-fin shapes including circular pins and strip fins were studied. Different pin-fin spacings for circular pins (S/D = 2, 4) and strip fins (S/W = 8, 16) were investigated, respectively. In addition, the thickness effect of the strip fin was included in this study. The regionally averaged heat transfer measurement method was used to acquire the heat transfer coefficients on two opposite featured surfaces within the test channel. For each configuration, the tested Reynolds number was ranging from 20,000 to 80,000. The results indicate that the channel with circular pins has better heat transfer enhancement and higher pressure loss than their strip fins counterparts. However, the strip fins are considered better designs in terms of thermal performance. For the gas turbine designers aim at developing an improved internal cooling feature, this work demonstrates the great potential of the strip fins as a novel and effective cooling design compared with the conventional circular pins.
A Nonlinear Autoregressive With Exogenous Inputs Artificial Neural Network Model for Building Thermal Load Prediction
Authors: Yu Byeongho , Kim Dongsu , Cho Heejin , Mago Pedro 
Published: November 2019

Abstract
Thermal load prediction is a key part of energy system management and control in buildings, and its accuracy plays a critical role to improve building energy performance and efficiency. Regarding thermal load prediction, various types of prediction model have been considered and studied, such as physics-based, statistical, and machine learning models. Physical models can be accurate but require extended lead time for model development. Statistical models are relatively simple to develop and require less computation time, but they may not provide accurate results for complex energy systems with intricate nonlinear dynamic behaviors. This study proposes an artificial neural network (ANN) model, one of the prevalent machine learning methods to predict building thermal load, combining with the concept of nonlinear autoregressive with exogenous inputs (NARX). NARX-ANN prediction model is distinguished from typical ANN models because the NARX concept can address nonlinear system behaviors effectively based on its recurrent architectures and time indexing features. To examine the suitability and validity of NARX-ANN model for building thermal load prediction, a case study is carried out using the field data of an academic campus building at Mississippi State University (MSU). Results show that the proposed NARX-ANN model can provide an accurate and robust prediction performance and effectively address nonlinear system behaviors in the prediction.
Engineer Energy Dissipation in 3D Graphene Nanolattice Via Reversible Snap-Through Instability
Authors: Ni Bo , Gao Huajian 
Published: November 2019

AbstractCarbon micro/nanolattice materials, defined as three-dimensional (3D) architected metamaterials made of micro/nanoscale carbon constituents, have demonstrated exceptional mechanical properties, including ultrahigh specific strength, stiffness, and extensive deformability through experiments and simulations. The ductility of these carbon micro/nanolattices is also important for robust performance. In this work, we present a novel design of using reversible snap-through instability to engineer energy dissipation in 3D graphene nanolattices. Inspired by the shell structure of flexible straws, we construct a type of graphene counterpart via topological design and demonstrate its associated snap-through instability through molecular dynamics (MD) simulations. One-dimensional (1D) straw-like carbon nanotube (SCNT) and 3D graphene nanolattices are constructed from a unit cell. These graphene nanolattices possess multiple stable states and are elastically reconfigurable. A theoretical model of the 1D bi-stable element chain is adopted to understand the collective deformation behavior of the nanolattice. Reversible pseudoplastic behavior with a finite hysteresis loop is predicted and further validated via MD. Enhanced by these novel energy dissipation mechanisms, the 3D graphene nanolattice shows good tolerance of crack-like flaws and is predicted to approach a specific energy dissipation of 233 kJ/kg in a loading cycle with no permanent damage (one order higher than the energy absorbed by carbon steel at failure, 16 kJ/kg). This study provides a novel mechanism for 3D carbon nanolattice to dissipate energy with no accumulative damage and improve resistance to fracture, broadening the promising application of 3D carbon in energy absorption and programmable materials.
An Atomistic Perspective on the Effect of Strain Rate and Lithium Fraction on the Mechanical Behavior of Silicon Electrodes
Authors: Darbaniyan Faezeh , Yan Xin , Sharma Pradeep 
Published: November 2019

Abstract
The process of charging and discharging of lithium-ion batteries results in the periodic intercalation and ejection of lithium ions in the anode material. High-capacity anode materials that are of significant interest for next-generation batteries, such as silicon, undergo large deformation during this process. The ensuing electro-chemo-mechanical stresses and accompanying microstructural changes lead to a complex state of inelastic deformation and damage in the silicon electrode that causes a significant capacity loss within just a few cycles. In this study, we attempt to understand, from an atomistic viewpoint, the mechanisms underlying the plasticity behavior of Si-anode as a function of lithiation. Conventional molecular dynamics simulations are of limited use since they are restricted to loading rates in the order of 108 s−1. Practical charging-discharging rates are several orders of magnitude slower, thus precluding a realistic atomistic assessment of the highly rate-dependent mechanical behavior of lithiated silicon anodes via conventional molecular dynamics. In this work, we use a time-scaling approach that is predicated on the combination of a potential energy surface sampling method, minimum energy pathway, kinetic Monte Carlo, and transition state theory, to achieve applied strain rates as low as 1 s−1. We assess and compare the atomistic mechanisms of plastic deformation in three different lithium concentration structures: LiSi2, LiSi, and Li15Si4 for various strain-rates. We find that the strain rate plays a significant role in the alteration of the deformation and damage mechanisms including the evolution of the plastic deformation, nucleation of shear transformation zone, and void nucleation. Somewhat anomalously, LiSi appears to demonstrate (comparatively) the least strain rate sensitivity.
The Failure Theory for Isotropic Materials: Proof and Completion
Authors: Christensen Richard M. 
Published: November 2019

Abstract
This work represents the completion of the many developments in recent years on failure theory for homogeneous and isotropic materials. Presented here is the resulting failure formalism in final and technically complete form. Significant further results are also given for the verification of the failure formalism. The scope of this paper goes from the history of misguided failure theory investigations right up to the present final tested forms ready for applications. For every predicted failure level in terms of the stresses, there is an accompanying ductility level. This ranges from brittle failure up to fully ductile failure. The entire theory is calibrated by only two specified parameters (failure properties). Nothing else is needed. The seemingly interminable, actually centuries long search for the missing theory of failure has finally been brought to a resolute and successful conclusion.
Stall and Recovery Process of a Transonic Fan With and Without Inlet Distortion
Authors: Zhang Wenqiang , Vahdati Mehdi 
Published: November 2019

Abstract
The aim of this research is to study the stall and recovery behavior of a transonic fan stage with and without inlet distortion. For this purpose, simulations of the stall and recovery process of NASA stage 67 are performed with clean and distorted inflow conditions. The rotor is pushed into stall by closing the exit nozzle. It is shown that in both cases, stall is initiated via spike but the subsequent development of the stall differs. In the stable rotating stall, both cases contain one stall cell traveling at 63% shaft speed. During the recovery process, when the exit nozzle is gradually opened, the size of this stall cell reduces as the corrected mass flow increases. Although the fan stalls at a larger mass flow with inlet distortion, it recovers to a similar corrected mass flow as the case with clean inflow, which indicates that inlet distortion has minor effects on the recovery process for this blade. In spite of the lack of data, detailed analysis based on past experience and physical reasoning is used to demonstrate the validity on numerical simulations. The author appreciates that a validated computational fluid dynamics (CFD) study can provide instructive results to other researchers.
Bayesian Estimation of Snow-Avalanche Victim Pose: A Method to Assist Human and/or Robot First Responders to Quickly Locate a Buried Victim
Authors: Bourne Joseph R. , Leang Kam K. 
Published: November 2019

Abstract
Finding a victim buried in a snow avalanche as quickly as possible can significantly increase the victim’s survival rate. A body-pose estimation algorithm is described that quickly and efficiently estimates the victim’s pose (3D location and orientation) underneath the snow. The algorithm exploits non-parametric Bayesian estimation and considers the uncertainty in an avalanche transceiver’s magnetic-field measurement. Simulation results compare the performances between three victim-search methods: (1) naive raster-scanning search, (2) traditional industry-standard search along the measured magnetic field lines, and (3) search by the Bayesian-based technique. The results show that the Bayesian-based technique accurately determines the victim’s pose within two minutes. In contrast, the raster-scanning and magnetic-field-line following methods yield search times more than three to four times longer.
Sliding-Mode Control With Switching-Gain Adaptation for Trajectory Tracking of Underactuated Unmanned Surface Vessels
Authors: Yu Rui , Qi Haochen , Upadhyay Kamal , Zhou Hua 
Published: November 2019

Abstract
Robust trajectory tracking is a vitally important issue to underactuated unmanned surface vessels (USVs). In this paper, a sliding-mode control method with switching-gain adaptation is proposed to force an underactuated USV to track a predefined trajectory, despite the presence of parametric uncertainties and unknown environmental disturbances induced by the wave loads, the wind and the ocean currents. The proposed controller is designed using sliding-mode control (SMC) and backstepping and switching-gain adaptation techniques. In this methodology, SMC and backstepping technique are combined to enhance the robustness of the system, and the switching-gain adaptation law based on the ideal switching-gain is employed to alleviate the chattering problem. In addition, we have proved the global asymptotic stability of the closed-loop system under the discontinuous thruster forces or the varying uncertain terms related to the velocities and the environmental disturbances. Finally, numerical simulations are provided to demonstrate the robustness and effectiveness of the proposed method for trajectory tracking of underactuated USVs.
Optimal Transient Real-Time Engine-Generator Control in the Series-Hybrid Vehicle
Authors: Lock Jonathan , Arvidsson Rickard , McKelvey Tomas 
Published: November 2019

Abstract
We study the dynamic engine-generator optimal control problem with a goal of minimizing fuel consumption while delivering a requested average electrical power. By using an infinite-horizon formulation and explicitly minimizing fuel consumption, we avoid issues inherent with penalty-based and finite-horizon problems. The solution to the optimal control problem, found using dynamic programming and the successive approximation method, can be expressed as instantaneous non-linear state-feedback. This allows for trivial real-time control, typically requiring 10–20 CPU instructions per control period, a few bytes of RAM, and 5–20 KiB of nonvolatile memory. Simulation results for a passenger vehicle indicate a fuel consumption improvement in the region of 5–7% during the transient phase when compared with the class of controllers found in the industry. Bench-tests, where the optimal controller is executed in native hardware, show an improvement of 3.7%, primarily limited by unmodeled dynamics. Our specific choice of problem formulation, a guaranteed globally optimal solution, and trivial real-time control resolve many of the limitations with the current state of optimal engine-generator controllers.
Combined Energy and Comfort Optimization of Air Conditioning System in Connected and Automated Vehicles
Authors: Wang Hao , Amini Mohammad Reza , Song Ziyou , Sun Jing , Kolmanovsky Ilya 
Published: November 2019

Abstract
In this paper, we propose a combined energy and comfort optimization (CECO) strategy for the air conditioning (A/C) system of the connected and automated vehicles (CAVs). By leveraging the weather and traffic predictions enabled by the emerging CAV technologies, the proposed strategy is able to minimize the A/C system energy consumption while maintaining the occupant thermal comfort (OTC) within the comfort constraints, where the comfort is quantified by a modified predictive mean vote (PMV) model adapted for an automotive application. A general CECO problem is formulated and addressed using model predictive control (MPC) and weather/traffic previews. Depending on the ways of exploiting the preview information and enforcing the OTC constraint, different MPCs are developed based on solving different variations of the general CECO problem. The CECO-based MPCs are then tested in simulation using an automotive A/C system simulation model (CoolSim) as the virtual testbed. The simulation results show that, over SC03 driving cycle, the proposed CECO-based MPCs outperform the baseline cabin temperature tracking controller, reducing the A/C system energy consumption by up to 7.6%, while achieving better OTC according to the PMV-based metrics. This energy saving in A/C system translates to 3.1% vehicle fuel economy improvement. The trade-off between energy efficiency and OTC for different control scenarios is also highlighted.
A Probabilistic Technique for Allocation of Tasks With Priorities in a School of Autonomous Mobile Robots
Authors: Bakshi Soovadeep , Feng Tianheng , Yan Zeyu , Chen Dongmei 
Published: November 2019

Abstract
Using Autonomous Mobile Robots (AMRs) to collaboratively complete tasks has received a lot of attention in recent years from both industry and acedemia, especially in applications related to manufacturing automation. However, in spite of the technological progress, there are many challenges yet to be addressed in prioritized task allocation and scheduling of a school of AMRs in real time. This paper focuses on the real-time task allocation problem for a school of AMRs, i.e., given a prioritized task list and multiple AMRs, determining the set of tasks to be completed by each AMR. This paper proposes a probabilistic task allocation method which formulates the problem as a log-likelihood maximization problem, and uses a cyclic optimization scheme. This algorithm is shown to perform better when compared to commonly-used algorithms for asymmetric clustering. This proposed algorithm can be combined with scheduling methods to generate a ‘cluster-first, order-second’ solution to the multi-AMR task planning problem.
Multi-Objective Optimal Design of a PID Sliding Mode Controller With Three Different Reaching Laws
Authors: Xu Xiaotian , Sardahi Yousef , Boker Almuatazbellah 
Published: November 2019

Abstract
Sliding mode controllers (SMCs) are well-known nonlinear control techniques. The design of a SMC involves the selection of a sliding mode surface and reaching law. The constant, exponential, and power rate reaching laws are the most widely used. Selecting a reaching law is often based on the desired reaching time; that is how fast the state trajectory approaches the switching manifold. However, the selection of a reaching law does not only affect the reaching time (tr) but also other design specifications such as the settling time (ts), overshoot (Mp), and tracking error (JIAE). Indeed, the design of a closed-loop system usually involves multiple and often conflicting objectives. Therefore, a multi-objective optimal design approach that takes into consideration all the design requirements should be adopted. Furthermore, a systematic study is needed to evaluate and compare the performance of a SMC controller under these reaching laws in multi-objective settings. To this end, the problems of designing a PID (Proportional-Integral-Derivative) sliding mode controller applied to linear and nonlinear dynamic systems using the three reaching laws are formulated as multi-objective optimization problems (MOPs). The objective space includes tr, Mp, ts, and JIAE and the parameter space consists of the design gains of the reaching laws and the sliding mode surface. The non-dominated sorting genetic algorithm (NSGA – II) is used to solve the optimization problem. The solution of the MOP is a Pareto front of optimal design points. Therefore, comparing three Pareto fronts is not a straightforward task. As a result, sections of the Pareto fronts that satisfy some legitimate constraints on the objective space are extracted. Then, a comparison among these sections is conducted graphically. The results show that the exponential rate reaching law outperforms the other two laws in most of the objectives under investigation.