Miracle-dz/UniFAR-FTUs huggingface dataset:
Intra-mammary molecular mechanisms involved in the response to changes in milking frequency : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, Palmerston North, New Zealand

In dairy cows, short-term changes of milking frequency (MF) in early lactation have been shown to produce an immediate and a long-term effect on milk yield (MY). The effect is controlled locally within the mammary gland by as yet unknown factors. To investigate the intra-mammary molecular mechanisms that are involved in the MY response to MF, a unilateral milking frequency (UMF) experiment was conducted with udder halves of 17 multiparous pasture-fed dairy cows milked either four times a day (4x) or once a day (1x) for fourteen days from 5 ± 2 days in milk (DIM). Mean udderhalf MY during the treatment period was higher from the 4x compared to 1xudder halves and once returned to twice a day milking, continued to be higher until 200 DIM. Mammary biopsies were obtained on day fourteen of treatment from both udder halves of ten cows. Proliferation of mammary cells was higher in 4x-udder halves compared to 1x, whereas no difference in apoptosis levels was detected. Abundance of major milk protein gene mRNA was higher in tissue samples from 4x-udder halves compared with 1x. The effects of changes of MF in early lactation on the prolactin (PRL) and insulinlike growth factor I (IGF-I) pathways to determine their role in the MY response to MF. The activation of signal transducer and activator of transcription (STAT) 5 was measured as an indication of PRL signalling, which was higher following 4x-milked mammary tissue samples compared to 1x-milked, and correlated highly with milk protein gene mRNA abundance. Activation of STAT5 also correlated with the protein abundance of the extracellular matrix (ECM) interacting protein β1-integrin, which suggest a
Design of a controllable variable buoyancy module and its performance analysis as a cascaded system for selective underwater deployment

Variable buoyancy systems (VBSs) are commonly used in underwater vehicles to achieve efficient heave motion. Most of the time, these systems are used as a part of conventional underwater vehicles with diverse methods to achieve the necessary buoyancy variation. The potential of VBSs as standalone systems for heave motion underwater has not been given due attention and is still an unexplored area. In this paper, the design of a VBS as a standalone module for heave control and the possibility of using multiple such modules in a cascaded structure for selective underwater deployment is presented. Such cascaded systems have a variety of applications ranging from coastal surveillance to selective deployment for ocean sampling, and so on. A metallic-bellows-based variable buoyancy module (VBM), actuated using linear actuators, is proposed here. The mathematical modelling of the VBM and its open-loop performance are analysed for suitability with regards to the system to be cascaded. Two prototypes have been developed based on the optimal design requirements and tested. The developed modules are simple and efficient for shallow water applications, and can be used as add-ons for existing underwater vehicles or can just be used as standalone systems. These two modules are then cascaded and the performance of the cascaded system is analysed with simulations and experiments. The analysis shows the suitability of the system for selective deployment at various depths.
Deterministic Leader Election in Anonymous Radio Networks

Leader election is a fundamental task in distributed computing. It is a symmetry breaking problem, calling for one node of the network to become the leader, and for all other nodes to become non-leaders. We consider leader election in anonymous radio networks modeled as simple undirected connected graphs. Nodes communicate in synchronous rounds. In each round, a node can either transmit a message to all its neighbours, or stay silent and listen. A node v hears a message from a neighbour w in a given round if v listens in this round and if w is its only neighbour transmitting in this round. If v listens in a round in which more than one neighbour transmits, then v hears noise that is different from any message and different from silence. We assume that nodes are identical (anonymous) and execute the same deterministic algorithm. Under this scenario, symmetry can be broken only in one way: by different wake-up times of the nodes. In which situations is it possible to break symmetry and elect a leader using time as symmetry breaker? In order to answer this question, we consider configurations. A configuration is the underlying graph with nodes tagged by non-negative integers with the following meaning. A node can either wake up spontaneously in the round shown on its tag, according to some global clock, or can be woken up hearing a message sent by one of its already awoken neighbours. The local clock of a node starts at its wakeup and nodes do not have access to the global clock determining their tags. A configuration is feasible if there exists a distributed algorithm that elects a leader for this configuration. Our main result is a complete algorithmic characterization of feasible configurations. More precisely, we design a centralized decision algorithm, working in polynomial time, whose input is a configuration and which decides if the configuration is feasible. Using this algorithm we also provide a dedicated deterministic distributed leader election algorithm for each feasible configuration that elects a leader for this configuration in time O(n2σ, where n is the number of nodes and σ is the difference between the largest and smallest tag of the configuration. We then ask the question whether there exists a universal deterministic distributed algorithm electing a leader for all feasible configurations. The answer turns out to be no, and we show that such a universal algorithm cannot exist even for the class of 4-node feasible configurations. We also prove that a distributed version of our decision algorithm cannot exist.
Event-Triggered Localization Algorithm Based On Rf with IR Fingerprint and RSSI with PSO Techniques

Wireless sensor network is the field in which there are mobile sensor nodes. WSNs field is becoming immensely popular with thousands of tiny sensor nodes because of their vast applicability in myriad of applications for e.g. collecting data from unattended hazardous environments, monitoring, emergency rescue operations, and surveillance in military in the hostile, unfavourable terrains. Mobile Wireless Sensor Networks is an arising area for research in contradiction to their well-entrenched predecessor. Such networks are more versatile, flexible than the static sensor networks because in any scenario, the mobile wireless sensor networks can be deployed and contend with brisk topology variations. In this paper an event-triggered localization algorithm is proposed which is based on Radio Frequency with infrared Frequency fingerprint and RSSI with PSO techniques. The localization algorithm is applied for curtailing the error of average localization for mobile WSN and it also utilized for the escalation speed
NVMe Virtualization for Cloud Virtual Machines

Public clouds are rapidly moving to support Non-Volatile Memory Express (NVMe) based storage to meet the ever-increasing I/O throughput and latency demands of modern workloads. They provide NVMe storage through virtual machines (VMs) where multiple VMs running on a host may share a physical NVMe device. The virtualization method used to share the NVMe capability has important performance, usability and security implications. In this paper, we propose three NVMe storage virtualization methods: PCI device passthrough, virtual block device method, and Storage Performance Development Kit (SPDK) virtual host target method. We evaluate these virtualization methods in terms of performance, scalability, CPU overhead, technology maturity, security, and availability to use one or more of these methods in IBM public cloud.
Differentiating the Neuropharmacological Properties of Nicotinic Acetylcholine Receptor-Activating Alkaloids

Alkaloids that target nicotinic acetylcholine receptors (nAChR) are of great interest because of the critical role they play in mood and anxiety. However, understanding of the neuropharmacological effects of nicotinic alkaloids, such as cotinine and anatabine, is very limited. In this study, we investigated the neuropharmacological effects of three naturally occurring alkaloids—nicotine, cotinine, and anatabine—in vitro and in vivo. A single injection of nicotine induced anxiolytic-like behavioral features in mice by using the SmartCube® behavioral profiling system, while cotinine and anatabine had no detectable effect. The results were corroborated by using the zebrafish novel tank test (NTT), which showed a profound anxiolytic-like effect induced by multiple doses of nicotine after a single 20-min treatment. When the regulation of dopamine and norepinephrine release—the neurotransmitter systems relevant for anxiety—were examined in vitro, we found that nicotine stimulated the release of both norepinephrine and dopamine, while cotinine and anatabine mainly stimulated the dopamine release. The molecular targets of nicotine were confirmed to be nAChRs with its most potent activities against α4β2 and α6/3β2β3 subtypes in vitro. Anatabine was a weaker agonist for these receptors than nicotine. Cotinine was the least potent nAChR compound, only being able to activate α4β2 and α6/3β2β3 subtypes at high doses and no detectable activities against α3β4 and α7 subtypes at the concentrations tested. The observed effects were unlikely due to the off-target effect, because these alkaloids did not bind or regulate >160 other molecular targets in vitro. Thus, the present results suggest that natural nicotinic alkaloids can induce an anxiolytic-like behavior in nonclinical animal models, potency of which may depend on the activation of various nAChRs and regulation of various neurotransmitter systems. Further investigations would help understand their effects on humans, because non-clinical studies should not be taken as a direct indication for human behavior and nicotine is not risk free.
Best Practices for HPC Workloads on Public Cloud Platforms: A Guide for Computational Scientists to Use Public Cloud for HPC Workloads

HPC (high performance computing) applications come with a variety of requirements for computation, communication, and storage; and many of these requirements can be met with commodity technology available in public clouds. In this article, we report on results for several well-known HPC applications on IBM public cloud, and we describe best practices for running such applications on cloud systems in general. Our results show that public clouds are not only ready for HPC workloads, but they can provide performance comparable to, and in some cases better than, current supercomputers.
Examining Attachment to Robots: Benefits, Challenges, and Alternatives

Potential applications of robots in private and public human spaces have prompted the design of so-called “social robots” that can interact with humans in social settings and potentially cause humans to attach to the robots. The focus of this article is an analysis of possible benefits and challenges arising from such human-robot attachment as reported in the HRI literature, followed by guidelines for the use and the design of robots that might elicit attachment bonds. We start by analyzing the potential benefits for humans becoming attached to robots, which might include increased natural interaction, effectiveness and acceptance of the robot, social companionship, and well-being for the human. Turning to the potential risks associated with human-robot attachment, we discuss the possibly suboptimal use of the robot in the most benign cases, but also the potential formation of unidirectional emotional bonds, and the potential for deception and subconscious influence of the robot on the person in more severe cases. The upshot of the analysis then is a recommendation to reconceptualize relationships with social robots in an attempt to retain potential benefits of human-robot attachment, while mitigating (to the extent possible) its downsides.
Research on Fluid Resistance and Heat Transfer Characteristics of Oil Cooling for Aircraft Electrical Motor

The high-efficiency oil cooling technology is one of the key technologies to ensure the safe and reliable operation of aircraft electrical motor. The high flow resistance caused by the high viscosity of oil brings a large oil pressure problem, which is easy to reduce the efficiency of the system and damage the driving machinery. Meanwhile, the Heat Transfer Coefficient (HTC) is a critical parameter that influences the cooling effect. In order to research the oil pressure characteristics and ensure the heat exchange effect of the oil channel. In this article, the Computational Fluid Dynamics (CFD) model of oil channel is created, fluid characteristics and heat transfer characteristics of oil channel are analyzed based on fluid and heat transfer theory. In order to further reduce the pressure drop, split-flow oil channel was established. The fluid pressure and heat transfer characteristics of the oil channel are analyzed, then the oil pressure and heat transfer coefficient are calculated by CFD. It’s proved the split-flow oil channel can greatly reduce the oil pressure, and has a higher HTC at the same oil pressure, which provides a basis for the design of the cooling structure of the aircraft electrical motor.
The Influence of Switching Frequency and Bus Voltage on Loss Performance of Electric Motor Drive System

Electric vehicles are gradually replacing fuel-powered vehicles. The electric motor drive system is mainly composed of traction motor, inverter and control unit, which is the core of electric vehicles. However, due to the energy density of lithium battery, electric vehicle is very sensitive to cruising mileage, so efficiency has become an important performance index. Therefore, it is imperative to study the loss performance of the electric motor drive system. The system loss mainly includes motor loss and inverter loss. In this paper, an interior permanent magnet synchronous motor (IPMSM) with 8 poles and 48 slots is taken as an example to build a simulation model in ANSYS Twin Builder, and the influence of switching frequency and bus voltage on loss performance of electric motor drive system are studied under NEDC driving conditions. Simulation results show that the selection of switching frequency needs to be combined with the actual driving conditions and weighed between inverter loss and motor loss; When the ampere turns is certain, increasing the bus voltage can reduce the inverter loss, so as to reduce the total loss of the electric motor drive system.
Improving Real World Performance of Vision Aided Navigation in a Flight Environment

Abstract : The motivation of this research is to fuse information from an airborne imaging sensor with information extracted from satellite imagery in order to provide accurate position when GPS is unavailable for an extended duration. A corpus of existing geo-referenced satellite imagery is used to create a key point database. A novel algorithm for recovering coarse pose using by comparing key points extracted from the airborne imagery to the reference database is developed. This coarse position is used to bootstrap a local-area geo-registration algorithm, which provides GPS-level position estimates. This research derives optimizations for existing local-area methods for operation in flight environments.
Evaluation of Generation Planning Based on Super-efficiency CCR Model

There are often multiple generation development options for a particular region in the generation planning stage. It is necessary to conduct a comprehensive evaluation of multiple indexes of power planning options. The data envelopment analysis (DEA) method can evaluate the effectiveness of generation schemes containing multiple indicators. However, the method is susceptible to the accuracy of the raw data, and outliers may significantly impact the evaluation results. This paper uses temporal production simulation to solve the index of the generation planning scheme as the original data required by the DEA model and put forward the evaluation method of the generation planning scheme based on the super-efficiency CCR model. The effectiveness and practicality of the method are verified by taking the generation planning scheme of a provincial power grid in 2025 as an example.
A Framework for Evaluation of Debug Path Performance in SoC

With rapidly growing demands of debugging in embedded systems, the architecture of debug subsystem is becoming a challenging task to system designers. A typical multi-processor system-on-chip (MP-SoC) has several heterogeneous cores, and few other critical IPs whose tracing is important from debugging point of view. Typically, in on-the-fly host debugging mode, the minimum expectation is that the debug data path is able to provide sufficiently large instruction traces of all heterogeneous cores without any loss in non-invasive debug mode. For debug and diagnosis, a comprehensive run-time observation into the MPSoC shows how the software (e.g real-time) is executed. It becomes a challenging task in the pre-silicon stage to evaluate this performance requirement of debugging datapath in absence of an appropriate benchmark suite or appropriate bus functional model. Even, it is equally problematic to convince the customers after the post-silicon stage, about the competitive advantage of the device in terms of debugging. In this paper, we are proposing a performance evaluation framework for debug infrastructure of embedded devices (e.g ARM CoreSight) using few standard benchmarks and also, proposing a few performance metrics. It reduces the performance evaluation time and improved design quality significantly.
Faster Noisy Power Method

Given the capability to handle diverse resource constraints, such as communication, memory, or privacy, the noisy power method (Hardt and Price, 2014), as a meta algorithm for computing the dominant eigenspace of a matrix, has found wide applications in data analysis and statistics (e.g., PCA). For an input data matrix, the performance of the algorithm, as with the noiseless case, is characterized by the spectral gap, which largely dictates the convergence rate and affects the noise tolerance level as well (Hardt and Price, 2014). A recent analysis (Balcan et al., 2016) improved the dependency over the consecutive spectral gap ( λ k − λ k +1 ) (Hardt and Price, 2014) to the dependency over ( λ k − λ q +1 ) , where q could be much greater than the target rank k and thus result in better performance by a significantly larger gap. However, ( λ k − λ q +1 ) could still be quite small and potentially limit the applicability. In this paper, we further improve the dependency of the convergence rate over O ( λ k − λ q +1 ) to dependency over ˜ O ( (cid:112) λ k − λ q +1 ) in a certain regime of a new parameter, for a faster noise-tolerant algorithm. To achieve this goal, we propose faster noisy power method which introduces the momentum acceleration into the noisy power iteration, and present a novel analysis that differs from previous ones (Hardt and Price, 2014; Balcan et al., 2016). We also extend our algorithm to the distributed PCA and memory-efficient streaming PCA and get improved results accordingly in terms of the gap dependence.
An Power Quality Data Classification Method of Important Power User of Low-voltage Distribution Network based on Twin Networks

Aiming at the difficult problems of multi-source heterogenous data of power quality monitoring and management of important power user in low-voltage distribution network, this paper proposes a power quality data classification method of important power user of low-voltage distribution network based on twin neural networks. Firstly, the historical data of power users of different low-voltage distribution networks collected by existing power grid enterprises is analyzed. Secondly, according to the existing national standards of power quality, the twin-network method of power quality data classification of important low-voltage power users is proposed to realize the characteristic analysis of power quality of different power users. Finally, a case verifies the validity of the proposed method, in order to provide reference for power quality analysis of low-voltage distribution network in China.
Intelligent ANFIS controller of two cooperative 3-DOF manipulators: the case of manipulation under non-slip constraints

The control and modeling of mechanical systems, especially robotic manipulators, is a domain that currently obsesses many researchers. The goal of this work is to develop an intelligent control model of two 3-DOF manipulators handling a common object. This model will allow us to control the gripping force by an intelligent controller (ANFIS controller) under non-slip constraints. In the first step, we are interested in the class of rigid manipulators with a simple open chain with 3-DOF. We first present a detailed study of the models used for the control and command of cooperative robots, namely the geometrical, kinematic and dynamic models: direct and inverse. We will then simulate these models on MATLAB/Simulink in order to validate and improve our modeling.
Unleashing The Flexibiliy of Distributed Energy Resources Based on Cloud-edge-end Architecture

Facing the increasing flexibility requirement brought by large-scale renewables and the goal of carbon neutrality, demand-side distributed energy resources (DERs) will take an active part in providing flexible ramping products (FRPs). However, their potential for flexibility is currently significantly curtailed, since i) the capacity of individual DER is too small to enter the market; ii) in the centralized control framework, the integration of numerous DERs lead to excessive computational burden and no guarantee of user’s privacy. To unleash the hidden flexibility of DERs, this paper proposes a virtual power plant (VPP) operation strategy in a cloud-edge-end hierarchical architecture to manage and control DERs: in edge-end synergy, the virtual battery models are established to describe the aggregate flexibility of flexible loads; in cloud-edge synergy, an economic scheduling model is proposed for VPP participating energy and FRP market. The numerical results demonstrate that the proposed strategy can effectively exploit the flexibility of DERs and reduce the operating cost of VPP.
0Voltage Oriented Control Strategy of Three Phase PWM Rectifier in Future-oriented Smart Charging Stations

The three-phase PWM rectifier is used in the future-oriented smart charging station to realize the bidirectional power flow and the suppression of harmonics injected into the grid. In order to improve the steady-state and dynamic performance of the three-phase PWM rectifier, this paper proposes a voltage-oriented control strategy. First, the basic principle of the three-phase PWM rectifier is analyzed, and its mathematical model in the abc and dq coordinate system is established. On this basis, a three-phase PWM rectifier control strategy based on grid voltage orientation is proposed, the dual closed-loop control the system is analyzed and the controller parameters are designed. Finally, the correctness of the analysis and the effectiveness of the proposed control strategy are verified through the steady-state and dynamic experiments.