Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural and Hierarchical Partitioning of Virtual Microgrids in Power Distribution Network

Nowadays, the infrastructure and technologies in conventional distribution networks (CDNs) limit its further development to smart distribution networks. One way to overcome this is to develop CDNs using interconnected virtual microgrids (VMs); however, there is no consensus for an explicit definition of VMs. Therefore, in this paper, a comprehensive discussion on VMs is conducted, and a general framework for developing VMs is proposed. The core issue for developing VMs is to identify boundaries of VMs, and most of the suggested methods are based on analyzing operating states. In this paper, a different partitioning method, which is based on the analysis of structural characteristics, is proposed. The electrical coupling strength is defined as a composite weight coefficient for the analysis of electrical connection, and the electrical modularity is used to assess the quality of the partition so as to identify boundaries of VMs. This partitioning method is applied to the IEEE 33-bus distribution network and the PG&E 69-bus distribution network, and it can quickly evaluate the partitioning quality and effectively identify the boundaries of VMs.
Weighted Sum Energy Efficiency Optimization for Massive MIMO Two-Way Half-Duplex AF Relaying

We consider two-way amplitude and forward half-duplex massive multiple-input multiple output (MIMO) relaying with multiple user-pairs. Most of the existing massive MIMO relaying literature has optimized the network-centric global energy efficiency metric, which is a pseudo-concave (PC) function, and can be optimized using well-known Dinkelbach algorithm. We optimize the user-centric weighted sum energy efficiency (WSEE), which is defined as the weighted sum of energy efficiencies of all the users, and is not a PC function. We propose a successive convex approximation approach to optimize it, and analytically show that this approach yields a Karush–Kuhn–Tucker point of the original WSEE problem. We also reduce the computational complexity of the above approach by approximating it as a second order cone program. We numerically demonstrate the WSEE improvement achieved by the proposed algorithms over baseline equal- and random-power allocation algorithms.
Licochalcone A Protects the Blood–Milk Barrier Integrity and Relieves the Inflammatory Response in LPS-Induced Mastitis

Background/Aims: Mastitis is an acute clinical inflammatory response. The occurrence and development of mastitis seriously disturb women's physical and mental health. Licochalcone A, a phenolic compound in Glycyrrhiza uralensis, has anti-inflammatory properties. Here, we examined the effect of licochalcone A on blood-milk barrier and inflammatory response in LPS-induced mice mastitis. Methods: In vivo, we firstly established mice models of mastitis by canal injection of LPS to mammary gland, and then detected the effect of licochalcone A on pathological indexes, inflammatory responses and blood-milk barrier in this model. In vivo, Mouse mammary epithelial cells (mMECs) were treated with licochalcone A prior to the incubation of LPS, and then the inflammatory responses, tight junction which is the basic structure of blood-milk barrier were analyzed. Last, we elucidated the anti-inflammatory mechanism by examining the activation of mitogen-activated protein kinase (MAPK) and AKT/NF-κB signaling pathways in vivo and in vitro. Result: The in vivo results showed that licochalcone A significantly decreased the histopathological impairment and the inflammatory responses, and improved integrity of blood-milk barrier. The in vitro results demonstrated that licochalcone A inhibited LPS-induced inflammatory responses and increase the protein levels of ZO-1, occludin, and claudin3 in mMECs. The in vivo and in vitro mechanistic study found that the anti-inflammatory effect of licochalcone A in LPS-induced mice mastitis was mediated by MAPK and AKT/NF-κB signaling pathways. Conclusions and Implications: Our experiments collectively indicate that licochalcone A protected against LPS-induced mice mastitis via improving the blood–milk barrier integrity and inhibits the inflammatory response by MAPK and AKT/NF-κB signaling pathways.
Challenges and Prospects in Ocean Circulation Models

We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.
An Incentive Mechanism Design View for Hybrid Access in Small Cell Networks: Keeping a Secret Is Not Smart

In this paper, we investigate the hybrid access control policy in two-tier small cell networks from the perspective of incentive mechanism design, considering macro-cell base station's (MBS) private information. Then, we formulate this problem as a Stackelberg game. To be specific, the MBS and small cell base stations (SBSs) are modeled as leader and followers, respectively. A subsidy mechanism is adopted by MBS when the SBS can provide acceptable service level for macro user equipment. Moreover, we consider the impacts of MBS's private information on the Stackelberg equilibrium (SE) of the proposed game, and we present the equilibrium analysis and relationship under different available information circumstances. To obtain relatively satisfactory outcome for both MBS and SBS, we discuss the design of bargaining scheme based on the SE. Theoretical analysis and simulation results show that it is better for MBS to broadcast the private information to get more payoff from the perspective of incentive mechanism design.
Assessment of a Highly Multiplexed RNA Sequencing Platform and Comparison to Existing High-Throughput Gene Expression Profiling Techniques

The need to reduce per sample cost of RNA-seq profiling for scalable data generation has led to the emergence of highly multiplexed RNA-seq. These technologies utilize barcoding of cDNA sequences in order to combine samples into single sequencing lane to be separated during data processing. In this study, we report the performance of one such technique denoted as sparse full length sequencing (SFL), a ribosomal RNA depletion-based RNA sequencing approach that allows for the simultaneous sequencing of 96 samples and higher. We offer comparisons to well established single-sample techniques, including: full coverage Poly-A capture RNA-seq and microarray, as well as another low-cost highly multiplexed technique known as 3’ digital gene expression (3’ DGE). Data was generated for a set of exposure experiments on immortalized human lung epithelial (AALE) cells in a two-by-two study design, in which samples received both genetic and chemical perturbations of known oncogenes/tumor suppressors and lung carcinogens. SFL demonstrated improved performance over 3’ DGE in terms of coverage, power to detect differential gene expression, and biological recapitulation of patterns of differential gene expression from in vivo lung cancer mutation signatures.
Collision Avoidance: A Literature Review on Threat-Assessment Techniques

For the last few decades, a lot of attention has been given to intelligent vehicle systems, and in particular to automated safety and collision avoidance solutions. In this paper, we present a literature review and analysis of threat-assessment methods used for collision avoidance. We will cover algorithms that are based on single-behavior threat metrics, optimization methods, formal methods, probabilistic frameworks, and data driven approaches, i.e., machine learning. The different theoretical algorithms are finally discussed in terms of computational complexity, robustness, and most suited applications.
Calcium Dependent Reversible Aggregation of Escherichia coli Biomimicking Vesicles Enables Formation of Supported Vesicle Layers on Silicon Dioxide

The importance of using biomimicking membranes for various biological applications is rising, as such models are relevant for imitating real organisms. In addition, biomimicking membranes are usually much more repeatable in preparation and easier to handle during analysis than real organisms or biological membranes. In this work we developed a method for the adsorption of intact small unilamellar Escherichia coli (E. coli) vesicles (size Z-average of 73 nm) on SiO2 substrate material. We describe the adsorption process based on the use of two surface sensitive techniques, i.e., nanoplasmonic sensing (NPS) and quartz crystal microbalance (QCM). The acquired data show that the adsorption follows a two-step process. The first step is a slow adsorption of E. coli vesicle aggregates held together by 5 mM of calcium (size Z-average of 531 nm). The Z-average of the aggregates decreased almost three times when the calcium concentration was decreased to 0.1 mM. This suggests that the aggregates were disassembling to some extent when calcium was removed from the system. With both techniques, i.e., NPS and QCM, we observed a second rapid adsorption step after the solution was changed to deionized water. In this second step, the aggregates started to fall apart as the calcium concentration dropped, and the released vesicles started to adsorb onto unoccupied spots at the SiO2 surface of the sensors. Extensive release of mass from the surface was confirmed by QCM, where it was reflected by a sharp increase of frequency, while NPS, due to its lower sensing depth of a few tens of nanometers, did not record such a change. Taken together, we have developed a protocol to form a supported vesicle layer of E. coli vesicles on SiO2 surface using sodium 4-(2-hydroxyethyl)piperazine-1-ethanesulfonate buffer, thus enabling the preparation of E. coli biomimicking supported vesicle layers for interaction studies of compounds of interest. The immobilization happens via a two-step adsorption process.
Dynamic CoAP Mode Control in Real Time Wireless IoT Networks

IEEE 802.15. 4 is one of the preferred mechanisms to provide modulation and media access control in wireless Internet of Things networks. With the goal of preserving battery life, IEEE 802.15. 4 is characterized by low power consumption that results in low signal-to-noise ratios responsible of low transmission rates and high bit error rates. In these low rate lossy networks, and from the application layer perspective, the constrained application protocol provides lightweight session management and control with two modes of operation: 1) a reliable mode where retransmissions guarantee packet delivery at a cost of increased latency, power consumption, and throughput and 2) an unreliable mode that provides packet loss-prone delivery of packets with lower battery use. In this paper, we present a dynamic mode selection mechanism that extends battery life while minimizing latency as well as transmission rates and improving overall quality of service.
Chemical-Shift-Encoded Magnetic Resonance Imaging and Spectroscopy to Reveal Immediate and Long-Term Multi-Organs Composition Changes of a 14-Days Periodic Fasting Intervention: A Technological and Case Report

Objectives: The aim of this study was to investigate the feasibility of measuring the effects of a 14-day Periodic Fasting (PF) intervention (<200 cal) on multi-organs of primary interest (liver, visceral/subcutaneous/bone marrow fat, muscle) using non-invasive advanced magnetic resonance spectroscopic (MRS) and imaging (MRI) methods. Methods: One subject participated in a 14-day PF under daily supervision of nurses and specialized physicians, ingesting a highly reduced intake: 200 Kcal/day coupled with active walking and drinking at least 3 L of liquids/day. The fasting was preceded by a 7-day pre-fasting vegetarian period and followed by 14 days of stepwise reintroduction of food. The longitudinal study collected imaging and biological data before the fast, at peak fasting, and 7 days, 1 month, and 4 months after re-feeding. Body fat mass in the trunk, abdomen, and thigh, liver and muscle mass, were respectively computed using advanced MRI and MRS signal modeling. Fat fraction, MRI relativity index T2* and susceptibility (Chi), as well as Fatty acid composition, were calculated at all-time points. Results: A decrease in body weight (BW: −9.5%), quadriceps muscle volume (−3.2%), Subcutaneous and Visceral Adipose Tissue (SAT −34.4%; VAT −20.8%), liver fat fraction (PDFF = 1.4 vs. 2.6 % at baseline) but increase in Spine Bone Marrow adipose tissue (BMAT) associated with a 10% increase in global adiposity fraction (PDFF: 54.4 vs. 50.9%) was observed. Femoral BMAT showed minimal changes compared to spinal level, with a slight decrease (−3.1%). Interestingly, fatty acid (FA) pattern changes differed depending on the AT locations. In muscle, all lipids increased after fasting, with a greater increase of intramyocellular lipid (IMCL: from 2.7 to 6.3 mmol/kg) after fasting compared to extramyocellular lipid (EMCL: from 6.2 to 9.5 mmol/kg) as well as Carnosine (6.9 to 8.1 mmol/kg). Heterogenous and reverse changes were also observed after re-feeding depending on the organ. Conclusion: These results suggest that investigating the effects of a 14-day PF intervention using advanced MRI and MRS is feasible. Quantitative MR indexes are a crucial adjunct to further understanding the effective changes in multiple crucial organs especially liver, spin, and muscle, differences between adipose tissue composition and the interplay that occurs during periodic fasting.
Analysis and Optimization of Multisection Capacitive DACs for Mixed-Signal Processing

This paper examines the concept of multisection capacitive digital-to-analog converters (MS-CDACs), which enables a wider range of CDAC section segmentation options beyond split-CDAC and C–2C methods. In order to study the proposed approach, analysis and simulations are first conducted for all possible section arrangements of a 6-bit resolution MS-CDAC with minimum-sized unit capacitors; the study shows that MS-CDAC provides various options with reduced total capacitance compared to a single-section CDAC, and allowing for the tradeoff of area, switching energy, and speed versus static linearity and <italic>kT</italic>/<inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> noise. Thus, it is possible to find a structure that minimizes total capacitance while satisfying required static linearity and noise that cannot be achieved with the existing methods. Compensation of nonlinearities due to parasitic capacitance is accomplished by sizing the bridge capacitance(s). To verify effectiveness in a more practical design scenario, this approach is applied to a 10-bit MS-CDAC design. Using metal–insulator–metal capacitors available in a standard CMOS technology, under the condition that 95% of Monte Carlo simulation results have at most 0.5 LSB of |DNL|, the selected 10-bit MS-CDAC structure reduces total capacitance and switching energy by 97% and 98%, respectively, and MSB capacitance by a factor of 26 relative to the single-section CDAC. The postlayout simulations were also conducted to validate the MS-CDAC approach, achieving <0.1 LSB of <inline-formula> <tex-math notation="LaTeX">$\vert \text {DNL}\vert _{\mathrm {max}}$ </tex-math></inline-formula> in the presence of additional layout parasitics.
Thermal Energy Processes in Direct Steam Generation Solar Systems: Boiling, Condensation and Energy Storage

Direct steam generation coupled is a promising solar-energy technology, which can reduce the growing dependency on fossil fuels. It has the potential to impact the power-generation sector as well as industrial sectors where significant quantities of process steam are required. Compared to conventional concentrated solar power systems, which use synthetic oils or molten salts as the heat transfer fluid, direct steam generation offers an opportunity to achieve higher steam temperatures in the Rankine power cycle and to reduce parasitic losses, thereby enabling improved thermal efficiencies. However, its practical implementation is associated with non-trivial challenges, which need to be addressed before such systems can become more economically competitive. Specifically, important thermal-energy processes take place during flow boiling, flow condensation and thermal-energy storage, which are highly complex, multi-scale and multi-physics in nature, and which involve phase-change, unsteady and turbulent multiphase flows in the presence of conjugate heat transfer. This paper reviews our current understanding and ability to predict these processes, and the knowledge that has been gained from experimental and computational efforts in the literature. In addition to conventional steam-Rankine cycles, the possibility of implementing organic Rankine cycle power blocks, which are relevant to lower operating temperature conditions, are also considered. This expands the focus beyond water as the working fluid, to include refrigerants also. In general, significant progress has been achieved in this space, yet there remain challenges in our capability to design and to operate high-performance and low-cost systems effectively and with confidence. Of interest are the flow regimes, heat transfer coefficients and pressure drops that are experienced during the thermal processes present in direct steam generation systems, including those occurring in the solar collectors, evaporators, condensers and relevant energy storage schemes during thermal charging and discharging. A brief overview of some energy storage options are also presented to motivate the inclusion of thermal energy storage into direct steam generation systems.
Integrated Approach of Airgap Insertion for Circuit Timing Optimization

Airgap technology enables air to be introduced in inter-metal dielectric (IMD). Airgap between certain wires reduces coupling capacitance due to the reduced permittivity; this can be utilized to decrease circuit delay. We propose an integrated approach of airgap insertion with the goal of circuit timing optimization. It consists of three sub-problems. We first select the layers that employ airgap, called airgap layers, that maximize total negative slack (TNS) improvement; this yields TNS improvement of 7% to 15% and worst negative slack (WNS) improvement of 2% to 8%, compared to a simple assumption of airgap layers. Second, we reassign the layers of wires such that more wires on critical paths can be placed in airgap layers. This is formulated as integer linear programming (ILP), and a more practical heuristic algorithm is also proposed. It provides an additional 17% TNS improvement and 6% WNS improvement. Finally, we perform airgap insertion through ILP formulation, where a number of design rules are modeled with linear constraints. To reduce the heavy runtime of ILP, a layout partitioning technique is also applied. It implements a feasible airgap mask in a manageable time where the amount of inserted airgap is close to the optimal solution.
What Is the Maximum Achievable Oscillation Frequency in a Specified CMOS Process?

This paper for the first time presents an analytical approach for estimating maximum achievable oscillators’ frequency in a specific CMOS process independent of their topology. By employing the Mason function in the first place, it has been proven that ring oscillator with an inductive load can achieve higher oscillation frequencies compared to the other topologies. Then, by applying two-port analysis at the oscillation edge, the oscillation frequency as a function of circuit variables like passive network topology, number of stages, elements of the passive network, gain, and the phase difference between two ports can be achieved. In order to evaluate the maximum oscillation frequency, maximized frequency is applied to the space of variables. This analysis proposes a systematic procedure for designing an oscillator with maximum frequency in desired CMOS process for a known quality factor of passive elements. To examine the feasibility of the proposed technique, this methodology is applied to an optimal oscillator structure. The simulation results confirm that maximum achievable oscillator frequency is 20%–30% higher compared to the oscillator designed with conventional approach. The simulations are performed in the 0.18- $\mu \text{m}$ TSMC technology.
Thermal-aware Test Scheduling Strategy for Network-on-Chip based Systems

Rapid progress in technology scaling has introduced massive parallel computing systems with multiple cores on the integrated circuit (IC), in which a flexible and scalable packet-switched architecture, Network-on-Chip (NoC), is commonly used for communication among the cores. However, technology scaling has also increased the susceptibility to internal defects in such systems. So, manufacturing tests of such multicore systems is crucial and this is a complex and time-consuming process. Due to stress on time-to-market, test engineers focus on the reduction of testtime and perform parallel tests of cores. Due to aggressive technology scaling into the nanometer regime, power consumption is also becoming a significant burden. Moreover, power consumption during manufacturing tests is more as compared to normal operation. In addition, peak power consumption is often significantly higher than the average power values. The consumed power leads to high temperature and creates hotspots, which in turn leads to failure of good parts, resulting in yield loss. Thermal safety during testing is an utmost challenging problem in NoC-based multicore systems, including three-dimensional NoC-based (3D NoC) multicore systems due to stacking of layers. This work proposes a preemptive test scheduling technique for NoC-based multicore systems to reduce the testtime by minimizing conflicts of resource usage. The preemptive test scheduling problem has been formulated using Integer Linear Programming (ILP). In this article, authors have also presented a thermal-aware test scheduling technique to test cores in 2D as well as 3D stacked NoC-based multicore systems using a Particle Swarm Optimization (PSO) based approach. To improve the solution further, several innovative augmentation techniques have been incorporated in the basic PSO. Experimental results highlight the effectiveness of the proposed method in reducing testtime and peak temperature under the power constraints and achieve a tradeoff between testtime and peak temperature.