MRC Laboratory of Molecular Biology
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Digital interoperability in logistics and supply chain management: state-of-the-art and research avenues towards Physical Internet
No full textInteroperability is playing an increasing role for today's logistics and supply chain management (LSCM) because of the trends of cooperation or coopetition. Especially, digital interoperability concerning data or information exchange becomes a key enabler for the next evolutions that will massively rely upon digitalization, artificial intelligence, and autonomous systems. The notion of Physical Internet (PI) is one such evolution, an innovative worldwide logistic paradigm aimed at interconnecting and coordinating logistics networks for efficiency and sustainability. This paper investigates how digital interoperability can help interconnect logistics and supply networks as well as the operational solutions for sustainable development, and examines the new challenges and research opportunities for digital interoperability under the PI paradigm. To this end, we study the most relevant technologies for digital interoperability in LSCM, via a bibliometric analysis based on 208 papers published during 2010−2020. The results reveal that the present state-of-the-art solutions of digital interoperability are not fully aligned with PI requirements and show new challenges, research gaps and opportunities that need further discussion. Accordingly, several research avenues are suggested to advance research and applications in this area, and to achieve interconnection in logistics and supply networks for sustainability
Unbalanced exchange flow and its implications for the night cooling of buildings by displacement ventilation
No full textPassive ventilation of buildings at night forms an essential part of a low-energy cooling strategy, enabling excess heat that has accumulated during the day to self-purge and be replaced with cooler night air. Instrumental to the success of a purge are the locations and areas of ventilation openings, and openings positioned at low and at high levels are a common choice as there is then the expectation that a buoyancy-driven displacement flow will establish and persist. Desirable for their efficiency, displacement flows guide excess heat out through high-level openings and cooler air in through low-level openings. Herein we show that displacement flow cannot be maintained for the full duration of a purge. Instead, the flow must transition to an ‘unbalanced exchange flow’, whereby the cool inflow of air at low level is maintained but there is now a warm outflow and a cool inflow occurring simultaneously at the high-level opening. The internal redistribution of heat caused by this exchange alters the rate at which heat is self-purged and the time thought necessary to complete a purge. We develop a theoretical model that captures and predicts these behaviours. Our approach is distinct from all others which assume that a displacement flow will persist throughout the purge. Based on this enhanced understanding, and specifically that the transition to unbalanced exchange flow changes the rate of cooling and resultant emptying times, we anticipate that practitioners will be better placed to design passive systems that meet their target specifications for cooling
Understanding of Neighboring Fe-N<inf>4</inf>-C and Co-N<inf>4</inf>-C Dual Active Centers for Oxygen Reduction Reaction
No full textSingle atomic dispersed M-N-C (M = Fe, Co, Ni, Cu, etc.) composites display excellent performance for catalytic reactions. However, the analysis and understanding of neighboring M-N-C centers at the atomic level are still insufficient. Here, FeCo-N-doped hollow carbon nanocages (FeCo-N-HCN) with neighboring Fe-N4-C and Co-N4-C dual active centers as efficient catalysts are reported. Spherical aberration-corrected high angle annular dark-field scanning transmission electron microscopy, small area (1 nm2) electron energy loss spectroscopy, and X-ray absorption spectroscopy data analysis and fitting prove the neighboring Fe-N4-C and Co-N4-C dual active structure in FeCo-N-HCN. Experimental tests and density functional theory calculation results reveal that the FeCo-N-HCN catalyst displays better catalytic activity than Fe single-metal catalyst for oxygen reduction reaction (ORR), which is attributed to the synergistic effect of Fe-N4-C and Co-N4-C dual active centers reducing the reaction energy barriers for ORR. Although the catalytic performance of the FeCo-N-HCN catalyst is not comparable to the-state-of-art catalysts reported due to the low metal contents (Fe: 1.96 wt% and Co: 1.31 wt%), these results can refresh the understanding of neighboring M-N-C centers at the atomic level and provide guidance for the design of catalysts in the future
Enhancement of Frequency Stability in Injection Locked Bulk Mode MEMS Oscillators
No full textThis paper reports experimental results demonstrating significant gains in frequency stability for bulk acoustic wave (BAW) silicon disk resonator oscillators due to the locking of degenerate modes. The results show that when two degenerate modes are locked, the minimum Allan deviation is improved by a factor of more than two times in comparison with the minimum Allan deviation for oscillators locked to the individual degenerate modes. A shortterm stability of 48.3 μHz (51 ppt @ 0.27 s integration time) is recorded for a MEMS oscillator with an output of 1 MHz which benchmarks favourably relative to the MEMS oscillator state-of-the-art and commercial crystal oscillators. The approach is applicable to the locking of oscillators based on degenerate modes generally and can be scaled to higher frequency axisymmetric resonators with the higher-order bulk modes also providing inherent immunity to shock and vibration
Development of a small modular boiling water reactor combined with external superheaters
No full textThe balance between sustainability, energy security and affordability are important trade-offs to consider in decarbonizing the current energy system. The two practical alternatives for moving forward seem to be either reducing the energy storage costs to enable deployment the intermittent renewables on a large scale or developing an affordable and more flexible nuclear power. A small modular boiling water reactor combined with external superheaters offers a significant improvement to the conventional nuclear system. The potential benefits include improvement in cycle thermal efficiency, reduction in the size of the vessel, and the capability to adjust load while maintaining the reactor operation at 100% of its full power. In this paper, the conceptual design of a Small Modular Boiling Water Reactor (SMBWR) combined with external superheaters is presented along with investigation into some of its core design performance characteristics. It is found that the 4-batch in-core fuel management scheme offers a more favorable performance compared to the 3-batch scheme as it has lower power peaking, less excess reactivity, and more negative coolant void coefficient (CVC). The combination of a multi-batch fuel arrangement, coolant temperature variation, and control rods are required to control the reactivity swing in the SMBWR while keeping the power peaking below the safety limit throughout the depletion cycle
Driving behavior oriented torque demand regulation for electric vehicles with single pedal driving
No full textDriving behaviors, induced by psychological activities and environment stimulation, impose the dominant impact on vehicle driving performance. To exhaustively improve the performance of electric vehicles (EVs), information unscrambled from various driving behaviors is recommended to be incorporated into the controlling process. In this context, a novel method is presented to regulate the torque demand of EVs with single pedal driving (SPD) by efficiently interpreting intention from different driving behaviors for eco driving. Specifically, a brand-new driving behavior identifier (DBI) is constructed by integrally employing the binary dragonfly algorithm (BDA) and adaptive neuro-fuzzy inference system with particle swarm optimization (ANFIS-PSO). Simultaneously, the whale optimization algorithm (WOA) generates the torque demand look-up tables (TDLTs) offline under different driving behaviors for SPD by referring to the constraints from drivability and energy efficiency. In the instant implementation, the driving behaviors are identified instantaneously by the DBI, and the homologous TDLTs are assigned to vehicle controller, thereby attaining efficient control of vehicle powertrain. A case study about the vehicle traction control is performed to validate the prospective optimal performance of the proposed method and further evaluate the impact on vehicle performance from driving behaviors
Stiffness and strength of stabilized organic soils—part ii/ii: Parametric analysis and modeling with machine learning
No full textPredicting the range of achievable strength and stiffness from stabilized soil mixtures is critical for engineering design and construction, especially for organic soils, which are often considered “unsuitable” due to their high compressibility and the lack of knowledge about their mechanical behavior after stabilization. This study investigates the mechanical behavior of stabilized organic soils using machine learning (ML) methods. ML algorithms were developed and trained using a database from a comprehensive experimental study (see Part I), including more than one thousand unconfined compression tests on organic clay samples stabilized by wet soil mixing (WSM) technique. Three different ML methods were adopted and compared, including two artificial neural networks (ANN) and a linear regression method. ANN models proved reliable in the prediction of the stiffness and strength of stabilized organic soils, significantly outperforming linear regression models. Binder type, mixing ratio, soil organic and water content, sample size, aging, temperature, relative humidity, and carbonation were the control variables (input parameters) incorporated into the ML models. The impacts of these factors were evaluated through rigorous ANN-based parametric analyses. Additionally, the nonlinear relations of stiffness and strength with these parameters were developed, and their optimum ranges were identified through the ANN models. Overall, the robust ML approach presented in this paper can significantly improve the mixture design for organic soil stabilization and minimize the experimental cost for implementing WSM in engineering projects
Virtual Reality design-build-test games with physics simulation: opportunities for researching design cognition
No full textIncreasing the range of methods available for researching design cognition provides new opportunities for studying the phenomena of interest. Here we propose an approach for observing design activities, using Virtual Reality (VR) design-build-test games with built-in physics simulation. To illustrate this, we report on two exploratory design workshops where two groups of participants worked to solve a technical design problem using such a platform. Participants were asked to sketch ideas to solve the problem, and then to design, test and iterate some of their developed design concepts in a VR game. Researchers were able to obtain continuous and multifaceted recordings of participants’ behavior during the various design activities. This included on-screen design activities, verbal utterances, physical gestures, digital models of design outputs, and records of the test outcomes. Our experiences with the workshops are discussed with respect to the opportunities that similar VR game platforms offer for design cognition research, both in general and specifically in terms of ideation, prototyping, problem reframing, intrinsic motivation and demonstrated vulnerability. VR game platforms not only offer a valuable addition to existing research options, but additionally offer a basis for developing training interventions in design education and practice
On-chip perivascularnichesupporting stemness of patient-derived glioma cells in a serum-free, flowable culture
No full textGlioblastoma multiforme (GBM) is the most common and the most aggressive type of primary brain malignancy. Glioblastoma stem-likecells (GSCs) can migrate in vascular niches within or away from the tumour mass, increasing tumour resistance to treatments and contributing to relapses. To study individual GSC migration and their interactions with the perivasculature of the tumour microenvironment, there is a need to develop a human organotypicin vitromodel. Herein, we demonstrated a perivascularniche-on-a-chip, in a serum-free condition with gravity-driven flow, that supported the stemness of patient-derived GSCs and foetal neural stem cells grown in a three-dimensional environment (3D). Endothelial cells from three organ origins, (i) human brain microvascular endothelial cells (hCMEC/D3), (ii) human umbilical vein endothelial cells (HUVECs) and, (iii) human lung microvascular endothelial cells (HMVEC-L) formed rounded microvessels within the extracellular-matrix integrated microfluidic chip. By optimising cell extraction protocols, systematic studies were performed to evaluate the effects of serum-free media, 3D cell cultures, and the application of gravity-driven flow on the characteristics of endothelial cells and their co-culture with GSCs. Our results showed the maintenance of adherent and tight junction markers of hCMEC/D3 in the serum-free culture and that gravity-driven flow was essential to support adequate viability of both the microvessel and the GSCs in co-culture (>80% viability at day 3). Endpoint biological assays showed upregulation of neovascularization-related genes (e.g., angiopoietins, vascular endothelial growth factor receptors) in endothelial cells co-cultured with GSCs in contrast to the neural stem cell reference that showed insignificant changes. The on-chip platform further permitted live-cell imaging of GSC - microvessel interaction, enabling quantitative analysis of GSC polarization and migration. Overall, our comparative genotypic (i.e.qPCR) and phenotypic (i.e.vessel permeability and GSC migration) studies showed that organotypic (brain cancer cells-brain endothelial microvessel) interactions differed from those within non-tissue specific vascular niches of human origin. The development and optimization of this on-chip perivascularniche, in a serum-free flowable culture, could provide the next level of complexity of anin vitrosystem to study the influence of glioma stem cells on brain endothelium
Electrotherapies for Glioblastoma
No full textNon-thermal, intermediate frequency (100–500 kHz) electrotherapies present a unique therapeutic strategy to treat malignant neoplasms. Here, pulsed electric fields (PEFs) which induce reversible or irreversible electroporation (IRE) and tumour-treating fields (TTFs) are reviewed highlighting the foundations, advances, and considerations of each method when applied to glioblastoma (GBM). Several biological aspects of GBM that contribute to treatment complexity (heterogeneity, recurrence, resistance, and blood-brain barrier(BBB)) and electrophysiological traits which are suggested to promote glioma progression are described. Particularly, the biological responses at the cellular and molecular level to specific parameters of the electrical stimuli are discussed offering ways to compare these parameters despite the lack of a universally adopted physical description. Reviewing the literature, a disconnect is found between electrotherapy techniques and how they target the biological complexities of GBM that make treatment difficult in the first place. An attempt is made to bridge the interdisciplinary gap by mapping biological characteristics to different methods of electrotherapy, suggesting important future research topics and directions in both understanding and treating GBM. To the authors' knowledge, this is the first paper that attempts an in-tandem assessment of the biological effects of different aspects of intermediate frequency electrotherapy methods, thus offering possible strategies toward GBM treatment