Large Footprint Research Articles

예관(睨觀) 신규식(申圭植) 연구의 동향과 과제

The purpose of this study is to review existing academic research and present future research tasks about the life and ideology of Shin Kyusik, an anti-Japanese activist. We find this is a fitting way to commemorate the 100th anniversary of his death.
 Around 38 research theses about Shin Kyusik have been published to date. Among these theses, the majority focus on Shin’s independence struggles, while four studies are related to Daejonggyo religion, and five studies are about his book, 『Korean Spirit』 as well as the various poems he also authored. The impacts of these theses may seem minor when compared to his accomplishments, which left a large footprint in the Korean independence activists, however they are still valuable to inform us of his views and achievements.
 In this study, the historical facts about Shin’s acts are first introduced by classifying the results of previous studies according to their subject. Second, this study then examines some generally misunderstood facts about Shin’s life and his anti-Japanese activists, but those that were corrected through follow-up studies were also summarized. The views of the researchers on the contents of the issues are also expressed in this study.
 While previous studies have contributed to illuminating Shin Kyusik’s accomplishments to further Korean independence, researchers have not sufficiently delved into Shin’s ideology and his life as an independence activist. Errors concerning the date of Shin’s birth and the time of his exile to Shanghai have also been corrected through the follow-up studies, but his historic roles in establishing the Provisional Government of Korea still remains controversial.
 In the future, when conducting in-depth research on Shin Kyusik, it will also be necessary to focus on his ideology, his historic role and ideas in Daejonggyo Religion, and his solidarity with Chinese revolutionaries. It will also be worthwhile analyzing and discussing his poems to have a complete body of research about his life and ideology.

Germanium Monosulfide as a Natural Platform for Highly Anisotropic THz Polaritons.

Terahertz (THz) electromagnetic radiation is key to access collective excitations such as magnons (spins), plasmons (electrons), or phonons (atomic vibrations), thus bridging topics between optics and solid-state physics. Confinement of THz light to the nanometer length scale is desirable for local probing of such excitations in low-dimensional systems, thereby circumventing the large footprint and inherently low spectral power density of far-field THz radiation. For that purpose, phonon polaritons (PhPs) in anisotropic van der Waals (vdW) materials have recently emerged as a promising platform for THz nanooptics. Hence, there is a demand for the exploration of materials that feature not only THz PhPs at different spectral regimes but also host anisotropic (directional) electrical, thermoelectric, and vibronic properties. To that end, we introduce here the semiconducting vdW-material alpha-germanium(II) sulfide (GeS) as an intriguing candidate. By employing THz nanospectroscopy supported by theoretical analysis, we provide a thorough characterization of the different in-plane hyperbolic and elliptical PhP modes in GeS. We find not only PhPs with long lifetimes (τ > 2 ps) and excellent THz light confinement (λ0/λ > 45) but also an intrinsic, phonon-induced anomalous dispersion as well as signatures of naturally occurring, substrate-mediated PhP canalization within a single GeS slab.

Valorization of South African Coal Wastes through Dense Medium Separation

Sustainable management of coal waste is one of the major environmental concerns for coal mining, whether active or legacy, worldwide. Coal dump deposits demand a large physical area or footprint for disposal of solid waste, change the topography, and generate both pyritic dust and acid rock drainage (ARD) where pyritic coal waste is deposited. The beneficiation of dump deposits or, preferably, of coal waste prior to its dumping can reduce or even eliminate the liabilities related to coal waste management. In this work, dense medium separation studies of coal discards, using heavy liquids, resulted in three pooled fractions from typical South African coal waste discards from the Mpumalanga region for future use: (a) a fraction of low density with increased calorific value; (b) a fraction of intermediate density, rich in ash and acid neutralizing minerals and lower in sulfur; and (c) a fraction of high density, rich in sulfidic minerals including pyrite. The fractions were characterized using particle size analysis, sink-float studies, static tests to predict ARD potential, proximateand ultimate analysis, and gross calorific value. The results showed that approximately 70% of this discard coal is composed of a material of sufficient quality for energy generation in conventional power stations. A pyrite-rich concentrate made up 2% of the total discard mass; comprising more than 45% of the sulfidic mineral present in the feed and displaying no acid neutralizing capacity (ANC). The remaining discard fraction, with intermediate density, presented potential to be used for several ends including soil fabrication, co-disposal or as aggregate material in civil engineering; additional testing to ensure applicability for the selected re-purposing option should be chosen based on proposed use.

Evaluating the adoption of e-banking services by SMEs in the common monetary area

There has been limited study from a southern-African perspective investigating factors that affect the adoption of e-banking specific to small and medium enterprises (SMEs) in developing African economies. To date, little is known about SME uptake of e-banking in the southern African common monetary area (CMA), comprising South Africa, Lesotho, Namibia, and Eswatini. This knowledge gap is problematic for banks in providing SME support for the transition to e-banking, given the current move by banks toward embracing digital strategies. This study focused on a single bank with a large footprint in the CMA, intending to add to the body of academic knowledge regarding the adoption of e-banking services by SMEs. It employed a qualitative methodology involving one-on-one, semi-structured, open-ended interviews with purposefully selected Bank X staff in each country of the CMA, using the literature reviewed to identify themes relevant to the proposed conceptual model. The conclusions of this research have led to a framework for e-banking adoption. A framework such as this may positively impact the profitability and sustainability of an SME by ensuring the adoption of e-banking services and utilization of available financial products to improve business opportunities via the e-banking channels of Bank X.

New challenges for gravity concentration and classification of fine particles

“The net zero emission” mantra may prove to become the new “mother of invention” for minerals processing. The need for change is locked in, and rising, creating new opportunities, especially in gravity concentration and classification. The challenge is to identify and deliver what is required.This paper is concerned with the gravity concentration and classification of particles in a medium of water, involving particles typically finer than 1.0 mm. One of the greatest challenges is in delivering large scale, highly efficient, desliming at ∼10 μm to overcome the effects of viscosity, and in turn maximize the value of the resource. This need is most apparent in one of the world’s most significant commodities, iron ore.There should also be a much greater role for gravity concentration across this full-size range, increasingly in the range below 0.1 mm, the historical preserve of flotation. If the particle density can deliver sufficient selectivity, then in principle gravity concentration should be considered. This is especially true where reverse flotation is deployed, which requires a multi-stage flowsheet, very large footprint, and chemicals, to deliver what could be achieved in a single physical stage of gravity concentration. Mechanisms for amplifying segregation forces, including G forces and inclined settling, need to be exploited to deliver the necessary solids throughput.Classification will be challenged by the emerging requirements for gravity concentration, comminution, and coarse/fine particle flotation circuits to ensure beneficiation can straddle two decades in size ranges from 1.0 to 0.1 mm down to 0.1 to 0.01 mm, via classification at an intermediate size, nominally 0.1 mm. While in principle mechanical screens offer ideal classification, the hydrodynamic approach may ultimately deliver the optimum robustness, control, throughput, and efficiency, despite the variation in separation size with particle density, provided synergy can be realised by integrating it correctly within the overall circuit.

Memory access optimization for particle operations in computational fluid dynamics-discrete element method simulations

Computational Fluid Dynamics – Discrete Element Method is used to model gas-solid systems in several applications in energy, pharmaceutical and petrochemical industries. Computational performance bottlenecks often limit the problem sizes that can be simulated at industrial scale. The data structures used to store several millions of particles in such large-scale simulations have a large memory footprint that does not fit into the processor cache hierarchies on current high-performance-computing platforms, leading to reduced computational performance. This paper specifically addresses this aspect of memory access bottlenecks in industrial scale simulations. The use of space-filling curves to improve memory access patterns is described and their impact on computational performance is quantified in both shared and distributed memory parallelization paradigms. The Morton space filling curve applied to uniform grids and k-dimensional tree partitions are used to reorder the particle data-structure thus improving spatial and temporal locality in memory. The performance impact of these techniques when applied to two benchmark problems, namely the homogeneous-cooling-system and a fluidized-bed, are presented. These optimization techniques lead to approximately two-fold performance improvement in particle focused operations such as neighbor-list creation and data-exchange, with ∼ 1.5 times overall improvement in a fluidization simulation with 1.27 million particles.

Calculation of seasonal agricultural grey water footprint in monsoon region based on river reference conditions

Grey water footprint accounting is of great significance to water resources management. The two important parameters of grey water footprint accounting, the natural background concentration of pollutants and the pollutant export coefficient, have obvious seasonal differences in the monsoon region, while the possible seasonal differences of grey water footprint in the monsoon region had been less considered in the previous research of grey water footprint accounting. This paper calculated the seasonal agricultural grey water footprint of Zhangjiakou City in North China by taking the river reference condition of total phosphorus as its natural background concentration and considering the seasonal difference of river reference condition of total phosphorus and the pollutant export coefficient. The results showed that the agricultural grey water footprint calculated with the reference condition of total phosphorus as the natural background concentration were 1.60 and 1.38 times of that calculated with zero as the natural background concentration in the rainy season and dry season, respectively. Due to the seasonal difference in the proportion of pollutants entering the river and the reference condition of total phosphorus, the agricultural grey water footprint showed obvious seasonal differences. The agricultural grey water footprint in rainy season was 11.73 times higher than that in dry season. In the composition of agricultural grey water footprint in Zhangjiakou from 2003 to 2018, the grey water footprint of livestock and poultry accounted for a large proportion. Districts and counties with relatively large agricultural grey water footprint in Zhangjiakou were concentrated in the south and north of Zhangjiakou, mainly including Zhuolu, Huailai, Yuxian, Xuanhua and Zhangbei; The districts and counties with relatively small agricultural grey water footprint were mainly located in the urban area of Zhangjiakou, including Qiaodong District, Qiaoxi District and Xiahuayuan District. This paper could clarify the seasonal difference of agricultural grey water footprint accounting in monsoon region and promote the development of grey water footprint accounting methods.

Influence of COVID-19 on the 10-year carbon footprint of the Nagoya University Hospital and medical research centre

Background:Amidst the climate crisis, a key goal of the medical sector is to reduce its large carbon footprint. Although the Coronavirus disease 2019 (COVID-19) pandemic greatly impacted the medical sector, its influence on carbon footprints remains unknown. Therefore, the aim of this study was to evaluate changes in the carbon footprint of a university hospital with a medical research centre over the past 10 years.Methods:Data on electricity, gas, and water usage, pharmaceutical and medical supply costs, and waste amounts were recorded for Nagoya University Hospital from April 2010 to March 2021. The relevant emission factors were obtained from the Japanese government and the overall monthly carbon footprint was reported according to the Greenhouse Gas Protocol. The effect of the COVID-19 pandemic on the carbon footprint was then compared for three types of emission sources. Moreover, a regression model was used to plot quadratic functions as approximate functions using monthly carbon emissions and monthly average external temperatures. Finally, the monthly carbon footprint was calculated per hospital admission.Results:The overall carbon footprint of the hospital was 73,546 tCO2e in 2020, revealing an increase of 26.60% over the last 10 years. Carbon emissions from electricity consumption represented 26% of total emissions. The individual carbon footprints of pharmaceuticals, medical supplies, waste, and water usage also increased from 2010 to 2020. The overall monthly carbon footprint was positively correlated with the average monthly temperature (R2 = 0.7566, p < 0.001). Compared with 2019, the overall carbon footprint decreased by 2.19% in 2020. Moreover, the monthly carbon footprint per hospital admission increased significantly between 2018 (0.24 tCO2e/admission) and 2020 (0.26 tCO2e/admission) (p = 0.002).Conclusion:The overall carbon footprint of the hospital generally increased over the last decade. During the COVID-19 epidemic in 2020, the carbon footprint decreased slightly, likely because of the reduced number of patients. However, the carbon footprint per admission increased, which was attributed to more complicated patient backgrounds because of the ageing population. Therefore, evaluation of carbon emissions in the medical sector is urgently required in order to act on the climate crisis as soon as possible.

β-Glucosidase Immobilized on Magnetic Nanoparticles: Controlling Biomolecule Footprint and Particle Functional Group Density to Navigate the Activity-Stability Tradeoff.

In the present work, the immobilized footprint of β-glucosidase (BGL) on silica-coated iron oxide was explored to produce reusable catalysts with flexible active sites for high activity and heightened storage stability. Synthesized iron oxide particles were coated with silica and functionalized with various densities of (3-aminopropyl)triethoxysilane (APTES) to obtain particles with amine densities ranging from 0 to 3 × 10-5 mol/g particle. The amine-modified particles were activated with glutaraldehyde, and subsequently, BGL was immobilized using either a 0.1 or 1 mg/mL enzyme solution to produce biomolecules with a large or small footprint on the particle surface. The initial activity, activity for subsequent hydrolysis cycles, activity after extended storage, and biomolecule footprint were studied as a function of APTES density and concentration of enzyme used for immobilization. At high immobilization amounts, the specific activity and footprint were reduced, but the immobilized biomolecules were stable during storage. However, at low enzyme immobilizations, the activity of the enzymes was retained, the immobilized enzymes adopted large footprints, and the storage stability increased with APTES density relative to the free enzyme. These results highlight how controlling both the protein load and functional group density can yield immobilized enzymes possessing high activity, which are stable during storage.

SAR and ASCAT Tropical Cyclone Wind Speed Reconciliation

Wind speed reconciliation across different wind sources is critically needed for extending available satellite wind records in Tropical Cyclones. The deviations between wind references of extremes, such as the moored buoy data and dropsonde wind estimates for guidance on geophysical model function development, are one of the main causes of wind speed differences for wind products, for instance, the overestimation of Synthetic Aperture Radars (SARs) relative to ASCAT winds. The study proposes a new wind speed adjustment to achieve mutual adjustment between ASCAT CMOD7 winds and simultaneous SAR wind speeds. The so-called CMOD7D-v2 adjustment is constructed based on the statistical analysis of SAR and ASCAT Tropical Cyclone acquisitions between 2016 and 2021, showing a satisfactory performance in wind speed reconciliation for winds with speeds higher than 14 m/s. Furthermore, the error characteristics of the CMOD7D-v2 adjustment for Tropical Cyclone winds are analyzed using the Triple Collocation analysis technique. The analysis results show that the proposed wind adjustment can reduce ASCAT wind errors by around 16.0% when adjusting ASCAT winds to SAR wind speeds. In particular, when downscaling SAR winds, the improvement in ASCAT wind errors can be up to 42.3%, effectively alleviating wind speed differences across wind sources. Furthermore, to avoid the impacts of large footprints by ASCAT sensors, wind speeds retrieved from SAR VV signals (acting as a substitute for ASCAT winds) are adjusted accordingly and compared against SAR dual-polarized winds and collocated Stepped Frequency Microwave Radiometer (SFMR) observations. We find that the bias values of adjusted winds are lower than products from other adjustment schemes by around 5 m/s at the most extreme values. These promising results verify the plausibility of the CMOD7D-v2 adjustment, which is conducive to SAR and ASCAT wind speed comparisons and extreme wind analysis in Tropical Cyclone cases.

Development, evaluation, and implementation of building downwash and plume rise enhancements in AERMOD

ABSTRACT Recent research has pointed out many reasons why the building downwash formulation in AERMOD needs to be updated due to: overly simplified equations for building wake development; equations that do not account for porous or streamlined structures; a discontinuity in the streamline equation; and over predictions when compared to field observations for buildings with a large footprint. Because of these issues, a research study was initiated in late 2016 with an overall objective of improving the building downwash algorithms in PRIME. The research study involved the use of wind tunnel modeling to develop a database of wind speed and turbulence intensity measurements downwind of various rectangular solids and streamlined (i.e., tanks and towers) structures. Based on those measurements, new equations (PRIME2) were developed to better describe the turbulence increase and velocity deficit in building wakes for these structure types. The PRIME2 building wake equations for turbulence intensity increase and velocity deficit were shown to agree better with wind tunnel observations than the current PRIME equations in AERMOD. The new equations were documented in a journal article and were added to AERMOD’s PRIME subroutine. A new version of AERMOD was then compiled with the new enhanced turbulence and wind speed equations (PRIME2) for evaluation. The key feature of the PRIME2 equations is that building wake enhanced turbulence decays rapidly back to ambient levels above the top of the building versus the current PRIME theory that has constant enhanced turbulence extending up to the height of the wake. This paper provides details on the implementation of the PRIME2 code into AERMOD, PRIME plume rise enhancements, the field databases used to evaluate PRIME2, and the evaluation of PRIME2 against three field databases. The paper shows that AERMOD with the PRIME2 building downwash equations and other enhancements provides the overall best agreement with field observations. Implications: While AERMOD/PRIME is supposed to provide accurate and unbiased estimates (within a factor of two), recent research has identified several problems with the current building downwash theory in AERMOD and comparisons against field observations have shown significant under and overpredictions. One major problem is that the current theory has the wake effect extending well above the top of the building while new research shows that the wake effect decays rapidly above the top of the building. This could lead AERMOD to underpredict or overpredict ground-level concentrations. Based on recent wind tunnel tests, a new building downwash theory has been developed and documented in a Journal article. This theory has been added to the PRIME building downwash algorithm in AERMOD and is currently included as an Alpha option in AERMOD. This paper evaluates that new theory against field observations and demonstrates that the updated theory provides better agreement with field observations than the current AERMOD. This paper points out that research and development of model building downwash improvements should be an ongoing process to help ensure a “sustainable” future where these improvements can ultimately provide a model with unbiased performance and thereby allow for responsible industrial development. This study has shown that improvements can be made in a rather quick manner and be included as Alpha options in EPA model updates. The next challenge is to transition these options from Alpha to Beta options and then finally to a default status.

A Coaxial to Air-Filled Substrate Integrated Waveguide Transition With Near-Octave Bandwidth

In this letter, a wideband coaxial to air-filled waveguide transition is proposed, which has been realized by the substrate integrated waveguide (SIW) technology. The present design incorporates several air-filled vias of varying hole diameter to efficiently match the impedance over a wide operating bandwidth in the dominant TE10 mode, hence replacing the need for dielectric taper or larger footprint. A transition prototype has been designed and tested to validate the results. The measured return loss is better than 15 dB and insertion loss of 1 ± 0.1 dB over the band of interest (9.5–15 GHz), hence portraying a near-octave bandwidth from the proposed design.

GeNVoM: Read Mapping Near Non-Volatile Memory.

DNA sequencing is the physical/biochemical process of identifying the location of the four bases (Adenine, Guanine, Cytosine, Thymine) in a DNA strand. As semiconductor technology revolutionized computing, modern DNA sequencing technology (termed Next Generation Sequencing, NGS) revolutionized genomic research. As a result, modern NGS platforms can sequence hundreds of millions of short DNA fragments in parallel. The sequenced DNA fragments, representing the output of NGS platforms, are termed reads. Besides genomic variations, NGS imperfections induce noise in reads. Mapping each read to (the most similar portion of) a reference genome of the same species, i.e., read mapping, is a common critical first step in a diverse set of emerging bioinformatics applications. Mapping represents a search-heavy memory-intensive similarity matching problem, therefore, can greatly benefit from near-memory processing. Intuition suggests using fast associative search enabled by Ternary Content Addressable Memory (TCAM) by construction. However, the excessive energy consumption and lack of support for similarity matching (under NGS and genomic variation induced noise) renders direct application of TCAM infeasible, irrespective of volatility, where only non-volatile TCAM can accommodate the large memory footprint in an area-efficient way. This paper introduces GeNVoM, a scalable, energy-efficient and high-throughput solution. Instead of optimizing an algorithm developed for general-purpose computers or GPUs, GeNVoM rethinks the algorithm and non-volatile TCAM-based accelerator design together from the ground up. Thereby GeNVoM can improve the throughput by up to 3.67×; the energy consumption, by up to 1.36×, when compared to an ASIC baseline, which represents one of the highest-throughput implementations known.

Can a bioactive interbody device reduce the cost burden of achieving lateral lumbar fusion?

Intervertebral devices are increasingly utilized for fusion in the lumbar spine, along with a variety of bone graft materials. These various grafting materials often have substantial cost burdens for the surgical procedure, although they are necessary to overcome the limitations in healing capacity for many traditional interbody devices. The use of bioactive interbody fusion devices, which have demonstrable stimulatory capacity for the surrounding osteoblasts and osteoprogenitor cells and allow for osseointegration, may reduce this heavy reliance on osteobiologics for achieving interbody fusion. The objective of this study was to evaluate the rate of successful interbody fusion with a bioactive lateral lumbar interbody titanium implant with limited volume and low-cost graft material. The authors conducted a retrospective study (May 2017 to October 2018) of consecutively performed lateral lumbar interbody fusions with a bioactive 3D-printed porous titanium interbody device. Each interbody device was filled with 2-3 cm3/cage of a commercially available ceramic bone extender (β-tricalcium phosphate-hydroxyapatite) and combined with posterior pedicle screw fixation. No other biological agents or grafts were utilized. Demographic, clinical, and radiographic variables were captured. Fusion success was the primary endpoint of the study, with graft subsidence, fixation failure, and patient-reported outcomes (Oswestry Disability Index [ODI] and visual analog scale [VAS]-back and -leg pain scores) collected as secondary endpoints. The authors utilized a CT-based fusion classification system that accounted for both intervertebral through-growth (bone bridging) and ingrowth (integration of bone at the endplate-implant interface). In total, 136 lumbar levels were treated in 90 patients. The mean age was 69 years, and 63% of the included patients were female. Half (50.0%) had undergone previous spinal surgery, and a third (33.7%) had undergone prior lumbar fusion. A third (33.7%) were treated at multiple levels (mean levels per patient 1.51). One year after surgery, the mean improvements in patient-reported outcomes (vs preoperative scores) were -17.8 for ODI (p < 0.0001), -3.1 for VAS-back pain (p < 0.0001), and -2.9 for VAS-leg pain (p < 0.0001). Bone bridging and/or appositional integrity was achieved in 99.3% of patients, including 97.8% who had complete bone bridging. No fixation loosening or implant failure was observed at any segment. Low-grade graft subsidence (Marchi grade ≤ I) occurred in 3 levels (2.2%), and intraoperative endplate violation occurred twice (1.5%). High-grade subsidence was not found. No implant failure or revision surgery for pseudarthrosis/subsidence was necessary. The use of bioactive titanium interbody devices with a large surface footprint appears to result in a very high rate of effective fusion, despite the use of a small volume of low-cost biological material. This potential change in the osteobiologics required to achieve high fusion rates may have a substantially beneficial impact on the economic burden inherent to spinal fusion.

An Efficient and Lightweight Method for Human Ear Recognition Based on MobileNet

In recent years, biometric recognition patterns have attracted the attention of many researchers, among which human ears, as a unique and stable biometric feature, have significant advantages in verifying personal identity. In the Internet era, a system with low computing cost and good real-time performance is more popular. Most of the existing ear recognition methods are based on a large parameter network model, which causes a large memory footprint and computational overhead. This paper proposes an efficient and lightweight human ear recognition method (ELERNet) based on MobileNet V2. Based on the MobileNet V2 model, dynamic convolution decomposition is introduced to enhance the representation ability of human ear features. Then, combined with the coordinate attention mechanism, the spatial features of human ear images are aggregated to locate the location information of the human ear features more accurately. We conducted experiments on AWE and EarVN1.0 human ear datasets. Compared with the MobileNet V2 model, the recognition accuracy of our method is significantly improved. Using less computing hardware resources, the ELERNet model achieves 83.52% and 96.10% Rank-1 (R1) recognition accuracy, respectively, which is better than other models. Finally, we provide a visual interpretation using GradCAM technology, and the results show that our method can learn specific and discriminative features in the ear images.

A field study of the surface disturbance effects of animals and motor vehicles on aeolian sediment emission from a silty playa surface

Dry playa surfaces can be extremely vulnerable to disturbance which breaks their surface crusts resulting in increased aeolian sand and dust emissions. Trampling by livestock and motor vehicles is an important source of this disturbance. The Hamoun Lakes in the Sistan region of Iran are a major source area of dust storms which are causing damage to infrastructure and communities. This study performed portable wind tunnel tests of controlled surface disturbance by animals (cow, sheep) and motor vehicles (automobile, motorcycle) on a silty playa surface of Hamoun Saberi lake. The aim of this study was to assess the effect of different levels of trampling and disturbed surfaces by both vehicles and livestock on dust emission at wind speeds of 6 and 12 m s−1. A significant increase of sediment emission was found with increased number of passes of vehicles and livestock and the degree of surface disturbance, more so at the high wind speed (12 m s−1). No significant differences were observed between a 10–20% disturbance level and an undisturbed surface, but statistically significant differences became apparent when disturbances reached 50–60% to 90–100% compared to undisturbed surfaces. Greater emission rates were reached by disturbances provided by automobile and cow compared to motorcycle and sheep, indicating greater trampling effects of automobile and cow likely related to greater weight and larger footprint. The automobile was the most surface-destructive of the four anthropogenic disturbances, providing emission in a lower number of passes compared to the motorcycle, cow and sheep. Better management of vehicle and livestock allocation on playas subject to disturbance, such as the Hamoun Lakes, will be a useful strategy to reduce disturbance and the frequency and intensity of dust storms.

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel implementations, inadequate. This paper introduces a new generation of the STochastic Engine for Pathway Simulation (STEPS) project (http://steps.sourceforge.net/), denominated STEPS 4.0, and its core components which have been designed for improved scalability, performance, and memory efficiency. STEPS 4.0 aims to enable novel scientific studies of macroscopic systems such as whole cells while capturing their nanoscale details. This class of models is out of reach for serial solvers due to the vast quantity of computation in such detailed models, and also out of reach for naive parallel solvers due to the large memory footprint. Based on a distributed mesh solution, we introduce a new parallel stochastic reaction-diffusion solver and a deterministic membrane potential solver in STEPS 4.0. The distributed mesh, together with improved data layout and algorithm designs, significantly reduces the memory footprint of parallel simulations in STEPS 4.0. This enables massively parallel simulations on modern HPC clusters and overcomes the limitations of the previous parallel STEPS implementation. Current and future improvements to the solver are not sustainable without following proper software engineering principles. For this reason, we also give an overview of how the STEPS codebase and the development environment have been updated to follow modern software development practices. We benchmark performance improvement and memory footprint on three published models with different complexities, from a simple spatial stochastic reaction-diffusion model, to a more complex one that is coupled to a deterministic membrane potential solver to simulate the calcium burst activity of a Purkinje neuron. Simulation results of these models suggest that the new solution dramatically reduces the per-core memory consumption by more than a factor of 30, while maintaining similar or better performance and scalability.

Bricks Using Clay Mixed with Powder and Ashes from Lignocellulosic Biomass: A Review

The production of fired or stabilized bricks from lignocellulosic biomass ash is thoroughly examined in this article. Bricks are typically made through the high-temperature firing process or by stabilizing the mixture with binders such as lime and cement. These bricks have a large carbon footprint and high levels of grey energy. In many parts of the world, the excessive use of clay as a natural raw material for the production of conventional bricks will lead to its scarcity. The mixing of clay with lignocellulosic ash during brick manufacturing leads to a better and more reliable solution that conserves scarce natural resources and reduces the impact of environmental pollution. This study aims to review the state of the art in the production of bricks based on lignocellulosic ashes and their physical, thermal, and mechanical properties. The most recent data in the literature related to the manufacture of lignocellulosic ash-based bricks either by firing, cementing or geopolymerization, the design of mixtures, as well as the identification of the main factors influencing the performance and durability of these bricks are presented and discussed. Despite extensive research, there is still very little commercial use of waste bricks in general and lignocellulosic biomass ash in particular. Various toxicity issues of lignocellulosic ash used in brick production limit their use on an industrial scale due to a lack of appropriate standards. In order to achieve practical production of bricks from lignocellulosic ash, research is still needed on standardizing and sustaining biomass ash recycling.

Enabling circuit-switching in modern on-chip networks

Contemporary flow control mechanisms, especially virtual channels, are employed by modern on-chip networks to allow better utilization of the link bandwidth through buffering and packet switching. Despite of being the de facto option in designs, they are also the sources of large energy footprint and long per-hop latency. On the other hand, dated and simpler flow controls such as circuit switching can draw far less power while offering an end-to-end latency analogous to wire delay. In this paper, we therefore take a further step from utilizing a single flow control mechanism within the network to allowing circuit-switching to work alongside virtual channels, which provides latency-competitive and energy-efficient on-chip network designs. Furthermore, to enable circuit switching in modern networks-on-chip, we present two independent proposals so that circuits can be formed in a network either temporally or spatially. In our evaluations, we find that both of our proposals can help achieve a very competitive latency per flit, for up to 30% lower with the temporal approach and for up to 10% lower with the spatial approach, while also dramatically suppressing the energy footprint with either approach by up to 27% and 25%, respectively.

Tetraplex Immunophenotyping of Cell Surface Proteomes via Synthesized Plasmonic Nanotags and Portable Raman Spectroscopy.

Multiplex immunophenotyping of cell surface proteomes is useful for cell characterization as well as providing valuable information on a patient's physiological or pathological state. Current methods for multiplex immunophenotyping of cell surface proteomes still have associated technical pitfalls in terms of limited multiplexing capability, challenging result interpretation, and large equipment footprint limited to use in a laboratory setting. Herein, we presented a portable surface-enhanced Raman spectroscopy (SERS) assay for multiplex cell surface immunophenotyping. We synthesized and functionalized customizable SERS nanotags for cell labeling and subsequent signal measurement using a portable Raman spectrometer. We extensively evaluated and validated the analytical assay performance of the portable SERS immunophenotyping assay in two different cellular models (red blood cells and breast cancer cells). In terms of analytical specificity, the cell surface immunophenotyping of both red blood cells and breast cancer cells correlated well with flow cytometry. The portable SERS immunophenotyping assay also has comparable analytical repeatability to flow cytometry, with coefficient of variation values of 21.89-23.33% and 6.88-17.32% for detecting red blood cells and breast cancer cells, respectively. The analytical detection limits were 77 cells/mL for red blood cells and 1-17 cells/mL for breast cancer cells. As an alternative to flow cytometry, the portable SERS immunophenotyping assay demonstrated excellent analytical assay performance and possessed advantages such as quick sample-to-result turnaround time, multiplexing capability, and small equipment footprint.