Fast Consumption Research Articles

Monitoring ER Ca2+ by Luminescence with Low Affinity GFP-Aequorin Protein (GAP).

The endoplasmic reticulum (ER) is the main cellular reservoir of Ca2+, able to accumulate high amounts of calcium close to the millimolar range and to release it upon cell activation. Monitoring of Ca2+ dynamics within the ER lumen is best achieved using genetically encoded and targeted reporters. Luminescent probes based on the photoprotein aequorin have provided significant insight to measure subcellular Ca2+. Here we describe a robust and quantitative method based on the Ca2+ indicator of the GFP-Aequorin Protein (GAP) family, targeted to the ER lumen. A low Ca2+ affinity version of GAP, GAP1, carrying mutations in two EF-hands of aequorin, reconstituted with coelenterazine n has a reduced affinity for Ca2+ such that it conforms with the [Ca2+] values found in the ER and it slows the consumption of the probe by Ca2+. This feature is advantageous because it avoids fast aequorin consumption allowing long-term (longer than 1h) ER Ca2+ measurements. GAP1 targeted to the ER allows monitoring of resting [Ca2+]ER and Ca2+ dynamics in intact cells stimulated with IP3-produced agonists. In addition, GAP1 can record Ca2+ mobilization in permeabilized cells challenged with IP3. We also provide a detailed calibration procedure which allows to accurately convert the luminescence signal into [Ca2+]ER.

Extraordinarily Time- and Memory-Efficient Large-Scale Canonical Correlation Analysis in Fourier Domain: From Shallow to Deep.

Canonical correlation analysis (CCA) is a correlation analysis technique that is widely used in statistics and the machine-learning community. However, the high complexity involved in the training process lays a heavy burden on the processing units and memory system, making CCA nearly impractical in large-scale data. To overcome this issue, a novel CCA method that tries to carry out analysis on the dataset in the Fourier domain is developed in this article. Appling Fourier transform on the data, we can convert the traditional eigenvector computation of CCA into finding some predefined discriminative Fourier bases that can be learned with only element-wise dot product and sum operations, without complex time-consuming calculations. As the eigenvalues come from the sum of individual sample products, they can be estimated in parallel. Besides, thanks to the data characteristic of pattern repeatability, the eigenvalues can be well estimated with partial samples. Accordingly, a progressive estimate scheme is proposed, in which the eigenvalues are estimated through feeding data batch by batch until the eigenvalues sequence is stable in order. As a result, the proposed method shows its characteristics of extraordinarily fast and memory efficiencies. Furthermore, we extend this idea to the nonlinear kernel and deep models and obtained satisfactory accuracy and extremely fast training time consumption as expected. An extensive discussion on the fast Fourier transform (FFT)-CCA is made in terms of time and memory efficiencies. Experimental results on several large-scale correlation datasets, such as MNIST8M, X-RAY MICROBEAM SPEECH, and Twitter Users Data, demonstrate the superiority of the proposed algorithm over state-of-the-art (SOTA) large-scale CCA methods, as our proposed method achieves almost same accuracy with the training time of our proposed method being 1000 times faster. This makes our proposed models best practice models for dealing with large-scale correlation datasets. The source code is available at https://github.com/Mrxuzhao/FFTCCA.

Effect of recycled aggregates with different parent strength and fly ash on flexural strength of recycled aggregate concrete prisms

Fast consumption of conventional ingredients of concrete and waste generated due to demolishing old buildings is a multi-fold problem in the concrete industry. Hence the sustainable alternative of it is the need of the day. In this research work effect of binary blending of demolished waste and fly ash on the flexural strength of plain concrete prism is presented. The properties of aggregates and cement are evaluated. The physical and chemical properties of fly ash were determined. Recycled aggregates from demolished waste with different mix ratios (1:2:4 and 1:1.5:3) were used. Optimization of recycled aggregates; by evaluating concrete cylinders in 12 batches; showed 35% as optimum. At the optimum dosage of recycled aggregates fly ash was used from 2.5% to 15% with an increment of 2.5% to optimize its dosage. Compressive strength test of the standard-size cylinders and their comparison with control concrete showed a 10% dosage of a fly as the optimum percentage to replace the cement in the concrete matrix. Using both optimized dosages of recycled aggregates and fly ash prism specimens of900mmx150mmx300mm were cast in four batches. The beam specimens were cured for 28 days followed by an evaluation of flexural strength and deflection under centric load in the universal testing machine. Test results of flexural strength (only 15% loss) showed good potential for both waste materials in the concrete matrix. Recycled aggregate with higher parent strength showed better performance than its other counterparts. With higher-strength recycled aggregates residual flexural strength was recorded as equal to 93%. For all specimens recorded deflection was within the allowable limits of ACI-318.

Tailoring magnetism in chromium-doped zinc cobalt ferrite nanostructure for advanced spintronic memory devices

Soft magnetic ferrites serve as a crucial component in a wide array of sensing and actuating applications across various industries, including consumer electronics, automotive systems, spintronics, and more. These materials also find utility in spintronics, particularly for next-generation magnetic random-access memory (MRAM) due to their excellent inductive properties, which enhance the performance and scalability of spintronic memory devices. This study focuses on fine-tuning soft magnetic ferrites for inductive applications by doping them with Cr ions. By utilizing advanced experimental techniques such as the vibrating sample magnetometer (VSM) for bulk magnetometry and X-ray magnetic circular dichroism (XMCD) alongside X-ray absorption spectroscopy for atomic studies, the research aims to investigate the structural, electronic, and magnetic properties of the nanoferrites. Addition of doping in the soft ferrites observes reduction in the general magnetic parameters, with the only exception being coercivity, which decreases from 381 Oe to 275 Oe as the doping concentration increases from x = 0 to x = 0.02, and then increases to 350 Oe at x = 0.03. Through such precise tuning of the nanoparticles, this study aims to investigate the controllable soft magnetic properties of the nanoferrites, thereby paving the way for fast access times, non-volatility, and low energy consumption, presenting a compelling alternative to conventional memory technologies.

Multifunctional Silver‐Enzyme Nanogels Assembly with Efficient Trienzyme Cascades for Synergistic Diabetic Wound Healing

AbstractDiabetic wound healing presents a persistent clinical challenge, often characterized by prolonged healing times, and can be particularly difficult to achieve in a hyperglycemic environment. In this study, a multi‐functional silver‐enzyme nanogels assembly (Ag‐nGHC) is designed by focusing on the complex diabetic wound environment. Glucose oxidase (GOX), horseradish peroxidase (HRP), and catalase (CAT) are modified within polymeric nanogel layers and assembled into a large enzyme cluster with silver ions. The close attachment of three enzymes ensures fast and continuous consumption of a high level of glucose, generation of oxygen, and hydroxyl radicals (•OH) around the wound site. Meanwhile, the silver ions within the Ag‐nGHC assembly act as an effective agent to kill bacteria. This cascade enzyme system significantly improves the microenvironment of the wound site by reducing bacterium infection and alleviating hypoxia as well as hyperglycemia. Sequentially, the improved environment facilitates the later processes including anti‐inflammatory, re‐epithelialization, and angiogenesis, evidenced by enhancing polarization toward M2 macrophages and increasing CD31 signals in this study. Overall, the Ag‐nGHC materials are proven to achieve multifunctional properties toward complicated diabetic wound healing processes (attributes such as adaptability, hypoxia‐alleviated, anti‐hyperglycemic, antimicrobial, anti‐inflammatory, and angiogenic) and showed great potential for the treatment of chronic diabetic wound.

Heterojunction photoelectric device with fast response speed and low power consumption composed of WSSe and AlN

Through the accurate calculation of density functional theory, reveal the excellent photoelectric properties of the AlN/WSSe and WSSe/AlN heterojunction. Especially, the hole mobility of the AlN/WSSe heterojunction is as high as 3919 cm2Vs-1in armchair direction, and the hole mobility of the WSSe/AlN heterojunction is as high as 4422 cm2Vs-1in the zigzag direction. Interestingly, when two H atoms are adsorbed in the WSSe surface, the Gibbs free energy change are -0.093 eV and -0.984 eV, which tends to zero, which can promote the spontaneous reaction of electrocatalytic water decomposition to produce H2. In addition, the AlN/WSSe heterojunction exhibits significant photoelectric effect photocurrent (1.15 a02/photon) in the armchair direction and the heterojunctions have lower threshold voltage (1.5 V), that indicate the AlN/WSSe and WSSe/AlN heterojunction have great application prospect in manufacturing high-performance optoelectronic devices with fast response and low power consumption.

Reconfigurable aJ-Level Ferroelectric Transistor-Based Boolean Logic for Logic-in-Memory.

Logic-in-memory (LIM) architecture holds great potential to break the von Neumann bottleneck. Despite the extensive research on novel devices, challenges persist in developing suitable engineering building blocks for such designs. Herein, we propose a reconfigurable strategy for efficient implementation of Boolean logics based on a hafnium oxide-based ferroelectric field effect transistor (HfO2-based FeFET). The logic results are stored within the device itself (in situ) during the computation process, featuring the key characteristics of LIM. The fast switching speed and low power consumption of a HfO2-based FeFET enable the execution of Boolean logics with an ultralow energy of lower than 8 attojoule (aJ). This represents a significant milestone in achieving aJ-level computing energy consumption. Furthermore, the system demonstrates exceptional reliability with computing endurance exceeding 108 cycles and retention properties exceeding 1000 s. These results highlight the remarkable potential of a FeFET for the realization of high performance beyond the von Neumann LIM computing architectures.

Fast fashion consumption as a female competition strategy: implications for sustainable consumption

Fast fashion consumption as a female competition strategy: implications for sustainable consumption

Ultrahigh Stability and Operation Performance in Bi-doped GeTe/Sb2Te3 Superlattices Achieved by Tailoring Bonding and Structural Properties.

Changes in bond types and the reversible switching process between metavalent and covalent bonds are related to the operating mechanism of the phase-change (PC) behavior. Thus, controlling the bonding characteristics is the key to improving the PC memory performance. In this study, we have controlled the bonding characteristics of GeTe/Sb2Te3 superlattices (SLs) via bismuth (Bi) doping. The incorporation of Bi into the GeTe sublayers tailors the metavalent bond. We observed significant improvement in device reliability, set speed, and power consumption induced upon increasing Bi incorporation. The introduction of Bi was found to suppress the change in density between the SET and RESET states, resulting in a significant increase in device reliability. The reduction in Peierls distortion, leading to a more octahedral-like atomic arrangement, intensifies electron-phonon coupling with increased bond polarizability, which are responsible for the fast set speed and low power consumption. This study demonstrates how the structural and thermodynamic changes in phase change materials alter phase change characteristics due to systematic changes of bonding and provides an important methodology for the development of PC devices.

Restoration of motion-blurred numeral image using a complex-amplitude diffractive processor.

We propose a complex-amplitude diffractive processor based on diffractive deep neural networks (D2NNs). By precisely controlling the propagation of an optical field, it can effectively remove the motion blur in numeral images and realize the restoration. Comparative analysis of phase-only, amplitude-only, and complex-amplitude diffractive processor reveals that the complex-amplitude network significantly enhances the performance of the processor and improves the peak signal-to-noise ratio (PSNR) of the images. Appropriate use of complex-amplitude networks contributes to reduce the number of network layers and alleviates alignment difficulties. Due to its fast processing speed and low power consumption, complex-amplitude diffractive processors hold potential applications in various fields including road monitoring, sports photography, satellite imaging, and medical diagnostics.

Multi-Criteria Decision Making In The Selection Of Electric Sports Utility Vehicles: Integrated Critic–Copras Method

The aim of this study was to assess and determine the most suitable electric sports utility vehicle (e-SUV) alternatives for consumers who are considering buying an e-SUV that is sold in Turkey. Accordingly, 10 different vehicles were selected using specific criteria from the e-SUVs available through distributor sales in Turkey. CRITIC and COPRAS methods were used to rank these vehicles. The results of the CRITIC method for determining the weights of the criteria were the following three: fast charging time, energy consumption, and price. The results of the analyses conducted using the COPRAS method and these weights determined the e-SUV rankings. Based on these results, the top three alternatives were Subaru Solterra, New MG ZS EV, and BMW iX3 eDrive20.

The study on the reason why ZnS catalyst cannot suppress the shuttle effect of polysulfides in lithium-sulfur (Li–S) battery

The catalytic effect of zinc sulfide (ZnS) on the transformation of polysulfides (Li2S8) to lithium sulfide (Li2S) has been proven by the enhancement in the rate performance of lithium-sulfur (Li–S) batteries incorporating ZnS particles into the cathode. Accordingly, the shuttling effect of polysulfide should also be suppressed. However, the expected phenomenon is not found in the Li–S batteries with ZnS particles being added in the cathodes. In order to find the intrinsic mechanism of this phenomenon, detailed catalytic effects of ZnS particles on different polysulfide molecules are investigated. It is shown that ZnS can only enhance the reaction from Li2S4 to Li2S and it has almost no catalytic effect on the reaction from Li2S6 to Li2S4. This is why the shuttle effect of Li2S6 cannot be effectively prohibited. This mechanism is further verified via combining ZnS particles with S–C@PVA yolk-shell particles containing sulfur (S) and carbon black (C) as the core and PVA as the shell. Although the reaction from Li2S6 to Li2S4 cannot be directly catalysed by ZnS particles, it can still be enhanced when ZnS particles are distributed within the S–C@PVA yolk-shell structure (S–C–ZnS@PVA) because the reaction speed from the Li2S4 to Li2S is accelerated. The fast consumption of Li2S4 will result in the enhancement of the reaction from Li2S6 to Li2S4, which will largely reduce the diffusion of Li2S6 out of the PVA shell. While if ZnS particles are located outside the S–C@PVA yolk-shell structure (S–C@PVA-ZnS), large amount of Li2S6 can still diffuse out of the PVA shell and enter into the electrolyte since the transformation from is Li2S6 to Li2S4 relatively low. Both the rate performance and cycle stability of the batteries with S–C–ZnS@PVA cathodes are higher than those with S–C@PVA-ZnS ones. These results will give a guidance for the preparation of Li–S battery with high performance.

Driving waveform optimization of electrowetting displays based on pixel's 2-D model for reducing oil reflux.

Electrowetting displays (EWD) are believed to represent a new generation of electronic paper technology with fast responses, high reflectivity, and low power consumption. Despite their bright market prospects, the luminance stability of displays is still hindered by oil film reflux. So, we presented a combination of simulation and experimentation to enhance the performance of EWD. Firstly, an EWD simulation model was established using the phase field method (PFM). To ensure the accuracy of the model, it was proposed that the use of velocity field parameters could suppress mass non-conservation. During a 10-second simulation process, the total mass decreased by only 7.94x10-6%. Furthermore, the charge accumulation field was introduced to simulate oil film reflux. For the 5-second simulation, the maximum charge accumulation in the DC driving waveform was 2.61x10-5C/m2. Meanwhile, it was demonstrated that the AC driving waveform reduced charge accumulation in the three-phase contact line (TPCL) by 7.62% compared to the DC driving waveform. Based on this simulation model, a driving waveform was proposed, which included a driving waveform with a gradient changing waveform to achieve fast opening, and an alternating current (AC) driving waveform stage to inhibit the charge accumulation. The experimental results indicated that the maximum luminance fluctuation was 8.82, and the luminance data variance was 3.34 by using the proposed driving waveform. Compared to the traditional waveform, the response time was improved by 75.9%, the luminance was improved by 4.70%, and the luminance fluctuation stability improved by 79.34%.

MURE: Multi-layer real-time livestock management architecture with unmanned aerial vehicles using deep reinforcement learning

In recent years, the combination of unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) has gained popularity in livestock management (LM) due to energy constraints and network instability. Limited energy storage of sensor nodes (SNs) and the possibility of packet loss contribute to fast energy consumption and unstable networks, respectively. UAVs serve as relay nodes and data sinks, addressing these issues by temporarily storing data to reduce SN workload and establishing mobile nodes for network stability. We propose two innovations based on previous work: 1) We introduce a multi-layer wireless network architecture, categorizing UAVs into two layers based on their functions including data collection and data processing. This enhances task parallelization, bridging performance gaps among multiple UAVs; 2) We overcome the mobility limitation of SNs, considering their real-time movement in the network. Through deep reinforcement learning, UAVs learn to cooperatively locate moving SNs. This accounts for the inevitable mobility of livestock in the industry. Additionally, we simulate the environment and compare our approach to traditional methods, evaluating metrics such as collected data per timestep (DCPS), energy consumed per timestep (ECPS), and network stability (NS). Experimental results demonstrate that our method outperforms traditional approaches, achieving a data collecting gain of 4.84% and 8.20% compared to the methods without considering SN mobility or the multi-layer characteristics of WSNs, respectively. Under energy consumption limits, our method yields energy savings of 3.00% and 1.35% respectively. Furthermore, we extensively study and validate our method against other path planning algorithms, including genetic particle swarm optimization (GPSO), modified central force optimization (MCFO), and rapidly-exploring random trees (RRT). Our approach surpasses these methods in terms of data collecting efficiency and network stability.

Inhibiting effects during the co-conversion of lauric acid and anisole over Ni and NiMo catalysts

The co-hydroconversion of lauric acid and anisole was carried out over Ni and NiMo catalysts T=260 and 280 °C and pH2=40 bar. Ni/Al2O3 demonstrated a high activity in converting anisole to cyclohexane, but lauric acid conversion was suppressed over this catalyst. In the co-conversion of their mixture the phenolic had no effect on the conversion of the acid, but the latter prevented the cleavage of the C-O bond in both anisole and reaction intermediates. It was assumed that the successful conversion of anisole in its mixture with lauric acid required that a catalyst should provide the fast consumption of the acid component. Accordingly, NiMo/Al2O3 possessed a high activity in lauric acid conversion, and a high cyclohexane yield from anisole was observed after the complete consumption of the acid. The results of the present study can be useful for the rational design of a catalyst for the effective hydroconversion of bio-oil.

Early-stage diffusion and oxidation behavior of Cr-Nb coated Zr alloy accident tolerant fuel cladding materials at 1200°C–1500°C

Although the Cr-coated Zr alloys are considered as the most promising accident tolerant fuel cladding materials in recent years, the Cr-Zr interdiffusion problem is a major obstacle for the widely used of the Cr coating. In this study, Cr-Nb coated Zr alloy samples were prepared by magnetron sputtering. The Nb layer was designed as a barrier layer to retard the Cr-Zr interdiffusion. By using a fast-in and fast-out equipment, short time annealing was conducted in argon environment to study the coating evolution in high temperature environment. Results show that the Nb coating can retard the inward diffusion of Cr because of the low diffusion coefficient of Cr in the Nb layer. However, the complete miscibility between Nb and Zr lead to the fast consumption of the Nb coating. After 10 min annealing at 1200 °C, the 2.5 μm Nb coating disappeared, and a Cr-Zr-Nb mixed phase formed between the residual Cr coating and Zr substrate. The early-stage microstructure evolution of the sample was analyzed, and the barrier effect of the Nb coating was summarized.

A Flow-Through Biosensor System Based on Pillar[3]Arene[2]Quinone and Ferrocene for Determination of Hydrogen Peroxide and Uric Acid

Simple and reliable electrochemical sensors are highly demanded in medicine and pharmacy for the fast determination of metabolites and biomarkers of diseases. In this work, a flow-through biosensor system was developed on the base of a screen-printed carbon electrode modified with pillar[3]arene[2]quinone and ferrocene implemented in carbon black. The modification was performed in a single step and resulted in the formation of a stable layer with good operation characteristics. Uricase was immobilized on the inner walls of a replaceable reactor by carbodiimide binding. A flow-through cell was manufactured by 3D printing from poly(lactic acid). The flow-through system was first optimized on the hydrogen peroxide assay and then used for the determination of 1 nM–0.1 mM uric acid (limit of detection 0.3 nM, 20 measurements per hour). Implementation of ferrocene resulted in a synergetic increase in the cathodic current of H2O2 reduction measured by flow switching in chronoamperometric mode. The developed system was tested on the determination of uric acid in artificial urine and Ringer–Locke solution and showed a recovery rate of 96–112%. In addition, the possibility of determination of H2O2 in commercial disinfectants was shown. Easy assembly, fast and reliable signal and low consumption of the reagents make the system developed attractive for routine clinical analysis of metabolites.

Liquid Chromatography-Mass Spectrometry-Based Metabolomics Reveals Dynamic Metabolite Changes during Early Postmortem Aging of Donkey Meat.

Metabolic changes in donkey meat during the early postmortem period have not been previously reported. The LC-MS-based metabolomics technique was conducted to understand the metabolic profiles and identify the key metabolites of donkey meat in the first 48 h postmortem. The pH values showed a decreasing trend followed by an increasing trend. Shear force was the lowest at 4 h and the highest at 24 h (p < 0.05). For the metabolome, some candidate biomarker metabolites were identified, such as adenine, inosine, n-acetylhistidine, citric acid, isocitrate, and malic acid. Predominant metabolic pathways, such as citrate cycle (TCA cycle), alanine, aspartate and glutamate metabolism, and purine metabolism, were affected by aging time. Overabundant n-acetylhistidine was identified in LT, declined at 12 h postmortem aging, and then increased. This may explain the significantly lower pH at 12 h postmortem. Adenine was higher at 4 h postmortem, then declined. Decreased ADP may indicate a fast consumption of ATP and subsequent purine metabolism in donkey meat. The results of this study provided new insights into early postmortem aging of donkey meat quality.

UNVEILING THE POLITICAL IMPACT OF FAST FASHION CONSUMPTION: THE ROLE OF LOWER MIDDLE CLASS IN ENVIRONMENTAL CRISIS IN INDONESIA?

ABSTRACT. This article delves into the impact and role of the lower middle class on Indonesia’s environmental landscape. Despite their social and economic marginalization, this demographic heavily relies on cheap, easily accessible fast fashion for clothing, leading to detrimental environmental consequences such as ecosystem degradation and pollution. This research was carried out by conducting a literature review through library research, where the data came from library data collection. This study further analyzes literature regarding socio-economic dynamics and environmental problems. This approach unveiled the lower middle class’s profound influence of fast fashion consumption on Indonesia’s environment. The research highlights the lower middle class’s pivotal role in fast fashion waste distribution, exacerbating environmental pollution. Hence, governmental intervention becomes imperative to regulate fast fashion production, manage waste, and restrict the influx of second-hand fast fashion businesses. The article concludes by emphasizing the lower middle class’s dual role as both major consumers and victims of global capitalism in the fast fashion industry, necessitating state protection through various policy measures. These include elevating product quality standards, ensuring fair labor practices, enhancing consumer protection, and controlling the influx of foreign fast fashion products. Ultimately, the study underscores the necessity of comprehensive governmental interventions to mitigate the environmental repercussions of fast fashion consumption, safeguarding both the lower middle class and Indonesia’s environment.

Microheater Chips with Carbon Nanotube Resistors.

The specific and excellent properties of the low-dimensional nanomaterials have made them promising building blocks to be integrated into microelectromechanical systems with high performances. Here, we present a new microheater chip for in situ TEM, in which a cross-stacked superaligned carbon nanotube (CNT) film resistor is located on a suspended SiNx membrane via van der Waals (vdW) interactions. The CNT microheater has a fast high-temperature response and low power consumption, thanks to the micro/nanostructure of the CNT materials. Moreover, the membrane bulging amplitude is significantly reduced to only ∼100 nm at 800 °C for the vdW interaction between the CNTs and the SiNx membrane. An in situ observation of the Sn melting process is successfully conducted with the assistance of a customized flexible temperature control system. The uniform wafer-scaled CNT films enable a high level of consistency and cost-effective mass production of such chips. The as-developed in situ chips, as well as the related techniques, hold great promise in nanoscience, materials science, and electrochemistry.