Important Applications Research Articles

Near-IR Photoinduced Electrochemiluminescence Imaging with Structured Silicon Photoanodes.

Infrared (IR) imaging devices that convert IR irradiation (invisible to the human eye) to a visible signal are based on solid-state components. Here, we introduce an alternative concept based on light-addressable electrochemistry (i.e., electrochemistry spatially confined under the action of a light stimulus) that involves the use of a liquid electrolyte. In this method, the projection of a near-IR image (λexc = 850 or 840 nm) onto a photoactive Si-based photoanode, immersed into a liquid phase, triggers locally the photoinduced electrochemiluminescence (PECL) of the efficient [Ru(bpy)3]2+-TPrA system. This leads to the local conversion of near-IR light to visible (λPECL = 632 nm) light. We demonstrate that compared to planar Si photoanodes, the use of a micropillar Si array leads to a large enhancement of local light generation and considerably improves the resolution of the PECL image by preventing photogenerated minority carriers from diffusing laterally. These results are important for the design of original light conversion devices and can lead to important applications in photothermal imaging and analytical chemistry.

Custom-tailoring zwitterion-based nanofiltration membranes for organic molecule desalination with sub-200 Da molecular weight

Organic molecule desalination with nanofiltration has important practical application significance. Zwitterion-based nanofiltration membranes (ZNFMs) with selective channels for monovalent salts have been prepared to improve the separation performance. However, most ZNFMs tend to be restricted by their loose structures, which results in unsatisfactory rejection for small molecules with sub-200 Da molecular weight. In this study, a synchronous modification strategy during the heat treatment of interfacial polymerization was proposed, in which various multi-amine solutions were employed as the novel medium of heat treatment to regulate the structures of ZNFMs. The pore size distribution of membranes could be narrowed to a certain degree through cross-linking by corresponding multi-amines. The optimized ZNFMs exhibited excellent retention to small molecules. For example, the retention of glucose was dramatically increased to 96.5%. Meanwhile, the ZNFMs also had low rejection for monovalent salts, such as KCl (26.7 %). Consequently, the separation factor between glucose and KCl reached 21.2, which demonstrated a great potential for organic molecule desalination with sub-200 Da molecular weight.

Semi-analytical solutions of Newtonian fluid-FENE-P fluid core annular flow

Water-lubricated transportation of viscous oil is an important application of core annular flow (CAF), which significantly reduces friction pressure drop and saves pump power. However, the core oil floats up due to the density difference of oil and water, causing instability and even destruction of CAF, which restricts the application and development of the drag reduction technology. The viscoelastic fluid in the annular can inhibit the tendency of the core oil to float up and enhance the stability of the CAF. Nevertheless, theoretical studies related to the viscoelastic fluid CAF are currently missing. To make up for the lack of theoretical research, the solutions of laminar concentric viscous oil-viscoelastic fluid CAF in horizontal and inclined pipes are obtained in this work, and the annular fluid is regarded as viscoelastic fluid conforming to the FENE-P model. Based on the Navier–Stokes equation and FENE-P model, a non-dimensional CAF model is established, and the Newton–Raphson method is used to solve the model. The rheological behavior of annular fluid and the effects of viscoelastic fluid rheology and viscosity ratio on various CAF flow characteristics, including holdup, pressure gradient, slip ratio, and Ledinegg instability, are investigated. The results indicate that the shear-thinning effect of viscoelastic fluid has a significant effect on water holdup and expands the multi-solution region. Different from Newtonian fluid, when the annulus fluid is viscoelastic, the slip ratio can be less than 2. The most significant property is that the shear-thinning effect can transform the hydraulic characteristic curve in the multi-valued region into a single-valued curve, which helps to eliminate Ledinegg instability.

Microwave Speech Recognizer Empowered by a Programmable Metasurface.

Speech recognition becomes increasingly important in the modern society, especially for human-machine interactions, but its deployment is still severely thwarted by the struggle of machines to recognize voiced commands in challenging real-life settings: oftentimes, ambient noise drowns the acoustic sound signals, and walls, face masks or other obstacles hide the mouth motion from optical sensors. To address these formidable challenges, an experimental prototype of a microwave speech recognizer empowered by programmable metasurface is presented here that can remotely recognize human voice commands and speaker identities even in noisy environments and if the speaker's mouth is hidden behind a wall or face mask. The programmable metasurface is the pivotal hardware ingredient of the system because its large aperture and huge number of degrees of freedom allows the system to perform a complex sequence of sensing tasks, orchestrated by artificial-intelligence tools. Relying solely on microwave data, the system avoids visual privacy infringements. The developed microwave speech recognizer can enable privacy-respecting voice-commanded human-machine interactions is experimentally demonstrated in many important but to-date inaccessible application scenarios. The presented strategy will unlock new possibilities and have expectations for future smart homes, ambient-assisted health monitoring, as well as intelligent surveillance and security.

Randomly Shifted Lattice Rules with Importance Sampling and Applications

In financial and statistical computations, calculating expectations often requires evaluating integrals with respect to a Gaussian measure. Monte Carlo methods are widely used for this purpose due to their dimension-independent convergence rate. Quasi-Monte Carlo is the deterministic analogue of Monte Carlo and has the potential to substantially enhance the convergence rate. Importance sampling is a widely used variance reduction technique. However, research into the specific impact of importance sampling on the integrand, as well as the conditions for convergence, is relatively scarce. In this study, we combine the randomly shifted lattice rule with importance sampling. We prove that, for unbounded functions, randomly shifted lattice rules combined with a suitably chosen importance density can achieve convergence as quickly as O(N−1+ϵ), given N samples for arbitrary ϵ values under certain conditions. We also prove that the conditions of convergence for Laplace importance sampling are stricter than those for optimal drift importance sampling. Furthermore, using a generalized linear mixed model and Randleman–Bartter model, we provide the conditions under which functions utilizing Laplace importance sampling achieve convergence rates of nearly O(N−1+ϵ) for arbitrary ϵ values.

A decentralized and security-enhanced professional title evaluation system in universities under mobile Internet of Things

Digital online application is a commonly used method for professional title evaluation in colleges and universities. With the rapid development of the mobile Internet of Things, the fastest way for users to access the evaluation system is through mobile devices. However, this also poses security challenges to the traditional professional title evaluation system. Therefore, this paper proposes a decentralized and security-enhanced digital title evaluation system in mobile IoT. Since the system uses blockchain to implement a decentralized review process, the transparency and fairness of the review process are guaranteed. At the same time, the review data and reviewer information in the system are encrypted and stored in the distributed network to ensure the security and non-tamperability of the data. All review records are recorded on the blockchain, and anyone can view and verify the legitimacy of the review results. Additionally, the system incorporates security enhancement mechanisms such as identity verification, smart contracts, and auditing functions to improve the credibility of the evaluation process and prevent cheating under mobile IoT. Experiments have shown that this system has important application value in the field of professional title review in universities, which can improve review efficiency, reduce human intervention, and provide strong support for the credibility of review results.

The Circular Economy: Recent debates and research trends

The Circular Economy is one of the most prominent cross-disciplinary and cross-sectoral concepts to emerge in recent decades. It has permeated academia, policymaking, business, NGOs, and the general public, leading to numerous applications of the concept, some of which only partially overlap. In this article, we review recent debates and research trends in the Circular Economy, outlining the ten most common groups of its conceptualizations using the PRISMA (Preferred Items for Systematic Reviews and Meta-Analysis) method. We then propose a post disciplinary and transnational research program on the Circular Economy that would not only combine hard and soft sciences in unprecedented ways but also have important practical applications, such as developing tools to embed the Circular Economy in natural, technical, economic, and socio-cultural settings.

Mid-infrared bimodal wide metamaterial absorber based on double-layer silicon nitride structure

Infrared band occupies a very important position in the electromagnetic wave band. Traditional infrared devices use the inherent properties of natural materials to achieve the regulation of electromagnetic waves, but the limited ability of such devices to regulate electromagnetic waves can't well meet our needs. In this paper, we reported a metamaterial absorber of Cr-Si3N4-Cr-Si3N4-Ti based on double-layer metal-insulator-metal (MIM). It is investigated with the optimal structural parameters of 490 nm, 330 nm, 30 nm, 720 nm, 120 nm, in descending order, at which the absorptive properties are studied. When the light wave is incident vertically, it can be obtained from the experimental simulation that this absorber has polarisation insensitivity. Because of the coupling effect of the surface plasmon resonance and the high-loss material, the bandwidth of absorption greater than 90% can reach 9190 nm, and the average absorption in the target long-wave infrared band (9.506∼18.145 μm) is 94.8%. By selecting different geometrical parameters of the structure, the absorption spectrum can be adjusted independently. In addition, the absorber has good incident angle insensitivity in TE and TM modes. Also, the absorber we proposed has a plain structure, is convenient for manufacturing, the material is easier to obtain, which ensures a good absorption bandwidth and average absorptivity, and the study of this metamaterial absorber has important applications in solar cells, satellite radiothermographs, photodetectors, and spectral imaging.

Non-pyrogenicity and biocompatibility of parylene-coated magnetic bead implants.

Clinical grade magnetic bead implants have important applications in interfacing with the human body, providing contactless mechanical attachment or wireless communication through human tissue. We recently developed a new strategy, magnetomicrometry, that uses magnetic bead implants as passive communication devices to wirelessly sense muscle tissue lengths. We manufactured clinical-grade magnetic bead implants and verified their biocompatibility via intramuscular implantation, cytotoxicity, sensitization, and intracutaneous irritation testing. In this work, we test the pyrogenicity of the magnetic bead implants via a lagomorph model, and we test the biocompatibility of the magnetic bead implants via a full chemical characterization and toxicological risk assessment. Further, we test the cleaning, sterilization, and dry time of the devices that are used to deploy these magnetic bead implants. We find that the magnetic bead implants are non-pyrogenic and biocompatible, with the insertion device determined to be safe to clean, sterilize, and dry in a healthcare setting. These results provide confidence for the safe use of these magnetic bead implants in humans.

Review on Medical Applications of Manganese Oxide (Mn2+, Mn3+, and Mn4+) Magnetic Nanoparticles

Apart from our imagination, the nanotechnology industry is rapidly growing and promises that the substantial changes that will have significant economic and scientific impacts be applicable to a wide range of areas, such as aerospace engineering, nanoelectronics, environmental remediation, and medical healthcare. In the medical field, magnetic materials play vital roles such as magnetic resonance imaging (MRI), hyperthermia, and magnetic drug delivery. Among them, manganese oxide garnered great interest in biomedical applications due to its different oxidation states (Mn2+, Mn3+, and Mn4+). Manganese oxide nanostructures are widely explored for medical applications due to their availability, diverse morphologies, and tunable magnetic properties. In this review, cogent contributions of manganese oxides in medical applications are summarized. The crystalline structure and oxidation states of Mn oxides are highlighted. The synthesis approaches of Mn-based nanoparticles are outlined. The important medical applications of manganese-based nanoparticles like magnetic hyperthermia, MRI, and drug delivery are summarized. This review is conducted to cover the future impact of MnOx in diagnostic and therapeutic applications.

Inference of annealed protein fitness landscapes with AnnealDCA.

The design of proteins with specific tasks is a major challenge in molecular biology with important diagnostic and therapeutic applications. High-throughput screening methods have been developed to systematically evaluate protein activity, but only a small fraction of possible protein variants can be tested using these techniques. Computational models that explore the sequence space in-silico to identify the fittest molecules for a given function are needed to overcome this limitation. In this article, we propose AnnealDCA, a machine-learning framework to learn the protein fitness landscape from sequencing data derived from a broad range of experiments that use selection and sequencing to quantify protein activity. We demonstrate the effectiveness of our method by applying it to antibody Rep-Seq data of immunized mice and screening experiments, assessing the quality of the fitness landscape reconstructions. Our method can be applied to several experimental cases where a population of protein variants undergoes various rounds of selection and sequencing, without relying on the computation of variants enrichment ratios, and thus can be used even in cases of disjoint sequence samples.

Deep energy-pressure regression for a thermodynamically consistent EOS model

In this paper, we aim to explore novel machine learning (ML) techniques to facilitate and accelerate the construction of universal equation-Of-State (EOS) models with a high accuracy while ensuring important thermodynamic consistency. When applying ML to fit a universal EOS model, there are two key requirements: (1) a high prediction accuracy to ensure precise estimation of relevant physics properties and (2) physical interpretability to support important physics-related downstream applications. We first identify a set of fundamental challenges from the accuracy perspective, including an extremely wide range of input/output space and highly sparse training data. We demonstrate that while a neural network (NN) model may fit the EOS data well, the black-box nature makes it difficult to provide physically interpretable results, leading to weak accountability of prediction results outside the training range and lack of guarantee to meet important thermodynamic consistency constraints. To this end, we propose a principled deep regression model that can be trained following a meta-learning style to predict the desired quantities with a high accuracy using scarce training data. We further introduce a uniquely designed kernel-based regularizer for accurate uncertainty quantification. An ensemble technique is leveraged to battle model overfitting with improved prediction stability. Auto-differentiation is conducted to verify that necessary thermodynamic consistency conditions are maintained. Our evaluation results show an excellent fit of the EOS table and the predicted values are ready to use for important physics-related tasks.

Chromium Picolinate Regulates Bone Metabolism and Prevents Bone Loss in Diabetic Rats.

Diabetic osteoporosis (DOP) is an abnormal metabolic disease caused by long-term hyperglycemia. In this study, a model rat of streptozotocin (STZ)-induced diabetes was established, and chromium picolinate (5 mg·kg-1) was given; the changes in blood glucose and body weight were detected before and after administration; and bone mineral density (BMD), bone morphology, bone turnover markers, inflammatory cytokines, and oxidative stress indicators were observed in each group. We found that after chromium picolinate (CP) intervention for 8 weeks, the blood glucose level was decreased; the BMD, the bone histomorphology parameters, and the pathological structure were improved; the expression of bone resorption-related proteins was downregulated; and the expression of bone formation-related proteins was upregulated. Meanwhile, serum antioxidant activity was increased, and inflammatory cytokine levels were decreased. In conclusion, CP could alleviate DOP by anti-oxidation, inhibition of bone turnover, anti-inflammation, and regulation of the OPG/RANKL/RANK signaling pathway. Therefore, CP has important application values for further development as a functional food or active medicine in DOP treatment.

Metabolic Engineering of Escherichia coli for Production of 2,5-Dimethylpyrazine.

2,5-Dimethylpyrazine (2,5-DMP) is a high-value-added alkylpyrazine compound with important applications in both the food and pharmaceutical fields. In response to the increasing consumer preference for natural products over chemically synthesized ones, efforts have been made to develop efficient microbial cell factories for the production of 2,5-DMP. However, the previously reported recombinant strains have exhibited low yields and relied on expensive antibiotics and inducers. In this study, we employed metabolic engineering strategies to develop an Escherichia coli strain capable of producing 2,5-DMP at high levels without the need for inducers or antibiotics. Initially, the biosynthesis pathway of 2,5-DMP was constructed that realized 2,5-DMP production from glucose. Subsequently, efforts focused on enhancing 2,5-DMP production by improving the availability of the cofactor NAD+ and precursor l-threonine. Additionally, the supply and conversion of l-threonine were balanced by optimizing the copy number of the key gene tdh on the chromosome and by modifying the l-threonine transport system. The final engineering strain D19 produced 3.1 g/L of 2,5-DMP, which is the highest titer for fermentative production of 2,5-DMP using glucose as the carbon source up to date. The strategies used in this study lay a good foundation for the production of 2,5-DMP on a large scale.

Dual-Color Visual Ratiometric Fluorescence Sensing for H2O and D2O Mixtures Using a Hexanuclear Ln(III) Cluster-Based Metal-Organic Framework.

High-purity heavy water (D2O) is a strategic material owing to its important application in the fields of nuclear energy and scientific research. D2O always tends to get contaminated by H2O owing to its strong hygroscopicity. Herein, a bimetallic hexanuclear Ln(III) cluster-based metal-organic framework (Eu0.5Tb0.5-TZB-MOF) has been synthesized for fluorescence sensing of the D2O-H2O binary mixtures. Eu0.5Tb0.5-TZB-MOF can be used to immediately differentiate D2O or H2O via fluorescent color responses that are obvious to the naked eye and allow for quantitative ratiometric analysis using simple spectrophotometry. Fluorescence titration experiments demonstrate that both trace H2O in D2O and trace D2O in H2O can be quantitatively detected. Mechanistic studies demonstrate that the weaker vibrational quenching of the O-D oscillator compared to the O-H oscillator, in addition to the terbium-to-europium energy transfer, triggered the fluorescence signal response.

Porous Conductive Textiles for Wearable Electronics.

Over the years, researchers have made significant strides in the development of novel flexible/stretchable and conductive materials, enabling the creation of cutting-edge electronic devices for wearable applications. Among these, porous conductive textiles (PCTs) have emerged as an ideal material platform for wearable electronics, owing to their light weight, flexibility, permeability, and wearing comfort. This Review aims to present a comprehensive overview of the progress and state of the art of utilizing PCTs for the design and fabrication of a wide variety of wearable electronic devices and their integrated wearable systems. To begin with, we elucidate how PCTs revolutionize the form factors of wearable electronics. We then discuss the preparation strategies of PCTs, in terms of the raw materials, fabrication processes, and key properties. Afterward, we provide detailed illustrations of how PCTs are used as basic building blocks to design and fabricate a wide variety of intrinsically flexible or stretchable devices, including sensors, actuators, therapeutic devices, energy-harvesting and storage devices, and displays. We further describe the techniques and strategies for wearable electronic systems either by hybridizing conventional off-the-shelf rigid electronic components with PCTs or by integrating multiple fibrous devices made of PCTs. Subsequently, we highlight some important wearable application scenarios in healthcare, sports and training, converging technologies, and professional specialists. At the end of the Review, we discuss the challenges and perspectives on future research directions and give overall conclusions. As the demand for more personalized and interconnected devices continues to grow, PCT-based wearables hold immense potential to redefine the landscape of wearable technology and reshape the way we live, work, and play.

Organosilicon elastomers of MWCNTs and nano-sized metals for heating purposes

Silicone elastomers are continuously gaining importance in a variety of industrial applications, including strain gauges, electrical heaters, electromagnetic interference, and electrostatic discharge protection coatings. But these materials have certain drawbacks such as high cost, poor resistance to solvents, low tear strength, limited high-temperature resistance, difficulty in bonding and limited abrasion resistance. Therefore, unique nanocomposites of organosilicon elastomers with metals have been prepared using MWCNTs. The prepared nanocomposites demonstrated nano-diameter structures (15–60 nm) with micron-sized fibrous structures (12–60 μm). Aluminum elongated inclusions (60 µm in size) and bronze spherical inclusions (12–30 µm) were observed in the nanocomposites. The composites containing MWCNTs, Co-Mo/Al2O3-MgO catalyst and bronze (3 wt. %) had the maximum thermal and electrical conductivity. The prepared nanocomposites were used to make the heaters. The heating of the heaters was carried out by applying a voltage of 12–24 V. The Highest temperature achieved was more than 50 °C in all the heaters. By supplying 12–24 V electricity to the heaters in the ventilation and heat recirculation system, the interior of a minibus or living space can be heated. The developed electric heater has another important economic application in temperature-controlled materials.

Computation of Structural Descriptors of Pyrene Cored Dendrimers through Quotient Graph Approach and Its Graph Entropy Measures

Dendrimers are highly defined hyperbranched artificial macromolecules, synthesised by convergent or divergent approach with specific applications in various fields. Dendrimers can be represented as graph models, from which a quantitative description can be drawn in relation with their structural properties. The distance-based and the degree-based descriptors have great importance and huge applications in structural chemistry. These indices together with entropy measures are found to be more effective and have found application in scientific fields. The idea of graph entropy is to characterise the complexity of graphs. The use of these graph invariants in quantitative structure property relationship and quantitative structure activity relationship studies has become of major interest in recent years. In this paper, the distance-based molecular descriptors of pyrene cored dendrimers are studied applying the technique of converting original graph into quotient graphs using Θ∗-classes. It is to be noted that, since the pyrene cored dendrimer, Gn is not a partial cube, usual cut method is not applicable. Further, various degree-based descriptors and their corresponding graph entropies of the pyrene cored dendrimers are also studied. Based on the obtained results, a comparative analysis as well as a regression analysis was carried out.

Ovarian follicular waves in ovulation induction in assisted reproduction techniques

Background: A greater understanding of the menstrual cycle and multiple waves of antral ovarian follicular development has challenged traditional concepts of female reproductive physiology and the foundations of assisted reproductive technologies (ART). Approximately two-thirds of women develop two follicle waves throughout an interovulatory interval, and the remainder exhibit three waves of follicle development. Major and minor waves of follicle development have been observed. Major waves are those in which a dominant follicle develops; dominant follicles either regress or ovulate. In minor waves, the physiological selection of a dominant follicle is not manifested. Knowledge of the waves of antral follicular development has led to the global adoption of novel ovarian stimulation strategies in which stimulation can be initiated at various times throughout the cycle. Random-start and luteal-phase ovarian stimulation regimens have important clinical applications in women requiring urgent oocyte or embryo cryopreservation for fertility preservation before chemotherapy.
 Objective: To evaluate the role of multiple waves of the antral ovarian follicular in the menstrual cycle in ovulation induction in ART.
 Methods: A literature search using the keywords “multiple waves of antral ovarian follicular development, In Vitro Fertilization, Ovarian stimulation ” was performed in the PubMed database.
 Outcome: Random start and luteal phase of ovulation induction in ART offer the same results in fertilization and pregnancy rates as conventional early follicular phase start.
 Conclusion: The primary benefits of the random-start protocol include a patient-oriented approach to care, timely and efficient treatment, and a lower dropout rate. Women with poor ovarian reserve and those diagnosed with cancer will have a greater chance of successful assisted reproduction with the use of these strategies.

Antioxidant and antiproliferative effect of a glycosaminoglycan extract from Rapana venosa marine snail.

Marine glycosaminoglycans (GAG) isolated from different invertebrates, such as molluscs, starfish or jellyfish, have been described as unique molecules with important pharmacological applications. Scarce information is available on GAG extract from Rapana venosa marine snail. The aim of this study was to isolate a GAG extract from R. venosa marine snail and to investigate its physicochemical, antioxidant and antiproliferative properties for further biomedical use. The morphology, chemical and elemental composition of the extract were established as well as the sulfate content and N- to O-sulfation ratio. Fourier transform infrared (FTIR) spectra indicated that GAG extract presented similar structural characteristics to bovine heparan sulfate and chondroitin sulfate. The pattern of extract migration in agarose gel electrophoresis and specific digestion with chondroitinase ABC and heparinase III indicated the presence of a mixture of chondroitin sulfate-type GAG, as main component, and heparan sulfate-type GAG. Free radical scavenging and ferric ion reducing assays showed that GAG extract had high antioxidant activity, which slightly decreased after enzymatic treatment. In vitro MTT and Live/Dead assays showed that GAG extract had the ability to inhibit cell proliferation in human Hep-2 cell cultures, at cytocompatible concentrations in normal NCTC clone L929 fibroblasts. This capacity decreased after enzymatic digestion, in accordance to the antioxidant activity of the products. Tumoral cell migration was also inhibited by GAG extract and its digestion products. Overall, GAG extract from R. venosa marine snail exhibited antioxidant and antiproliferative activities, suggesting its potential use as novel bioactive compound for biomedical applications.