Loop Structure Research Articles

Case Study on Dynamic Identification of Overburden Fracture and Strong Mine Pressure Mechanism of Isolated Working Face Based on Microseismic Clustering

Strong mine pressure has a great impact upon the safety production of coal mines. Microseismic information provides a more advanced technical means for overburden fracture dynamic identification and mine pressure mechanism research, since it contains rich information on rock fracture sources. In this study, the isolated LW8102 working face in Tongxin Mine was investigated in order to propose a spatio-temporal microseismic event data analysis method based on the k-means clustering algorithm. This algorithm can handle dynamic identification of overburden fractures constrained by spatiotemporally discrete distributions of microseismic events. This provided the dynamic extension process and the fracture distribution pattern of the overburden: eight fracture extensions were formed in the overburden. In each extension, vertical fractures connected the low and high rock layers in the LW8102 and LW8103 goafs, and through fractures connected the LW8102 and LW8103 goafs in their high, middle, and low levels. Some extensions had fractures that were connected to form a closed loop structure. In the vertical fracture, there was a tendency for one or two layers of the stratum to fail first, and then extend to one or both sides. The process of through and vertical fracture propagation followed a certain temporal sequence, reflected primarily in two forms: firstly, as the vertical fracture extended to a certain layer, it provided the initial rupture space for through fracture spreading; secondly, the through fracture first broke, and then extended to the vertical fracture until it intersected with the vertical fracture or provided the initial rupture space for the expansion of the vertical fracture. By matching the overburden fracture to the mine pressure that responded to the support resistance, we analyzed the mechanism of mine pressure at the working face. Through fracture at the high level was found to be the primary cause of the occurrence of mining pressure. It was precisely placed that the formation of multiple adjacent high through fractures 110 m from the floor, triggering simultaneous instability motion of the lower multi-layer level rock; this was the main reason for the phenomenon of strong mine pressure at the working face. Meanwhile, high through fracture at 80 m from the floor was the main reason for the phenomenon of large mine pressure at the working face.

Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network

Emerging evidence has proved that circular RNAs (circRNAs) are implicated in pathogenic processes. They are regarded as promising biomarkers for diagnosis due to covalently closed loop structures. As opposed to traditional experiments, computational approaches can identify circRNA-disease associations at a lower cost. Aggregating multi-source pathogenesis data helps to alleviate data sparsity and infer potential associations at the system level. The majority of computational approaches construct a homologous network using multi-source data, but they lose the heterogeneity of the data. Effective methods that use the features of multi-source data are considered as a matter of urgency. In this paper, we propose a model (CDHGNN) based on edge-weighted graph attention and heterogeneous graph neural networks for potential circRNA-disease association prediction. The circRNA network, micro RNA network, disease network and heterogeneous network are constructed based on multi-source data. To reflect association probabilities between nodes, an edge-weighted graph attention network model is designed for node features. To assign attention weights to different types of edges and learn contextual meta-path, CDHGNN infers potential circRNA-disease association based on heterogeneous neural networks. CDHGNN outperforms state-of-the-art algorithms in terms of accuracy. Edge-weighted graph attention networks and heterogeneous graph networks have both improved performance significantly. Furthermore, case studies suggest that CDHGNN is capable of identifying specific molecular associations and investigating biomolecular regulatory relationships in pathogenesis. The code of CDHGNN is freely available at https://github.com/BioinformaticsCSU/CDHGNN.

Identifying circRNA-miRNA interaction based on multi-biological interaction fusion.

CircRNA is a new type of non-coding RNA with a closed loop structure. More and more biological experiments show that circRNA plays important roles in many diseases by regulating the target genes of miRNA. Therefore, correct identification of the potential interaction between circRNA and miRNA not only helps to understand the mechanism of the disease, but also contributes to the diagnosis, treatment, and prognosis of the disease. In this study, we propose a model (IIMCCMA) by using network embedding and matrix completion to predict the potential interaction of circRNA-miRNA. Firstly, the corresponding adjacency matrix is constructed based on the experimentally verified circRNA-miRNA interaction, circRNA-cancer interaction, and miRNA-cancer interaction. Then, the Gaussian kernel function and the cosine function are used to calculate the circRNA Gaussian interaction profile kernel similarity, circRNA functional similarity, miRNA Gaussian interaction profile kernel similarity, and miRNA functional similarity. In order to reduce the influence of noise and redundant information in known interactions, this model uses network embedding to extract the potential feature vectors of circRNA and miRNA, respectively. Finally, an improved inductive matrix completion algorithm based on the feature vectors of circRNA and miRNA is used to identify potential interactions between circRNAs and miRNAs. The 10-fold cross-validation experiment is utilized to prove the predictive ability of the IIMCCMA. The experimental results show that the AUC value and AUPR value of the IIMCCMA model are higher than other state-of-the-art algorithms. In addition, case studies show that the IIMCCMA model can correctly identify the potential interactions between circRNAs and miRNAs.

Experimental observation of Berry phases in optical Möbius-strip microcavities

The Möbius strip, a fascinating loop structure with one-sided topology, provides a rich playground for manipulating the non-trivial topological behaviour of spinning particles, such as electrons, polaritons and photons, in both real and parameter spaces. For photons resonating in a Möbius-strip cavity, the occurrence of an extra phase—known as the Berry phase—with purely topological origin is expected due to its non-trivial evolution in parameter space. However, despite numerous theoretical investigations, characterizing the optical Berry phase in a Möbius-strip cavity has remained elusive. Here we report the experimental observation of the Berry phase generated in optical Möbius-strip microcavities. In contrast to theoretical predictions in optical, electronic and magnetic Möbius-topology systems where only Berry phase π occurs, we demonstrate that a variable Berry phase smaller than π can be acquired by generating elliptical polarization of resonating light. Möbius-strip microcavities as integrable and Berry-phase-programmable optical systems are of great interest in topological physics and emerging classical or quantum photonic applications.

Research on thermoacoustic refrigeration system driven by waste heat of industrial buildings

Industrial production process continuously produces a large amount of stable waste heat, which has great potential for recovery and utilization. As a new energy conversion and utilization technology, thermoacoustic technology has a good application prospect in low-grade heat sources utilization, with advantages of simple structure, long service life and low cost, and can be applied in waste heat recovery field. The current thermoacoustic studies pay more attention to the improvement of thermoacoustic conversion efficiency. Power output should be considered while paying attention to efficiency in the field of engineering application. The thermoacoustic refrigeration system proposed in this paper uses waste heat generated in industrial buildings to regulate indoor temperature. Based on the theory of traveling-standing wave acoustic field, a design concept of thermoacoustic system was proposed, that is, two thermoacoustic cores are placed on both sides of the high impedance zero phase position to limit the high impedance zero phase phenomenon at the independent thermoacoustic core position. On the basis of this study, the topology of thermoacoustic refrigeration system operating in traveling-standing wave phase was proposed. A two-stage thermoacoustic engine/refrigerator coupled loop structure was adopted to realize the traveling-standing wave acoustic field through the non-uniform alternate distribution of thermoacoustic units. Based on the topology, numerical simulation and system optimization were carried out, and an experimental prototype was set up for experimental studies. The experimental results show good consistency with the simulation results. Under the condition of no load, the lowest cooling temperature reached by thermoacoustic refrigerator is −12℃, and the maximum cooling capacity is 0.95 kW. This study shows that the thermoacoustic refrigeration system driven by waste heat can significantly reduce the energy consumption of industrial buildings in terms of indoor temperature regulation, and improve the energy utilization ratio of industrial buildings.

CircEML1 facilitates the steroid synthesis in follicular granulosa cells of chicken through sponging gga-miR-449a to release IGF2BP3 expression

Non-coding RNAs (ncRNAs) induced competing endogenous RNAs (ceRNA) play crucial roles in various biological process by regulating target gene expression. However, the studies of ceRNA networks in the regulation of ovarian ovulation processing of chicken remains deficient compared to that in mammals. Our present study revealed that circEML1 was differential expressed in hen's ovarian tissues at different ages (15 W/20 W/30 W/68 W) and identified as a loop structure from EML1 pre-mRNA, which promoted the expressions of CYP19A1/StAR and E2/P4 secretion in follicular granulosa cells (GCs). Furthermore, circEML1 could serve as a sponge of gga-miR-449a and also found that IGF2BP3 was targeted by gga-miR-449a to co-participate in the steroidogenesis, which possibly act the regulatory role via mTOR/p38MAPK pathways. Meanwhile, in the rescue experiment, gga-miR-449a could reverse the promoting role of circEML1 to IGF2BP3 and steroidogenesis. Eventually, this study suggested that circEML1/gga-miR-449a/IGF2BP3 axis exerted an important role in the steroidogenesis in GCs of chicken.

Dual factor coactivatable fluorescent nanosensor with boosted cytoplasmic biomarker accessibility toward selective tumor imaging

Fluorescent nanosensor-based tumor imaging holds great promise in cancer diagnosis and treatment assistance, yet the signal contrast is heavily hampered by the unspecific/unwanted activation at microscopic regions with a highly restricted local abundance of biomarkers. Herein, we developed an activation boosting strategy by the integration and manipulation of dual-factor coactivation of sensing and lysosome escape facilitated the rise of cytosolic biomarker accessibility. By employing hybrid DNA probes on gold nanoquenchers, ATP sensing initiated conformation switch of the corresponding aptamer units triggered the exposure of a hidden toehold in a loop structure. Sequentially, miRNA-21 sensing was triggered by toehold-mediated strand displacement and detachment of the binding complexes. The application of lysosomotropic agent chloroquine at optimized time interval facilitated the release of nanosensors into the cytosol and a ∼10.5-fold increment of intracellular fluorescence in vitro, while coactivation improved the cancer-to-normal cell signal ratio by ∼5.9 times. The synergy effects led to a high tumor-to-normal tissue ratio value of ∼7.9 in the in vivo imaging results. This strategy establishes a new paradigm of fluorescent nanosensors for selective and specific tumor imaging.

GPS Receiver VFLL-Assisted PLL High Dynamic Weak Signal Tracking Based on a Maximum Likelihood Estimation

This paper proposes a GPS receiver vector frequency-locked loop-assisted phase-locked loop (VFAPLL) structure based on the maximum likelihood estimation (MLE) method for highly dynamic weak-signal scenarios. In this structure, the loop structure does not include a frequency discriminator, and the signal is directly input to the navigation filter after down-conversion, coherent integration, and other processing to avoid nonlinear noise error. Due to the high dimension and nonlinearity of the cost function of the MLE algorithm, the Levenberg Marquardt (LM) algorithm is used to optimize it. The proposed VFAPLL is compared with the VFAPLL implemented based on the extended Kalman filter (EKF) algorithm and the frequency locked loop assisted phase locked loop (FAPLL) implemented based on MLE. Through simulation verification, it was shown that the VFAPLL (MLE) has higher tracking accuracy, lower loss-of-lock threshold, and better robustness to the input signal than the other two loops.

Role of the Probe Sequence/Structure in Developing an Ultra-Efficient Label-Free COVID-19 Detection Method Based on Competitive Dual-Emission Ratiometric DNA-Templated Silver Nanoclusters as Single Fluorescent Probes.

We report the development of a label-, antibody-, enzyme-, and amplification-free ratiometric fluorescent biosensor for low-cost and rapid (less than 12 min) diagnosis of COVID-19 from isolated RNA samples. The biosensor is designed on the basis of cytosine-modified antisense oligonucleotides specific for either N gene or RdRP gene that can form silver nanoclusters (AgNCs) with both green and red emission on an oligonucleotide via a one-step synthesis process. The presence of the target RNA sequence of SARS-CoV-2 causes a dual-emission ratiometric signal transduction, resulting in a limit of detection of 0.30 to 10.0 nM and appropriate linear ranges with no need for any further amplification, fluorophore, or design with a special DNA fragment. With this strategy, five different ratiometric fluorescent probes are designed, and how the T/C ratio, the length of the stem region, and the number of cytosines in the loop structure and at the 3' end of the cluster-stabilizing template can affect the biosensor sensitivity is investigated. Furthermore, the effect of graphene oxide (GO) on the ratiometric behavior of nanoclusters is demonstrated and the concentration-/time-dependent new competitive mechanism between aggregation-caused quenching (ACQ) and aggregation-induced emission enhancement (AIE) for the developed ssDNA-AgNCs/GO nanohybrids is proposed. Finally, the performance of the designed ratiometric biosensor has been validated using the RNA extract obtained from more than 150 clinical samples, and the results have been confirmed by the FDA-approved reverse transcription-polymerase chain reaction (RT-PCR) diagnostic method. The diagnostic sensitivity and specificity of the best probe is more than >90%, with an area under the receiver operating characteristic (ROC) curve of 0.978.

Modeling the dynamics of innovation ecosystems

Demand for solving systemic problems has resulted in the need for new forms of innovation. Accordingly, the concept of innovation ecosystem has emerged. Ecosystems are intrinsically more fluid than networks, which set ups the need to understand and orchestrate the internal dynamics of innovation ecosystem in order to have successful innovation outcomes. The dynamics of ecosystems, however, is not well understood. In this paper the dynamics of innovation ecosystems has been studied by applying the methodology of system dynamics. The purpose of the study is to support the creation of innovation ecosystems and the orchestration of existing ecosystems so that they could be more successful. Key factors generating dynamics in innovation ecosystems were identified. They form the elements of the system dynamics model of innovation ecosystems. The causal loop structure between the model elements indicates how the key factors of dynamics influence the outcome of ecosystem.

THOC5 complexes with DDX5, DDX17, and CDK12 to regulate R loop structures and transcription elongation rate

THOC5, a member of the THO complex, is essential for the 3'processing of some inducible genes, the export of a subset of mRNAs and stem cell survival. Here we show that THOC5 depletion results in altered 3'cleavage of >50% of mRNAs and changes in RNA polymerase II binding across genes. THOC5 is recruited close to high-density polymerase II sites, suggesting that THOC5 is involved in transcriptional elongation. Indeed, measurement of elongation rates invivo demonstrated decreased rates in THOC5-depleted cells. Furthermore, THOC5 is preferentially recruited to its target genes in slow polymerase II cells compared with fast polymerase II cells. Importantly chromatin-associated THOC5 interacts with CDK12 (a modulator of transcription elongation) and RNA helicases DDX5, DDX17, and THOC6 only in slow polymerase II cells. The CDK12/THOC5 interaction promotes CDK12 recruitment to R-loops in a THOC6-dependent manner. These data demonstrate a novel function of THOC5 in transcription elongation.

Projection of fuel cell electric vehicle demand reflecting the feedback effects between market conditions and market share affected by spatial factors

The Korean government has planned policies to increase the penetration rate of fuel cell electric vehicles (FCEVs). Policy intervention has a positive effect on FCEV diffusion. Infrastructure distribution plays a significant role in accelerating penetration rate at the early stage of the market. Although inevitably differences exist in the accessibility of hydrogen refueling stations (HRSs) by region due to various constraints, few studies have considered accessibility in detail. This study analyzes how policies that vary depending on time and space, including infrastructure distribution, impact demand for FCEVs. A multistage structure is employed in the analysis to reflect the influence of spatial factors. Vehicle preference is analyzed through a discrete choice experiment at the first stage. The second stage solves the location problem and predicts the market share of FCEVs by reflecting the feedback effect between FCEVs’ market share and the accessibility of HRSs through a loop structure. The results indicate that improving access to HRSs positively affects the initial stage of the market; however, after accessibility reaches a certain level, it no longer affects the market share. The subsidies for hydrogen refueling costs bring a relatively rapid change to the gradually increasing penetration rate of FCEVs.

DeepCubist: Molecular Generator for Designing Peptidomimetics based on Complex three-dimensional scaffolds

Mimicking bioactive conformations of peptide segments involved in the formation of protein-protein interfaces with small molecules is thought to represent a promising strategy for the design of protein-protein interaction (PPI) inhibitors. For compound design, the use of three-dimensional (3D) scaffolds rich in sp3-centers makes it possible to precisely mimic bioactive peptide conformations. Herein, we introduce DeepCubist, a molecular generator for designing peptidomimetics based on 3D scaffolds. Firstly, enumerated 3D scaffolds are superposed on a target peptide conformation to identify a preferred template structure for designing peptidomimetics. Secondly, heteroatoms and unsaturated bonds are introduced into the template via a deep generative model to produce candidate compounds. DeepCubist was applied to design peptidomimetics of exemplary peptide turn, helix, and loop structures in pharmaceutical targets engaging in PPIs.

CircSMARCC1 and CircLRBA are potential biomarkers in forensic postmortem diagnosis of acute myocardial infarction

Postmortem diagnosis of acute myocardial infarction (AMI), especially early AMI, is a challenge for forensic scientists. Circular RNAs (circRNA) are a unique type of RNA with a closed loop structure and more stability, compared with linear RNA. We aimed at evaluating whether circRNAs are ideal postmortem diagnostic markers for AMI. We employed bioinformatics methods to screen for target circRNAs. Divergent and convergent primers were used to confirm the loop structure. Ribonuclease R (RNaseR) digestion and artificial simulated room temperature test were performed to evaluate the stability of circRNAs. Furthermore, RT-PCR analysis was performed to assess the expressions of target circRNAs in a mouse model of AMI and in autopsy cases, while the diagnostic significance of circRNAs was evaluated by the receiver-operator characteristic (ROC) curve. The bioinformatics analysis screened out circSMARCC1 and circLRBA as target circRNAs. Agarose gel electrophoresis revealed the loop structure of target circRNAs. RNaseR digestion and the artificial simulated room temperature test showed that the stability of circRNAs was good. In mouse AMI model, circSMARCC1 levels were elevated while circLRBA levels were suppressed. Finally, in forensic autopsy cases, circSMARCC1 levels were significantly elevated, while circLRBA levels were significantly suppressed in the MI and early-MI group, relative to the normal control group. The ROC curve analysis showed that both circSMARCC1 and circLRBA can distinguish between AMI and normal control cases. Futher, a combination of the two circRNAs can increase the diagnostic efficacy of AMI. Thus, circSMARCC1 and circLRBA are potential biomarkers for postmortem diagnosis of AMI.

Systematic identification and characterization of repeat sequences in African swine fever virus genomes

African swine fever virus (ASFV) is a large DNA virus that infects domestic pigs with high morbidity and mortality rates. Repeat sequences, which are DNA sequence elements that are repeated more than twice in the genome, play an important role in the ASFV genome. The majority of repeat sequences, however, have not been identified and characterized in a systematic manner. In this study, three types of repeat sequences, including microsatellites, minisatellites and short interspersed nuclear elements (SINEs), were identified in the ASFV genome, and their distribution, structure, function, and evolutionary history were investigated. Most repeat sequences were observed in noncoding regions and at the 5’ end of the genome. Noncoding repeat sequences tended to form enhancers, whereas coding repeat sequences had a lower ratio of alpha-helix and beta-sheet and a higher ratio of loop structure and surface amino acids than nonrepeat sequences. In addition, the repeat sequences tended to encode penetrating and antimicrobial peptides. Further analysis of the evolution of repeat sequences revealed that the pan-repeat sequences presented an open state, showing the diversity of repeat sequences. Finally, CpG islands were observed to be negatively correlated with repeat sequence occurrences, suggesting that they may affect the generation of repeat sequences. Overall, this study emphasizes the importance of repeat sequences in ASFVs, and these results can aid in understanding the virus's function and evolution.

Distributed Temperature and Curvature Sensing Based on Raman Scattering in Few-Mode Fiber

We propose and experimentally demonstrate a distributed temperature and curvature sensing method based on spontaneous Raman backscattered lights in a few-mode optical fiber. A loop structure is used to demodulate the distributed temperature information using the Raman anti-Stokes (AS) scattering lights. And the fiber curvature is estimated by the loss of Raman Stokes (S) light. This system can measure temperature and curvature at the same position of the fiber simultaneously. The experimental results show that the temperature uncertainty and spatial resolution can reach up to 0.24 °C and 1.8 m on 6 km sensing fiber. Besides, the maximum measurement error is 0.11 cm within the curvature measurement range of 0.5–3 cm.

A Miniaturized Wireless Passive Frequency Selective Surface Sensor for High-Temperature Applications

A passive and wireless sensor based on frequency selective surface (FSS) is presented for high-temperature applications. The sensor consists of a bent square loop array deposited in an alumina dielectric substrate. By inserting four symmetrical slots in the square loop structure, the dimension of the FSS unit cell is as compact as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.13 \lambda _{{0}}$ </tex-math></inline-formula> . The results show that the resonant frequency of the sensor decreases from 13.96 to 13.172 GHz with an average sensitivity of 0.81 MHz/°C when the temperature rises from 25 to 1000 °C. It was found that the resonant frequency shift is mainly attributed to the variations in permittivity of the substrate material. The sensor has a stable resonant frequency for both TE and TM polarizations under incident angles with a range of 0°–30°. The proposed sensor, which has the advantages of miniaturization, low profile, high sensitivity, and excellent angular stability, can be potentially applied in various harsh environments.

Polarimetric signatures of hot spots in black hole accretion flows

Context. The flaring events observed in the Sagittarius A* supermassive black hole system can be attributed to the nonhomogeneous nature of the near-horizon accretion flow. Bright regions in this flow may be associated with density or temperature anisotropies, corresponding to so-called “bright spots” or “hot spots.” Such orbiting features may explain observations at infrared wavelengths, as well as recent findings at millimeter wavelengths. Aims. In this work, we study the emission from an orbiting equatorial bright spot, imposed on a radiatively inefficient accretion flow background, to find polarimetric features indicative of the underlying magnetic field structure and other system variables, including inclination angle, spot size, black hole spin, and more. Specifically, we investigate the impact of these parameters on the Stokes 𝒬 − 𝒰 signatures that commonly exhibit a typical double loop (pretzel-like) structure. Methods. Our semi-analytical model, describing the underlying plasma conditions and the orbiting spot, is built within the framework of the numerical radiative transfer code ipole, which calculates synchroton emission at 230 GHz. Results. We showcase the wide variety of 𝒬 − 𝒰 loop signatures and the relation between inner and outer loops. For the vertical magnetic field topology, the inner 𝒬 − 𝒰 loop is explained by the suppression of the synchrotron emission as seen by the distant observer. For the radial and toroidal magnetic field topologies, the inner 𝒬 − 𝒰 loop corresponds to the part of the orbit where the spot is receding with respect to the observer. Conclusions. Based on our models, we conclude that it is possible to constrain the underlying magnetic field topology with an analysis of the 𝒬 − 𝒰 loop geometry, particularly in combination with circular polarization measurements.

Research and experiment on control loop system of Source Measure Unit

Aiming at the problem that the capacitive load of the source measure unit (SMU) system affects the stability of the loop control, this paper makes an in-depth theoretical analysis of the loop control system based on the SMU. A theoretical and circuit model is established after the analysis. In the control loop structure, an integrator with proportional amplification serves as an error amplifier for the control loop system to obtain sufficient phase margin at the optimal bandwidth. A phase-lead compensation capacitor scheme is studied and proposed to achieve the maximum tolerance range to achieve the loop stability. The results show that the simulation and experimental results are basically consistent. The results verify the theoretical correctness and practical value of this SMU control loop system, and provide a theoretical basis for the research of the SMU control loop structure of the subsequent SIP process.

Washability and abrasion resistance of illuminative knitted e-textiles with POFs and silver-coated conductive yarns

For the integration of conductive yarns in e-textiles, knitting offers structural versatility and malleability for wider product applications in the contexts of wearables and interiors. To enable mass adoption of conductive materials, it is imperative for users to be able to launder these materials as part of product maintenance. Interactive textiles knitted from polymeric optical fibres (POFs) and silver-coated conductive yarns are able to illuminate and change colours via integrated touch sensor systems. Current research only focuses on the washability and abrasion resistance of conductive yarns solely and not both POF and conductive yarn within the same fabric structure. This study is novel as it investigates the washability and abrasion resistance of POF and silver-coated conductive yarn integrated knitted textiles with different loop structures and the impact to their illuminative function. POFs were knitted within the same fabric structure by the inlay method using a 7-gauge industrial hand-operated flatbed knitting machine. This study examined how washing and abrasion affect POFs and silver-coated conductive yarn in five different knit structures, and the illuminative function of the knitted textiles. Washing and abrasion affected the resistance of conductive yarns. Scratches and bent POFs were observed after 20 gentle washing cycles. However, washing had minimal impact on the illuminative function of the knitted e-textiles examined in this study. The experiments provide evidence that e-textiles knitted with POFs and conductive yarns in the same fabric structure withstand washing and abrasion and thus have the potential for mass market adoption in fashion and interior applications.