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Bi2O2Se holds potential for the realization of 2D optical modulators due to its broadband nonlinear response, air stability and carrier mobility. Here, the authors report the realization of defect-engineered Bi2O2Se nanoplates as saturable absorbers for femtosecond solid-state lasers, showing improved output power and pulse duration.

Investigating the spatial distribution characteristics and influencing factors of various industry types is critical for promoting the high-quality transformation and development of China's industry. This study combined the Getis-Ord Gi* statistic method, the random forest-based importance assessment method, and the geographically weighted regression method to determine the spatial distribution characteristics of four industry types and their influencing factors. The results revealed that the raw material industry was primarily concentrated in the surrounding districts and counties of Linyi and Qingdao. The food and light textile industry was mainly concentrated in the surrounding districts and counties of Qingdao, and a few were concentrated in some counties of Linyi. The processing and manufacturing industry was also concentrated in the surrounding districts and counties of Qingdao, and a few were concentrated in the belt regions connecting Jinan, Zibo, and Weifang. The high-tech industry was mainly concentrated in the surrounding districts and counties of Jinan and Qingdao. The key spatial influencing factors of the four industry types were different. The number of employees in the secondary industry and road density were most important in determining the spatial distribution of the raw material industry. The financial environment and number of research institutions were most important to the spatial distribution of the food and light textile industry. The gross domestic product and number of medical facilities were most important to the spatial distribution of the processing and manufacturing industry. Urbanization rate, number of research institutions, and gross domestic product were most important to the spatial distribution of the high-tech industry. Geographically weighted regression analysis revealed that the impact intensity of these key factors on the industry exhibits significant spatial heterogeneity. Taken together, these results are useful for formulating the development strategy for each industrial type in different regions.

BackgroundAmelioration of depression in patients with post-stroke depression (PSD) remains challenging.ObjectiveThe primary vision was to explore the effect of transcranial magnetic stimulation (TMS) in combination with citalopram on patients with PSD.MethodsOne hundred eligible patients who were diagnosed with PSD were recruited and randomly assigned to the control group (n = 50) or the TMS group (n = 50). The controls were given citalopram (10 mg/d for consecutive 8 weeks), while, in addition to citalopram, patients in the TMS group were also given TMS at 5 Hz once a workday for 8 weeks. The primary outcome was patient depression status as reflected by 17-item Hamilton Rating Scale for Depression (HAMD-17) score, and the secondary outcome was patient neuropsychological score determined by Mini-Mental State Examination (MMSE) and Wisconsin Card Sorting Test (WCST).ResultsPatients treated with TMS in combination with citalopram had a drastic decrease in HAMD-17 score during treatment. Bigger changes in HAMD-17 score between baseline and 2 weeks as well as between baseline and 8 weeks in the TMS group were observed (P < 0.01). Patients in both groups had increased MMSE scores after treatment. Data of WCST revealed patients with TMS treatment completed more categories (P < 0.01) and had a lower RPP in comparison to patients in the control group (P < 0.0001). Additionally, TMS in combination with citalopram strikingly improved patients' MMSE scores when compared with those taking citalopram alone. Last, there was no striking difference in side effects between the two groups (P > 0.05).ConclusionOur study found TMS in combination with citalopram is conducive to improving depression status and neuropsychological function, which holds great promise for treating PSD.

ReS2, as a new member of transition metal dichalcogenides (TMDCs), has emerged as a promising substrate for semiconductor surface-enhanced Raman spectroscopy (SERS) due to its unique optoelectronic properties. Nevertheless, the sensitivity of the ReS2 SERS substrate poses a significant challenge to its widespread application in trace detection. In this work, we present a reliable approach for constructing a novel ReS2/AuNPs SERS composite substrate, enabling ultrasensitive detection of trace amounts of organic pesticides. We demonstrate that the porous structures of ReS2 nanoflowers can effectively confine the growth of AuNPs. By precisely controlling the size and distribution of AuNPs, numerous efficient and densely packed “hot spots” were created on the surface of ReS2 nanoflowers. As a result of the synergistic enhancement of the chemical and electromagnetic mechanisms, the ReS2/AuNPs SERS substrate demonstrates high sensitivity, good reproducibility, and superior stability in detecting typical organic dyes such as rhodamine 6G and crystalline violet. The ReS2/AuNPs SERS substrate shows an ultralow detection limit of 10−10 M and a linear detection of organic pesticide molecules within 10−6–10−10 M, which is significantly lower than the EU Environmental Protection Agency regulation standards. The strategy of constructing ReS2/AuNPs composites would contribute to the development of highly sensitive and reliable SERS sensing platforms for food safety monitoring.

Abstract Localization of epileptogenic zone currently requires prolonged intracranial recordings to capture seizure, which may take days to weeks. The authors developed a novel method to identify the seizure onset zone (SOZ) and predict seizure outcome using short‐time resting‐state stereotacticelectroencephalography (SEEG) data. In a cohort of 27 drug‐resistant epilepsy patients, the authors estimated the information flow via directional connectivity and inferred the excitation‐inhibition ratio from the 1/f power slope. They hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non‐SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation‐inhibition balance. They found flatter 1/f power slope in non‐SOZ regions compared to the SOZ, with dominant information flow from non‐SOZ to SOZ regions. Greater differences in resting‐state information flow between SOZ and non‐SOZ regions are associated with favorable seizure outcome. By integrating a balanced random forest model with resting‐state connectivity, their method localized the SOZ with an accuracy of 88% and predicted the seizure outcome with an accuracy of 92% using clinically determined SOZ. Overall, this study suggests that brief resting‐state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long‐term ictal recordings.

Predicting the prognosis of patients in advance is conducive to providing personalized treatment for patients. Our aim was to predict the therapeutic efficacy and progression free survival (PFS) of patients with liver metastasis of colorectal cancer according to the changes of computed tomography (CT) radiomics before and after chemotherapy.MethodsThis retrospective study included 139 patients (397 lesions) with colorectal liver metastases who underwent neoadjuvant chemotherapy from April 2015 to April 2020. We divided the lesions into training cohort and testing cohort with a ratio of 7:3. Two - dimensional region of interest (ROI) was obtained by manually delineating the largest layers of each metastasis lesion. The expanded ROI (3 mm and 5 mm) were also included in the study to characterize microenvironment around tumor. For each of the ROI, 1,316 radiomics features were extracted from delineated plain scan, arterial, and venous phase CT images before and after neoadjuvant chemotherapy. Delta radiomics features were constructed by subtracting the radiomics features after treatment from the radiomics features before treatment. Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were applied in the training cohort to select the valuable features. Based on clinical characteristics and radiomics features, 7 Cox proportional-hazards model were constructed to predict the PFS of patients. C-index value and Kaplan Meier (KM) analysis were used to evaluate the efficacy of predicting PFS of these models. Moreover, the prediction performance of one-year PFS was also evaluated by area under the curve (AUC).ResultsCompared with the PreRad (Radiomics form pre-treatment CT images; C-index [95% confidence interval (CI)] in testing cohort: 0.614(0.552-0.675) and PostRad models (Radiomics form post-treatment CT images; 0.642(0.578-0.707), the delta model has better PFS prediction performance (Delta radiomics; 0.688(0.627-0.749). By incorporating clinical characteristics, CombDeltaRad obtains the best performance in both training cohort [C-index (95% CI): 0.802(0.772-0.832)] and the testing cohort (0.744(0.686-0.803). For 1-year PFS prediction, CombDeltaRad model obtained the best performance with AUC (95% CI) of 0.871(0.828-0.914) and 0.745 (0.651-0.838) in training cohort and testing cohort, respectively.ConclusionCT radiomics features have the potential to predict PFS in patients with colorectal cancer and liver metastasis who undergo neoadjuvant chemotherapy. By combining pre-treatment radiomics features, post-treatment radiomics features, and clinical characteristics better prediction results can be achieved.

Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients’ interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.

Diagnosability is an important metric parameter for measuring the reliability of multiprocessor systems. The pessimistic diagnosis strategy is a classic diagnostic model based on the PMC model. The class of folded Petersen cubes, denoted by FPQn,k, where n,k≥0 and n,k≠0,0, is introduced as a competitive model of the hypercubes, which is constructed by iteratively applying the Cartesian product operation on the hypercube Qn and the Petersen graph P. In this paper, by exploring the structural properties of the folded Petersen cubes FPQn,k, we first prove that FPQn,k is n+3k diagnosable under the PMC model. Then, we completely derive that the pessimistic diagnosability of FPQn,k is 2n+6k−2 under the PMC model. Furthermore, the diagnosability and the pessimistic diagnosability of the class of folded Petersen cubes, including the hypercube, folded Petersen graph, and hyper Petersen graph, are obtained.

Noninvasive electromagnetic measurements are utilized effectively to estimate large scale dynamic brain networks. Sohrabpour et al. propose a novel electrophysiological source imaging approach to estimate the location and size of epileptogenic tissues in patients with epilepsy.

High-quality fluorescent probes based on carbon dots (CDs) have promising applications in many fields owing to their good stability, low toxicity, high quantum yield, and low raw material price. The fluorine- and nitrogen-doped fluorescent CDs (NFCDs) with blue fluorescence was successfully synthesized using 3-aminophenol and 2,4-difluorobenzoic acid as the raw material by the hydrothermal method. The NFCDs as probe can be used to directly and indirectly detect Fe3+ (detection range: 0.1–150 μM and detection limit: 0.14 μM) and ascorbic acid (AA) (detection range: 10–80 μM and detection limit: 0.11 μM). The NFCDs-based probe shows exceptional selectivity and strong anti-interference for Fe3+ and ascorbic acid (AA). In addition, we examined the response of NFCDs to Fe3+ and AA in living cells, which showed that the timely use of AA can reduce the effects of iron poisoning. This has important biological significance. This means that using NFCDs as fluorescent probes is beneficial for Fe3+ and AA detection and observing their dynamic changes in living cells. Thus, this work may contribute to the study of Fe3+- and AA-related diseases.

Pyemotes zhonghuajia Yu, Zhang & He (Prostigmata: Pyemotidae), discovered in China, has been demonstrated as a high-efficient natural enemy in controlling many agricultural and forestry pests. This mite injects toxins into the host (eggs, larvae, pupae, and adults), resulting in its paralyzation and then gets nourishment for reproductive development. These toxins have been approved to be mammal-safe, which have the potential to be used as biocontrol pesticides. Toxin proteins have been identified from many insects, especially those from the orders Scorpions and Araneae, some of which are now widely used as efficient biocontrol pesticides. However, toxin proteins in mites are not yet understood. In this study, we assembled the genome of P. zhonghuajia using PacBio technology and then identified toxin-related genes that are likely to be responsible for the paralytic process of P. zhonghuajia. The genome assembly has a size of 71.943 Mb, including 20 contigs with a N50 length of 21.248 Mb and a BUSCO completeness ratio of 90.6% (n = 1367). These contigs were subsequently assigned to three chromosomes. There were 11,183 protein coding genes annotated, which were assessed with 91.2% BUSCO completeness (n = 1066). Neurotoxin and dermonecrotic toxin gene families were significantly expanded within the genus of Pyemotes and they also formed several gene clusters on the chromosomes. Most of the genes from these two families and all of the three agatoxin genes were shown with higher expression in the one-day-old mites compared to the seven-day-pregnant mites, supporting that the one-day-old mites cause paralyzation and even death of the host. The identification of these toxin proteins may provide insights into how to improve the parasitism efficiency of this mite, and the purification of these proteins may be used to develop new biological pesticides.

Summary: Members of a disintegrin and metalloproteinases with thrombospondin motif (ADAMTS) family have been implicated in various vascular diseases. However, their functional roles in early embryonic vascular development are unknown. In this study, we showed that Adamts18 is highly expressed at E11.5-E14.5 in cells surrounding the embryonic aortic arch (AOAR) and the common carotid artery (CCA) during branchial arch artery development in mice. Adamts18 deficiency was found to cause abnormal development of AOAR, CCA, and the third and fourth branchial arch appendages, leading to hypoplastic carotid body, thymus, and variation of middle cerebral artery. Adamts18 was shown to affect the accumulation of extracellular matrix (ECM) components, in particular fibronectin (Fn), around AOAR and CCA. As a result of increased Fn accumulation, the Notch3 signaling pathway was activated to promote the differentiation of cranial neural crest cells (CNCCs) to vascular smooth muscle cells. These data indicate that Adamts18-mediated ECM homeostasis is crucial for the differentiation of CNCCs.

Carbon dots (CDs), a class of fluorescent nanomaterials, have attracted widespread attention from researchers. Because of their unique chemical properties, these high-quality fluorescent probes are widely used for ion and molecule detection. Excess intake of many ions or molecules can cause harm to the human body. Although iron (in the form of Fe3+ ions) is essential for the human body, excess iron in the human body can cause many diseases, such as iron poisoning. In this study, we have synthesized fluorine and nitrogen co-doped carbon dots (FNCDs) by a hydrothermal method. These FNCDs exhibited good stability, selectivity, and anti-interference ability for Fe3+. Fe3+ could be detected in the range of 0.2–300 μM, and their detection limit is up to 0.08 μM. In addition, the recovery and relative standard deviation measured by the standard addition recovery method were not higher than 107.5% and 1.1%, respectively, indicating that FNCDs have good recovery and accuracy for Fe3+ detection.

A Cr4+-doped TiTe3O8 crystal with dimensions up to 21 mm × 21 mm × 11 mm was grown successfully by the top-seeded solution growth method. A high-resolution X-ray diffraction experiment showed that the full width at half-maximum of the rocking curve was 41.90″. Energy-dispersive spectrometry (EDS) and X-ray fluorescence spectroscopy (XRF) proved that Cr4+ ions have been doped into the TiTe3O8 crystal with molar percentage of 4.9%. The Cr:TiTe3O8 crystal exhibited an absorption range from 995 to 1565 nm, which is suitable for passive Q switch at 1064 nm. Then, a passive Q-switching solid-state laser operating at 1064 nm was realized using a Cr:TiTe3O8 crystal as the saturable absorber. The maximum laser pulse energy is calculated to be 0.7 μJ, and the maximum peak power reaches 0.7 W.

The aim of this study was to identify critical genes associated with neuropathic pain. We also used the competing endogenous RNA (ceRNA) hypothesis to identify related long non-coding RNAs (lncRNAs) and messenger RNAs (miRNAs) with potential regulatory roles. We downloaded GSE107180 from the Gene Expression Omnibus database, screened differentially expressed genes (DEGs) using R software, performed comprehensive bioinformatic analyses, and validated the expression of lncRNA Slc6a19os, miR-125a-5p, miR-125b-5p, miR-351-5p, and Sox11 by qRT-PCR and Western blots. We identified 620 DEGs in spared nerve injury (SNI) mice compared with sham (control) mice, including 309 mRNAs and 311 non-coding RNAs. The up-regulated mRNAs were enriched primarily in several inflammation-related GO biological processes and KEGG signaling pathways. A ceRNA network was constructed that included 82 mRNAs, 4 miRNAs, and 2 lnRNAs. An ingenuity pathway analysis (IPA)-based interaction network for mRNAs differentially expressed in the ceRNA identified several biological processes, including “cellular development, connective tissue development and function, tissue development.” Compared with sham mice, lncRNA Slc6a19os and Sox11 expression were significantly up-regulated in dorsal root ganglion (DRG) samples from SNI mice detected using qRT-PCR and Western blots (P < 0.05). MiR-125a-5p, miR-125b-5p, and miR-351-5p expression were down-regulated in DRG samples from SNI mice detected using qRT-PCR (P < 0.05). We concluded that Sox11 and lncRNA Slc6a19os were novel essential genes in the pathogenesis and progression of neuropathic pain and speculated that these two genes were regulated by miR-125a-5p, miR-125b-5p, and miR-351-5p.

Management of gastrointestinal stromal tumors (GISTs) has been revolutionized by the identification of activating mutations in KIT and PDGFRA and clinical application of RTK inhibitors in advanced disease. Stratification of GISTs into molecularly defined subsets provides insight into clinical behavior and response to approved targeted therapies. Although these RTK inhibitors are effective in most GISTs, resistance remains a significant clinical problem. Development of effective treatment strategies for refractory GISTs requires identification of novel targets to provide additional therapeutic options. Global kinome profiling has the potential to identify critical signaling networks and reveal protein kinases essential in GISTs. Using multiplexed inhibitor beads and mass spectrometry, we explored the majority of the kinome in GIST specimens from the 3 most common molecular subtypes (KIT mutant, PDGFRA mutant, and succinate dehydrogenase deficient) to identify kinase targets. Kinome profiling with loss-of-function assays identified an important role for G2/M tyrosine kinase, Wee1, in GIST cell survival. In vitro and in vivo studies revealed significant efficacy of MK-1775 (Wee1 inhibitor) in combination with avapritinib in KIT mutant and PDGFRA mutant GIST cell lines as well as notable efficacy of MK-1775 as a monotherapy in the engineered PDGFRA mutant line. These studies provide strong preclinical justification for the use of MK-1775 in GIST.

In this research, the complete mitochondrial genome (mitogenome) of Phthorimaea operculella was sequenced and annotated. The mitogenome of P. operculella is 15,269 bp in length and contains 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, 2 ribosome RNA (12s and 16srRNA) genes and 1 control region. In addition, we used Endoclita signifier as the outgroup to analyze phylogenetic relationship, and the phylogenetic tree showed the sister relationship between P. operculella and Tuta absoluta.

In this study, we sequenced and annotated the complete mitochondrial genome (mitogenome) of Neotoxoptera formosana (Takahashi) (Hemiptera: Aphididae). The complete mitogenome of N. formosana is 15,642 bp in length, and includes 13 protein-coding genes (PCGs), 2 ribosome RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and one control region. The overall base composition was as follows: 45.2% of A, 5.8% of G, 10.5% of C, and 38.4% of T, with a total of A + T content of 83.6%. The phylogenetic tree showed that N. formosana and Myzus persicae were clustered into one branch. This result will enrich the mitogenome of family Aphididae.

Summary: ADAMTSs (a disintegrin and metalloproteinase with thrombospondin motifs) are secreted metalloproteinases that play a major role in the assembly and degradation of the extracellular matrix (ECM). In this study, we show that ADAMTS18, produced by the epithelial cells of distal airways and mesenchymal cells in lung apex at early embryonic stages, serves as a morphogen in lung development. ADAMTS18 deficiency leads to reduced number and length of bronchi, tipped lung apexes, and dilated alveoli. These developmental defects worsen lipopolysaccharide-induced acute lung injury and bleomycin-induced lung fibrosis in adult Adamts18-deficient mice. ADAMTS18 deficiency also causes increased levels of fibrillin1 and fibrillin2, bronchial microfibril accumulation, decreased focal adhesion kinase signaling, and disruption of F-actin organization. Our findings indicate that ECM homeostasis mediated by ADAMTS18 is pivotal in airway branching morphogenesis.

The majority of gastrointestinal stromal tumor (GIST) patients develop resistance to the first-line KIT inhibitor, imatinib mesylate (IM), through acquisition of secondary mutations in KIT or bypass signaling pathway activation. In addition to KIT, AKT is a relevant target for inhibition, since the PI3K/AKT pathway is crucial for IM-resistant GIST survival. We evaluated the activity of a novel pan-AKT inhibitor, MK-4440 (formerly ARQ 751), as monotherapy and in combination with IM in GIST cell lines and preclinical models with varying IM sensitivities. Dual inhibition of KIT and AKT demonstrated synergistic effects in IM-sensitive and -resistant GIST cell lines. Proteomic analyses revealed upregulation of the tumor suppressor, PDCD4, in combination treated cells. Enhanced PDCD4 expression correlated to increased cell death. In vivo studies revealed superior efficacy of MK-4440/IM combination in an IM-sensitive preclinical model of GIST compared with either single agent. The combination demonstrated limited efficacy in two IM-resistant models, including a GIST patient-derived xenograft model possessing an exon 9 KIT mutation. These studies provide strong rationale for further use of AKT inhibition in combination with IM in primary GIST; however, alternative agents will need to be tested in combination with AKT inhibition in the resistant setting.

The use of carbon dots (CDs) with dual emission based on ratiometric fluorescence has been attracting attention in recent times for more accurate ion detection since they help avoid interference from background noise, probe concentration, and complexity. Herein, novel dual-emission nitrogen-doped CDs (NCDs) were prepared by a simple method for Cu2+ and ClO- detection. The NCDs showed excellent anti-interference ability and selectivity for different emissions. In addition, a good linear relationship was observed between the fluorescence intensity (FI) of the NCD solutions in different emissions with Cu2+ (0–90 μM) and ClO− (0–75 μM). The limits of both Cu2+ detection and ClO− were very low, at 17.7 and 11.6 nM, respectively. The NCDs developed herein also showed a good recovery rate in water for Cu2+ and ClO− detection. Hence, they are expected to have a more extensive application prospect in real samples.

Inorganic quantum dots (QDs) have excellent optical properties, such as high fluorescence intensity, excellent photostability and tunable emission wavelength, etc., facilitating them to be used as labels and probes for bioimaging. In this study, CdSe@ZnS QDs are used as probes for Fluorescence lifetime imaging microscope (FLIM) and stimulated emission depletion (STED) nanoscopy imaging. The emission peak of CdSe@ZnS QDs centered at 526nm with a narrow width of 19nm and the photoluminescence quantum yield (PLQY) was 64%. The QDs presented excellent anti-photobleaching property which can be irradiated for 400min by STED laser with 39.8mW. The lateral resolution of 42.0nm is demonstrated for single QDs under STED laser (27.5mW) irradiation. Furthermore, the CdSe@ZnS QDs were for the first time used to successfully label the lysosomes of living HeLa cells and 81.5nm lateral resolution is obtained indicating the available super-resolution applications in living cells for inorganic QD probes. Meanwhile, Eca-109 cells labeled with the CdSe@ZnS QDs was observed with FLIM, and their fluorescence lifetime was around 3.1ns, consistent with the in vitro value, suggesting that the QDs could act as a satisfactory probe in further FLIM-STED experiments.

Single-crystal fibers (SCFs) have a great application potential in high-power lasers due to their excellent performance. In this work, high-quality and crack-free Yb3+:Lu3Al5O12 (Yb:LuAG) SCFs were successfully fabricated by the micro-pulling-down (μ-PD) technology. Based on the laser micrometer and the X-ray Laue diffraction results, these Yb:LuAG SCFs have a less than 5% diameter fluctuation and good crystallinity along the axial direction. More importantly, the distribution of Yb ions is proved to be uniform by electron probe microanalysis (EPMA) and the scanning electron microscope (SEM). In the laser experiment, the continuous-wave (CW) output power using a 1 mm diameter Yb:LuAG single-crystal fiber is determined to be 1.96 W, at the central wavelength of 1047 nm, corresponding to a slope efficiency of 13.55%. Meanwhile, by applying a 3 mm diameter Yb:LuAG SCF, we obtain a 4.7 W CW laser output at 1049 nm with the slope efficiency of 22.17%. The beam quality factor M2 is less than 1.1 in both conditions, indicating a good optical quality of the grown fiber. Our results show that the Yb:LuAG SCF is a potential solid-state laser gain medium for 1 μm high-power lasers.

The pressure equation, generated while solving the incompressible Navier−Stokes equations with the segregated iterative algorithm such as PISO, produces a series of linear equation systems as the time step advances. In this paper, we target at accelerating the iterative solution of these linear systems by improving their initial guesses. We propose a weighted group extrapolation method to obtain a superior initial guess instead of a general one, the solution of the previous linear equation system. In this method, the previous solutions that are used to extrapolate the predicted solutions are carefully organized to address the oscillatory solution on each grid. The proposed method uses a weighted average of the predicted solutions as the new initial guess to avoid over extrapolating. Three numerical test results show that the proposed method can accelerate the iterative solution of most linear equation systems and reduce the simulation time up to 61.3%.

Single-molecule surface-enhanced Raman scattering (SERS) has been extensively studied over the past decade. In this paper, we propose a novel method to obtain ultrahigh enhancement of local electric fields by using a silver nanoshell with a gain core above a silver substrate. Numerical results show that an ultrahigh enhancement factor of the local electric field on the order of 105-106 and a SERS enhancement factor on the order of 1020-1025 can be obtained with the present system. The SERS enhancement factor is five orders of magnitude greater than the highest theoretical value reported for SERS applications at the single-molecule level. In addition, we use the finite-element method to analyze in detail the influences of the gain coefficient of the gain core and the other structure parameters on the enhancement factor.

The hybrid atomistic-continuum coupling method based on domain decomposition serves as an important tool for the micro-fluid simulation. There exists a certain degree of parallelism load imbalance when directly using the USHER algorithm in the domain decomposition–based hybrid atomistic-continuum coupling method. In this article, we propose a grid-based parallel algorithm for particle insertion, named WI-USHER, to improve the efficiency of the particle insertion operation when restricting the size of the region to be inserted or with higher number density. The WI-USHER algorithm slices the region to be inserted into finer grids with proper spacing scale, marks parts of finer grids in black according to three exclusive rules, that is, Single Particle Occupation (SPO), Single Particle Coverage (SPC), and Multi-Particles Coverage (MPC), and finds the target insertion point in the remained white grids. We use two test cases to show the superiority of our WI-USHER algorithm over the USHER algorithm. The WI-USHER algorithm performs lower averaged force evaluation times, which decreases from O ( 10 4 ) to O ( 10 3 ) compared to the USHER algorithm when the number density of slightly high to high value. The percentage of the total parallel simulation time processed by the particle insertion operation decreases from 23.5% to 3% compared to the USHER algorithm.

Underwater sensor networks have wide application prospects, but the large-scale sensing node deployment is severely hindered by problems like energy constraints, long delays, local disconnections, and heavy energy consumption. These problems can be solved effectively by optimizing sensing node deployment with a genetic algorithm. However, the genetic algorithm (GA) needs many iterations in solving the best location of underwater sensor deployment, which results in long running time delays and limited practical application when dealing with large-scale data. The classical parallel framework Hadoop can improve the GA running efficiency to some extent while the state-of-the-art parallel framework Spark can release much more parallel potential of GA by realizing parallel crossover, mutation, and other operations on each computing node. Giving full allowance for the working environment of the underwater sensor network and the characteristics of sensors, this paper proposes a Spark-based parallel GA to calculate the extremum of the Shubert multi-peak function, through which the optimal deployment of the underwater sensor network can be obtained. Experimental results show that while faced with a large-scale underwater sensor network, compared with single node and Hadoop framework, the Spark-based implementation not only significantly reduces the running time but also effectively avoids the problem of premature convergence because of its powerful randomness.

The sound propagation in a wedge-shaped waveguide with perfectly reflecting boundaries is one of the few range-dependent problems with an analytical solution. This provides a benchmark for the theoretical and computational studies on the simulation of ocean acoustic applications. We present a direct finite volume method (FVM) simulation for the ideal wedge problem, and both time and frequency domain results are analyzed. We also study the broadband problem with large-scale parallel simulations. The results presented in this paper validate the accuracy of the numerical techniques and show that the direct FVM simulation could be applied to large-scale complex acoustic applications with a high performance computing platform.

Mitochondrial genomes are highly conserved in genetic processes and serve as a useful molecular marker for phylogenetic and evolutionary analysis. In this study, the complete mitochondrial genome of Uroobovella oviformis was sequenced and annotated. The mitochondrial genome is a closed, double-stranded circular molecule of 14,306 bp length and contains the typical 37 genes. All of the protein-coding genes started with ATN and terminated with TAA except COX2, COX3, and CYTB, which stopped with single T. The whole mitochondrial genome of U. oviformis showed a heavy AT nucleotide bias (77.69%), a positive AT-Skew (0.035), and a negative GC-Skew (−0.320), as well as translocation of seven genes including CYTB and ND6. The phylogenetic tree was constructed by Bayesian inference and maximum likelihood methods using three different datasets (PCG, PCG12, and AA), which were constructed to discuss the phylogenetic status of Mesostigmata. The analysis showed that the branching relationships among the six trees were consistent and all families except the Laelapidae were recovered as monophyletic. Furthermore, U. oviformis forms a separate clade and is located at the base of Mesostigmata and has a closer relationship with Antennophorina. [ABSTRACT FROM AUTHOR]