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Probing and tuning the electron tunneling in metal electrode–insulator–metal nanoparticle systems provide a unique vision for understanding the fundamental mechanism of electrochemistry and broadening the horizon in practical applications of molecular electronics in many electrochemical systems. Here we report a plasmonic imaging technique to monitor the local double-layer charging of individual Au nanoparticles deposited on gold electrode separated by monolayer of n-alkanethiol molecules. The thickness of molecular monolayer tunes the tunneling kinetics and conductivity, which predicts the heterogeneous behavior on the modified electrode surface for different electrochemical systems. We studied the distance dependence of the electron tunneling and double layer charging processes by a plasmonic-based electrical impedance microscopy. By performing fast Fourier transform analysis of the recorded plasmonic image sequences, we can quantify the interfacial impedance of single nanoparticles and the tunneling decay constant of molecular layer. We further observed the electron neutralization dynamics during single-nanoparticle collisions on different surfaces. This optical readout of electron tunneling demonstrates an imaging approach to determine the electrical properties of metal electrode–insulator–metal nanoparticle systems, which include the electron tunneling mechanism and local impedance.

Objective Serum lipids have been shown to regulate inflammatory and immune processes, but little is known about their association with thyroid autoimmunity. This study aimed to investigate the association of serum lipids with thyroid autoantibody positivity in the general population with normal thyroid-stimulating hormone (TSH) levels. Methods Data regarding the 7,688 subjects’ baseline characteristics were retrospectively collected. All subjects were categorized into four groups according to thyroid autoantibodies against thyroglobulin (TgAb) and thyroid peroxidase (TPOAb) positivity and serum lipid levels were compared. Binary logistic regression models were used to evaluate the risk of TgAb or TPOAb positivity with increasing serum lipid levels. Results In 6,456 included subjects, after adjusting for confounders, the risk of TgAb positivity was positively associated with increasing low-density lipoprotein cholesterol (LDL-C) levels (OR 1.10, 95%CI 1.02–1.19, P = 0.014) and negatively correlated with the increasing high-density lipoprotein cholesterol (HDL-C) levels (OR 0.80, 95%CI 0.67–0.96, P = 0.014). In female subjects, the association between increasing LDL-C (OR 1.15, 95%CI 1.05–1.26, P = 0.004) or HDL-C levels (OR 0.74, 95%CI 0.60–0.91, P = 0.005) and TgAb positivity become more pronounced. Moreover, there was a positive correlation between LDL-C levels and TPOAb positivity (OR 1.14, 95%CI 1.02–1.26, P = 0.016). Conclusion We have shown the associations of HDL-C and LDL-C with thyroid autoantibody positivity in the general population with normal TSH levels in a gender-dependent manner. This study highlights that serum lipids may be new predictors of thyroid autoimmunity even when TSH is within the reference range.

In neonatal hypoxic-ischemic brain damage (HIBD), in addition to damage caused by hypoxia and ischemia, over-activation of inflammation leads to further deterioration of the condition, thus greatly shortening the optimal treatment time window. Ischemic penumbra, the edematous area encompassing the infarct core, is characterized by typical activation of microglia and overt inflammation, and prone to incorporate into the infarct core gradually after ischemia onset. If treated in time, the cells located in the penumbra can survive, thereby impeding the expansion of the infarction. We demonstrated for the first time that in the acute phase of HIBD in neonatal mice, treatment of Oxiracetam (ORC) significantly curtailed the size of ischemic penumbra together with drastic reduction of infarction. By staining various cellular markers, we found that the penumbra was defined and concentrated with activated microglia. We also analyzed transmission electron microscopy and Luminex assay results to elucidate the mechanisms involved. We further confirmed that ORC switched polarization of microglia from the inflammatory towards the alternatively activated phenotype, thus promoting microglia from being neurotoxic into neuroprotective. Meanwhile, ORC decreased proliferation of microglia; however, their functions of phagocytosis and autophagy were otherwise enhanced. Last, we clarified that ORC promoted autophagy through the AMPK/mTOR pathway, which further induced the transition of the inflammatory to the alternatively activated phenotype in microglia. The pro-inflammatory factors secretion was inhibited as well, thereby reducing the progression of the infarction. Taken together, it is concluded that Oxiracetam reduced the expansion of ischemic infarction in part via regulating the interplay between microglia activation and autophagy, which would delay the progression of HIBD and effectively prolong the time window for the clinical treatment of HIBD.

The aim of this pilot study was to evaluate the effect of the timing of postoperative orthodontic force application on bone remodeling during tooth movement into surgical alveolar defects with bone grafts in beagle dogs.Six beagle dogs underwent surgery for buccal dehiscence-type defects (width, 5 mm; height, 6 mm) on the distal root of maxillary second premolars bilaterally for 12 defects. After 1-month healing, bone-augmentation procedures were undertaken at the dehiscence defects. The second premolars were protracted buccally for 6 weeks into the surgical sites immediately (F-0), at 4 weeks (F-4), or 8 weeks (F-8) after grafting. Orthodontic tooth movement was monitored using digital models. Remodeling of alveolar bone was evaluated by histology, histomorphometry, immunohistochemistry, microcomputed tomography, and fluorescence microscopy.Group F-0 showed significant expansion (mean, 2.42 mm) and tipping (mean, 9.03°) after completing orthodontic tooth treatment. The vertical bone defect was significantly lower in groups F-4 and F-8 than that in group F-0 (mean, 2.1, 2.7, and 4.5 mm, respectively). In group F-4, the formation of new bone and mineralization were significantly greater than those in groups F-0 and F-8 (P 0.05). Group F-4 showed a minimal amount of bone-material remnants. Immunohistochemistry showed the highest expression of collagen-1 and osteopontin in group F-4, followed by group F-8 and group F-0, which demonstrated high osteoblast activity and enhanced bone remodeling in group F-4.Orthodontic force application at 4 weeks after an augmentation procedure provided the best functional stimulation for an alveolar bone graft. This strategy enhanced new-bone regeneration and degradation of bone substitutes and, eventually, promoted bone remodeling in the bone-grafted area.

A plasmonic in-plane zone-plate (IPZP) is analytically proposed and numerically analyzed. The proposed scheme consists of several discretely metallic nano-slits, which couple incident vortices into SPP and form focal spots. Wave front information of incident beam is reflected in the field distribution along “focal plane” of IPZP, and therefore, the proposed structure can be used for topological charge detection. Besides, an orthogonal slit array IPZP achieving simultaneous spin and orbital angular momentum detection is elaborated. IPZP structure has relatively high fabrication tolerance and the parameters can be adjusted to fit various operating wavelength. The proposed structure is expected to find potential applications in orbital angular momentum communication and high-dimensional quantum entanglement.

Convolutional neural network (CNN) based object detection algorithms are becoming dominant in many application fields due to their superior accuracy advantage over traditional schemes. Among them, You Look Only Once (YOLO) is one of the most popular detection frameworks that show best trade-offs between speed and accuracy. However, due to the intrinsic high computational workload of CNN, it is still challenging when targeting high-throughput processing with low cost in energy consumption. In this paper, we propose a hardware/software (HW/SW) co-design methodology targeting CPU+FPGA-based heterogeneous platforms. Firstly, we extend a novel sparse convolution algorithm to the YOLOv2 framework, and then develop a resource-efficient FPGA accelerator architecture based on asynchronously executed parallel convolution cores. Secondly, algorithm-level optimization schemes, including hardware-aware neural network pruning, clustering and quantization are introduced, which successfully save the computational workload of the YOLOv2 algorithm by 7 times. Finally, an end-to-end design space exploration flow for FPGA-based accelerator design is presented and two HW/SW partition strategies are studied and implemented. Experimental results show that our design can achieve a peak throughput of 2.13 TOPS (72.5 fps) on an Intel Arria-10 GX1150 FPGA under the working frequency of 211 MHz, while the detection accuracy is 74.45 on the PASCAL VOC2007 dataset.

Background Previous studies have reported a negative relationship between thyroid-stimulating hormone (TSH) and renal function in euthyroid individuals, but others have found that higher free thyroxine (FT4) was associated with an increased risk of chronic kidney disease. This study was designed to analyze the relationship between thyroid and renal function from a new perspective of sensitivity to thyroid hormone. Methods This retrospective study included 2831 euthyroid individuals who underwent a health examination at the First Hospital of China Medical University between January 2017 and December 2018. Parametric Thyroid Feedback Quantile-based Index (PTFQIFT4), TSH index (TSHI), thyrotroph T4 resistance index (TT4RI), free triiodothyronine to FT4 ratio (FT3/FT4), the secretory capacity of the thyroid gland (SPINA-GT) and the sum activity of peripheral deiodinases (SPINA-GD) were calculated. We also innovated the TT3RI and PTFQIFT3 indices based on FT3 and TSH. Renal function was assessed by estimated glomerular filtration rate (eGFR) CKD-EPI and creatinine-cystatin C-KDIGO equations. Results After adjustment of basic characteristics and comorbidities, linear regression showed that eGFR CKD-EPI was positively associated with FT3/FT4 (β = 23.31), and inversely correlated to PTFQI FT4 (β= −2.69) (both p

BackgroundPrevious studies on the association between thyroid function and non‐alcoholic fatty liver disease (NAFLD) have contradicted. Acquired resistance to thyroid hormone theory might provide a reasonable explanation for these contradictions. We aimed to analyze the association between sensitivity to thyroid hormone indices with NAFLD.MethodsA total of 4,610 individuals from the health medical center of the First Hospital of China Medical University were included in this study. The previously used thyroid feedback quantile-based index (TFQIFT4) was calculated. Also, we substituted free triiodothyronine (FT3) into the TFQI formulas to get the TFQIFT3 index. NAFLD was defined using abdominal ultrasound.ResultsStudy results showed that FT3/FT4 and TFQIFT3 were positively correlated with the triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels (PPFT4 was positively correlated with HDL-C level (P < 0.05). After adjustment for multiple confounders, FT3, FT3/FT4, and TFQIFT3 were positively associated with the risks of dyslipidemia and NAFLD (P < 0.05). TFQIFT3 and FT3/FT4 performed better than TFQIFT4 on ROC analyses for NAFLD prediction, although the diagnostic sensitivity and specificity at the optimal cut-points were low. However, no association was observed between TFQIFT4 with the risks of dyslipidemia and NAFLD.ConclusionTFQIFT3 and FT3/FT4 can be used as new indicators for predicting dyslipidemia and NAFLD, although with low sensitivity and specificity at the optimal cut-points, while TFQIFT4 has insufficient evidence in predicting dyslipidemia and NAFLD.

Background The clinical value of indocyanine green (ICG) in laparoscopic radical gastrectomy remains controversial. We performed this meta-analysis to investigate the safety and efficacy of ICG fluorescence imaging-guided radical gastrectomy. Methods All relevant studies published until 30 October 2020 were retrieved from several databases. Fixed- and random-effects models were used to analyze the results based on different heterogeneity levels. Data were expressed as odds ratios or weighted mean differences along with 95% confidence intervals. The Grading of Recommendations, Assessment, Development, and Evaluation system scale was used for quality of evidence evaluation. Results This meta-analysis included six cohort studies that investigated 622 patients. Compared with conventional radical gastrectomy, ICG fluorescence imaging-guided gastrectomy facilitates complete lymph node dissection, reduces intraoperative blood loss, and shortens the length of postoperative hospitalization. Moreover, we observed no significant intergroup differences in the operative time, first exhaust time, and postoperative complications. Conclusion ICG fluorescence imaging-guided radical gastrectomy scores over conventional gastrectomy and appears to be a promising approach in patients who require radical gastrectomy. However, further research is warranted to explore the potential long-term survival benefit of ICG fluorescence imaging in patients with gastric cancer.

Neighbor discovery is important for docking applications, where mobile nodes communicate with static nodes situated at various rendezvous points. Among the existing neighbor discovery protocols, the probabilistic methods perform well in average cases but they have aperiodic, unpredictable, and unbounded discovery latency. Yet, deterministic protocols can provide bounded worst-case discovery latency by sacrificing the average-case performance. In this study, we propose a mobility-assisted slot index synchronization (MASS), which is a new synchronization technique that can improve the average-case performance of deterministic neighbor discovery protocols via slot index synchronization without incurring additional energy consumption. Furthermore, we propose an optimized beacon strategy in MASS to mitigate beaconing collisions, which can lead to discovery failures in situations where multiple neighbors are in the vicinity. We evaluate MASS with theoretical analysis and simulations using real traces from a tourist tracking system deployed at the Mogao Grottoes, which is a famous cultural heritage site in China. We show that MASS can reduce the average discovery latency of state-of-the-art deterministic neighbor discovery protocols by up to two orders of magnitude.

Plasmonically induced transparency (PIT) in hexagon boron nitride (h-BN)-graphene-silica grating-based structure is proposed and demonstrated. By tuning the chemical potential of graphene and changing the geometry parameters of the proposed structure, PIT can be realized both within the upper reststrahlen (RS) band and outside the RS band. The group delay of the PIT window is analyzed and can be up to ~0.15 ps within the upper RS band via changing the chemical potential of graphene and the parameters of the silica grating. Apart from that, a refractive index (RI) sensor with a sensitivity of up to 0.336 μm per RI unit outside the RS band is proposed by changing the RI of the sensor media. The proposed structure may have the application in the graphene-h-BN-based slow light devices and optical sensors.

Vectorial vortex beams have attracted much attention due to the exotic polarization and phase characteristics. Miniaturized optical elements for vectorial vortices generation and detection are highly desired. In this paper, a vectorial vortex beam detection scheme based on plasmonic interferences on a structured gold film is proposed. The well designed plasmonic structure couples a small portion of energy of the incident beam into surface plasmon polaritons and forms interference patterns. By analyzing interference fringes, spin and orbital angular momentum of incident beams can be detected. The proposed structure has the advantage of realizing nondestructive detection, while the parameters can be adjusted to meet various operation requirements. The proposed scheme provides a new method for on-chip vectorial vortex beam detection.

ContextThyroid hormone influences glucose homeostasis through central and peripheral regulations. To date, the link between sensitivity to thyroid hormones and prediabetes remains unknown. We aimed to investigate the association between thyroid hormones sensitivity and risk of prediabetes in both general and euthyroid populations.MethodsParticipants with serum free triiodothyronine (FT3), free thyroxine (FT4), and thyrotropin (TSH) measurements from the health checkup programs of the First Hospital of China Medical University were collected. We measured the parameters representing central and peripheral sensitivities to thyroid hormones (central sensitivity, assessed by calculating Thyroid Feedback Quantile-based Index (TFQI), TSH Index (TSHI), and Thyrotroph Thyroxine Resistance Index (TT4RI); peripheral sensitivity, evaluated by FT3/FT4 ratio). Associations between thyroid hormones sensitivities and risk of prediabetes were assessed with logistic regression.ResultsA total of 4378 participants (mean age ± SD, 49 ± 11 years) were included, with 1457 (33%) subjects had prediabetes. The risk of prediabetes was negatively associated with levels of TSHI (odds ratio [OR] 0.91; 95% confidence interval [CI], 0.85–0.97), TT4RI (OR 0.91; 95% CI, 0.84–0.99) and Parametric TFQI (PTFQI) (OR 0.89; 95% CI, 0.83–0.95) among all subjects. The association remained significant in euthyroid subjects and euthyroid subjects with negative thyroid autoimmunity. Higher FT3/FT4 ratio was associated with a mild increased risk of prediabetes (95% CI 1.09; 1.02–1.16). Compared with subjects in the lowest quartile of PTFQI, those in the highest quartile had lower risk of prediabetes (0.70; 95% CI, 0.58–0.84).ConclusionsDecreased central sensitivity to thyroid hormones is associated with lower risk of prediabetes. This demonstrates the complex interaction between thyroid system and glucose metabolism. Future studies are warranted to confirm our findings and underlying mechanisms.

Semi-supervised learning exploits unlabeled data to improve generalization ability with insufficient annotations. In recent years, Mean Teacher method (MT) obtained impressive performance using prediction consistency as regularization. However, severe ambiguity in medical images makes the targets in the teacher model highly unreliable in obscure regions, thereby limits the model capability. To address this problem, we propose a novel multi-task learning semi-supervised framework to gain hierarchical consistency through training process. Specifically, we introduce region and shape predictions as subtasks to obtain the coarse-grained location and fine-grained boundary information. Then we predict pixel-level segmentation by fusing the hierarchical feature. Since calculating consistency loss in more loose regions typically alleviates the degradation caused by learning from unreliable targets, our teacher model generate guidance from each of the subtasks. Moreover, we focus on the geometrical correlations in different tasks and proposed the constraint method to refine the segmentation for accurate guidance. Experiments on the left atrium segmentation dataset show our algorithm achieves state-of-the-art performance comparing with other semi-supervised methods.

An innovative structural modification, top-storey softening, is herein proposed in conjunction with optimally tuned top-floor tuned mass damper inerter (TMDI) for improved serviceability performance in typical core-frame slender buildings with rectangular floor plan susceptible to wind-induced vortex shedding (VS) effects causing occupant discomfort. This is supported through formulating a novel optimal TMDI tuning problem in which TMDI inertial properties, i.e., attached mass and inertance, as well as the lateral top-storey stiffness are design parameters aiming to minimize peak acceleration of the highest occupied floor. The optimal TMDI tuning problem is numerically solved for a wide range of design parameters for a 34-storey composite core-frame building subject to stochastic spatiallycorrelated wind-force field accounting for VS effects. A low-order dynamical model capturing faithfully modal properties of the case-study building is developed to facilitate computational work and parametric investigation. It is found that top-storey softening reduces attached TMDI mass/weight requirements and inerter force for fixed performance and inertance. It further reduces TMDI stroke and achieves increased robustness to TMDI stiffness and damping properties as well as to the assumed inherent structural damping. It is concluded that by leveraging inertance and top-storey stiffness, the proposed solution can efficiently control VS-induced floor acceleration with small additional gravitational (added weight) and horizontal (inerter and damping) forces.

Background: To quantitatively and qualitatively evaluate alveolar defects of mandibular anterior alveolar bone in three different types of malocclusion with cone-beam computed tomography (CBCT).Methods: A total of 542 teeth from 30 skeletal class I malocclusion (mean age: 19.26±5.63), 33 class II malocclusion (mean age: 19.36±4.17), and 28 class III malocclusion (mean age: 21.47±4.53) patients were evaluated with CBCT. Sagittal sectional views were evaluated with regard to labial and lingual alveolar bone thickness and vertical alveolar bone level. Analysis of variance and Tukey’s test were used for statistical comparisons at PResults: Qualitative analysis: Class II (64.47%) and Class III malocclusions (58.43%) had higher prevalence of dehiscence than Class I malocclusions (32.96%),PConclusions: The Class II group, followed by the class III group, showed the most severe alveolar bone deficiency For these patients undergoing orthodontic treatment, special care should be taken to avoid aggravated preexisting alveolar bone loss in the mandibular anterior teeth.

The tuned mass-damper-inerter (TMDI) couples the classical tuned mass-damper (TMD), with an inerter device developing a resisting force proportional to the relative acceleration of its ends by the “inertance” constant. Previous works demonstrated that the inclusion of the TMDI leads to more efficient broadband vibration control for a range of different structures under different actions. This paper proposes a novel optimal TMDI design formulation to address occupants’ comfort in wind-excited slender tall buildings susceptible to vortex shedding (VS) effects and to explore optimal TMDI’s potential for transforming part of the windinduced kinetic energy to usable electricity in tall buildings. Attention is focused on investigating benefits of TMDIs with different inertial properties (i.e., secondary mass/weight and inertance) configured in different topologies defined by the number of floors spanned by the inerter device to connect the secondary mass to the building structure. Optimally designed TMDIs for a wide range of inertial properties and three different topologies are obtained through numerical solution of the underlying optimization problem for a benchmark 305.9m tall building with more than 6 height-to-width ratio subjected to experimentally calibrated spatiallycorrelated across-wind force field accounting for VS effects. Performance-based design (PBD) graphs on the TMDI inertial (mass-inertance) plane are furnished demonstrating that any fixed structural performance level in terms of occupants’ comfort (i.e., peak top floor acceleration) can be achieved through lightweight TMDIs if compared with classical TMDs as long as sufficient inertance is provided. Further, TMDI robustness to host structure properties and to reference wind velocity is shown to increase by increasing inertance or by spanning more floors in connecting the secondary mass with the host structure by the inerter. Lastly, it is found that increased available energy for harvesting in wind excited tall buildings is achieved by incorporating electromagnetic motors in TMDIs with varying damping property, while concurrent reduced floor acceleration and increased available energy for harvesting is accomplished by TMDI topologies with inerters spanning more floors.

The tuned mass‐damper‐inerter (TMDI) is a linear passive dynamic vibration absorber for motion control of dynamically excited building (primary) structures. It couples the classical tuned mass damper (TMD), comprising a secondary mass attached to the top building floor via a spring and dashpot, with an inerter, a mechanical element resisting relative acceleration, which links the secondary mass to a lower floor. Recent studies demonstrate that TMDI motion control effectiveness is influenced by the vibration modes of the uncontrolled primary structure. Herein, this influence is quantified through a parametric investigation considering a wide range of white-noise excited primary structures modelled as cantilevered continuous beams with various shapes and, therefore, different vibration modes. This quantification is facilitated by considering a low-order model of TMDI-equipped flexural cantilever which accounts for the effect of flexural rigidity and mass distribution of the primary structure as well as the influence of the fundamental mode shape to the location that the inerter connects the secondary mass to the primary structure. The investigation is further supported by optimal H2 tuning of TMDI aiming to minimize the free-end primary structure displacement under white noise excitation. It is shown that the TMDI achieves enhanced structural performance as the inerter links the secondary mass further away from the top of the primary structure where the mass is attached to for all primary structure shapes. Moreover, it is found that improved TMDI performance and reduced stroke (relative secondary mass displacement with respect to the primary structure) are achieved for primary structure shapes with stiffness and mass distribution weighted heavier towards the base of the structure (i.e., when most of material is concentrated towards the bottom end of the structure) either through appropriate shaping or through increase of base to free-end depth ratio for fixed non-uniform shapes.

Recently, modular building construction has gained massive momentum as it continues to help many cities around the globe to tackle the ongoing housing crisis and the pressing demand for healthcare facilities during the pandemic. As a relatively new structural solution, there is a need to study modular buildings' optimal design. In this regard, previous studies focused only on employing optimisation techniques at the member level to enhance the structural capacity of steel beams in modular building systems (MBS). This paper explores the applicability and effectiveness of an optimality criteria (OC)-based minimum-weight design method in reducing self-weight of MBS while maintaining their overall lateral stiffness measured by natural frequency. This is achieved by pursuing an innovative optimisation investigation involving a three-storey, standalone MBS with hinged inter-module joints, together with a comparative moment-resisting frame (MRF) benchmark structure with two different beam-column connection rigidities. Continuous-valued sizing optimisation of two structural systems under a single frequency constraint is achieved through a novel, numerically stable, iterative OC algorithm. The latter is developed from frequency-related OC formulated rigorously through the Lagrange multiplier approach. The discrete minimum-weight design is supported by a mapping strategy designed to round the continuous optimum to the most economical standard steel sections. Pertinent numerical results show that the proposed method can achieve significant steel savings for the adopted MBS without compromising its modal stiffnesses. Further, it is found that the MRF structure with semi-rigid connections can meet the same target frequencies with slightly smaller steel tonnages. It is envisioned that this study will pave the way towards achieving more resilient and cost-effective modular units and tall modular buildings that further support the building industry in meeting its goals of construction efficiency and sustainability.

A novel, simultaneous strain and temperature sensor utilizing polarization maintaining fiber (PMF) and multimode fiber (MMF) is proposed and experimentally demonstrated in this paper. The sensing head of this sensor can be obtained by splicing PMF and MMF in the structure of PMF-MMF-PMF. The extinction ratio of the transmission spectrum can be over 30 dB. The strain sensitivities of sensor by two spectrum dips can be 1.01 pm/μe and 1.27 pm/μe in the range from 0 to 2000 μe. Meanwhile, the temperature sensitivities of 49 pm/°C and 41 pm/°C can be achieved by two spectrum dips in the range from 30 °C to 70 °C. The sensitivity difference between the two spectrum dips can be used to realize dual parameters fiber sensing. This sensor exhibits the advantages of simple fabrication, compact structure and multi-purpose measuring. It may have the great potential in fields of robot arms and artificial limbs.

Buildings account for a significant portion of the world’s electricity consumption, including industrial, commercial, residential, hospital buildings, etc. During building operation, significant energy consumption and economic loss may be caused due to various forms of electricity theft. To this end, an ensemble model for electricity theft detection method based on genetic optimization is developed. At first, synthetic samples that have an approximate distribution to that of true samples of electricity theft are prepared through use of a synthetic minority oversampling technique (SMOTE). Afterwards, features of anomalous electricity consumption are extracted with the aid of dimension reduction through principal component analysis (PCA). Finally, an ensemble deep learning network based on AdaBoost is established to mine implicit information in continuous time series data and detect anomalous electricity consumption of labelled users. Moreover, the hyperparameters of the deep neural network are optimized based on a genetic algorithm (GA). By taking data pertaining to the electricity consumption of users collected from smart meters of the State Grid Corporation of China as examples, the results show that our model is superior to other detection methods (such as support vector machine (SVM), random forest (RF), and traditional artificial neural network (ANN)) in the sensitivity and the area under the curve (AUC).

To meet the mission requirements of long-endurance and unmanned marine environment observation, the natural energy-driven unmanned surface vehicle (NSV) usually takes special sailing paths to increase energy capture to achieve the purpose of improving endurance. Aiming at the route planning problems of the “Wave Rider” NSV in the time-varying ocean wind field, this paper is organized as follows. Firstly, a visual modeling method of the real-time-varying ocean wind field for NSV is proposed. Then, through the wind energy capture experiment, the NSV system energy net output model is calculated, and a Dynamic Dijkstra algorithm considering wind energy capture (DW–Dijkstra) has been proposed in this paper based on a Dijkstra algorithm, of which weight function has been improved. Accordingly, the NSV long-endurance dynamic path planning method is designed. Finally, the DW–Dijkstra algorithm has been verified through a set of comparison simulations and a set of semi-physical comparison simulations. The results show that the DW–Dijkstra algorithm can plan a collision-free and high-efficiency energy capture path in the real-time-varying ocean wind field environment in the southern waters of China. Compared with the traditional A* algorithm and the Wind_A* algorithm, the proposed method can save energy by between 15.07% and 6.50%, respectively, which effectively increases the endurance of the NSV.

The purpose of this study was to investigate the effect of iodine supplementation during pregnancy on thyroid function and also its effect on postpartum depression in an iodine-sufficient area. Healthy pregnant women were divided into three groups: group A (vitamin iodine–150) receiving vitamin containing 150 μg iodine, group B (vitamin iodine–0) receiving vitamin without iodine, and group C (no vitamin) receiving no vitamin. General information was collected by questionnaire and thyroid function was determined in the third trimester of pregnancy. Depression was assessed 1 month postpartum by the Edinburgh postnatal depression scale (EPDS). The results showed that there was no significant difference in thyroid-stimulating hormone (TSH) level among the three groups (P > 0.05). FT4 concentration was significantly lower in group A (n = 234: 10.68 pmol/L) than in group B (n = 220: 11.47 pmol/L) and group C (n = 195: 11.64 pmol/L) (P

This paper investigates the potential of tuned mass dampers (TMDs) coupled with inerter devices in different tuned mass dampers inerter (TMDI) topologies to dissipate oscillations in tall buildings due to vortex shedding in the across wind direction while generating electric energy. The TMDI is first optimized for minimizing peak accelerations for serviceability purposes in a 74 storey benchmark steel building under different wind intensity levels. It is seen that TMDI stiffness and damping optimal parameters are robust to design/reference wind velocity and, therefore, to potential climate change effects, while achieving same level of performance using significantly smaller attached mass compared to the classical TMD. Then, a regenerative electromagnetic motor (EM) is added to the TMDI allowing for varying the TMDI damping property as well as transforming part of the dissipated kinetic energy to electricity. It is shown that by increasing TMDI damping above the optimal value for vibration suppression and/or by reducing the inerter property increases the available energy for harvesting at the expense of larger floor accelerations. Therefore, it is concluded that by relaxing serviceability limit state requirements associated with occupancy considerations renders possible an increase in energy generation in wind-excited tall buildings.

A novel reflective liquid level sensor based on single-mode-offset coreless-single-mode (SOCS) fiber structure is proposed and experimentally demonstrated. Theory analyses and experimental results indicate that offset fusion can remarkably enhance the sensitivity of sensor. Ending-reflecting structure makes the sensor compact and easy to deploy. Meanwhile, we propose a laser sensing system, and the SOCS structure is used as sensing head and laser filter simultaneously. Experimental results show that laser spectra with high optical signal-to-noise ratio (−30 dB) and narrow 3-dB bandwidth (

In this letter, a novel all-fiber ring laser refractive index (RI) sensor is proposed and experimentally demonstrated. Such sensor is obtained by inserting a segment of cladding-less fiber between two sections of single-mode fiber with one core-offset joint, which is designed to enlarge the extinction ratio. With the help of ring laser sensing system, a 3-dB bandwidth below 0.2 nm and an optical signal-to-noise ratio near 30 dB can be achieved. Meanwhile, the high output power and the side-mode suppression ratio of the sensor are presented. Experimental results show that the RI sensitivity is 52.3 nm/RIU in the RI range of 1.334–1.370. The sensor also has the advantages of simple structure and low cost, preforming potentials in large-scale productions.

Staphylococcal scalded skin syndrome causes widespread skin denudation primarily in infants < 1 year old. Selection of empiric therapy is complicated by rising rates of antibiotic resistance in community-acquired staphylococcal infections. Consistent with a previous study, this retrospective review found that SSSS-associated isolates were more likely to be clindamycin-resistant and less likely to be methicillin-resistant compared to overall staphylococcal infections. We favor cephalosporins and penicillinase-resistant penicillins (eg, oxacillin) for empiric management of SSSS, with consideration of adding MRSA coverage in communities with high MRSA prevalence or failure to improve following several days of treatment.

TCP does not work well in modern cellular networks because the current congestion-window-based (cwnd-based) congestion control mechanism intimately couples congestion control and packet dispatch, which provides TCP with only indirect control of the effective data rate. The throughput degradation arising from the cwnd-based mechanism is especially serious when the uplink is congested. We describe PropRate, a new rate-based TCP algorithm that directly regulates the packets in the bottleneckbuffer to achieve a trade-off in terms of delay and throughput along a more efficient frontier than conventional cwnd-based TCP variants. To the best of our knowledge, PropRate is the first TCP algorithm that allows an application to set and achieve a target average latency, if the network conditions allow for it. Also, unlike the cwnd-based TCP mechanism, our new rate-based TCP mechanism is significantly more resilient to saturated uplinks in cellular networks. PropRate does not require modifications at the receiver and is amenable to practical deployment in the base stations and proxies in mobile cellular networks.

Due to the characteristic of surface plasmon polaritons (SPP) excitation, radial polarized beams and circular polarized beams are widely used for plasmonic lens and plasmonic near field focusing. In this paper, a plasmonic lens based on in-plane total internal reflection (TIR) scheme is proposed and numerically demonstrated to achieve the simultaneous nanofocusing of azimuthal and radial polarized beams. By means of the in-plane TIR mechanism, the operation bandwidth of lens ranges from visible light to mid-infrared. The proposed structure has been utilized in the design of a plasmonic liquid refractive index sensor and is expected to find potential applications in near-field optical energy focusing, near-field imaging and sensing.

Both plasmon-phonon-polariton (SPP-PHP) modes and phonon-polariton (PHP) modes supported in graphene-coated hexagon boron nitride (h-BN) single nanowire are presented. The field distributions of the lowest 5 order modes of SPP-PHP modes supported in graphene-coated hexagon boron nitride nanowire pairs (SPP-PHP-GHNP) and the lowest 5 order modes of PHP modes supported in graphene-coated hexagon boron nitride nanowire pairs (GHNP) are also demonstrated and analyzed, respectively. The results of numerical calculation show that SPP-PHP-GHNP mode 0 owns the strongest confinement and lowest loss among the lowest 5 order modes of SPP-PHP-GHNP. Furthermore, the field enhancement of SPP-PHP-GHNP mode 0 can reach over 105 by controlling the geometry parameters of GHNP. Meanwhile, the influence of tuning the Fermi level of graphene on the field enhancement is also presented in the paper. The proposed structure may improve the development of graphene-h-BN-based optoelectronic devices.

Neighbor discovery is essential for docking applications, where mobile nodes communicate with static nodes situated at various rendezvous points. In existing neighbor discovery protocols, the probabilistic protocols perform well in the average-case but have a periodic, unpredictable and unbounded discovery latency. While the deterministic protocols can provide a bounded worst-case discovery latency, they achieve this by sacrificing the average-case performance. In this paper, we propose a new synchronization technique, called Mobility-Assisted Slot index Synchronization (MASS). MASS improves the average-case performance of deterministic neighbor discovery protocols via slot index synchronization, without incurring additional energy consumption. We evaluate MASS through both theoretical analysis and simulations of the real traces from a tourist tracking system deployed at Mogao Grottoes, a famous cultural heritage site in China. We show that MASS can reduce the average discovery latency of state-of-the-art deterministic neighbor discovery protocols by up to 2 orders of magnitude.

With the significant increase in cellular data usage, it is critical to better understand the characteristics and behavior of cellular data networks. With both laboratory experiments and crowd-sourcing measurements, we investigated the characteristics of the cellular data networks for the three mobile ISPs in Singapore. We found that i) the transmitted packets tend to arrive in bursts; ii) there can be large variations in the instantaneous throughput over a short period of time; iii) large separate downlink buffers are typically deployed, which can cause high latency when the throughput is low; and iv) the networks typically implement some form of fair queuing policy.

It is not uncommon for the uplink buffers of cellular data networks to be saturated when the uplink bandwidths are low. This can cause the ACK packets for a downlink TCP flow to be severely delayed. Since existing TCP implementations are ACK-clocked, the downstream flow will suffer significant degradation, causing the downlink to be under-utilized. We present a new TCP variant, called TCP Receiver-Rate Estimation (TCP-RRE), that addresses this problem directly by eliminating ACK clocking. Instead, it uses TCP timestamps to estimate the receiving rate at the receiver, which it then uses to determine the sending rate. We show that TCP-RRE is able to improve download speeds by 2 to 4 times compared to existing TCP variants in both simulation and on real commercial cellular data networks. Our solution is practical because it is compatible with existing TCP implementations, requires no modifications to existing mobile devices, and is thus immediately deployable in existing ISP proxies.