A compact rectangular waveguide (RWG) H-plane T junction (HT) over the WR28 is realized in this paper. Capacitive flute and inductive stage are adopted to settle the discontinuities of the T junction, by which, the operating bandwidth is expanded to the whole WR-28 band. The capacitive flute and inductive stage are easy processed with high error tolerance. For demonstration, the RWG H-plane T junction operating at Ka band is designed, fabricated, and measured. The measured return loss is greater than 20 dB from 24 GHz to 40 GHz. The measured insertion loss is less than 3.22 dB, which corresponds to a power-combining efficiency of 95.0%. The measured results are in good agreement with the simulated ones.

Aiming at the problems of small speed and large memory resource consumption for aerial images got by Unmanned Aerial Vehicle (UAV), which caused by the high pixel, high precision and large size, a real-time image stitching method integrating feature information transfer and image slicing is proposed. It improves the speed of image stitching and reduces the memory consumption in the stitching process. The position data is used to calibrate images firstly. Then image feature extraction is done by the Speeded Up Robust Features (SURF) algorithm. The gradual in and out method is used for image fusion. After each stitching is completed, the feature points of the stitched image are no longer re-extracted, on the contrary, the feature information of the previous image is transferred to realize continuous frame stitching. The stitched image using N images is sliced and stored, and the system memory is freed. The experiments are carried on real aerial images of a certain place. The results have shown that the stitching time of each ten images is 7.935 seconds, and the memory consumption is below 700MB stably. The results verified that the proposed method can get good performance in speed and memory.

In this paper, we investigate the controllability under positivity constraints from the birth of a size-structured population system with delayed birth process. Firstly, we establish the well-posedness and positivity property of the model. Secondly, and more importantly, we derive a sufficient condition for boundary approximate controllability under state and control positivity constraints. The method relies on the feedback theory of infinite-dimensional positive systems.

Conventional transcranial direct-current stimulation (tDCS) delivered to the primary motor cortex (M1) has been shown to enhance implicit motor sequence learning (IMSL). Conventional tDCS targets M1 but also the motor association cortices (MAC), making the precise contribution of M1 to IMSL presently unclear. We aimed to address the roles of these areas by comparing conventional tDCS of M1 and MAC to High-Definition (HD) tDCS, which more focally targets M1. In this sham-controlled, crossover study in 89 healthy adults, we used mixed-effects models to analyze sequence-specific and general learning effects in the acquisition, short- and long-term consolidation phases of IMSL, as measured by the serial reaction time task. Conventional tDCS did not influence general learning, improved sequence-specific learning during acquisition (anodal: M=42.64 ms, sham: M=32.87 ms, p=.041) and deteriorated it at long-term consolidation (anodal: M=75.37 ms, sham: M=86.63 ms, p=.019). HD tDCS did not influence general learning, slowed performance specifically in sequential blocks across all learning phases (all p’s<.050), and consequently deteriorated sequence-specific learning during acquisition (anodal: M=24.13 ms, sham: M=35.67 ms, p=.014) and long-term consolidation (anodal: M=60.03 ms, sham: M=75.01 ms, p=.002). Our findings indicate that generalized stimulation of M1 and MAC enhanced acquisition, but hindered consolidation of IMSL. In contrast, focal M1 stimulation by HD tDCS worsened overall performance, likely due to cathodal inhibition of MAC as induced by the return electrodes. Consequently, this disruption of performance supports the notion that these areas fundamentally contribute to IMSL as an integral part in the cortico-basal ganglia-thalamo-cortical network.

The epigenetic factor bromodomain and extra-terminal domain (BET) proteins have multiple functions in regulating cell proliferation, differentiation and inflammation via binding to acetylated lysines on histones. JQ1 and I-BET726, new inhibitors of BET proteins, have potential therapeutic benefit for autoimmune diseases (AD). In this study, we explored the effects of JQ1 and I-BET726 on innate and adaptive immunity in experimental autoimmune encephalomyelitis (EAE) model to investigate the mechanism and therapeutic benefit for AD. The effects of JQ1 and I-BET726 on LPS-induced inflammation were investigated in innate and adaptive immune cells of dendritic cells (DCs), macrophages, and DC-dependent T cells. Different pro-inflammatory cytokines were assessed via real-time PCR, flow cytometry, and Elispot. Moreover, the effects of JQ1 and I-BET726 on EAE animals were further investigated, including the effects on alleviating clinical symptoms and inhibiting inflammation and demyelination in spinal cords via real-time PCR and immunohistochemical staining. JQ1 and I-BET726 efficiently inhibited LPS-increased TNF-α and IL-6 expression in bone marrow-derived DC and macrophage of Raw264.7 cells. They also suppressed adaptive immunity by down-regulating CD80/CD86 and IL-12/GM-CSF expressions, and inhibiting DC-dependent T cell priming. Moreover, they effectively inhibited TNF-α and IL-6 involved inflammatory changes in the spinal cords of EAE model, including inflammatory cell infiltration and demyelination. Most importantly, JQ1 and I-BET726 efficiently attenuated the clinical deterioration of EAE mice. Our results indicate that JQ1 and I-BET726 possess therapeutic benefits for autoimmune diseases by adjusting innate and adaptive immune response, indicating that BET bromodomain might be potential molecular targets for autoimmune disease therapy.

The aggregation of the remaining battery capacity of EVs can be used as distributed energy storage to participate in electricity market auxiliary services in the form of V2G, however, their reliability is affected by the uncertainty of EV travel. In this paper, we consider the uncertainty of EV load response and propose a resolution method for quantifying the reliability of EV aggregation capacity in the day-ahead market. The paper first classifies EV users by analyzing historical charging data. Secondly, based on the composite Poisson process, the V2G capacity and reliability model for the aggregator’s participation in the day-ahead auxiliary service bidding are proposed and validated using actual data. Based on this model, aggregators can decide the power of V2G bidding for any time slot on day t+1 according to the reliability requirements of the standby market for the standby capacity contracted before that day. Finally, this paper organically combines PV and EV aggregators in the microgrid and uses genetic algorithms to optimize the simulation of the microgrid voltage operation state under different scenarios in the IEEE 33-node system. The results show the effectiveness of the coordinated optimization scheme of PV and EV clusters for the optimization of microgrid voltage.

Growth of morphological traits in Atlantic puffin (Fratercula arctica) offspring has typically been characterized by linear models, despite clearly displaying nonlinear patterns. We assessed the fit of six typical avian growth models to measurements of puffling mass, wing length, and tenth primary feather length. Across all three biometrics, the first- and second-best performing models were nonlinear, and the worst performing model was the linear model. Specifically, the preferred model for mass, wing, and tenth primary growth was the quadratic model, logistic model, and extreme value function model, respectively. The preferred models were used to generate separate growth curves for individual chicks, from which parameter estimates for growth rate, normalized growth rate, inflection value, and asymptotic value can be extracted. These parameter estimates are easily interpretable and comparable between several of the nonlinear models. We recommend the reported models in future studies incorporating metrics of puffling growth, and encourage the use of this methodology to explore nonlinear growth patterns across avian species.

Low noise is a key requirement of Readout Integrated Circuits (ROIC) in hyperspectral applications for its low radiation. Correlated Double Sampling (CDS) is commonly used to suppress noise. In this paper, CDS is improved by adjusting the time interval between the clamp and sample-and-hold (SH), which can filter low-frequency noise flexibly. An ROIC input stage integrated with low-noise capacitive trans-impedance amplifiers (CTIA) and CDS with adjustable interval (AICDS) is designed in 180 n m CMOS process. A timing generator is proposed to vary the interval regulation amount from 0 μs to 15 μs . The SPECTRE simulation indicates that, by decreasing this time interval, the noise electrons are significantly decreased from 48.72 e - to 22.15 e - , and SNR is enhanced by 5 dB (20 pA injection current). The design of AICDS can improve the noise performance of hyperspectral ROIC, thus can be widely used.

We examined whether the alpha band-coherence between the T7-Fz (verbal analytical-motor planning) brain areas were related to superior performance in sports. We searched for related papers across eight databases: ProQuest Central, ProQuest Psychology Journals, PsycARTICLES, PsycINFO, SPORTDiscus, MEDLINE, Scopus, and Web of Science using relevant keywords (i.e., EEG AND sports AND coherence). Seven studies, with a total of 194 participants, met our inclusion criteria and were shortlisted for statistical analysis. We compared EEG coherence data for both within-subject and between-subject experimental designs. Results indicated that athletes had lower coherence in T7-Fz brain pathway for alpha band activation (Hedges’ g = -.54; p = .03) when performing better. Theoretically, these results corroborate the notion that athletes become more “neurally efficient” as the verbal and motor areas of their brains function more independently, i.e., the neural efficiency hypothesis. Accordingly, athletes who can limit verbal interference are more likely to perform a sporting task successfully.

Tamoxifen is the most used hormonal therapy for estrogen receptor positive breast cancer. CYP2D6 is the main enzyme in the metabolic pathway of tamoxifen to endoxifen. Variations in endoxifen plasma concentrations are associated with CYP2D6 polymorphisms. This study aimed to determine the association between the CYP2D6 polymorphisms and endoxifen plasma concentrations in a cohort of Zimbabwean breast cancer patients (n = 40). TaqMan genotyping and copy number assays were done to determine CYP2D6 genotypes. Tamoxifen and metabolites were quantitated using LC-MS/MS. The population had high frequencies of the CYP2D6 reduced function alleles, *17 (15%) and *29 (18%). The median endoxifen concentration was 4.78 ng/ml and 55% of the patients, mostly intermediate metabolizers were below the endoxifen therapeutic threshold 5.97 ng/ml. The CYP2D6 phenotypes and activity scores were significantly associated with endoxifen plasma concentrations (p = 0.0151) and with endoxifen to N-desmethyl tamoxifen ratios (p = 0.0006).

Background and Objective Acarbose is a widely used α-glucosidase inhibitor to control postprandial hyperglycemia in type 2 diabetes mellitus patients. Recently, quite a few pilot studies on acarbose bioequivalence (BE) in Asian populations have defined new pharmacodynamic (PD) parameters as reliable endpoints. However, pivotal studies utilizing these new PD parameters were rarely reported. The study aims to explore acarbose BE using the new PD parameters and compare their applicability and sensitivity. Methods The study was conducted with an open, randomized, two-period crossover design using the test (T) or reference (R) drug at the dose of 2*50 mg. 64 subjects were recruited, with a one-week washout period. Serum glucose and insulin concentrations were determined after sucrose administration (baseline) and sucrose/acarbose co-administration. Results Using the parameters of rectifying method, which conducts pre-dose value deduction, the geometric mean ratios of Cmax,r and AUC0-2h,r were 102.91% and 105.29%, respectively. The 90% CIs of Cmax,r and AUC0-2h,r were all within acceptance limits (80.00-125.00%). The new parameters exhibited superior applicability and sensitivity in the evaluation of acarbose BE in healthy subjects. The incidence of AEs after the T drug or R drug was comparable, and healthy subjects were well tolerated. Conclusions The results from our study manifested that the PD parameters of the rectifying method demonstrate superior applicability and sensitivity in the evaluation of acarbose BE in healthy subjects. The T and R drug were bioequivalent using the novel PD parameters as primary endpoints, and both drugs demonstrated good safety and tolerability.

This paper proposes a novel algorithm that accurately predicts market trends and trading entry points for US 30-year-treasury bonds using a hybrid approach of 1-Dimensional Convolutional Neural Network (1DCNN), Long-Short Term Memory (LSTM), and XGBoost algorithms. We compared the performance of various strategies using 1DCNN and LSTM and found that existing state-of-the-art methods based on LSTM have excellent results in market movement prediction tasks, but the effectiveness of 1DCNN and LSTM in terms of trading entry point and market perturbations has not been studied thoroughly. We demonstrate, through experiments that our proposed 1DCNN-BiLSTM-XGBoost algorithm combined with moving averages crossover effectively mitigates noise and market perturbations, leading to high accuracy in spotting trading entry points and trend signals for US 30-year-treasury-bonds. Our experimental study shows that the proposed approach achieves an average of 0.0001% Root Mean Squared Error and 100% R-Square, making it a promising method for predicting the market trends and trading entry points.

A document by Kelly Cristine Tarquinio Marinho. Click on the document to view its contents.

Trophic cascades are important determinants of food web dynamics and functioning, yet mechanisms explaining variations in trophic cascade strength remain elusive. Here we combine a mesocosm experiment (phytoplankton-zooplankton-shrimp) and theoretical models to disentangle the relative importance of two processes driving trophic cascade: primary productivity (productivity hypothesis) and energy transfer efficiency (energy transfer hypothesis). Our experimental systems showed consistently positive effects of trophic cascade across mesocosms with different nutrient inputs and zooplankton communities. Moreover, the strength of trophic cascade increased with the energy transfer efficiency between herbivores and predators, but did not change with the primary productivity. These findings are further corroborated by our analyses of food chain models in more general settings. Combined, our results support the energy transfer hypothesis but falsify the productivity hypothesis. Our study contributes an integrative perspective to reconcile energetic and population dynamics in food webs, which has useful implications for ecosystem management.

Polycyclic aromatic hydrocarbons (PAHs) contain a large group of chemical compounds that have two or more aromatic rings in their structure. These materials are produced from the incomplete burning of organic materials (such as oil, coal, wood, etc.). Natural and human activities have caused these substances to widely enter the human life cycle and affect the body’s health and functioning. After entering the body, these substances accumulate in the lungs, brain, and fat tissue, therefore, due to the high-fat mass in women, this group is more vulnerable to PAH. With the increased concentration of many of these substances in the body, problems such as genetic toxicity, carcinogenesis and mutagenesis occur. In addition to a general look at these damages, specifically how the mutagenesis process and its effects on the body are examined in detail. PAHs can become more active metabolites (BP-7-trans-dihydrodiol, benzo [a] pyrene diol-epoxide) bind to DNA, and cause mutations in DNA strands by producing ROS. PAHs produce harmful metabolites by regulating the activity of xenobiotic pathway enzymes (cytochrome P450, epoxide hydrolase, and peroxidases). For all the above, it is necessary to investigate the mechanism of their effect on the body. Due to the importance of this issue, detailed and comprehensive information is not available in sufficient quantity in this case, thus, in this research, it has been mentioned in detail and at the end of their risk assessment, it has also been examined.

Metastatic breast cancer with a large fungating breast mass in a developed country: A caveat to our strategy

A 72-year-old White male complained of memory loss, trouble recalling names and events, and a regular-duty deterioration. Hypertension, type 2 diabetes, and hyperlipidemia characterized the patient's history. He never drank or used drugs. His mother had Alzheimer's, and his father had a stroke. The patient's physical examination was unremarkable except for a 20-out-of-30 Mini-Mental State Examination (MMSE) score, suggesting mild cognitive impairment. Rivastigmine 1.5 mg twice a day was started, with a four-week escalation to 6 mg twice daily. He was given a cholinesterase inhibitor and memantine to slow cognitive impairment. Treatment efficacy and side effects were extensively examined.

We report a rare case of giant cell tumor tendon sheath in 26 year old man as a benign soft tissue tumor of thumb; managed by complete excision. Histopathological examination revealed spindle shaped cells with numerous multi-nucleated giant cells. Keywords: soft tissue tumor, tendon sheath, distal phalanx, thumb

The failure mechanisms caused by electrostatic discharge (ESD) effects at ambient temperatures ranging from -75℃ to 125℃ are investigated by Silvaco TCAD simulator. The devices are NMOS transistors fabricated with 28nm fully depleted silicon-on-insulator (FDSOI) technology. Results indicate that with an increase in temperature, the first breakdown voltage of the device decreased by 27.32%, while the holding voltage decreased by approximately 8.49%. The total current density, lattice temperature, and potential etc. were extracted for a detailed insight into the failure process. These findings provide valuable references for the design and development of ESD protection devices applied at different temperature ranges.

As a sequel to previous papers, we assess, in a more general form, the performance of real income per head / capita using generalized aggregate production function under optimal control conditions. The role of the population growth dynamics in all of this is carefully tracked, especially as it varies from primarily exponential to sturdily logistic. Analytical, qualitative and numerical simulation procedures are used to decode the population associated parameters that engender qualitative variations in the evolution of real income per head. Non-labour factors of production per effective labour are here used as the state vector, whereas the output variable is income per effective labour, whilst consumption and investments relative to the above production factors, per effective labour apiece, become the control vector. The quadratic cost functional consisting of the control and state vectors, time-discounted, turns the objective functional. Largely, real income per head rises much quicker and generates higher time-values provided the population growth mechanism is chiefly exponential in contrast to being largely logistic, given the technological process of research and development (R & D). Contrarily, under any other technology, real income per head rather rises much quicker and generates higher time-values so long as the underlying population growth mechanism is chiefly logistic, and remotely utterly exponential. Such outcomes exert consequences across board with regard to economic management in underdeveloped (where population growth is exponential) and developed (where population growth is firmly logistic) economies alike, as well as those in-between these two extremes.

A document by Wilderson Medina. Click on the document to view its contents.

A total of 32 individual samples of Hetian Qing donkeys were collected in this study, including 4 male donkeys and 28 female donkeys. Genotype data were collected by the Simplified Genome Sequencing (GBS) technology, and then genetic diversity, genetic structure, inbreeding degree and family analysis were carried out. The results showed that a total of 55399 SNP loci were detected, and the genotype detection rate of individuals was ≥ 90%; There are 45557 SNP loci through quality control, of which 95.5% are polymorphic; The average effective allele number is 0.048, the polymorphism information content is 0.273, and the average minimum allele frequency is 0.250; The average observed heterozygosity was 0.347, and the average expected heterozygosity was 0.340; The average IBS (state homology) genetic distance was 0.268; There are 49 ROHs (homozygous fragments of genome length), 73.47% of which are between 1 and 5 Mb in length. The average length of each ROH is 1.75 Mb, and the average inbreeding coefficient is 0.003; The 32 Hetian Qing donkeys can be divided into 6 families, and the individual number of each family is significantly different. To sum up, the Hetian Qing donkey population has low heterozygosity, low inbreeding degree, few families, and large differences in the number of individuals in each family, which is easy to cause the loss of genetic diversity.

Based on the brief introduction of circumferential pulmonary vein radiofrequency ablation for atrial fibrillation, this paper reviewed the research progress of perioperative nursing care of radiofrequency ablation, and summarized the perioperative nursing points of radiofrequency ablation for atrial fibrillation in China in recent years, in order to provide theoretical reference for subsequent clinical nursing work.

This paper studies the practical fixed-time average consensus problem for general continuous linear multi-agent systems under switching topologies. Firstly, a distributed fixed-time consensus control protocol based on dynamic event-triggered mechanism is designed by using the local information exchange between individual agents. The protocol introduces auxiliary dynamic variables, and the triggering condition changes in real time based on the dynamic variable obtained online, which can significantly reduce the number of triggering events, effectively decrease the energy dissipation of the system and the update frequency of the controller. Then, under the designed control protocol, the sufficient conditions for the multi-agent system to solve the practical fixed-time average consensus problem are given, and it is proved that there is no Zeno behavior in the system. Finally, the simulation results verify the effectiveness of the conclusions.