Applying the improved social network analysis method and the idea of rolling window regression, this paper explores the impact of HSR network on the quality of urbanization and its dynamics. Based on a sample of 273 cities in China over 2009–2019, we find that the high-speed railway network has an increasing positive effect on the quality of urbanization, which proves the existence of network effect. The empirical results further show that this effect is closely related to the cov-erage rate of high-speed rail network. In addition, heterogeneity analysis reveals that urban ag-glomeration cities are the main beneficiaries. Academically, our study provides a plausible expla-nation and evidence from network size differences for the two conflicting views of the HSR effect. Practically, we also propose some important policy implications for countries in different high-speed rail network construction stages.

The authors attempt to addresses the importance of timely detection and management of cervical intraepithelial neoplasia (CIN) to prevent cervical cancer. The study focuses on the potential of electrical impedance spectroscopy (EIS) as an adjunct to colposcopy, aiming to enhance the accuracy of identifying high-grade cervical lesions. Colposcopy, a widely used technique, exhibits variable sensitivity in detecting high-grade lesions, which relies on the expertise of the operator. The study's primary objective is to evaluate the effectiveness of combining colposcopy with EIS in detecting high-grade cervical lesions among patients initially diagnosed with low-grade CIN based on cytology. We employ a cross-sectional observational design, recruiting 101 women with abnormal cervical cytology results. The participants undergo colposcopy with acetic acid and subsequent EIS using the ZedScan device. The ZedScan results are categorized into color-coded probability levels, with red indicating the highest likelihood of high-grade squamous intraepithelial lesions (HSIL) occurrence. Results reveal that ZedScan exhibits a sensitivity rate of 89.5% and a specificity rate of 84% for detecting high-grade lesions. Colposcopy, on the other hand, records a sensitivity rate of 85.5% and a specificity rate of 92%. The agreement rate between ZedScan and biopsy is 79.2%, as indicated by a kappa coefficient of 0.71, while the agreement rate between colposcopy and biopsy is 74.3%, with a kappa coefficient of 0.71.

The performance and lifespan of cutting tools are significantly influenced by their surface quality. The present report highlights recent advances in enhancing the surface characteristics of tungsten carbide and high-speed steel cutting tools using a novel micro-machining technique for polishing and edge-honing. Notably, the main aim is to reduce the surface roughness while maintaining the hardness of the materials at an optimal level. By conducting a thorough analysis, of surfaces obtained with different techniques. It was that micro-machining method effectively decreased the surface roughness of the cutting tools, most effectively of the techniques investigated. Significantly, the surface roughness is reduced from an initial measurement of 400 nm to an impressive value of 60 nm. No significant change in hardness was observed, which guarantees the maintenance of the mechanical properties of the cutting tools. This analysis enhances the comprehension of surface enhancement methodologies for cutting tools through the presentation of these findings. The observed decrease in surface roughness, along with the consistent hardness, exhibits potential for improving tool performance. These enhancements possess the capacity to optimise manufacturing processes, increase tool reliability, and minimise waste generation.

FLASH-RT represents a novel therapeutic radiation modality that holds remarkable potential for mitigating radiation therapy’s adverse side effects. This cutting-edge technology allows for the sparing of healthy tissue while precisely targeting cancerous cells by administering an ultra-high dose-rates of typically between 10 and 30 Gy in less than a few hundred milliseconds. FLASH-RT has demonstrated impressive results in small-animal models, prompting scientists to adapt and advance existing technologies to make it a viable treatment option for humans. However, producing the ultra-high-dose-rate radiation required for the therapy remains a significant challenge. Several radiation sources, such as very high energy electrons (VHEEs), low energy electrons, x-rays, and protons, have been studied for their ability to deliver the necessary dose. Among them, FLASH-x-ray has gained the most attention owing to its capacity to penetrate deeply seated tumours. Despite the complexity of the process, the potential advantages of FLASH-RT make it an exciting area of research. To achieve the FLASH effect, high-frequency, pulsed irradiated accelerator technology can be employed. Sparing healthy tissue, it may allow for more aggressive and effective cancer treatments, leading to a better quality of life for patients. Ongoing research and development will be necessary to refine and optimize this approach to radiation therapy.

Based on the Generalized bracket, or Beris-Edwards, formalism of non-equilibrium thermodynamics, we have recently proposed [Stephanou et al. Materials, 13, 2867 (2020)] a new differential constitutive model for the rheology of entangled polymer melts and solutions. It has amended the shortcomings of a previous model that was too strict in the values of the convective constraint release parameter for the model not to violate the second law of thermodynamics and has been shown capable of predicting a transient stress undershoot (following the overshoot) at high shear rates. In this work, we wish to further examine this model’s capability of predicting the rheological response of industrial polymer systems by extending it to its multiple-mode version. The comparison against industrial rheological data (High-Density Polyethylene resins), as compared against available experimental data in (a) Small Amplitude Oscillatory shear, (b) start-up shear, and (c) start-up uniaxial elongation, is noted to be good.

Aiming at the prediction of environmental vibrations induced by elevated high-speed railway, a machine-learning method is developed by combining random forest algorithm and Bayesian optimization, which using the dataset from on-site experiments . When it comes to achieving a rapid and effective prediction of environmental vibration, there is few research on com-parisons and verifications of different algorithms, and neither on parameter tuning and optimi-zation of machine learning algorithms. In this paper, a field experiment is firstly carried out to measure the ground vibrations caused by high-speed trains running on bridge, and then the en-vironmental vibration characteristics are analyzed in view of ground accelerations and weighted vibration levels. Subsequently, three machine-learning algorithms of linear regression, support vector machine and random forest are developed by using experimental database, and their prediction performance are discussed. Finally, two optimization models for the hyperparameter set of random forest algorithm are further compared. It turns out that the integrated random forest algorithm has higher accuracy in predicting environmental vibration than linear regression and support vector machine; the Bayesian optimization has excellent performance and high efficiency in achieving efficient and in-depth optimization of parameters, and can be combined with the RF machine learning algorithm to effectively predict the environmental vibrations induced by the high-speed railway.

In a search for a reliable, inexpensive, and versatile technique for high-throughput kinetic assays of drug metabolism, we elected to rehire an old-school approach based on the determination of formaldehyde (FA) formed in cytochrome P450-dependent demethylation reactions. After evaluating several fluorometric techniques of FA detection, we choose the method based on the Hantzsch reaction with acetoacetanilide as the most sensitive, robust, and adaptable to high-throughput implementation. Here we provide a detailed protocol for the use of our new technique for automatized assays of cytochrome P450-dependent drug demethylations and discuss its applicability for high-throughput scanning of the pathways of drug metabolism in the human liver. To probe our method further, we applied it to re-evaluating the pathways of metabolism of ketamine, a dissociative anesthetic, and potent antidepressant increasingly used in the treatment of alcohol withdrawal syndrome. Probing the kinetic parameters of ketamine demethylation by 11 major cytochrome P450 (CYP) enzymes, we demonstrate that besides CYP2B6 and CYP3A enzymes, which were initially recognized as the primary metabolizers of ketamine, an important role is also played by CYP2C19, and CYP2D6, while the involvement of CYP2C9 suggested in the previous reports deemed insignificant.

Transarterial embolization (TAE) for high-flow pancreaticoduodenal artery (PDA) aneurysms in patients with celiac-trunk stenosis by the median arcuate ligament (MAL) has been found effective both after rupturing and to prevent rupture. The objective was to describe the TAE techniques used and their effectiveness in excluding PDA aneurysms due to MAL syndrome. This single-center retrospective study done at the Dijon-Bourgogne University Hospital included all patients treated by TAE in 2010–2022 for ruptured or unruptured high-flow PDA aneurysms caused by MAL syndrome. We identified 14 patients (7 women and 7 men; mean age, 64 years). Packing and trapping techniques were used alone or together. Occlusion was with microcoils, co-polymer, or cyanoacrylate glue, used separately or combined. Technical success was achieved in 13 (93%) patients. Clinical success was achieved in 12 (86%) patients. One major and two minor complications were recorded within the first 30 days. No complications occurred after 30 days. Follow-up ranged from 1 to 84 months. No cases of aneurysm recanalization were recorded to date. TAE had high technical and clinical success rates in our patients with unruptured or ruptured PDA aneurysms due to MAL syndrome.

Lung cancer is the leading cause of global cancer-related mortality resulting in ~1.8 million deaths annually. Systemic, molecular targeted, and immune therapies have provided significant improvements of survival outcomes for patients. However, drug resistance usually arises and there is an urgent need for novel therapy screening and personalized medicine. 3D patient-derived organoid (PDO) models have emerged as a more effective and efficient alternative for ex vivo drug screening than 2D cell culture and patient-derived xenograft (PDX) models. In this review, we performed an extensive search of lung cancer PDO-based ex vivo drug screening studies. Lung cancer PDOs were successfully established from fresh or biobanked sections/biopsy of lung tumors, PDXs, and pleural affusion. PDOs were subject to ex vivo drug screening with chemotherapy, targeted therapy and immune therapy agents. PDOs mainly recapitulated the genomic alterations, transcriptomic landscape and drug sensitivity of primary tumors. Although sample sizes of the previous studies were limited and some technical challenges remained, PDOs showed promise to screen novel therapy drugs. With the technical advance of high throughput, tumor-on-chip, combined microenvironment, and air-liquid interface (ALI), the drug screening using PDOs would serve better for precision care of lung cancer patients.

China is rich in coal resources under water bodies. However, for a long time, the safety prediction of high-intensity mining under water bodies is one of the problems encountered by the coal industry. It is of great significance to realize safe mining under water bodies, improve the recovery rate of coal resources and protect reservoir resources. Therefore, this article takes the No. 5 coal seam and No. 11 mining area of Wangwa Coal Mine as the research object, and integrates physical simulation, numerical simulation, theoretical analysis and other methods to study the development height of water-conducting fracture zones in fully mechanized top coal caving mining. Solid-liquid coupling physical simulation test reveals the failure characteristics of overlying strata in goaf and the seepage law of reservoir water under the influence of mining. By comparing the monitoring data of borehole leakage, the measured data obtained by borehole peeping with the height data of water-conducting fracture zone obtained by the traditional empirical formula of three-under standard, the error between the two is as high as -29.39 %. In this case, the variance correction coefficient is used to correct the empirical formula, and on this basis, in order to effectively protect the surface water dam and water body, the mining height of coal seam in the working face with limited height mining is inversely derived. The research results provide a basis for the safety prediction of high-intensity mining under the reservoir dam in the ecologically fragile areas of western China and provide a scientific guarantee for the formulation of safety measures under such conditions.

Background. There are scant data about the effectiveness of high flow nasal cannula (HFNC) oxygen therapy in patients hospitalized with severe acute respiratory failure (ARF) in non-intensive medical wards, particularly regarding the effect on arterial oxygenation compared to conventional oxygen therapy (COT) and non-invasive ventilation (NIV) or continuous positive airway pressure (CPAP). Methods. In a retrospective observational study, oxygenation parameters were measured before and immediately after HFNC initiation in 37 consecutive patients hospitalized in a geriatric ward in 2017. Results. HFNC was used as escalation therapy for untreatable hypoxia after failure of NIV/CPAP (n=18) or COT (n=19). Twenty-two patients died, 2 were transferred to the intensive care unit, while 13 were discharged alive. A “do not intubate” status was identified in 17 of the 22 deceased patients. Partial pressure of oxygen (pO2, p< 0.0001), oxygen saturation (SO2, p< 0.0001), pO2/fraction of inspired oxygen ratio (p=0.004) and peripheral SO2 measured by pulse oximetry (p< 0.0001) significantly increased soon after HFNC application. Oxygenation improvements were greater after escalation from NIV/CPAP and in patients discharged alive. Conclusion. HFNC significantly improved oxygenation in severe ARF after failure of COT or NIV/CPAP and may be particularly suitable for older patients hospitalized in non-intensive medical wards.

Purpose: The purpose of this study was to evaluate the dosimetric impact of multiple channels compared to a single channel in high dose rate (HDR) vaginal cuff brachytherapy (VCBT). Methods and materials: Sample plans of HDR VCBT from both single and multiple channel cylinders at 2.5, 3.0 and 3.5 cm in diameter were created and analyzed. The doses were prescribed either at the 0.5 cm depth with 5.5 Gy for 4 fractions or at the cylinder surface with 8.8 Gy for 4 frac¬tions, in various treatment lengths ranging from 3 to 8 cm. A 0.5 cm ring target volume called PTV_Eval was contoured for each plan and served as the target volume for dosimetric evaluation. Mean doses and the doses covering 90% (D90), 10% (D10), and 5% (D5) of PTV_Eval were calculated and compared. The same treatment lengths, same prescription regimens, same target volume contouring and same plan evaluation methods were repeated for the similar size single channel and multiple channel cylinders. Results: The mean doses of both regimens with the multi-channel cases (6.3 to 7.1 Gy) were comparable to single channel ones (6.4 and 7.5 Gy). The ranges of D90, D10 and D5 were from 3.654 to 5.04 Gy, 8.44 to 10.08 Gy and 8.84 to 10.86 Gy in the multi-channel cases, but from 5.36 to 5.76 Gy, 7.40 to 9.97 Gy and 8.16 to 11.93 Gy in the single channel cases, respectively. Conclusion: The single channel and multiple-channel cylinder deliver a similar mean dose, but with marked heterogeneity in D90, D5 and D10 for the same prescription dose and target volume. Multi-channel cylinders adequately cover the target volume, but given the heterogeneity, increased treatment time and cost are best suited for asymmetric target volumes.

In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian Coherent Structures (LCS) in large-scale Direct Numerical Simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient, constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains requiring efficient search algorithms in large structured domains. While this manuscript focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication.

Ozonated sunflower oil (OSO) is well known functional oil with its antioxidant, antimi-crobial, anti-allergic, and skin-moisturizing properties. However, studies on the effects of OSO on high-cholesterol diet (HCD)-induced metabolic disorders have been scarce. In the current study, we aimed to determine the anti-inflammatory effects of OSO on lipid me-tabolism in adult hypercholesterolemic zebrafish and its embryo. Microinjection of OSO (final 2%, 10 nL) into zebrafish embryos under presence of carboxymethyllysine (CML, 500 ng) protected acute embryo death upto 61% survival, while sunflower oil (final 2%) showed much less protection around 42% survival. The microinjection of OSO was more effective than SO to inhibit reactive oxygen species (ROS) production and apoptosis in the CML induced embryo toxicity. Intraperitoneal injection of OSO under presence of CML protected acute death from CML-induced neurotoxicity with improved hepatic inflamma-tion, less detection of ROS and interleukin (IL)-6, and lowering blood total cholesterol (TC) and triglyceride (TG), while SO-injected group did not protect the CML-toxicity. Long-term supplementation of OSO (final 20%, wt/wt) with HCD for 6 months resulted higher sur-vivability than HCD alone group or HCD+SO group (final 20%, wt/wt) with significant lowering of plasma TC and TG levels. The HCD+OSO group showed the least hepatic in-flammation, fatty liver change, ROS, and IL-6 production. In conclusion, short-term treat-ment of OSO by injection exhibited potent anti-inflammatory activity against acute neuro-toxicity of CML in zebrafish and its embryo. Long-term supplementation of OSO in diet also revealed the highest survivability and blood lipid-lowering effect through potent an-ti-oxidant and anti-inflammatory activity.

To determine promethazine (PMZ) and its metabolites promethazine sulfoxide (PMZSO) and monodesmethyl-promethazine (Nor1PMZ) in swine muscle, fat, kidney, and liver, a sample preparation and high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis method were established and validated. The sample was extracted with 0.1% formic acid-acetonitrile, and the extract was purified with acetonitrile-saturated n-hexane. After concentration by rotary evaporation, the extract was re-dissolved in 0.1% formic acid-water and acetonitrile (80:20, v/v). The HPLC-MS/MS column used was a Waters Symmetry C18 (100 mm × 2.1 mm i.d., 3.5 μm), with 0.1% formic acid-water and acetonitrile as the mobile phase, and the target compounds were determined by positive ion scan and multiple reaction monitoring. PMZ and Nor1PMZ were quantified with deuterated promethazine (PMZ-d6) as the internal standard, while PMZSO was quantified by external standard method. The limits of detection (LOD) and limits of quantification (LOQ) of PMZ and PMZSO in muscle, liver, and kidney spiked samples were 0.05 μg/kg and 0.1 μg/kg, respectively, while those of Nor1PMZ were 0.1 μg/kg and 0.5 μg/kg, respectively. The LOD and LOQ of analytes in fat spiked sample were 0.05 μg/kg and 0.1 μg/kg, respectively. The sensitivity of this method reaches or exceeds its presented in previous reports. The analytes PMZ and PMZSO showed good linearity within the range of 0.1 μg/kg to 50 μg/kg, while Nor1PMZ showed good linearity within the range of 0.5 μg/kg to 50 μg/kg, with correlation coefficients (r) greater than 0.99. The recoveries of the target compounds in the sam-ples were between 81.73% and 107.17%, and the precision ranged from 1.78% to 10.47%. This study developed for the first time an HPLC-MS/MS method for the determination of PMZ and its metabolites PMZSO and Nor1PMZ in four swine edible tissues, comprehensively covered target tissues of monitoring object, which is applicable for monitoring veterinary drug residues in ani-mal-derived foods and ensuring food safety.

The use of spirocycles in drug discovery and medicinal chemistry has been booming in the last two decades. This has clearly translated in the landscape of approved drugs. Among two dozen clinically used medicines containing a spirocycle, 50% have been approved in the 21st century. The present review focuses on the notable synthetic routes to such drugs invented in industry and academia and is intended to serve as a useful reference source of synthetic as well as general drug information for researchers engaging in the design of new spirocyclic scaffolds for medicinal use or embarking upon analog syntheses inspired by the existing approved drugs.

High resolution melting (HRM) analysis is a powerful detection method for fast, high-throughput post-PCR analysis. A two-step HRM marker system was developed for identification of the N-, S-, R- and T-cytoplasms of onion. In the first step for identification of N-, S-, and R-cytoplasms, one forward primer was designed to the identical sequences of both cox1 and orf725 genes and two reverse primers specific to the polymorphic sequences of cox1 and orf725 genes were used. For the second step breeding lines with N-cytoplasm were evaluated with primers developed from the orfA501 sequence to distinguish between N- and T-cytoplasms. An amplicon with primers to the mitocondrial atp9 gene was used as an internal control. The two-step HRM marker system was tested using 246 onion plants. HRM analysis showed that the most common source of CMS, often used by Russian breeders, is S-cytoplasm, the rarest type of CMS is R-cytoplasm, and the proportion of T-cytoplasm among the analyzed breeding lines was 20.5%.

A high-voltage transmission tower consists of structures to avoid the risk of electric shock and to prevent the risk of collapse. Hence, towers are generally designed to be high-rise for efficiency. The main posts of the tower are primary structural members that resist loads under various load conditions. Therefore, the contribution of the secondary member to securing the stiffness and strength of the main posts by reducing the effective buckling length is important. However, there are no detailed design criteria for secondary members. In this study, the structural effects of horizontal members and braces on the torsional stiffness, elastic buckling strength, and load-carrying capacity of transmission towers were observed through various structural analysis methods including linear-elastic, eigenvalue, and geometric nonlinear and inelastic analyses under governing load combinations. According to the analytical study, rather than the horizontal members, the brace spacing significantly affects the structural performance. Therefore, the number of horizontal members can be minimized if sufficient brace members are erected. If the brace spacing is wide, it is recommended that the horizontal members be erected to create K bracing, and the buckling resistance of the main posts can be thus enhanced.

Arjunolic acid (AA) is a triterpenoid saponin majorly found in the Terminalia arjuna and is claimed to exert the cardiovascular protective effects as a phytomedicine. However, it is unclear how AA exerts the effects at the molecular level. Hence, this study used an in vitro model using lipopolysaccharide (LPS)-stimulated H9C2 and C2C12 myotubes to investigate the cardioprotective effects of arjunolic acid (AA) via MyD88-dependant TLR4 downstream signaling markers expression. The myotubes were developed by differentiating rat H9C2 and mouse C2C12 myoblast cells. The MTT viability assay was used to assess the cytotoxicity of AA. LPS induced in vitro cardiovascular disease model was developed in H9C2 and C2C12 myotubes. The treatment groups were designed such as control (untreated), LPS control, positive control (LPS+ pyrrolidine dithiocarbamate (PDTC)-25 µM), and treatment groups were co-treated with LPS and three doses of AA (50, 75, and 100 µM). The changes in the expression of TLR4 downstream signaling markers were evaluated through High Content Screening (HCS) and Western Blot (WB) analysis. The outcomes demonstrated that the expression of MyD88, MAPK, JNK, and NFκB markers were significantly upregulated in the LPS-treated groups compared to the untreated control. Evidently, the HCS analysis revealed that MyD88, NF-κB, p38, and JNK were significantly downregulated in the H9C2 myotube in the AA treated groups (50, 75, and 100 µM). For, the C2C12 myotube, the expression of NFκB was downregulated. TLR4 marker expression in H9C2 and C2C12 myotubes was subsequently decreased by AA treatment, suggesting possible cardioprotective effects of AA.

The likelihood of pre-hypertensive young adults developing hypertension has been steadily increasing over the past few years. Despite the fact that aerobic exercise training (AET) has demonstrated positive results in lowering high blood pressure, the efficacy of different types of AET among pre-hypertensive young adults has not been well-established. The objective of this study was to evaluate the effectiveness of high-intensity interval training (HIIT) and continuous moderate-intensity training (CMT) on blood pressure (BP) of physically inactive pre-hypertensive young adults. 32 adults (age 20.0±1.1 years and BMI 21.5±1.8) were randomly assigned into 3 groups: HIIT, CMT and control (CON). HIIT and CMT groups participated in 5 weeks of AET; while the CON group followed a DASH diet plan only. The HIIT protocol consisted of 1:4 minute work to rest ratio of participants 80%-85% heart rate reserve (HR-reserve) and 40%-60% HR-reserve respectively for 20-minutes, CMT group exercised at 40%-60% of HR-reserve continuously for 20-minutes. In both HIIT and CMT groups, systolic blood pressure (SBP) (3.8±2.8 mmHg, P=0.002 VS 1.6±1.5 mmHg, P=0.011) was significantly reduced. While, significant reductions in the diastolic blood pressure (DBP) (2.9±2.2 mmHg, P=0.002) and mean arterial pressure (MAP) (3.1±1.6mmHg, P<0.0005) were noted only in the HIIT group. No significant differences in SBP (-0.4±3.7 mmHg, P=0.718), DBP (0.4±3.4 mmHg, P=0.714), or MAP (0.1±2.5mmHg, P= 0.892) were observed in the CON group. Both HIIT and CMT decreased the BP in physically inactive pre-hypertensive young adults; however, HIIT yielded more beneficial results in terms of reducing the SPB, DBP and MAP.

BACKGROUND. Two sequelae of non-alcoholic steatohepatitis (NASH), ESLD and HCC, have become the leading causes for liver transplantation in the Western. The present study aims to approach the cellular metabolic disturbances involved in NASH progression that are associated with microbiota community changes. METHODS. Metabolic effects and microbiota community changes were explored in the murine with NASH progression by blocking the Na/K-ATPase/Src/reactive oxygen amplification loop using the synthetic targeting peptide pNaKtide. DNA from the terminal ileum microbiota habitat was obtained and amplified by PCR to develop DNA bacterial phylogenic sequence analysis of wild type and treated animals at 12, 24 and 48 weeks. Induced changes by pSrc normalization at 24 weeks were correlated with liver morphological changes, intestinal CD4+/CD8+ ratio, and liver macrophage CD14+ expression. Differences among groups were evaluated by ANOVA/t-test and Principal Component Analysis (PCA). RESULTS. Microbiota communities varied significantly at all time points (12, 24 and 48 weeks), with an increase of Verrucomicrobia and a decrease of Bacteroidetes and Firmicutes in the HFD group. Microbiota community changes regressed to their wild-type state at 24 weeks on treated animals, and those changes were associated with a decrease in liver inflammation and senescence, lower ileum CD4+/CD8+ T cells and higher liver CD14+ cells (p<0.05). Concomitantly, the metabolic disturbances in our diet-induced NASH model were normalized by NKA/Src signaling blockage and exercise with a paucity of apoptotic activity, mitigation of cell senescence, and regression of liver fibrosis (p<0.01). CONCLUSIONS. pSrc inhibition at caveolar α1-Na/K-ATPase rescinded NASH-related metabolic disturbances establishing resident physiological microbiota communities with concomitant paucity on apoptotic activity and regression of liver fibrosis; effects that were associated with both gut and liver T-lymphocyte responses.

During the COVID-19 pandemic, individuals with symptoms other than cough or fever have refrained from seeking medical advice. However, a delay in treatment might lead to serious consequences. At the same time, digital health initiatives have emerged to overcome this bottleneck of healthcare. Herein, we report the results of a multi-center initiative using a combination of patient history and artificial intelligence (AI) to identify individuals with rare neuromuscular diseases. First, a questionnaire with 46 items was developed by interviewing patients with muscular dystrophies, amyotrophic lateral sclerosis, Morbus Pompe, neuropathies, and myasthenia gravis. Second, patients with proven neurological diseases answered the questionnaire. Third, a combination of classifiers (artificial neural network, support vector, and random forest) was trained and, finally, the system was challenged with new questionnaires. Users with an abnormal questionnaire pattern received a unique code for data privacy and contact details for a neurologist for further advice. The neurologists confirmed or refuted the AI-based diagnosis. The questionnaire was accessed 3122 times, leading to 853 unique codes. Only for a few patients the computer-based diagnoses and the confirmed final diagnoses were reported to us. However, for these few patients, the genetic testing and high CK levels finally ended their long-lasting diagnostic odyssey.

Early diagnosis and treatment have always been highly desired in the fight against cancer, and detection of circulating tumor DNA (ctDNA) has recently been touted as highly promising for early cancer screening. Consequently, the detection of ctDNA in liquid biopsy gains much attention in the field of tumor diagnosis and treatment, which has also attracted research interest from the industry. However, traditional gene detection technology is difficult to achieve low cost, real-time and portable measurement of ctDNA. Electroanalytical biosensors have many unique advantages such as high sensitivity, high specificity, low cost and good portability. Therefore, this review aims to discuss the latest development of biosensors for minimal-invasive, rapid, and real-time ctDNA detection. Various ctDNA sensors are reviewed with respect to their choices of receptor probes, detection strategies and figures of merit. Aiming at the portable, real-time and non-destructive characteristics of biosensors, we analyze their development in the Internet of Things, point-of-care testing, big data and big health.

One of the intriguing recent results in the field of high-entropy alloys is the discovery of single-phase equiatomic multi-component Laves intermetallics. However, there is no clear understanding that a combination of chemical elements will form such high-entropy compounds. Here we contribute to understanding this issue by modifying the composition of duodenary TiZrHfNbVCrMoMnFeCoNiAl (12x) alloy in which we recently reported the fabrication of hexagonal C14 Laves phase. We consider three alloys based on 12x: 7x=12x-VCrMoMnFe, 12x+Sc, 12x+Be and observe that all of them crystalize with the formation of C14 Laves phase as a dominant structure. We report that 12x+Be alloy reveals single-phase C14 structure with very high concentration of structural defects and ultra-fine dendritic microstructure with almost homogenous distribution of the constituted elements over the alloy matrix. The 7x and 12x+Sc alloys contain C14 as a main phase and unknown impurity phases. To characterize the materials, we examine their heat capacity, electrical conductivity and magnetic properties. The measurements reveal that the Laves phases are Curie-Weiss paramagnets, which demonstrate metallic conduction; 7x and 12x alloys also reveal a pronounced Kondo-like anomaly. Analysis of experimental data as well as ab initio calculations suggests that chemical complexity and compositional disorder cause strong s-d band scattering and thus the rather high density of d-states in the conduction band. Analysis of the results suggests that the mechanism of Laves phase formation in multicomponent multi-principal element metallic alloys is may be the same as in polydisperse hardspheres mixtures. Another important conclusion is that the configurational entropy is a negligible factor in the stabilization of multi-element Laves phases.

Understanding of the decisive role of the interaction mechanism and kinetics in the combustion processes is highly relevant for the elaboration of optimal conditions for obtaining Mo-Cu composite powders. From this perspective, the efficient delivery of the reduction mechanism of copper and molybdenum oxides with combined Mg + C reducing agents at high heating rates is crucial to develop a valuable approach for the combustion synthesis of Mo-Cu composite powders. Herein, we shed light on the mechanism of the reactions in all the studied binary, ternary and quaternary systems contemporaneously demonstrating the effect of the heating rate on the conversion degree. The combination of two highly exothermic and speedy reactions (MoO3+3Mg and CuO+Mg vs MoO3+CuO+4Mg) led to a slow interaction with weak self-heating (dysynergistic effect) due to a change in the reaction mechanism. On the other hand, it has been shown that during the simultaneous utilization of the Mg and C reducing agents, the process begins exclusively with carbothermic reduction, and at relatively high temperatures it continues with magnesiothermic one. The effective activation energy values of the magnesiothermic stages of the studied reactions were determined by Kissinger isoconversional method.

In Acropora, the complex canals in a coral colony connect all polyps into a holistic network to collaborate in performing biological processes. There are various types of canals, including calice, axial canals, and other internal canals, with structures that are dynamically altered during different coral growth states due to internal calcium transport. However, few studies have considered the regulation of calcium transport in Acropora. In this study, we investigated the morphological changes of the axial canal in six Acropora muricata samples by high resolution micro-computed tomography, observing the patterns of the axial canal during the processes of new branch formation and truncated branch rebuilding. We visualized the formation of a new branch from a calice and deposition of the iconic hexactin skeletons in the axial canal. Furthermore, the diameter and volume changes of the axial canal in truncated branches during rebuilding processes were calculated, revealing that the volume ratio of calcareous deposits in the axial canal exhibit significant increases within the first three weeks, returning to levels in the initial state in the following week. This work indicates that the axial canal can transport calcium to form hexactin skeletons in a new branch and rebuild the tip of a truncated branch. The calcium transport along canal network regulates various growth processes, including budding, branching, skeleton forming, and self-rebuilding of an Acropora colony. Understanding the changes in canal function under normal and extreme conditions will provide theoretical guidance for restoration and protection of coral reefs.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology, and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as a support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park in a business environment, so as to clarify the socio-economic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

Transplant of human cancer cells into zebrafish larvae has emerged as a useful methodology in cancer research. Zebrafish have very low husbandry costs, are amenable to large-scale drug screening, and are unmatched for optical clarity in live animal imaging. However, there is currently no consensus on the ideal methods for xenograft of human cancer cells into zebrafish. Here, we have examined the effects of transplant site and housing temperature on both zebrafish larvae and human cancer cells using survival analyses, metabolomic approaches, and in vivo imaging. Our data show that while zebrafish larvae can adapt to the ideal conditions for mammalian cells, human cancer cells are highly sensitive to both temperature change and transplant site. Human cells housed in slightly cooler than physiologic temperatures had a significantly altered metabolism that resulted in changes in growth, survival, and response to chemotherapy. Cancer cells xenografted into the yolk of the larvae also had reduced proliferation and drug response compared to those xenografted into the soma, in part due to the differences in metabolites available at these sites. In total, temperature and transplant site can have profound effects on xenografted cells. Standardization of zebrafish xenograft methods will enhance data reproducibility between individual laboratories.

The novel coronavirus (COVID-19) was first reported in the U.S. on December 29, 2019 and has spread rapidly throughout the country, affecting individuals with varying severity due to their risk status. According to the Centers for Disease Control and Prevention, it is estimated that 45.4% of US adults are at higher risk for complications from coronavirus disease because of cardiovascular disease, diabetes, respiratory disease, hypertension, or cancer. In this study, we developed a mathematical model to assess the impact of a COVID-19 vaccine among low and high risk groups. Numerical simulations shows vaccinating both low and high risk groups simultaneously, rather than prioritizing the vaccine on high risk group only, further reduces the daily mortality. The result supports the need for an aggressive vaccination program, regardless of whether individuals are within the low or high risk population.

A new approach to fabricate TiNi surfaces combining the advantages of both monolithic and porous materials for implants is used in this work. New materials were obtained by depositing a porous TiNi powder onto monolithic TiNi plates followed by sintering at 1200°C. Then, further modification of the material surface with a high-current-pulsed electron beam (HCPEB) was carried out. Three materials obtained (one after sintering and two after subsequent beam treatment by 20 and 30 pulses, respectively) were studied by XRD, SEM, EDX, EIS methods, profilometry and OCP measurements. Structural and compositional changes caused by HCPEB treatment were investigated. Surface properties of the samples during their storage in saline for 10 days were studied and a model experiment with cell growth (MCF-7) was carried out for the sample unmodified with electron beam to detect cell appearance on different surface locations.

An extension of the models used to generate fractal traffic flows is presented by means of the formulation of a model that considers the use of one-dimensional chaotic maps. Based on the disaggregation of the temporal series generated by the model, a valid explanation of behavior of the values of Hurst exponent is proposed and the feasibility of their control from the parameters of the proposed model is shown.

Lipophilicity can be measured with different methods, such as Shake-Flask or liquid chromatography. HPLC presents the advantage of overcoming solubility issues and therefore extending the range of lipophilicity to high values. A specific HPLC method, called ELogD, had been developed 20 years ago on a C₁₆-amide stationary phase, enhancing hydrophobic and hydrogen bond interactions to mimic octanol-water partition. The emergence of novel stationary phases added to the need for a less complex mobile phase has led to the development of a new HPLC assay called alphaLogD, applicable to neutral and basic compounds at pH 7.4, that combines superficially porous particles, a high number of equilibriums between solutes and stationary phase, and results in a lower number of isocratic methods to determine the logk’_w at a higher throughput. Statistical studies have been run to successfully evaluate the alphaLogD method compared to the Shake-Flask method and to allow this lipophilicity measurement into the so-called Beyond-Rule-of-5-molecules space.

Remote sensing technology provides a new way to explore the earth for geoscience applications. In the context of continuous deepening of geological research and the vigorous development of geospatial information science, 3D geological modeling technology has become a research hotspot in the intersection of earth science and information science. The traditional 3D geological modeling technology refers to underground 3D modeling using geological data. This modeling method can only display the underground scene in 3D visualization, but cannot display the surface in detail. In this study, remote sensing technology is adopted to improve the traditional 3D geological modeling method, so that geological modeling can be integrated with remote sensing image, and a new 3D geological modeling method based on remote sensing technology is developed. This method can perform integrated 3D visualization of underground and aboveground scenes, which provides a new way for disaster prevention and reduction, geological prospecting and tectonic interpretation. The new 3D geological modeling method is mainly applied in the geological field, and has made new progress in multi-source heterogeneous geological data fusion, large-scale high-precision modeling, geological grid subdivision, attribute modeling technology, remote sensing image fusion and other aspects. Taking the Ya'an area as an example, this paper makes use of the new generation of 3D geological modeling technology to carry out 3D geological modeling and visual display. The 3D visualization in Ya'an area verifies the feasibility and effectiveness of the new 3D geological modeling method based on remote sensing technology in the current data environment.

In this paper, we present a high-speed, unified elliptic curve cryptography (ECC) processor for arbitrary Weierstrass curves over GF(p), which to the best of our knowledge, outperforms other similar works in terms of execution time. Our approach employs the combination of the schoolbook long and Karatsuba multiplication algorithm for the elliptic curve point multiplication (ECPM) to achieve better parallelization while retaining low complexity. In the hardware implementation, the substantial gain in speed is also contributed by our n-bit pipelined Montgomery Modular Multiplier (pMMM), which is constructed from our n-bit pipelined multiplier-accumulators that utilizes DSP primitives as digit multipliers. Additionally, we also introduce our unified, pipelined modular adder/subtractor (pMAS) for the underlying field arithmetic, and leverage a more efficient yet compact scheduling of the Montgomery ladder algorithm. The implementation on the 7-series FPGA: Virtex-7, Kintex-7, and XC7Z020, yields 0.139, 0.138, and 0.206 ms of execution time, respectively. Furthermore, since our pMMM module is generic for any curve in Weierstrass form, we support multi-curve parameters, resulting in a unified ECC architecture. Lastly, our method also works in constant time, making it suitable for applications requiring high speed and SCA-resistant characteristics.

The objective of this experiment was to study the effect of feeding pellet containing high sulfur (PELFUR) diet and fresh cassava root (FCR) to Thai native beef cattle on feed use efficiency, ruminal characteristics, and blood metabolites. Four male Thai native beef cattle (150 ± 15.0 kg of body weight (BW)) were allocated with a 2 × 2 factorial arrangement in a 4 × 4 Latin square design. Factor A was FCR supplementation at 15 and 20 g/kg of BW. Factor B was the sulfur level in the PELFUR ration at 15 and 30 g/kg of dry matter (DM). No interaction effect was found among FCR supplementation and PELFUR in terms of feed intake and nutrient intake (p > 0.05). Cyanide intake was significantly increased based on FCR supplementation (p < 0.05), whereas sulfur intake was increased by level addition of PELFUR levels (p < 0.05). There were interaction effects among FCR supplementation and PELFUR on digestibility coefficients of DM and organic matter (OM) (p < 0.05). FCR supplementation at 20 g/kg BW with PELFUR 30 g/kg demonstrated the highest digestibility of DM and OM. Moreover, interactions were observed between FCR and PELFUR for bacterial populations (p < 0.01). The populations of bacteria were highest in FCR supplementation at 20 g/kg BW with PELFUR 30 g/kg at various feeding times. An interaction effects from among feeding FCR with PELFUR was found on blood thiocyanate concentrations at various feeding times (p < 0.01). The highest mean values of blood thiocyanate were observed when feeding FCR at 20 g/kg BW with PELFUR at 30 g/kg. No interaction effect was found between FCR and PELFUR on total volatile fatty acids (VFA) and their profiles (p >0.05). However, the proportions of the total VFA at 0 and 4 h post-feeding were increased when FCR at 20 g/kg BW was supplemented (p < 0.01). FCR at 20 g/kg BW could enhance propionate (C3) at 4 h post-feeding when compared with FCR at 15 g/kg BW (p < 0.01). Moreover, supplementation of PELFUR at 30 g/kg increased the total VFA at 0 and 4 h post-feeding, whereas the concentration of C3 at 4 h post-feeding was enhanced (p < 0.05). However, no significant changes were found for any parameters among treatments and between the main effect of FCR and PELFUR supplementation (p > 0.05). In conclusion, feeding of two combinations (FCR 20 g/kg BW with PELFUR 30 g/kg) could promote the nutrient digestibility, the bacterial populations, and the rate of disappearance of cyanide without having any adverse effect on rumen fermentation.

The understanding of water quality and its underlying processes is important for the protection of aquatic environments enabling the rare opportunity of access to a domain expert. Hence, an explainable AI (XAI) framework is proposed that is applicable to multivariate time series resulting in explanations that are interpretable by a domain expert. The XAI combines in three steps a data-driven choice of a distance measure with explainable cluster analysis through supervised decision trees. The multivariate time series consists of water quality measurements, including nitrate, electrical conductivity, and twelve other environmental parameters. The relationships between water quality and the environmental parameters are investigated by identifying similar days within a cluster and dissimilar days between clusters. The XAI does not depend on prior knowledge about data structure, and its explanations are tendentially contrastive. The relationships in the data can be visualized by a topographic map representing high-dimensional structures. Two comparable decision-based XAIs were unable to provide meaningful and relevant explanations from the multivariate time series data. Open-source code in R for the three steps of the XAI framework is provided.

The determination of crack propagation velocities can provide valuable information for a better understanding of damage processes of concrete. The spatio-temporal analysis of crack patterns developing at a speed of several hundred meters per second is a rather challenging task. In the paper, a photogrammetric procedure for the determination of crack propagation velocities in concrete specimens using high-speed camera image sequences is presented. A cascaded image sequence processing which starts with the computation of displacement vector fields for a dense pattern of points on the specimen’s surface between consecutive time steps of the image sequence chain has been developed. These surface points are triangulated into a mesh, and as representations of cracks, discontinuities in the displacement vector fields are found by a deformation analysis applied to all triangles of the mesh. Connected components of the deformed triangles are computed using region-growing techniques. Then, the crack tips are determined using principal component analysis. The tips are tracked in the image sequence and the velocities between the time stamps of the images are derived. A major advantage of this method as compared to established techniques is in the fact of its allowing for spatio-temporally resolved, full-field measurements rather than point-wise measurements and that information on crack width can be obtained simultaneously. To validate the experimentation, the authors processed image sequences of tests on four compact-tension specimens performed on a split-Hopkinson tension bar. The images were taken by a high-speed camera at a frame rate of 160,000 images per second. By applying to these datasets the image sequence processing procedure as developed, crack propagation velocities of about 800 m/s were determined with a precision in the order of 50 m/s.

We report herein high-resolution x-ray diffraction measurements of basal plane bending of homoepitaxial single-crystal diamond (SCD). The results reveal that growth parameters such as temperature, growth time and basal plane bending of the substrate affect the basal plane bending of SCD. First, the basal plane bending of SCD depends mainly on the substrate itself. The basal plane bending of SCD becomes more severe with increasing basal plane bending of the substrate and this type of basal plane bending cannot be recovered. The SCD growth experiments show that the basal plane bending increases at high temperature and with increasing growth time. Finally, to understand the mechanism behind basal plane bending, we investigate the substrate-surface temperature distribution as a function of basal plane bending of SCD fabricated by chemical vapour deposition (CVD). This allows us to propose a bending model and understand the origin of basal plane bending. The results indicate that an uneven temperature distribution on the substrate surface is the main cause of the CVD diamond base-plane bending.

We introduce firm solar forecasts as a strategy to operate optimally overbuilt solar power plants in conjunction with optimally sized storage systems so as to make up for any power prediction errors, hence entirely remove load balancing uncertainty emanating from grid-connected solar fleets. A central part of this strategy is plant overbuilding that we term implicit storage. We show that strategy, while economically justifiable on its own account, is an effective entry step to least-cost ultra-high solar penetration where firm power generation will be a prerequisite. We demonstrate that in absence of an implicit storage strategy, ultra-high solar penetration would be vastly more expensive. Using the New York Independent System Operator (NYISO) as a case study, we determine current and future cost of firm forecasts for a comprehensive set of scenarios in each ISO electrical region, comparing centralized vs. decentralized production and assessing load flexibility’s impact. We simulate the growth of the strategy from firm forecast to firm power generation. We conclude that ultra-high solar penetration enabled by the present strategy, whereby solar would firmly supply the entire NYISO load, could be achieved locally at electricity production costs comparable to current NYISO wholesale market prices.

For traffic management under sudden disaster in high-density areas, the first and foremost step is to prevent traffic congestion in the disaster-affected area by traffic flow control, as to provide enough and flexible traffic capacity for emergency evacuation and emergency rescue. Catastrophe border identification is the foundation and the key to traffic congestion prediction under sudden disaster. This paper uses a mathematical model to study the regional traffic flow in the high-density area under sudden fire disaster based on the Cusp Catastrophe Theory (CCT). The catastrophe border is identified by fitting the CCT-based regional traffic flow model to explore the stable traffic flow changing to the instable state, as to provide a theoretical basis for traffic flow manage and control in disaster-affected areas, and to prevent the traffic flow being caught into disorder and congestion. Based on VISSIM simulator data by building simulation scenarios with and without sudden fire disaster in a Sudoku traffic network, the catastrophe border is identified as 439pcu/lane/h, 529pcu/lane/h, 377pcu/lane/h at 5s, 10s, 15s data collection interval respectively. The corresponding relative precision, which compares to the method of Capacity Assessment Approach (CAA), is 89.1%, 92.7% and 76.5% respectively. It means that 10s data collection interval would be the suitable data collection interval in catastrophe border identification and regional traffic flow control in high-density area under sudden fire disaster.

Predictive simulation of concurrent debris flow using only pre-disaster information has proven to be difficult as a result of problems in predicting the location of debris-flow initiation (i.e., slope failure). However, because catchment topography has concave characteristics, with all channels in a catchment joining each other as they flow downstream, it is possible to predict damage to downstream area using relatively inaccurate initiation points. Based on this, this paper presents methodologies employing debris-flow initiation points generated randomly using statistical slope failure prediction. A many-case simulation across numerous initiation points was performed to quantify the effect of slope-failure location in terms of deviations in the predicted water level and terrain deformation. It was found that the relative standard deviation diminished as the points approached the downstream area, indicating a location-based predictability effect.

The purpose of this study is to propose a consecutive manufacturing process system to secure the productivity of excellent STKN540B steel tube in the respect of economy and safety as the supporting material for mega structures such as building, bridge and ship. The components of consecutive manufacturing are press-bending, orbital auto welding and steel tube correction. By using STKN540B a high-strength steel material with low yield point that requires a special manufacturing process unlike other steel materials, an actual tube manufacturing is carried out at each stage in this experimental study. With this, the quality of steel tube and the efficiency of the manufacturing process are analyzed to draw out some points to improve in the future.

As time progresses and technology improves, biological data sets are continuously increasing in size. New methods and new implementations of existing methods are needed to keep pace with this increase. In this paper, we present a high performance computing(HPC)-capable implementation of Iterative Random Forest (iRF). This new implementation enables the explainable-AI eQTL analysis of SNP sets with over a million SNPs. Using this implementation we also present a new method, iRF Leave One Out Prediction (iRF-LOOP), for the creation of Predictive Expression Networks on the order of 40,000 genes or more. We compare the new implementation of iRF with the previous R version and analyze its time to completion on two of the world's fastest supercomputers Summit and Titan. We also show iRF-LOOP's ability to capture biologically significant results when creating Predictive Expression Networks. This new implementation of iRF will enable the analysis of biological data sets at scales that were previously not possible.

Prolonged high-intensity grinding can modify the crystal structure of solid substances and/or induce chemical reaction, which is referred to as mechanochemical reaction. Such reactions can exert positive influences on hydrometallurgical processes, therefore, many researchers have applied mechanochemical reactions for metals dissolution from minerals. The mechanism of mechanochemical reaction has been investigated using solid analyses and simulations. Structural changes caused by mechanochemical reaction are not yet sufficiently clarified because the ground samples are amorphous. The objective of this study was to analyze structural changes of cerianite in weathered residual rare earth ore by mechanochemical reduction. Structural change was analyzed by x-ray absorption near-edge structure and extended x-ray absorption fine structure analysis at the cerium L_III- and K-edges. These analyses revealed that the structural change of cerianite in this ore induced by mechanochemical reduction involved oxygen vacancy production. The process of the oxygen vacancy formation was closely coupled with the quantum effect of localization–delocalization of the 4f electron of cerium.

Low-frequency electron paramagnetic resonance (EPR) is used to extract the EPR parameter A-mid and support the approximate X-band value of g-mid for Ba(Co_yZn_1/3-yTa_2/3)O₃. Although cobalt hyperfine structure for the [+/−1/2> state is often unresolved at X-band or S-band, it is resolved in measurements on this compound. This allows for detailed analysis of the molecular orbital for the [+/−1/2> state, which is often the ground state. Moreover, this work shows that the EPR parameters for Co substituted into Zn compounds gives important insight into the properties of zinc binding sites.

We examine the mass balance of the glaciers in the Novaya Zemlya Archipelago, located in the Russian High Arctic using time series of time-variable gravity from the NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, laser altimetry data from the NASA Ice Cloud and land Elevation Satellite (ICESat) mission, and radar altimetry data from the ESA CryoSat-2 mission. We present a new algorithm for detecting changes in glacier elevation from these satellite altimetry data and evaluate its performance in the case Novaya Zemlya by comparing the results with GRACE. We find that the mass loss of Novaya Zemlya increased from 10±5 Gt/yr over 2003-2009 to 14±4 Gt/yr over 2010-2016, with a brief period of near mass balance between 2009 and 2011. The results are consistent across the gravimetric and altimetric methods. Furthermore, the analysis of elevation change from CryoSat-2 indicates that 60\% of the mass loss occurs at low elevation, where thinning rates are highest. We also find that marine-terminating glaciers in Novaya Zemlya are thinning significantly faster than land-terminating glaciers, which indicates an important role of ice dynamics of marine-terminating glaciers. We posit that the glacier changes have been caused by changes in atmospheric and ocean temperatures. We find that the increase in mass loss after 2010 is associated with a warming in air temperatures, which increased the surface melt rates. There is no enough information on the ocean temperature at the front of the glaciers to conclude on the role of the ocean, but we posit that the temperature of subsurface ocean waters must have increased during the observation period.

This paper aims to study the surface homogenization and integrity of Ti-6Al-4V alloy by longitudinal-torsional coupled ultrasonic vibration assisted ball-end milling. A method of continuous processing between the flat surface and freeform surface connection is proposed by using ultrasonic vibration assisted ball-end precision milling, during this process, it is not necessary to exchange the cutting tool. The way has been explored for changing the homogenization of surface on Ti-6Al-4V by ultrasonic vibration-assisted milling (UVAM). Cutting experiments employing three parameters, cutting speed, feed rate and depth of cut and two types of machining forms using ball-end milling with UVAM and conventional milling (CM) respectively. The high frequency cutting force, finished surface roughness, topography and residual stresses on the surface and tool wear have been measured by advanced instruments. Particularly, adopting the high frequency cutting force measurement system, it is concluded cutting force in ball-end milling decreased significantly using UVAM as against CM. Moreover, the surface roughness by UVAM with ball-end milling is much better than the CM at a high cutting speed. However, an opposite trend is observed at a low cutting speed. Especially, there is a steep decrease from Ra 0.828 μm average value at 4000 rpm to Ra 0.129 μm average value at 5000 rpm. At the same time, the homogenization of surface roughness and residual stresses decrease significantly in UVAM as compared to which in CM when taking the transversal-longitudinal ratio into consideration. Cutting experiments and measuring results are demonstrated the validity and feasibility of UVAM with ball-end milling, and this method enjoys significant advantages compared to CM process.

Viruses can infect a cell via one or both routes viz. cell-to-cell (c-c) or cell-free (c-f) . Pathogenesis studies of various viruses, including HIV, have shown that c-c transmission yields a significantly higher infection magnitude than the c-f route. Expectedly, potent antibodies inhibited c-f infection more efficiently than with c-cell transmission. To achieve a one-step, synchronous infection cycle that provides amplified infection, we have studied a consistent and efficient c-c HIV infection model since 1992. H9 cells persistently infected with HTLV-IIIB (H3B cells) and uninfected target CD4+ lymphocyte line (HuT78) were mixed in a ratio of 1:4 respectively. We have recently used this model to produce HIV designer antigens that have been shown to elicit monoclonal as well as polyclonal specific antibodies against novel epitopes that are formed post virus-cell engagement, but prior to fusion. The model can be extended for HIV neutralizing antibody assays or drug inhibitors against high multiplicity of infection.

Land-cover classification that uses very-high-resolution (VHR) remote sensing images is a topic of considerable interest. Although many classification methods have been developed, there is still room for improvements in the accuracy and usability of classification systems. In this paper, a novel post-processing approach based on a dual-adaptive majority voting strategy (D-AMVS) is proposed for improving the performance of initial classification maps. D-AMVS defines a strategy for refining each label of a classified map that is obtained by different classification methods from the same original image and fusing the different refined classification maps to generate a final classification result. The proposed D-AMVS contains three main blocks. 1) An adaptive region is generated by extending gradually the region around a central pixel based on two predefined parameters (T1 and T2) in order to utilize the spatial feature of ground targets in a VHR image. 2) For each classified map, the label of the central pixel is refined according to the majority voting rule within the adaptive region. This is defined as adaptive majority voting (AMV). Each initial classified map is refined in this manner pixel by pixel. 3) Finally, the refined classified maps are used to generate a final classification map, and the label of the central pixel in the final classification map is determined by applying AMV again. Each entire classified map is scanned and refined pixel by pixel based on the proposed D-AMVS. The accuracies of the proposed D-AMVS approach are investigated through two remote sensing images with high spatial resolutions of 1.0 and 1.3 m, respectively. Compared with the classical majority voting method and a relatively new post-processing method called general post-classification framework, the proposed D-AMVS can achieve a land-cover classification map with less noise and higher classification accuracies.

This article reports a novel and efficient method to synthesize graphene by thermal decomposition process. In this method, silicon carbide (SiC) thin films grown on Si(100) wafers with an AlN buffer layer were used as substrates. A CO₂ laser beam heating without vacuum or controlled atmosphere was applied for SiC thermal decomposition. The physical, chemical, morphological, and electrical properties of the laser-produced graphene were investigated for different laser energy densities. The results demonstrate that graphene was produced in form of small islands with quality, density and properties depending on the applied laser energy density. Furthermore, the produced graphene exhibits a sheet resistance characteristic similar to graphene grown on mono-crystalline SiC wafer, which indicates its potential for electronic device applications.

This paper presents a new high-efficiency-high-step-up based converter integrating two stype DC-DC Boost and Flyback coupled magnetic converter with recovery stage dedicated to smart HVDC distributed architecture in renewable energy production systems. Appropriate duty cycle ratio assumes that the recovery stage work with parallel charge and discharge to achieve high step-up voltage gain. Besides, the voltage stress on the main switch is reduced with a passive clamp circuit and thus, low on-state resistance Rdson of the main switch can be adopted to reduce conduction losses. The circuit is simple to control. As a final point of this research, the simulation and the prototype investigational results are presented to demonstrate the effectiveness of this proposed converter.

Background: Several preventive strategies to reduce dyslipidaemia, have been suggested of which dietary modification features as an important one. Addition of almonds in our daily diets has been proposed to beneficially impact the lipid profile. This review critically examines the available evidence assessing the effect of almonds on dyslipidaemia in the South Asian (particularly Indian) context. Methods: An extensive review comprising of epidemiological studies, clinical trials, meta-analyses and systematic reviews was conducted from published literature from across the world. Studies examining the effect of almonds on different aspects of dyslipidaemia viz. high LDL-C, low HDL-C, triglyceridaemia, high total cholesterol levels have been included. Results: Dyslipidaemia is a major risk factor for coronary heart disease and strategies to manage dyslipidaemia have been shown to reduce the incidence of CVD. Although there are proven pharmacological therapies to help manage this condition, there are not many nutritional interventions which can impact dyslipidaemia. Almonds have been shown to reduce LDL-C which is a known risk factor for CHD, in several studies and the effect of almonds has been well documented in systematic reviews and meta-analysis of clinical trials. Conclusions: Addition of almonds in the diet has been shown to not only to reduce LDL-C levels, but also to maintain HDL-C levels. This review informs about the use of this simple nutritional strategy which may help manage known major risk factors for heart disease such as high LDL-C and low HDL-C levels especially in the context of South Asians.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

The high radio frequency polarization imaging of non-thermal emission from active galactic nuclei (AGN) is a direct way to probe the magnetic field strength and structure in the immediate vicinity of supermassive black holes (SMBHs) and is crucial in testing the jet-launching scenario. To explore the the magnetic field configuration at the base of jets in blazars, we took advantage of the full polarization capabilities of the GMVA (Global Millimeter VLBI Array). With an angular resolution of ~50 micro-arcseconds at 86 GHz, one could reach scales down to ~900 Schwarzschild radii (for a 10^9 solar mass black hole). We present here the preliminary results of our study on the blazar BL Lac. Our results imply that on sub-mas scales the core and central jet of BL Lac is significantly polarized with two distinct regions of polarized intensity. We also noted a great morphological similarity between the 7mm/3mm VLBI images at very similar angular resolution.

High average power narrow-linewidth tunable solid-state lasers in the wavelength region between 2 to 3 μm are attractive light sources for many applications. This paper reports a narrow-linewidth widely-tunable laser system based on the polycrystalline Cr2+:ZnSe elements pumped by the repetitively-pulsed 2.1 µm Ho3+:YAG laser operating at the tens of kilohertz pulse rate. An advanced procedure of ZnSe-element doping and surface improvement was applied to increase the laser-induced damage threshold, which resulted in an increase of the output power of the Cr2+:ZnSe laser system. The high-average-power laser system comprised double master-oscillators and power amplifiers: Ho3+:YAG and Cr2+:ZnSe laser oscillators, and Ho3+:YAG and Cr2+:ZnSe power amplifiers. The output wavelength was widely tuned within 2.3-2.7 µm by an acousto-optical tunable filter inside the Cr2+:ZnSe master oscillator cavity. The narrow-linewidth operation at the pulse repetition rate of 20-40 kHz in a high-quality beam with the average output power up to 9.7 W was demonstrated.

Accurate knowledge of flow rates is essential for hydraulic systems, as it allows for calculating hydraulic power when combined with pressure measurements. This data is helpful in applications such as predictive maintenance. However, most flow rate sensors in fluid power systems operate invasively, disrupting the flow and producing inaccurate results, particularly for transient flow conditions. A common approach is calculating the flow rate using the pressure difference along a pipeline based on the Hagen-Poiseuille law. However, this method is limited to laminar, steady, incompressible flow. This paper presents a novel soft sensor with an analytical model for transient, compressible pipe flow based on two pressure signals, thus no actual volumetric flow rate sensor is required. The model is derived by solving the fundamental fluid equations in the Laplace domain and converting the solution back to the time domain to obtain a physical representation. The relationship between the pressure difference signal and flow rate is derived using the four-pole theorem. The resulting analytical solution, including a convolution integral with a weighting function, shows high accuracy for transient and steady flows. This new equation enables the development of a soft sensor capable of non-invasive flow rate measurements for various pipe flow conditions.

Precise monitoring of NOx concentrations in nitric oxide delivery systems is crucial to ensure the safety and well-being of patients undergoing inhaled nitric oxide (iNO) therapy for pulmonary arterial hypertension. Currently, NOx sensing in commercialized iNO instruments predominantly relies on chemiluminescence sensors, which not only drives up costs but also limits their portability. Herein, we developed solid state gas sensors utilizing Ni-based sensing materials for effectively tracking the level of NO and NO2 in NO delivery system. These sensors comprised of NiO-SE or (NiFe2O4+30 wt.% Fe2O3)-SE vs. Mn-based RE demonstrated high selectivity towards 100 ppm NO under the interference of 10 ppm NO2 or 3 ppm NO2 under the interference of 100 ppm NO, respectively. Meanwhile, excellent stability, repeatability, and humidity resistance were also verified for proposed sensors. Sensing mechanisms were thoroughly investigated through assessments of adsorption capabilities and electrochemical reactivity. It turns out that the superior electrochemical reactivity of NiO towards NO, alongside with the NO2 favorable adsorption characteristics of (NiFe2O4 + 30 wt.% Fe2O3), is the primary reason for the high selectivity to NOx. These findings indicate a bright future for the application of these NOx sensors in innovative iNO treatment technologies.

Understanding hydrological processes is vital for managing phenomena such as floods and droughts and incorporating them into planning processes, as urbanization and the consequent increase in impervious surfaces have reduced natural landscapes, negatively impacting water infiltration and increasing surface runoff, which has led to more frequent urban floods. Recent research highlights the growing need to develop hydrological solutions at increasingly specific urban scales, emphasizing the importance of data collection, modeling, and micro-basin delineation, which are crucial for analyzing runoff behavior, sediment transport, and water quality. Topographical data is fundamental for hydrological analysis and can be collected through on-site surveys using tools such as total stations and GPS. However, these methods can be costly and time-consuming. Alternatively, remote sensing techniques, such as Digital Elevation Models (DEMs), offer cost-effective and efficient ways to gather topographical information. DEMs, often combined with Geographic Information Systems (GIS), represent elevation data and are widely available for free from various global agencies. These tools are invaluable in hydrological studies, as they help to model basin morphology and surface runoff patterns accurately. However, although there are models with global coverage, their resolutions are only occasionally optimal for hydrographic analysis. Additionally, some countries have regulatory agencies and institutions that generate geographic information, including DEMs, from national to local scales.

Flexible humidity sensors (FHS) with fast response and durability to high-humidity environment are highly desirable for practical applications. Herein, an FHS based on crosslinked sodium alginate (SA) and MXene was fabricated, which exhibited high sensitivity (impedance varied from 107 to 105 Ω between 10% and 90% RH), good selectivity, prompt response (response/recover time of 4 s/11 s), high sensing linearity (R2 = 0.992) on a semi-logarithmic scale, relatively small hysteresis (~5% RH), good repeatability, and good resistance to high humid environment (negligible change in sensing properties after placed in 98% RH over 24 h). It is proposed that the formation of crosslinking structure of SA and introduction of MXene with good conductivity and high specific surface area contributed to the high performance of the composite FHS. Moreover, the FHS could promptly differentiate respiration status, recognize speech and measure fingertip movement, indicating potentials in breath monitoring and non-contact human-machine interactions. This work provides guidance for developing advanced flexible sensors with wide application scope in wearable electronics.

Carbon fiber-reinforced polymer (CFRP), noted for its outstanding properties including high specific strength and superior fatigue resistance, is increasingly employed in aerospace and other demanding applications. This study investigates the interactions between CFRP composites and high-energy lasers (HEL), with continuous wave laser powers reaching up to 120 kW. A novel automated sample exchange system, operated by a robotic arm, minimizes human exposure while enabling a sequence of targeted laser tests. High-speed imaging captures the rapid expansion of a plume consisting of hot gases and dust particles during the experiment. The research significantly advances empirical models by systematically examining the relationship between laser power, perforation times, and ablation rates. It demonstrates scalable predictions for the effects of high-energy laser radiation. Detailed examination of the damaged samples, both visually and via micro-focused computed X-ray tomography, offers insights into heat distribution and ablation dynamics, highlighting the anisotropic thermal properties of CFRP. Compression-after-impact (CAI) tests further assess the residual strength of the irradiated samples, enhancing the understanding of CFRP’s structural integrity post-irradiation. Collectively, these tests improve the knowledge of the thermal and mechanical behavior of CFRP under extreme irradiation conditions. The findings not only contribute to predictive modeling of CFRP's response to laser irradiation but also enhance the scalability of these models to higher laser powers, providing robust tools for predicting material behavior in high-performance settings.

The development of solar energy on a regional scale necessitates a thorough understanding of available resources. Cuba, facing prolonged economic, environmental, and energy crises, urgently needs to enhance its sustainability through solar energy. While solar resource mapping is widespread, Cuba lacks extensive field measurements, often relying on models that may not be ideally suited for large regions like Matanzas province. Spanning over 12,000 km² with nearly 150 km between its northern and southern extremes, Matanzas presents challenges for high-resolution solar mapping. This study introduces a methodology that integrates various methods and databases to achieve maximum resolution in the resulting solar map. The approach is designed for large areas where conventional high-resolution models fall short. By optimizing calculation times and parameterizing the entire surface latitudinally, a high-resolution solar resource map for Matanzas has been developed. This map significantly enhances the understanding of solar resources in Cuba and proposes new methodologies for analyzing solar potential in similarly large regions.

We investigated the effect of 0.6 MeV proton irradiation on the superconducting and normal state properties of thin-film YBa2Cu3O7−δ superconductors. A thin-film YBCO superconductor (≈ 567 nm thick) was subject to a series of proton irradiations with a total fluence of 7.6×1016p/cm2. Upon irradiation, Tc was drastically decreased from 89.3 K towards zero with a corresponding increase in its normal state resistivity above Tc. This increase in resistivity which indicates the increase of defects inside the thin-film sample can be converted to the dimensionless scattering rate. We found that the relation between Tc and dimensionless scattering rate obtained during proton irradiation approximates the generalized d-wave Abrikosov-Gor’kov theory better than the previous results obtained from electron irradiations. This is an unexpected result since the electron irradiation is known to be most effective to suppress superconductivity over other heavier ion irradiations such as proton irradiation. It suggests that the type of defects created by proton irradiation evolves from cascade defects (in bulk single crystals) to point-like defects (in thin-film single crystals) as the thickness decreases.

The nonlinear dynamics exhibited by aircraft flying at high angle of attack (AOA) pose great challenges to the design of flight control. The control design based on nonlinear dynamic inversion (NDI) is to reversely find the required control input based on the current nonlinear dynamics of the aircraft and the control objectives to be achieved. Since it is derived from the nonlinear dynamics of the aircraft, a single NDI controller can cover the entire flight envelope without the need for controller switching or gain scheduling. This paper employs the layered structure of the flight control loop to implement the NDI controller through the combination of aerodynamic control and thrust vectoring control (TVC). The resulting NDI controller is applied to an experimental F-16 installed with TVC to verify its high AOA maneuverability in the post-stall region. The verification simulation shows that the experimental F-16 under the NDI control can effectively track the high AOA command and successfully demonstrate the Herbst maneuver by performing the heading reversal with 70° AOA.

This study explores the intricacies of supplier relationships and inventory optimization within high-technology industries, offering a comprehensive analysis of the strategic imperatives and operational challenges faced by firms in these sectors. By adopting a qualitative research methodology involving semi-structured interviews with supply chain professionals and documentary analysis, the study provides in-depth insights into the evolving dynamics of supply chain management. Findings reveal a marked shift towards collaborative and strategic supplier relationships, characterized by trust, transparency, and joint innovation initiatives. These partnerships are essential for enhancing operational efficiency, driving product development, and navigating market uncertainties. Additionally, the research underscores the critical role of advanced technologies, such as artificial intelligence and the Internet of Things, in optimizing inventory levels and improving supply chain visibility. The integration of these technologies facilitates precise demand forecasting and proactive inventory management, thereby reducing costs and enhancing service levels. However, the study also highlights significant challenges, including geopolitical uncertainties, supply chain disruptions, and cultural barriers, which necessitate robust risk management strategies and adaptive supply chain practices. Strategic implications for organizational leaders and policymakers include the need to invest in supplier development, embrace digital transformation, and enhance risk management frameworks to build resilient and agile supply chains. This study contributes valuable insights into the complex interplay between supplier relationships, inventory optimization, and technological integration in high-technology industries, offering actionable recommendations for practitioners and researchers seeking to drive innovation and maintain competitiveness in a dynamic global marketplace.

Onions are known not only for their culinary importance but also for their nutritional and health-promoting properties. Both properties are closely linked to its content of organosulfur compounds, which account for up to 5% of the dry weight of an onion. Given the importance of these compounds, suitable analytical methods are required for their study. Two techniques should be highlighted in this context: gas chromatography coupled to mass spectrometry (GC-MS), and liquid chromatography coupled to mass spectrometry (LC-MS). In this study, eight different onion varieties were analyzed using two distinct analytical techniques: direct thermal desorption–gas chromatography-mass spectrometry (DTD-GC-MS) and high-resolution mass spectrometry (HRMS) on an LC-ESI-QqTOF instrument. Each method identified 18 different organosulfur compounds, with LC-HRMS targeting non-volatile compounds, such as cysteine sulfoxides, and GC-MS targeting volatiles, such as disulfides and trisulfides. The results obtained were studied using Pearson correlations and principal component analysis. No precise correlation was found between the initial organosulfur compounds in onions and their hydrolysates. Consequently, although GC is one of the most employed techniques in the scientific literature, the use of LC-HRMS or a combination of both techniques may offer a more comprehensive and accurate description of the metabolomic profile of onions.

Recently, research on ultra-high-performance concrete (UHPC) with the characteristics of ultra-high strength, high toughness, and high durability has been actively conducted from materials to actual structural applications. However, research on experimental methods that reflect the unique characteristics of UHPC, which are different from those of normal concrete, is insufficient. To solve the difficulties in applying the compressive creep test method for normal concrete to UHPC and to verify the validity of the recently proposed ASTM C 1856 standard test method, this study performed compressive creep tests on UHPC with variables of specimen size, sustained load intensity, fiber length, and strain measuring method. Two types of cylindrical specimens of ϕ100 × 200 mm and ϕ75 × 150 mm were used for a specimen size variable. The sustained load intensities of 10% to 40% based on the specified compressive strength of 150 MPa were applied. Two types of steel fiber lengths of 13 mm and 19.5 mm in the UHPC mix were used as a variable, and three strain measuring methods of the embedded strain gauge method, the attached strain gauge method, and the strain meter with stud measured the change in length of the UHPC specimens. The experimental results showed that the strain meter method using the standard rod had limitations due to the error in the verification process using the standard rod and the observation error of the measurer, and the sustained load intensity is preferable to 15% to 40% of the actual compressive strength. It was found that it is possible to perform a compressive creep test for UHPC using a specimen with a size of ϕ75 mm or more, and the fiber length did not affect the creep behavior of UHPC up to 19.5 mm. As a result of comparing the UHPC creep test results with the creep prediction model, the B3 model was found to most accurately predict the UHPC creep behavior. The creep coefficient pattern of the B3 model was very similar to the measured results, and well reflected the effects of the mixing ratio and compressive strength of UHPC.

At present, farmland abandonment（FA）is a severe phenomenon in China, imposing a serious restriction on agricultural production. In this context, it is of great significance to explore the logical relationship between high-standard farmland construction (HSFC) and FA to optimize land resource allocation and guarantee national food security. Based on 838 samples of farmers in the main rice production area of the Yangtze River Basin in China, this paper employs the Tobit model, the mediating effect model, and the moderated mediating effect model to analyze the impact of HSFC on FA at the micro level. The results show that (1) HSFC inhibits FA, and FA proportion decreases by 1.14% for every 1% increase in HSFC proportion, and the robustness test and endogeneity treatment also yield consistent conclusions. (2) Agricultural socialization services (ASS) play a positive mediating role in the influence path. HSFC promotes farmers' purchase of ASS, which in turn inhibits FA. (3) The agricultural labor transfer distance (ALTD) plays a positive moderating role in the relationship between HSFC and FA. The farther the distance, the more likely HSFC can promote farmers' purchase of ASS and inhibit FA. The results provide enlightenment on how to precisely implement HSFC policy, that is, to inhibit FA by improving the construction of high-standard farmland and the post-construction management as well as protection system. Moreover, this study helps guiding the development of ASS and optimizing the institutional environment for agricultural labor transfer, creating conditions for agricultural scale management.

High resolution information on nucleotide arrangement in the genome of any or-ganism is critical to understand its genetic makeup, function, and evolutionary his-tory. For years, DNA sequencing has provided crucial breakthroughs in the field of genomics and molecular biology. With the advent of technology, Next Generation Sequencing has now transformed the whole genome sequencing prospects, thus unveiling the novel and interesting features of an organism genome that can behold. Next generation sequencing platforms offer realistic approach to identify and anal-yses whole genome with high throughput, accuracy, scalability in a very short time span. Information obtained can be further used in improving our existing healthcare systems, designing novel and personalized therapeutic modules, making the envi-ronment sustainable and proactively preparing ourselves for future pandemics and outbreaks. This article discusses the various NGS technologies and approaches, their advantages, drawbacks, and futuristic usage in different fields. Though still in nascent stages and marred with flaws, with ongoing advancement, NGS will indeed have promising impacts in the future.

In the current complex and uncertain macroeconomic situation, improving the inherent resilience of the new energy vehicle industry chain is the key to effectively addressing various risks and challenges, and achieving dynamic balance between high-quality industrial development and industrial chain security. Based on the basic concept of resilience and the actual situation of new energy vehicle industry chain development, this study constructs a comprehensive evaluation index system for the resilience of the new energy vehicle industry chain, which includes four dimensional first-level indicators of coping resistance, adaptive resilience, autonomous control and leading competitiveness. In addition, it is measured by combining the data related to the new energy vehicle industry chain in Changzhou City. Our study shows that the situation on the new energy vehicle industry chain is complicated, and the comprehensive evaluation index system is more favorable for evaluating its resilience level.

The state detection of power cable is very important to ensure the reliability of power supply. Traditional sensors are mostly based on electric field detection, the operation is complex, and its efficiency needs to be improved. This paper optimizes the design and development of the magnetic field detection sensor for AC power cables. Firstly, through the establishment of the magnetic field sensor model, it is determined that permalloy is the material of the magnetic core, the optimal aspect ratio of the magnetic core is 20, and the ratio of coil length to core length is 0.3. Secondly, the coil simulation model is established, and it is determined that the optimal number of turns of the coil is 11000 turns, the diameter of the enamelled copper wire is 0.08mm, and the equivalent magnetic field noise of the sensor is 0.06pT. Finally, the amplifying circuit based on negative magnetic flux feedback is designed and the sensor is assembled, and the experimental circuit is built for sensitivity test. the results show that the sensitivity of the magnetic field sensor is 327.6mV/μT. The sensor designed in this paper has the advantages of small size, high sensitivity, easy to carry and high reliability.

Abstract Cholesterol has ruled the history of atherosclerotic cardiovascular diseases (CVD) for decades, and the transport of cholesterol by lipoproteins has become a cornerstone of our view of etiology of the disease. Discovery of the lipoprotein-specific transport of lipid oxidation products (LOP) has opened a new and exciting area in research of CVD by revealing strong connections between atherogenic LOP, lipoprotein transport functions and CVD. This review goes through the evidence in support of the lipoprotein-specific LOP transport and speculates of possible consequences of the proposed role of lipoprotein LOP transport as a risk factor. Association of lipoprotein LOP with known risk factors of CVD are largely parallel with those of cholesterol, and due to the common transport and cellular intake mechanisms the elucidation of independent effects of either cholesterol or LOP is difficult. Yet, unlike cholesterol, LOP can directly initiate and boost atherogenic processes. It therefore appears inevitable that increasing knowledge of the lipoprotein-specific LOP transport will affect the present view of the role of cholesterol in aetiology and as a risk factor of CVD.

High-grade gliomas are extremely fatal tumors, marked by severe hypoxia and therapeutic resistance. Autophagy is a cellular degradative process that can be activated by hypoxia, ultimately resulting in tumor advancement and chemo-resistance. Our study aimed to examine the link between autophagy markers expression in low (LGG) and high-grade gliomas (HGG). In 39 glioma cases, we assessed protein expression of autophagy markers LC3B, p62, and DRAM by immunohistochemistry (IHC) and mRNA expression of autophagy genes; PI3K, AKT, m-TOR, PTEN, ULK1, ULK2, UVRAG, Beclin 1 and VPS34 using RT-qPCR. Livak’s method was used to analyze the relative changes in gene expression and multi-variate Anova test and Spearman's correlation tests were performed for statistical significance. LC3B, p62, and DRAM expression were positive in 64.1%, 51.3%, and 28.2% of glioma cases respectively. The expression of LC3B and p62 was notably higher in HGG compared to LGG. VPS34 exhibited a significant differential expression and increased fold change and demonstrated strong positive correlations with Beclin1 (rs=0.768), UVRAG (rs=0.802), and ULK2 (rs=0.786) in HGG compared to LGG, thus highlighting the potential link between autophagy and glioma progression. We Provide preliminary data for functional analysis of autophagy using cell culture model and to identify potential targets for therapeutic interventions

The oxidative coupling of methane (OCM) to produce ethane and ethylene (C2 compounds) as platform chemicals involves complex chemistry with reactions both in the gas phase and on the catalyst surface, resulting in a distribution of products at the expense of C2 selectivity. This work uses experimental data from a variety of mixed metal oxides on supports at different reaction conditions (temperature, contact time, and reactant flow rates) to train a random forest regressor that predicts methane conversion and C2 selectivity (key performance indicators (KPIs)), and deploys it to locate optimal conditions that maximize C2 yield for a catalyst. Investigating the regressor interpretability via feature importance reveals that the choice of metals and support are crucial to C2 selectivity predictions, while the predictions of methane conversion are driven by the reaction conditions. The machine learning (ML) regressor is used as a surrogate to develop performance curves for each of the catalysts via a multi-objective optimization routine that seeks to maximize the KPIs in the decision space of reaction conditions, is seen to locate optimal conditions at which the maximum C2 yields for catalysts are predicted to be 15%, higher on average. Analyzing the catalysts in the space of their performance curves with respect to a popular OCM catalyst, Mn-Na2WO4/SiO2, reveals distinct patterns based on intrinsic properties of metals and supports. Further, the decision space with catalyst descriptors and reaction conditions is optimized for high C2 yields using the ML surrogate, in a static multi-objective optimization routine, and an adaptive Bayesian routine, where the latter was found to have a wider field focus in proposing catalyst formulations and conditions. Transition metal oxides on a variety of supports were proposed but not their lanthanide oxide counterparts.

In order to reveal the frost heaving mechanism of void water behind the lining of high-speed railway tunnels in cold regions，the voids were first classified according to the positional relationship between voids and waterproof panels，and then the water supply and discharge conditions of different types of voids were investigated，then the influence of the excretion conditions on the frost heave force was experimentally studied. Based on these conditions，circular wedge-shaped and flying saucer-shaped void freezing models were established to analyze the evolution process of accumulated water frost heave. Then，according to the relative position of the excretion channel and the void，the excretion coefficient was introduced，and the calculation method of the frost heaving force of the voided water was proposed，and the influencing factors and laws of the frost-heave force were revealed. The results are shown as follows: 1) The blockage of the excretion channel will lead to the generation of frost heaving force; 2) The freezing and thawing process of the water within the cavity develops from the thinnest part of the void edge to the thicker part，and the process of frost heave-thaw，water replenishment-re-freeze heave of the water within the cavity leads to greater and greater frost heave force; 3) The frost-heaving force of the water within cavity is controlled by the void height and the position of the excretion channel. The larger the cavity height is or the closer the excretion channel is to the bottom surface of the void，the greater the frost-heave force is.

This work deals with the analysis of phase composition of sintered Ti-Al-C composite materials under high voltage electrical discharge. The samples of Ti-Al-C powder composites were tested by SEM, Raman spectroscopy and XRD. It was determined that the treatment of the powder by high voltage electrical discharge (HVED) and further sintering at high temperatures using the method of spark plasma sintering (SPS) encourages the formation of the intermetallic reinforcing phases, carbides and different nanocarbon structures like graphene and fullerenes, as well as pure graphite. Intermetallic phases and nanocarbon structures improve mechanical and physical properties of the composites. By using experimental methods mentioned above, the phase composition of Ti-Al-C powder composites obtained at different sintering temperatures was determined.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

Estrogens play a protective role during early life stages. However, endogenous 17β-estradiol (E2) can accelerate atherosclerosis progression in low-grade inflammatory conditions like established atherosclerosis. Our single-center cohort study assessed sex-specific associations of gonadal hormones with oxidative stress, inflammation, and myocardial injury markers in 111 patients (37% women) diagnosed with acute myocardial infarction (MI) between July 2011 and December 2013. Blood samples were collected within 48 hours of symptom onset, and we measured sex steroids (E2, total testosterone [T]), oxidized low-density lipoproteins, high-sensitive C-reactive protein (CRP), white blood cell counts (WBC), and cardiac enzymes (creatine kinase [CK], the CK Muscle-Brain fraction [CK-MB], and high-sensitive troponin T [hsTnT]). The SYNTAX score gauged coronary disease severity from coronary angiography results. In men with acute MI, peak cardiac enzyme levels were predicted by post-percutaneous coronary intervention (PCI) E2 plasma levels (OR 1.011, p=0.047 - CK; OR 1.018, p=0.013 - CK- MB; OR 1.019, p=0.005 - TnT), peak WBC count (OR 1.487, p=0.015 - CK ; OR 1,709, p=0,005 - CK- MB; OR 1.391, p=0.012 - TnT), and peak CRP plasma levels (OR 1.040, p=0.033 - CK; OR 1.024, p=0.029 - CK-MB; OR 1.063, p=0.006 - TnT). T levels and E2/T ratio were associated with post-PCI CRP in these men (OR 0.980, p = 0.024 - T, OR 1.010, p = 0.076 - CRP). For women, peak WBC was a marker of highest testosterone (OR 1.348, p = 0.062), and only WBC was a significant indicator of myocardial injury extent (OR 1.426, p=0.039 - CK; OR 1.384, p=0.036 - CK-MB; OR 1.299, p=0.048 - TnT). During acute MI, elevated endogenous estradiol levels correlate with myocardial necrosis severity in men, while in women, increased leukocyte levels indicate acute myocardial damage. Elevated plasma T is associated with increased WBC in women. In men, post-PCI plasma CRP specifically indicates endogenous T levels and E2/T ratio during the acute phase.

Abstract: Microflora play an important role in the fermentation of blueberry wine, influencing the flavor and nutrient formation. Commercial yeasts give blueberry wines an average flavor profile that does not highlight the specific aroma and origin of the blueberry. In the present study, ITS1-ITS2 region sequencing analysis was performed using Illumina MiSeq high-throughput technology to sequence fermented blueberry wine samples of three Vaccinium ashei varieties, Gardenblue, Powderblue, and Britewell, from the Majiang appellation in Guizhou province to analyze the trends of fungal communities and the diversity of compositional structures in different periods of blueberry wine fermentation. The study's results revealed that 114 genera from 7 phyla were detected in 9 samples from different fermentation periods of blueberry wine. The main fungal phyla were Ascomycota, Basidiomycota, Kickxellomycota, Chytridiomycota, and Olpidiomycota. The main fungal genera were Hanseniaspora, Saccharomyces, unidentified, Aureobasidium, Penicillium, Mortierella, Colletotrichum, etc. Hanseniaspora was dominant in the pre-fermentation stage of blueberry wine, accounting for more than 82%; Saccharomyces was the dominant genera in the middle and late fermentation stages of blueberry wine, with Saccharomyces accounting for more than 72% in the middle of fermentation and 93% in the late fermentation stage. This study screened indigenous flora for the natural fermentation of blueberry wine in the Majiang production area of Guizhou, improved the flavor substances of the blueberry wine, highlighted the characteristics of the production area, and made the blueberry wine have the characteristic flavor of the production area.

Curcumin, a nontoxic and cheap natural medicine, has high therapeutic efficacy for many diseases including diabetes and cancers. Unfortunately, its exceedingly low water-solubility and rapid degradation in the body severely limit its bioavailability. In this work, we prepare a series of biocompatible poly(vinyl anisole)@nonlinear poly(ethylene glycol) (PVAS@PEG) core-shell nanogels with different PEG gel shell thickness to provide high water solubility, good stability, and controllable sustained release of curcumin. The PVAS nanogel core is designed to attract and store curcumin molecules for high drug loading capacity and the hydrophilic nonlinear PEG gel shell is designed to offer water dispersibility and thermo-responsive drug release. The obtained nanogels are monodispersed in spherical shape with clear core-shell morphology. The size and shell thickness of the nanogels can be easily controlled by changing the core-shell precursor feeding ratios. The optimized PVAS@PEG nanogels display a high curcumin loading capacity of 38.0 wt%. The nanogels can stabilize the curcumin from degradation at pH =7.4 and release the curcumin in response to heat in the physiologically important temperature range. The nanogels can enter cells effectively and exhibit negligible cytotoxicity to both the B16F10 and HL-7702 cells at a concentration up to 2.3 mg/mL. Such designed PVAS@PEG nanogels have a great potential to be used for delicate drug delivery.

Mallard (Anas platyrhynchos) are currently one of the most popular species in rare bird breeding in several southern provinces of China, but there are very few studies on the gut microbial communities of domestic and wild mallards. In this study, 16S rRNA gene high-throughput sequencing technology was used to compare the composition and diversity of gut microbial communities in domestic and wild mallards. Alpha diversity analysis revealed significant differences in the gut microbial communities of domestic and wild mallards. Beta diversity analysis showed that the two groups of stool samples were mostly separated on the principal coordinate analysis (PCOA) plot. In domestic mallards, Firmicutes (67.97%) was the most abundant bacterial phylum, followed by Proteobacteria (24.48%), Bacteroidetes (3.13%), Fusobacteria (2.21%), and Actinobacteria (1.10%). The dominant bacterial phyla in wild mallards were Firmicutes (79.02%), Proteobacteria (12.85%), Fusobacteria (3.37%), and Bacteroidetes (2.79%). At the genus level, a total of 10 dominant genera (Streptococcus, Enterococcus, Clostridium, Lactobacillus, Soilbacillus, Bacillus, Acinetobacter, Comamonas, Shigella, and Cetobacterium) with an average relative abundance greater than 1% were detected in the fecal samples of both groups. The average relative abundance of five potential pathogens (Streptococcus, Enterococcus, Acinetobacter, Comamonas, and Shigella) was higher in domestic mallards than in wild mallards. The enrichment of pathogenic bacteria in the intestinal tract of domestic mallards should be of sufficient concern.

Mallard (Anas platyrhynchos) are currently one of the most popular species in rare bird breeding in several southern provinces of China, but there are very few studies on the gut microbial communities of domestic and wild mallards. In this study, 16S rRNA gene high-throughput sequencing technology was used to compare the composition and diversity of gut microbial communities in domestic and wild mallards. Alpha diversity analysis revealed significant differences in the gut microbial communities of domestic and wild mallards. Beta diversity analysis showed that the two groups of stool samples were mostly separated on the principal coordinate analysis (PCOA) plot. In domestic mallards, Firmicutes (67.97%) was the most abundant bacterial phylum, followed by Proteobacteria (24.48%), Bacteroidetes (3.13%), Fusobacteria (2.21%), and Actinobacteria (1.10%). The dominant bacterial phyla in wild mallards were Firmicutes (79.02%), Proteobacteria (12.85%), Fusobacteria (3.37%), and Bacteroidetes (2.79%). At the genus level, a total of 10 dominant genera (Streptococcus, Enterococcus, Clostridium, Lactobacillus, Soilbacillus, Bacillus, Acinetobacter, Comamonas, Shigella, and Cetobacterium) with an average relative abundance greater than 1% were detected in the fecal samples of both groups. The average relative abundance of five potential pathogens (Streptococcus, Enterococcus, Acinetobacter, Comamonas, and Shigella) was higher in domestic mallards than in wild mallards. The enrichment of pathogenic bacteria in the intestinal tract of domestic mallards should be of sufficient concern.

A two-layer Fe-Cr-Al-Zr surface alloy was synthesized on a zirconium substrate by magnetron sputtering and subsequent low-energy high-current electron-beam (LEHCEB) processing. Thicknesses of the top Fe69Cr20Al11 (at.%) relatively large-grained (~1 µm) and transition Fe-Zr Cr-Al amorphous layers were about 0.7 and 0.6 µm, respectively. In turn, the amorphous layer consisted of two Fe64–54Zr8–22Cr21–17Al8–7 and Fe40–16Zr42–78Cr12–4Al6–2 (at.%) sublayers, differing in both zirconium and iron concentrations in wide ranges, which were separated by another nanocrystalline interlayer. The Fe-Cr-Al-Zr surface alloy serve as a diffusion barrier, preventing interaction of the zirconium substrate with oxygen from an environment. It was thermally stable up to ≈1173 K.

Existing research lacks studies that explore the impact of government fiscal support on the high-quality development of regional economy and society from the perspective of livelihood-based infrastructure construction. The investigation in this paper explores the economic and social effects of government fiscal support behavior from the perspective of livelihood infrastructure construction. On the basis of the TOPSIS-Entropy Method, this paper constructs an evaluation indicator that closely conforms to the denotation and requirements of high-quality development and then carries out empirical regressions in combination with government expenditure on people's livelihood to verify the theoretical hypothesis, whose transmission mechanism and moderating effect are further empirically tested. The results reveal that increasing government expenditure on people's livelihoods can effectively improve regional high-quality development, but the marginal improvement degree varies with different periods and locations. The mechanism test proves that the regional consumption level plays a significant part in the mediating effect, accounting for 24.27% of the total effect. Urbanization is also the critical impetus for regional high-quality development and positively moderates the promotion effect of people's livelihood fiscal expenditure. Our study presents a theoretical basis and policy inspiration for improving residents' quality of life and welfare level and improving people's livelihood in the midst of high-quality economic development.

Natural image matting is an essential technique for image processing that enables various applications, such as image synthesis, video editing, and target tracking. However, the existing image matting methods may fail to produce satisfactory results when computing resources are limited. Sampling-based methods can reduce the dimensionality of the decision space and therefore reduce computational resources by employing different sampling strategies. While these approaches reduce computational consumption, they may miss an optimal pixel pair when the number of available high-quality pixel pairs is limited. To address this shortcoming, we propose a novel multi-criterion sampling strategy that avoids missing high-quality pixel pairs by incorporating multi-range pixel pair sampling and high-quality samples selection method. This strategy is employed to develop a multi-criterion matting algorithm via Gaussian process, which searches for the optimal pixel pair by using the Gaussian process fitting model instead of solving the original pixel pair objective function. Experimental results demonstrate that our proposed algorithm outperforms other methods even with 1% computing resources, and achieves alpha matte results comparable to those yielded by the state-of-the-art optimization algorithms.

This study aims at better understanding the damage and fracture kinetics in flax fibres elements at both the unitary and bundle scales using an experimental setup allowing optical observation at high recording rate in the course of tensile loading. Defects issues from flax unitary fibre extraction are quantitated using polarized light microscopy. Tensile loading is conducted according to a particular setup adapted to fibres of 10 to 20 µm in diameter and 10 mm in length. Optical recording using high speed camera is performed during loading up to the failure at acquisition speed ranging from 108,000 to 270,000 frames per second. Crack initiation in polymer layers of fibre elements, propagation as well as damage mechanisms are captured. The results show different failure scenarios depending on the fibre element nature. In particular, fractured fibres underline either a fully transverse failure propagation or a combination of transverse and longitudinal cracking with different balances. Image recordings with high time resolution down to 3.7 μs suggest unstable system and transverse crack speed higher than 4 m/s and a slower propagation for longitudinal crack deviation.

Background: Although metastatic GCT is highly curable with initial cisplatin-based chemotherapy (CT), 20-30% of patients relapse. Salvage CT options include conventional (CDCT) and high dose chemotherapy (HDCT), however definitive comparative data remains lacking. We aimed to characterize the contemporary practice patterns of salvage CT across Canada. Methods: We conducted a 30-question online survey for Canadian medical and hematological oncologists with experience in treating GCT, assessing treatment availability, patient selection, and management strategies used for relapsed GCT patients. Results: Respondents included 30 staff; from 18 cancer centers across provinces. The most common CDCT regimens used were TIP (64%) and VIP (25%). HDCT was available for (70%) in 13 centers. HDCT regimen used included carboplatin and etoposide for 2 cycles (76% in 7 centers), 3 cycles (6% in two centers), and the TICE protocol (11%, in 2 centers). “Bridging” CDCT was used by 65% respondents. Post HDCT treatments considered include surgical resection for residual disease (87.5%), maintenance etoposide (6.3%) and sur-veillance only (6.3%). Conclusions: HDCT is the most commonly used GCT salvage strategy in Canada. Significant differences exist in the treatment availability, selection and delivery of HDCT, highlighting the need for standardization of care for patients with relapsed testicular GCT.

Large-area nanostructuring of glasses using intense laser beam remains a difficult task due to the extreme non-linear absorption of the laser energy by the material. Precise optimization of the process parameters is essential for fabricating nanostructures with large area coverage. In this study, we report the findings on creating high spatial frequency LIPSS (HSFL) on borosilicate glass through direct laser writing, using a femtosecond laser with a wavelength λ = 800 nm, pulse duration τ = 35 fs, and repetition frequency frep = 1 kHz. The orientation of the HSFL was found to be parallel to the electric field vector. We measured the single pulse ablation threshold (Fth=3.87±0.26 J/cm2) and incubation factor (S=0.68±0.03) of Borosilicate glasses for precise control for large area surface structuring. Single-spot experiments indicate that uniform LIPSS formation is limited by melt formation inside the irradiated area for higher fluence and a larger number of irradiated laser pulses. The orientation of the scan axis with the laser beam polarization is found to be significantly influencing the uniformity of the large area processing. We found that the orientation of the scan axis with the laser beam polarization significantly affects the uniformity of large-area processing, with redeposition and melt formation being higher when the scan axis is perpendicular to the laser beam polarization. Large-area processing of the borosilicate glass surface is done by line-by-line scanning over the surface with a scan orientation parallel to the laser beam polarization. The optical characterization reveals that the transmittance and reflectance of the borosilicate glass decreased significantly after processing. Also, the wettability of the surface has been changed from hydrophilic to super hydrophilic after processing. These chemical contamination-free and uniformly distributed structures have potential applications in optics, microfluidics, photovoltaics, and biomaterials.

This paper introduces a method to achieve optimal Gaussian estimation even when operating with low precision numerical representations of the full covariance matrix, such as 16-bit integer or 32-bit single precision formats, instead of more expensive double precision floating point representations (64 bits). The approximation's numerical error is accurately estimated in a conservative manner, resulting in minimal covariance inflation. When combined with a compressed estimator like the GCKF (Global Compressed Kalman Filter), which performs global updates at low frequency, this approach produces estimates that are nearly identical to the optimal ones. The deviation between the results obtained using this new approach and those obtained with the standard GCKF (which operates in double precision) is negligible. This new method is particularly relevant in high-dimensional estimation problems that require high-frequency operation. By leveraging the compressed operation of the GCKF, the estimation process applies the necessary approximation only during low-frequency global updates, using the single precision format instead of the more expensive double precision representations. The introduced numerical approximation is accurately estimated while maintaining a conservative approach, resulting in minimal covariance inflation. When combined with the GCKF, which performs global updates at low frequency, the estimates produced are almost identical to the optimal ones. This approach is particularly useful in high-dimensional estimation problems that require high-frequency operation. By representing the full covariance matrix in a low precision numerical format and applying appropriate scaling, memory usage is significantly reduced, offering substantial benefits for high-dimensional estimation problems and enabling real-time smoothing processes in such cases. By reducing the memory requirements for storing the full covariance matrix, the CPU avoids encountering a high number of page faults, resulting in improved processing performance. Lastly, the experimental section verifies the performance of the proposed approach in a single precision (32-bit floating point) GCKF SLAM process, assessing expected values and standard deviations of marginal PDFs.

This review article aims at improving understanding of the theoretical discussion on technonationalism. Reviewing conventional works of the literature proposes protectionist, innovationist, and strategic industrial approaches toward high-tech industries. The findings show that technonationalism is a concept linking technology and national security, seeking geoeconomic interests in the integrated global market to exert state power for economic statecraft. The nature of industry highly relies on the global value chain, and technological innovation in the high-tech sectors occurs mainly in the private sector; thus, this article points out the issue of embracing business interests into the state’s strategic addenda as a critical criterion of technonationalism. Also, technonationalism is a narrowly defined concept with state actors involved in national security affairs and high-tech business actors.

A phenotype is the composite of an observable expression of a genome for traits in a given environment. The trajectories of phenotypes computed from an image sequence and timing of important events in a plant’s life cycle can be viewed as temporal phenotypes and indicative of the plant’s growth pattern and vigor. In this paper, we introduce a novel method called FlowerPhenoNet which uses deep neural networks for detecting flowers from multiview image sequences for high throughput temporal plant phenotyping analysis. Following flower detection, a set of novel flower-based phenotypes are computed, e.g., the day of emergence of the first flower in a plant’s life cycle, the total number of flowers present in the plant at a given time, the highest number of flowers bloomed in the plant, growth trajectory of a flower and the blooming trajectory of a plant. To develop a new algorithm and facilitate performance evaluation based on experimental analysis, a benchmark dataset is indispensable. Thus, we introduce a benchmark dataset called FlowerPheno which comprises image sequences of three flowering plant species, e.g., sunflower, coleus, and canna, captured by a visible light camera in a high throughput plant phenotyping platform from multiple view angles. The experimental analyses on the FlowerPheno dataset demonstrate the efficacy of the FlowerPhenoNet.

Cancer stem cells remain a challenge to isolate and characterize because of their plastic phenotype. Using a microfluidic lab-on-a-chip based on ultra-high frequency dielectophoresis, we measured the electromagnetic signature of colorectal cancer cells and demonstrated that cancer stem cells show a distinct and lower electromagnetic signature than differentiated cells. The release of extracellular vesicles from tumor cells can drive tumor progression and metastasis development. As extracellular vesicles from cancer stem cells carry more aggressive content, we treated colorectal cancer cells with these vesicles to test whether the lab-on-a-chip can detect a change in phenotype. The electromagnetic signature of treated cells is modified in comparison to untreated cells and sometimes even when no biological change is observed. The lab-on-a-chip provides rapid and relevant result without prior labeling compared to conventional biological approaches. It could be useful in the clinic for early detection of cancer stem cells in the tumor mass and for monitoring the aggressive potential of extracellular vesicles in the bloodstream in order to adapt therapeutic management and prevent relapse.

For more than half a century, Manfred Deistler has been contributing to the construction of the rigorous theoretical foundations of the statistical analysis of time series and more general stochastic processes. Half a century of unremitting activity is not easily summarized in a few pages. In this short note, we chose to concentrate on a relatively little-known aspect of Manfred's contribution which nevertheless had quite an impact on the development of one of the most powerful tools of contemporary time series and econometrics: dynamic factor models.

Event-based vision is an emerging field of computer vision that offers unique properties such as asynchronous visual output, high temporal resolutions, and dependence on brightness changes to generate data. These properties can enable robust high-temporal-resolution object detection and tracking when combined with frame-based vision. In this paper, we present a hybrid, high-temporal-resolution, object detection and tracking approach, that combines learned and classical methods using synchronized images and event data. Off-the-shelf frame-based object detectors are used for initial object detection and classification. Then, event masks, generated per each detection, are used to enable inter-frame tracking at varying temporal resolutions using the event data. Detections are associated across time using a simple low-cost association metric. Moreover, we collect and label a traffic dataset using the hybrid sensor DAVIS 240c. This dataset is utilized for quantitative evaluation using state-of-the-art detection and tracking metrics. We provide ground truth bounding boxes and object IDs for each vehicle annotation. Further, we generate high-temporal-resolution ground truth data to analyze the tracking performance at different temporal rates. Our approach shows promising results with minimal performance deterioration at higher temporal resolutions (48 – 384 Hz) when compared with the baseline frame-based performance at 24 Hz.

This article presents results of the polarization laser studies of the optical and microphysical characteristics of the high-level clouds (HLC). The high-altitude matrix polarization lidar (HAMPL; Tomsk, Russia) is described. HAMPL measures vertical profiles of all elements of the backscattering phase matrix (BSPM) of the HLC. Based on the joint analysis of lidar and radiosonde observations it is shown that the spatial structure of the HLC containing oriented ice crystals is inhomogeneous in the horizontal wind direction. It includes local areas with oriented particles; the sizes of such areas are estimated together with the most probable meteorological conditions of their formation. The shortcomings of the radiosonde observations performed closest to the location of the HAMPL are described. The applicability of the ERA5 reanalysis data of the European Centre for Medium-Range Weather Forecasts for use as an alternative source of information on the vertical profiles of meteorological quantities for the interpretation of HLC lidar sensing data in Western Siberia was checked.

In the present study, we studied the effect of apolipoprotein A-1 (APOA1) on the spatial and molecular characteristics of bone marrow adipocytes, using well-characterized ApoA1 knockout mice. APOA1 is a central regulator of high-density lipoprotein cholesterol (HDL-C) metabolism, and thus HDL; our recent work showed that deficiency of APOA1 increases bone marrow adiposity in mice. We found that ApoA1 deficient mice have greatly elevated adipocytes within their bone marrow compared to wild type counterparts. Morphologically, the increased adipocytes were similar to white adipocytes, and displayed proximal tibial-end localization. Marrow adipocytes from wild type mice were significantly fewer and did not display bone-end distribution pattern. The mRNA levels of the brown/beige adipocyte-specific markers Ucp1, Dio2, Pat2, Pgc1a, and the expression of leptin were greatly reduced in the ApoA1 knock-out in comparison to the wild-type mice. In the knock-out mice adiponectin was remarkably elevated. In keeping with the close ties of hematopoietic stem cells and marrow adipocytes, we found that the elevated adiposity in the ApoA1 knock out mice is associated with a significant reduction of the hematopoietic stem cells and common myeloid, but not common lymphoid, progenitors. Moreover, the “beiging”-related marker osteopontin and the angiogenic factor VEGF were also reduced in the ApoA1 knock-out mice, further supporting the notion that APOA1, and most probably HDL-C, regulate bone marrow microenvironment, favouring beige/brown adipocyte characteristics.

The naturally occurring dipeptide carnosine (β alanyl L histidine) specifically attenuates tumor growth. Here, we asked whether other small imidazole containing compounds also affect viability of tumor cells without affecting non-malignant cells, and whether formation of histamine is involved. Patient-derived fibroblasts and glioblastoma cells were treated with carnosine, L alanyl L histidine (LA-LH), ß alanyl L alanine, L histidine, histamine, imidazole, β alanine and L alanine. Cell viability was assessed by cell-based assays and microscopy. The intracellular release of L histidine and formation of histamine was investigated by High Performance Liquid Chromatography coupled Mass Spectrometry. Whereas carnosine and LA LH inhibited tumor cell growth with minor effects on fibroblasts, L-histidine, histamine and imidazole affected viability in both cell types. Compounds without imidazole moiety did not diminish viability. In the presence of LA LH but not in the presence of carnosine a significant rise of intracellular amounts of histidine was detected in all cells. Formation of histamine was not detectable in the presence of carnosine, LA LH or histidine. In conclusion, the imidazole moiety of carnosine contributes to its anti-neoplastic effect, which is also seen in the presence of histidine and LA LH. Despite histamine had a strong effect on cell viability, formation of histamine is not responsible for the effects on cell viability of carnosine, LA LH and histidine.

Eating Disorders (ED) constitute a serious public health issue affecting predominantly women and appearing typically in adolescence or early adulthood. EDs are extremely difficult to treat as these disorders are ego-syntonic and many patients do not seek treatment. It is vital to focus on the development of successful early-intervention programs for individuals presenting at-risk and are on a trajectory towards developing EDs. This study is a randomized controlled trial evalu-ating an innovative digital gamified Acceptance and Commitment early-intervention program (AcceptME) for young females showing signs and symptoms of an ED and at high-risk for an ED. Participants (N=92; Mage=15.30 years, SD=2.15) received either AcceptME (N=62) or a waitlist control (N=30). Analyses indicated that the AcceptME program effectively reduced weight and shape concerns, with large effects when compared to waitlist controls. Most participants scored below the at-risk cut-off (WCS score<52) in the AcceptME at end-of-intervention (57.1%) com-pared to controls (7.1%) with odds of falling into the at-risk group being 14.5 times higher for participants in the control group. At follow-up, 72% of completers reported scores below the at-risk cut-off in the AcceptME group. The intervention also resulted in a decrease in ED symp-tomatology and increased body image flexibility. Overall, results suggest that the AcceptME program holds promise for early-intervention of young women at-risk for developing an ED.

Glioblastoma (GBM) is one of the most aggressive solid tumors, particularly due to the presence of cancer stem cells (CSCs). Today the characterization of this type of cells with an efficient, fast and low-cost method remains an issue. Hence, we have developed a microfluidic lab-on-a-chip based on dielectrophoresis (DEP) single cell electro-manipulation to measure the two crossover frequencies: f_x01 in low frequency range (below 500 kHz) and f_x02 in Ultra High Frequency range (UHF, above 50 MHz). First, in vitro conditions were investigated. U87-MG cell lines were cultured in different conditions in order to induce an undifferentiated phenotype. Then, ex vivo GBM cells from patients’ primary cell culture, were passed through the developed microfluidic system and characterized in order to reflect clinical conditions. This article demonstrates that the usual exploitation of low frequency range DEP does not allow the discrimination of the undifferentiated from the differentiated phenotypes of GBM cells. However, the presented study highlights the use of UHF-DEP as a relevant discriminant parameter. The proposed microfluidic lab-on-a-chip is able to follow the kinetic of U87-MG phenotype transformation in a CSC enrichment medium and their cancer stem cells phenotype acquirement.

Given the increasing public interest in how ingredients are processed and the growing demand for organic food products, it is critical to understand consumers’ expectations about the process-related quality of organic products. Consumers perceive organic food to be nutritious, healthy and either natural or less processed, as they are afraid of the loss of nutrients and other natural properties of the food products. However, emerging food processing technologies might generate healthy and safe food options with nutritional quality properties. Simplified communication schemes might help to overcome this barrier. The main objective of this paper is to propose a working definition of "careful processing" for organic products and test its consistency while being used in scoring different processing methods by consumers. Results show that the proposed definition allows to consistently rate alternative processing methods. Consumers tend to score novel processing methods such as pulsed electric fields and microwave as less careful, supporting the idea that organic consumers want the least man-made interference with their food products. Results show that a simple but effective definition of careful processing may help consumers to distinguish further organic food products from conventional ones, no matter which communication scheme is used.

The available magnetic field strength for high resolution NMR in persistent superconducting magnets has recently improved from 23.5 to 28 Tesla, increasing the proton resonance frequency from 1 to 1.2 GHz. For magic-angle spinning (MAS) NMR, this is expected to improve resolution, provided the sample preparation results in homogeneous broadening. We compare two-dimensional (2D) proton detected MAS NMR spectra of four membrane proteins at 950 and 1.2 GHz. We find a consistent improvement in resolution that scales superlinearly with the increase in magnetic field for three of the four examples. In 3D and 4D spectra, which are now routinely acquired, this improvement indicates the ability to resolve at least 2 and 2.5 times as many signals, respectively.