The balancing of rotating machinery as non-linear system passing across a resonant region

This paper presents a dynamical balancing method for the rotational part of machine as a nonlinear system with the decrease of rotation speed passing across a resonant region. After analyzing the nonlinear system and measurable vibration signals, a suitable procedure of dynamical balance for determining the magnitude and location of imbalance mass is proposed. A program on PC is made to illustrate the obtained procedure. The results of numeric examples show that it can be used well for dynamical balancing analysis

On the simulation technique of stochastic processes and nonlinear vibrations

In this paper the procedure and program for simulation of stochastic processes are represented. The program is applied to nonlinear mechanical systems subjected to stochastic stationary excitation. The results obtained are compared with the ones from other methods which are used for estimating the exactitude of simulation technique

DARK SOIL PITS AND GRAVES IN VOLCANIC CAVE C6.1, KRONG NO, DAK NONG PROVINCE: DOCUMENTATION AND DISCUSSION

Dark soil pits and graves are critical documents discovered in volcanic cave C6.1. As a result of the investigation and excavation of cave C6.1 conducted in 2017, 2018, and 2019, we have discovered vestiges of nine dark soil pits and seven relatively intact graves, together with teeth and other human remains scattered in the cultural layer. This is an important source of information on the racial composition of the prehistoric inhabitants of the Central Highlands during the Neolithic period, as well as the paleoenvironment, environmental adaptations, and flora and fauna that prehistoric inhabitants exploited for their livelihoods. This article introduces documents and reconstructs the socioeconomic picture of the prehistoric inhabitants of cave C6.1. It also contributes scientific documents for the general conservation and promotion of heritage to develop sustainable cultural tourism in Dak Nong Province

THE INFRASTRUCTURE AND ENVIRONMENT IN THE OLD TENEMENTS IN HANOI

Joint Research on Environmental Science and Technology for the Eart

Energy Lost in a Hydrogel Osmotic Engine Due to a Pressure Drop

Utilizing hydrogels to harvest salinity gradient energy from solutions of different salinities has recently attracted interest. Polyelectrolyte hydrogels exhibit cyclic swelling/deswelling when alternately exposed to freshwater and seawater. This can be utilized to convert the mixing energy of the two solutions into mechanical energy. Hydrogels consisting of a semi-interpenetrating network (semi-IPN) of poly(4-styrene sulfonic acid-co-maleic acid) sodium salt and polyacrylic acid was prepared at various cross-linking densities. The energy lost due to a pressure drop in the system during the deswelling/swelling process of these hydrogels is examined, and the effects of tubing dimensions, hydrogel cylinder size, gel particle size, and the volume fraction within the hydrogel cylinder occupied by the flowing liquid (ε) are investigated. In addition, a small-scale osmotic engine was compared to a scaled-up system. ε was found to be the factor that had the largest effect on the energy loss. It was found that ε is strongly dependent on the degree of swelling of the hydrogels. When the hydrogels swell, they deform more easily under pressure. This markedly decreases ε, thereby inducing a high pressure drop in the system and a correspondingly large energy loss. Accordingly, the pressure drop when pumping through the hydrogel is the major contributor to the energy loss in the system. When the hydrogel particles deform too much, the energy needed to pump the flowing liquid through the hydrogels exceeds the energy produced by the system. Developing a hydrogel system that deforms less in its swollen state is therefore essential for improving the energy efficiencies of these osmotic engines.publishedVersio

LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained deep networks on ImageNet and vision-language foundation models trained on web-scale data are prevailing approaches, their effectiveness on medical tasks is limited due to the significant domain shift between natural and medical images. To bridge this gap, we introduce LVM-Med, the first family of deep networks trained on large-scale medical datasets. We have collected approximately 1.3 million medical images from 55 publicly available datasets, covering a large number of organs and modalities such as CT, MRI, X-ray, and Ultrasound. We benchmark several state-of-the-art self-supervised algorithms on this dataset and propose a novel self-supervised contrastive learning algorithm using a graph-matching formulation. The proposed approach makes three contributions: (i) it integrates prior pair-wise image similarity metrics based on local and global information; (ii) it captures the structural constraints of feature embeddings through a loss function constructed via a combinatorial graph-matching objective; and (iii) it can be trained efficiently end-to-end using modern gradient-estimation techniques for black-box solvers. We thoroughly evaluate the proposed LVM-Med on 15 downstream medical tasks ranging from segmentation and classification to object detection, and both for the in and out-of-distribution settings. LVM-Med empirically outperforms a number of state-of-the-art supervised, self-supervised, and foundation models. For challenging tasks such as Brain Tumor Classification or Diabetic Retinopathy Grading, LVM-Med improves previous vision-language models trained on 1 billion masks by 6-7% while using only a ResNet-50.Comment: Update Appendi

Synthesized BiVO4 was by the co-precipitation method for Rhodamine B degradation under visible light

Recently, BiVO4 photocatalysts has been received much attention in field of catalysts. Because it can be used to degrade harmful organic catalysts in visible light, irradiation produces CO2, H2O and less harmful organic matter. In this study, we have successfully synthesized a BiVO4 photocatalysts via co-precipitation method in the presence of urea and different calcined temperatures. The survey calcined temperatures as 300°C; 350°C; 400°C and 450°C. The obtained materials were characterized by Scanning electron microscope (SEM) and X-ray diffraction (XRD). The photocatalytic activity was evaluated by the photocatalytic degradation of rhodamine B (RhB) degradation under visible compact Philip lamp (40W) light irradiation. The result indicates that all samples calcined are monoclinic scheelite structure of BiVO4. The BiVO4-350°C sample performed the best in the photodegradation of RhB

Pichia pastoris versus Saccharomyces cerevisiae:a case study on the recombinant production of human granulocyte-macrophage colony-stimulating factor

BACKGROUND: Recombinant human granulocyte-macrophage colony-stimulating factor (rhGM-CSF) is a glycoprotein that has been approved by the FDA for the treatment of neutropenia and leukemia in combination with chemotherapies. Recombinant hGM-CSF is produced industrially using the baker's yeast, Saccharomyces cerevisiae, by large-scale fermentation. The methylotrophic yeast, Pichia pastoris, has emerged as an alternative host cell system due to its shorter and less immunogenic glycosylation pattern together with higher cell density growth and higher secreted protein yield than S. cerevisiae. In this study, we compared the pipeline from gene to recombinant protein in these two yeasts. RESULTS: Codon optimization in silico for both yeast species showed no difference in frequent codon usage. However, rhGM-CSF expressed from S. cerevisiae BY4742 showed a significant discrepancy in molecular weight from those of P. pastoris X33. Analysis showed purified rhGM-CSF species with molecular weights ranging from 30 to more than 60 kDa. Fed-batch fermentation over 72 h showed that rhGM-CSF was more highly secreted from P. pastoris than S. cerevisiae (285 and 64 mg total secreted protein/L, respectively). Ion exchange chromatography gave higher purity and recovery than hydrophobic interaction chromatography. Purified rhGM-CSF from P. pastoris was 327 times more potent than rhGM-CSF from S. cerevisiae in terms of proliferative stimulating capacity on the hGM-CSF-dependent cell line, TF-1. CONCLUSION: Our data support a view that the methylotrophic yeast P. pastoris is an effective recombinant host for heterologous rhGM-CSF production

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke