Chatter is a limiting factor during boring of deep holes with long slender boring bars. In this article, a new magnetorheological (MR) damper is introduced to increase the stability of the boring ...process. The sponge-type configuration of the damper utilizes a minimal amount of MR fluid in the annulus around the boring bar. The MR fluid layer and the electromagnetic circuit are externally applied to the boring bar, which allows easy installation and adjustability in bar length. A custom made, bidisperse MR fluid is used to eliminate particle sedimentation and enhance the lifetime of the damper. The modal analysis of the boring bar with the new MR damper shows improvements in both the damping and the dynamic stiffness of the system. This enhancement significantly increases the chatter-free depth of cut on the stability lobe diagrams. This article presents the experimental validations on the boring of AL 7075 and Inconel 718 workpieces which are materials widely used in many aerospace applications. The damper is installed on a conventional boring bar for a CNC machining center setup, and its performance is tested under various machining conditions.
In this article, a sliding mode control of a magnetorheological fluid damper is presented for active damping of chatter in the boring process for the first time. A boring bar is integrated with an ...in-house developed magnetorheological fluid damper system. The variable gain super twisting sliding mode control algorithm is designed and implemented for suppressing the chatter in the boring process. Simulations of the controller show its fast response and robustness against disturbances and parametric uncertainties. Validation cutting tests performed under various machining conditions showed that the stability limit can be increased significantly with the sliding mode control of the magnetorheological fluid damper.
Summary
Some undamped vibrations may cause undesirable behavior such as noise, overloads, excessive displacements, and early fatigue failures in the mechanical systems. Active vibration control is ...crucial for some of the mechanical systems such as washing machines. This article proposes a new vibration control strategy (VCS) for reduction of vibrations in washing machine. VCS utilizes adaptive nonlinear terminal sliding mode control (NTSMC) of double coil shear mode magnetorheological (MR) dampers and DC‐DC buck converter. To achieve this goal, a control mechanism was designed that consists of two loops. The first loop implemented a force feedback control using proportional integral (PI) control and load cells. The second loop consists of adaptive NTSMC that was applied on buck converter to control current flow in MR dampers. The control law and finite convergence time to the equilibrium point were guaranteed for the current error using NTSMC. Moreover, an adaptive law was incorporated in NTSMC for the dynamic current control of MR dampers. The stability analysis of adaptive NTSMC was carried out using Lyapunov stability theory. An experimental setup was established for VCS that helps to study the performance of washing machine. A comparative analysis is presented for VCS with the passive dampers and other vibration control techniques that are reported in literature for washing machines.
The exponential growth of the internet and a multi-fold increase in social media users in the last decade have resulted in a massive growth of unstructured data. Aspect-Based Sentiment Analysis ...(ABSA) is challenging because it performs a fine-grain analysis; it is a text analysis technique where the opinions group is based on the aspect. The Aspect Extraction (AE) task is one of the core subtasks of ABSA; it helps to identify aspect terms in the text, comments, or reviews. The challenge of the Arabic AE task increases due to the complexity of the Arabic language. This work aims to develop the Arabic AE task by proposing transfer learning using state-of-art pre-trained contextual language models. We concatenate the Bidirectional Encoder Representation from Transformers (BERT) language model and contextualize string embeddings (Flair embedding) as a stacked embeddings layer for better word representation for Arabic language. Then, we extend it with different deep learning network architectures. For Arabic AE, the model is developed by concatenating the Arabic contextual language model, AraBERT, and Flair embedding as a contextual stacked embeddings layer with an extended layer, BiLSTM-CRF or BiGRU-CRF, for sequence labeling. Our proposed models are called BF-BiLSTM-CRF and BF-BiGRU-CRF. The proposed model is evaluated using the Arabic Hotel's reviews dataset. For performance evaluation, we used the F1 score. The experimental results show that the proposed BF-BiLSTM-CRF configuration outperformed the baseline and other models by achieving an F1score of 79.7%.
Power consumption is likely to remain a significant concern for
exascale
performance in the foreseeable future. In addition,
graphics processing units (GPUs)
have become an accepted architectural ...feature for exascale computing due to their scalable performance and power efficiency. In a recent study, we found that we can achieve a reasonable amount of
power
and
energy
savings based on the selection of algorithms. In this research, we suggest that we can save more power and energy by varying the
block size
in the
kernel configuration
. We show that we may attain more savings by selecting the optimum
block size
while executing the workload. We investigated two kernels on NVIDIA Tesla K40 GPU, a Bitonic Mergesort and Vector Addition kernels, to study the effect of varying block sizes on GPU
power
and
energy
consumption. The study should offer insights for upcoming exascale systems in terms of
power
and
energy
efficiency.
The research presented in the following paper focuses on the effectiveness of a modern standard Arabic corpus, AraFast, in training transformer models for natural language processing tasks, ...particularly in Arabic. In the study described herein, four experiments were conducted to evaluate the use of AraFast across different configurations: segmented, unsegmented, and mini versions. The main outcomes of the present study are as follows: Transformer models trained with larger and cleaner versions of AraFast, especially in question-answering, indicate the impact of corpus quality and size on model efficacy. Secondly, a dramatic reduction in training loss was observed with the mini version of AraFast, underscoring the importance of optimizing corpus size for effective training. Moreover, the segmented text format led to a decrease in training loss, highlighting segmentation as a beneficial strategy in Arabic NLP. In addition, using the study findings, challenges in managing noisy data derived from web sources are identified, which were found to significantly hinder model performance. These findings collectively demonstrate the critical role of well-prepared, segmented, and clean corpora in advancing Arabic NLP capabilities. The insights from AraFast’s application can guide the development of more efficient NLP models and suggest directions for future research in enhancing Arabic language processing tools.
There are unmet answers about the effect of the different forms of corticosteroids in the treatment of the warm autoimmune hemolytic anemia (WAIHA). We aimed to describe the initial response rate and ...the safety profile of different regimens and forms of parenteral corticosteroids versus the solo oral prednisolone as first-line strategies for newly diagnosed adult WAIHA.
We recruited 156 patients who treated with either oral prednisolone 1 mg/kg daily for 3 weeks or intravenous corticosteroids like dexamethasone 40 mg daily for 4 days, Methylprednisolone 1 g/day for 3 days, or Methylprednisolone 1 g/day for 5 days then followed by oral prednisolone 1 mg/kg/day for 3 weeks. Full clinical and laboratory evaluations were done every 3 days for 3 weeks.
The primary outcome was the rate of response at the end of the third-week post treatment. The rate of response was more in the group started the treatment intravenously (81.6% versus 41.7% and p = 0.0001). Multivariate cox regression analysis proved the predictivity of intravenous corticosteroid therapy for initial response.
The safety profile of the different forms and regimens of corticosteroids were comparable. Therefore, parenteral regimens can be used as a rescue treatment in severe cases of WAIHA.
•Cytokines are mediators of immune responses including GVHD.•Polymorphisms of cytokine genes result into high and low producer phenotypes.•There is ethnic variation in high and low producer cytokines ...genotype/phenotype.•This leads to variation in the contribution to GVHD in different populations.
Graft-versus-host disease (GVHD) is the major complication of allogeneic hematopoietic stem cell transplantation (HSCT); cytokines are recognized as important mediators in its pathogenesis. In this study we investigated the role of cytokine gene polymorphisms on HSCT outcome. A total of 106 patient and 98 donors were genotyped by polymerase chain reaction sequence specific primers (PCR-SSP) based assay for tumor necrosis factor-α−308 (TNFα -308), interleukin (IL)-6-174, IL-10-1082, −819, −592, Interferon-γ+874 (IFN-γ+874), and transforming growth factor-β1 (TGF-β1) codon10 and 25 polymorphisms. Except one in each category, all patients and donors were TNFα -308 high producers and the majority were IL-6-174 high producers (93.3% and 90.8% respectively); a pattern that would alleviate any potential biological impact. Patient's IFN-γ+874 showed significant association with the development of chronic GVHD. Patients with IFN-γ +874 high producer showed an 8 folds likelihood to develop chronic GVHD as compared to those with IFN-γ+874 low producer predicted phenotype (95% CI: 1.59-40.2, p = 0.01). Patient's TGFβ1-codon 10 and 25 high/intermediate producers showed a lower incidence of acute GVHD though it did not achieve statistical significance (p = 0.065) on account of the low frequency of this genotype in our patients and donors (11.4 and 8.2% respectively). Other factors contributing to risk of GVHD included older age for both acute and chronic (p = 0.01 and 0.02 respectively) with age 24 as the best discriminating cutoff; CD34+ cell dose for chronic GVHD (p = 0.045) with a dose of 8 × 106/kg as the best discriminating cutoff; and conditioning regimen with Flu/Bu associated with the lowest incidence of acute GVHD (p = 0.003) and no impact on chronic GVHD. In conclusion the current study further indicates a potential role of some cytokine gene polymorphisms in the development of GVHD. The relative distribution of high and low producer genotypes in different ethnic groups contributes to their biological impact in different populations.
Aspect-based sentiment analysis (ABSA) is a fine-grained type of sentiment analysis; it works on an aspect level. It mainly focuses on extracting aspect terms from text or reviews, categorizing the ...aspect terms, and classifying the sentiment polarities toward each aspect term and aspect category. Aspect term extraction (ATE) and aspect category detection (ACD) are interdependent and closely associated tasks. However, the majority of the current literature on Arabic aspect-based sentiment analysis (ABSA) deals with these tasks individually, assumes that aspect terms are already identified, or employs a pipeline model. Pipeline solutions employ single models for each task, where the output of the ATE model is utilized as the input for the ACD model. This sequential process can lead to the propagation of errors across different stages, as the performance of the ACD model is influenced by any errors produced by the ATE model. Therefore, the primary objective of this study was to investigate a multi-task learning approach based on transfer learning and transformers. We propose a multi-task learning model (MTL) that utilizes the pre-trained language model (AraBERT), namely, the MTL-AraBERT model, for extracting Arabic aspect terms and aspect categories simultaneously. Specifically, we focused on training a single model that simultaneously and jointly addressed both subtasks. Moreover, this paper also proposes a model integrating AraBERT, single pair classification, and BiLSTM/BiGRU that can be applied to aspect term polarity classification (APC) and aspect category polarity classification (ACPC). All proposed models were evaluated using the SemEval-2016 annotated dataset for the Arabic hotel dataset. The experiment results of the MTL model demonstrate that the proposed models achieved comparable or better performance than state-of-the-art works (F1-scores of 80.32% for the ATE and 68.21% for the ACD). The proposed SPC-BERT model demonstrated high accuracy, reaching 89.02% and 89.36 for APC and ACPC, respectively. These improvements hold significant potential for future research in Arabic ABSA.
This study aimed to determine the erythrocytic lipid peroxidation and haemoglobin oxidation as contributory factors causing anaemia in cattle (Friesian
×
Egyptian native breed) infected with
Babesia ...bigemina. Blood was collected from 32 cows infected with
B. bigemina along with 18 healthy cows as controls for determination of erythrocytic malondialdehyde (MDA), blood methaemoglobin (MetHb), plasma free haemoglobin (PHb), corpuscular osmotic fragility (COF), red blood cell count (RBC), total haemoglobin (Hb) and packed cell volume (PCV). Percentage of parasitaemia varied from 14% to 36%. MDA, MetHb, COF and PHb were significantly increased (
P
<
0.001) in infected cows versus controls. Parasitaemia was positively correlated (
P
<
0.001) with MDA, MetHb, COF and PHb. MDA was positively correlated (
P
<
0.001) with COF and PHb and negatively correlated (
P
<
0.001) with RBC, Hb and PCV. MetHb was negatively correlated (
P
<
0.001) with RBC, Hb and PCV and positively correlated (
P
<
0.001) with COF. In conclusion,
B. bigemina infection in cattle is associated with a parasitic burden-dependent corpuscular oxidative damage as indicated by membrane lipid peroxidation and methaemoglobin formation, which are contributed to COF and intravascular haemolysis.
