Search Results (4)

To investigate the thickening characteristics of ultrafine tailings and the relationship between bed height and underflow concentration, a series of experiments, including graduated cylinder sedimentation tests, small-scale dynamic thickening, and semi-industrial experiments, were conducted. The results show that adding flocculants accelerates settling velocity, with a significant change occurring at 50 g/t when the bridging effect weakens. Solid flux increases initially with feed concentration but decreases after reaching a peak at 8%, where the maximum solid flux is 0.322 t·m⁻²·h⁻¹. Reducing solid flux, lowering flocculant dosage, and increasing bed height all contribute to higher underflow concentration, while reducing solid flux and increasing flocculant dosage lowers overflow turbidity. The variation in underflow concentration in the deep cone thickener (DCT) occurs in three phases: continuous feeding with no discharge, dynamic equilibrium with a stable bed height, and bed descent with increasing underflow discharge. At the same bed height, underflow concentration is lower during the bed descent phase compared to the continuous feeding phase. This study offers valuable insights for the precise control of underflow concentration in ultrafine tailing thickening processes. Full article

Pathogenic variants in the Crumbs homolog 1 (CRB1) gene lead to severe, childhood-onset retinal degeneration leading to blindness in early adulthood. There are no approved therapies, and traditional adeno-associated viral vector-based gene therapy approaches are challenged by the existence of multiple CRB1 isoforms. Here, we describe three CRB1 variants, including a novel, previously unreported variant that led to retinal degeneration. We offer a CRISPR-Cas-mediated DNA base editing strategy as a potential future therapeutic approach. This study is a retrospective case series. Clinical and genetic assessments were performed, including deep phenotyping by retinal imaging. In silico analyses were used to predict the pathogenicity of the novel variant and to determine whether the variants are amenable to DNA base editing strategies. Case 1 was a 24-year-old male with cone–rod dystrophy and retinal thickening typical of CRB1 retinopathy. He had a relatively preserved central outer retinal structure and a best corrected visual acuity (BCVA) of 60 ETDRS letters in both eyes. Genetic testing revealed compound heterozygous variants in exon 9: c.2843G>A, p.(Cys948Tyr) and a novel variant, c.2833G>A, p.(Gly945Arg), which was predicted to likely be pathogenic by an in silico analysis. Cases 2 and 3 were two brothers, aged 20 and 24, who presented with severe cone–rod dystrophy and a significant disruption of the outer nuclear layers. The BCVA was reduced to hand movements in both eyes in Case 2 and to 42 ETDRS letters in both eyes in Case 3. Case 2 was also affected with marked cystoid macular lesions, which are common in CRB1 retinopathy, but responded well to treatment with oral acetazolamide. Genetic testing revealed two c.2234C>T, p.(Thr745Met) variants in both brothers. As G-to-A and C-to-T variants, all three variants are amenable to adenine base editors (ABEs) targeting the forward strand in the Case 1 variants and the reverse strand in Cases 2 and 3. Available PAM sites were detected for KKH-nSaCas9-ABE8e for the c.2843G>A variant, nSaCas9-ABE8e and KKH-nSaCas9-ABE8e for the c.2833G>A variant, and nSpCas9-ABE8e for the c.2234C>T variant. In this case series, we report three pathogenic CRB1 variants, including a novel c.2833G>A variant associated with early-onset cone–rod dystrophy. We highlight the severity and rapid progression of the disease and offer ABEs as a potential future therapeutic approach for this devastating blinding condition. Full article

Paste and thickened tailings (PTT) technology can improve the utilization and management of tailings from processing plants. The pore size distribution (PSD) and microstructure evolution affected by the rake shear in thickening tailings beds are essential to produce a high-density tailings underflow. Continuous thickening and computed tomography (CT) scanning tests were conducted to study the PSD with and without shear. The pore morphology was studied to reveal the shearing-dewatering performance of the tailings bed. The results show that at a flocculant solution concentration of 0.01 wt % and a feed slurry concentration of 10 wt%, the underflow concentration with and without shear can reach 58.5 wt %and 55.8 wt %, respectively. The CT image reconstruction models demonstrated that the porosity of the sheared tailings bed increased with the bed height. When the bed height increased from 2.5 to 10 cm, the porosity increased from 35.1% to 41.9%, the pore fractal dimension increased from the range 1.8–1.95 to the range 2.1–2.15, and the pore quantity decreased by 21.39%. The average pore volume increased with increasing height by 13.93%, 16.57% and 12.07%. The pore structure became more complex with the bed height, and the connectivity between pores increased to form water-flow channels, which were beneficial to the drainage of sealed water. Full article

This paper focuses on the time series prediction problem for underflow concentration of deep cone thickener. It is commonly used in the industrial sedimentation process. In this paper, we introduce a dual attention neural network method to model both spatial and temporal features of the data collected from multiple sensors in the thickener to predict underflow concentration. The concentration is the key factor for future mining process. This model includes encoder and decoder. Their function is to capture spatial and temporal importance separately from input data, and output more accurate prediction. We also consider the domain knowledge in modeling process. Several supplementary constructed features are examined to enhance the final prediction accuracy in addition to the raw data from sensors. To test the feasibility and efficiency of this method, we select an industrial case based on Industrial Internet of Things (IIoT). This Tailings Thickener is from FLSmidth with multiple sensors. The comparative results support this method has favorable prediction accuracy, which is more than 10% lower than other time series prediction models in some common error indices. We also try to interpret our method with additional ablation experiments for different features and attention mechanisms. By employing mean absolute error index to evaluate the models, experimental result reports that enhanced features and dual-attention modules reduce error of fitting ~5% and ~11%, respectively. Full article