An interpretable imbalanced semi-supervised deep learning framework for improving differential diagnosis of skin diseases

Dermatological diseases are among the most common disorders worldwide. This paper presents the first study of the interpretability and imbalanced semi-supervised learning of the multiclass intelligent skin diagnosis framework (ISDL) using 58,457 skin images with 10,857 unlabeled samples. Pseudo-labelled samples from minority classes have a higher probability at each iteration of class-rebalancing self-training, thereby promoting the utilization of unlabeled samples to solve the class imbalance problem. Our ISDL achieved a promising performance with an accuracy of 0.979, sensitivity of 0.975, specificity of 0.973, macro-F1 score of 0.974 and area under the receiver operating characteristic curve (AUC) of 0.999 for multi-label skin disease classification. The Shapley Additive explanation (SHAP) method is combined with our ISDL to explain how the deep learning model makes predictions. This finding is consistent with the clinical diagnosis. We also proposed a sampling distribution optimisation strategy to select pseudo-labelled samples in a more effective manner using ISDLplus. Furthermore, it has the potential to relieve the pressure placed on professional doctors, as well as help with practical issues associated with a shortage of such doctors in rural areas

Influence of Sewage Sludge Biochar on the Microbial Environment, Chinese Cabbage Growth, and Heavy Metals Availability of Soil

The effects of sewage sludge biochar (SSB) on the microbial environment, Chinese cabbage yield, and heavy metals (HMs) availability of soil were comprehensively investigated in this study. Results showed that the concentrations of the dehydrogenase (DHA) and urease in the soil added with 10% SSB were 3.60 and 1.67 times as high as that of the control soil, respectively, after planting; the concentrations of the bacteria, fungi, ammonia-oxidizing archaea (AOA), and ammonia-oxidizing bacteria (AOB) in the soil added with 10% SSB after planting reached 2.84, 2.62, 1.76, and 2.23 times, respectively, compared with those of the control group; the weights of the aboveground and underground parts of Chinese cabbage were 5.82 and 8.67 times as high as those of the control group, respectively. Moreover, the addition of SSB enhanced the immobilization of Cr, Ni, and Cd. All in all, SSB can improve the microbial environment of soil and inhibit the availability of HMs, which is very important for their utilization in barren soil

Influence of Sewage Sludge Biochar on the Microbial Environment, Chinese Cabbage Growth, and Heavy Metals Availability of Soil

The effects of sewage sludge biochar (SSB) on the microbial environment, Chinese cabbage yield, and heavy metals (HMs) availability of soil were comprehensively investigated in this study. Results showed that the concentrations of the dehydrogenase (DHA) and urease in the soil added with 10% SSB were 3.60 and 1.67 times as high as that of the control soil, respectively, after planting; the concentrations of the bacteria, fungi, ammonia-oxidizing archaea (AOA), and ammonia-oxidizing bacteria (AOB) in the soil added with 10% SSB after planting reached 2.84, 2.62, 1.76, and 2.23 times, respectively, compared with those of the control group; the weights of the aboveground and underground parts of Chinese cabbage were 5.82 and 8.67 times as high as those of the control group, respectively. Moreover, the addition of SSB enhanced the immobilization of Cr, Ni, and Cd. All in all, SSB can improve the microbial environment of soil and inhibit the availability of HMs, which is very important for their utilization in barren soil

Optical Data Transmission ASICs for the High-Luminosity LHC (HL-LHC) Experiments

We present the design and test results of two optical data transmission ASICs for the High-Luminosity LHC (HL-LHC) experiments. These ASICs include a two-channel serializer (LOCs2) and a single-channel Vertical Cavity Surface Emitting Laser (VCSEL) driver (LOCld1V2). Both ASICs are fabricated in a commercial 0.25-um Silicon-on-Sapphire (SoS) CMOS technology and operate at a data rate up to 8 Gbps per channel. The power consumption of LOCs2 and LOCld1V2 are 1.25 W and 0.27 W at 8-Gbps data rate, respectively. LOCld1V2 has been verified meeting the radiation-tolerance requirements for HL-LHC experiments.Comment: 9 pages, 12 figure

The 120Gbps VCSEL Array Based Optical Transmitter (ATx) Development for the High-Luminosity LHC (HL-LHC) Experiments

The integration of a Verticle Cavity Surface-Emitting Laser (VCSEL) array and a driving Application-Specific Integrated Circuit (ASIC) in a custom optical array transmitter module (ATx) for operation in the detector front-end is constructed, assembled and tested. The ATx provides 12 parallel channels with each channel operating at 10 Gbps. The optical transmitter eye diagram passes the eye mask and the bit-error rate (BER) less than 1E-12 transmission is achieved at 10 Gbps/ch. The overall insertion loss including the radiation induced attenuation is sufficiently low to meet the proposed link budget requirement.Comment: 10 pages, 9 figure

Experimental exploration of five-qubit quantum error correcting code with superconducting qubits

Quantum error correction is an essential ingredient for universal quantum computing. Despite tremendous experimental efforts in the study of quantum error correction, to date, there has been no demonstration in the realisation of universal quantum error correcting code, with the subsequent verification of all key features including the identification of an arbitrary physical error, the capability for transversal manipulation of the logical state, and state decoding. To address this challenge, we experimentally realise the $[\![5,1,3]\!]$ code, the so-called smallest perfect code that permits corrections of generic single-qubit errors. In the experiment, having optimised the encoding circuit, we employ an array of superconducting qubits to realise the $[\![5,1,3]\!]$ code for several typical logical states including the magic state, an indispensable resource for realising non-Clifford gates. The encoded states are prepared with an average fidelity of $57.1(3)\%$ while with a high fidelity of $98.6(1)\%$ in the code space. Then, the arbitrary single-qubit errors introduced manually are identified by measuring the stabilizers. We further implement logical Pauli operations with a fidelity of $97.2(2)\%$ within the code space. Finally, we realise the decoding circuit and recover the input state with an overall fidelity of $74.5(6)\%$, in total with $92$ gates. Our work demonstrates each key aspect of the $[\![5,1,3]\!]$ code and verifies the viability of experimental realization of quantum error correcting codes with superconducting qubits.Comment: 6 pages, 4 figures + Supplementary Material