The design and implementation of the all-in-one machine for killing and sorting in the small and medium-sized logistics center

To stop the COVID-19 spread, artificial intelligence and new technologies are also actively participating in the battle. For fighting against the virus, disinfection is one of the effective ways to block the spread of the virus. According to the preliminary market research, only in the large distribution centers is the operator-controlled machine disinfection, at present most of the small and medium-sized express logistics stations are through human resources to carry out disinfection, and sorting of express packages, so the dependence on human costs, medical resources can be imagined. To this end, we designed ultrasonic atomization disinfection, sorting, and whole load notification integrated machine based on deep learning [1] and Internet of Things [2] technology to cope with the trend of normalization and recurrence of the epidemic. After testing logistics with different labels, the experimental results show that the system can effectively distinguish different labels and carry out a series of operations such as disinfection, sorting, and notification of full load, which can be put into production and contribute to epidemic prevention work. © 2023 IEEE.

Biomarkers of COVID-19 and technologies to combat SARS-CoV-2.

Due to the unprecedented public health crisis caused by COVID-19, our first contribution to the newly launching journal, Advances in Biomarker Sciences and Technology, has abruptly diverted to focus on the current pandemic. As the number of new COVID-19 cases and deaths continue to rise steadily around the world, the common goal of healthcare providers, scientists, and government officials worldwide has been to identify the best way to detect the novel coronavirus, named SARS-CoV-2, and to treat the viral infection - COVID-19. Accurate detection, timely diagnosis, effective treatment, and future prevention are the vital keys to management of COVID-19, and can help curb the viral spread. Traditionally, biomarkers play a pivotal role in the early detection of disease etiology, diagnosis, treatment and prognosis. To assist myriad ongoing investigations and innovations, we developed this current article to overview known and emerging biomarkers for SARS-CoV-2 detection, COVID-19 diagnostics, treatment and prognosis, and ongoing work to identify and develop more biomarkers for new drugs and vaccines. Moreover, biomarkers of socio-psychological stress, the high-technology quest for new virtual drug screening, and digital applications are described.

All-in-One Digital Microfluidics System for Molecular Diagnosis with Loop-Mediated Isothermal Amplification.

In this study, an "all-in-one" digital microfluidics (DMF) system was developed for automatic and rapid molecular diagnosis and integrated with magnetic bead-based nucleic acid extraction, loop-mediated isothermal amplification (LAMP), and real-time optical signal monitoring. First, we performed on- and off-chip comparison experiments for the magnetic bead nucleic acid extraction module and LAMP amplification function. The extraction efficiency for the on-chip test was comparable to that of conventional off-chip methods. The processing time for the automatic on-chip workflow was only 23 min, which was less than that of the conventional methods of 28 min 45 s. Meanwhile, the number of samples used in on-chip experiments was significantly smaller than that used in off-chip experiments; only 5 µL of E. coli samples was required for nucleic acid extraction, and 1 µL of the nucleic acid template was needed for the amplification reaction. In addition, we selected SARS-CoV-2 nucleic acid reference materials for the nucleic acid detection experiment, demonstrating a limit of detection of 10 copies/µL. The proposed "all-in-one" DMF system provides an on-site "sample to answer" time of approximately 60 min, which can be a powerful tool for point-of-care molecular diagnostics.

All-in-One Metal-Oxide Heterojunction Artificial Synapses for Visual Sensory and Neuromorphic Computing Systems

An all-in-one artificial synapse integrating central nervous and sensory nervous functions utilizing low-dimensional metal-oxide heterojunction is demonstrated in this work. With an ion-electrolyte gate, synaptic emulations modulated by electrical and photonic stimulus have been integrated into one high-performance three-terminal artificial synapse. Various long-term and short-term synaptic plasticity functions have been achieved by altering the electrolyte-gate stimulus amplitude/width/frequency/number. The linear potentiation behavior and maintained states enable artificial synapses for neuromorphic computing. Simulated artificial neural network based on the artificial synapses achieved Covid-19 chest image recognition (>85%). The photo-sensing metal-oxide heterojunction enables the synaptic functions mimicking the biological visual sensory functions responding to optical and UV stimulus. Photonic synaptic plasticity modulations responding to photonic stimulus wavelength/power/width/number are investigated, and short-term/long-term synaptic plasticity transition was achieved. Dual-mode modulation combining photonic stimulus and gate stimulus was examined, along with a ‘AND Gate’ demonstration with electrical and photonic inputs. Finally, an artificial neural network was demonstrated based on the synapses with dual-mode synaptic weight modulation, indicating the potential of the artificial synapse for compact artificial intelligence systems combing neuromorphic computing and visual sensory nervous functions.

Bi-ECDAQ: An electrochemical dual-immuno-biosensor accompanied by a customized bi-potentiostat for clinical detection of SARS-CoV-2 Nucleocapsid proteins.

Multiplex electrochemical biosensors have been used for eliminating the matrix effect in complex bodily fluids or enabling the detection of two or more bioanalytes, overall resulting in more sensitive assays and accurate diagnostics. Many electrochemical biosensors lack reliable and low-cost multiplexing to meet the requirements of point-of-care detection due to either limited functional biosensors for multi-electrode detection or incompatible readout systems. We developed a new dual electrochemical biosensing unit accompanied by a customized potentiostat to address the unmet need for point-of-care multi-electrode electrochemical biosensing. The two-working electrode system was developed using screen-printing of a carboxyl-rich nanomaterial containing ink, with both working electrodes offering active sites for recognition of bioanalytes. The low-cost bi-potentiostat system (∼$80) was developed and customized specifically to the bi-electrode design and used for rapid, repeatable, and accurate measurement of electrochemical impedance spectroscopy signals from the dual biosensor. This binary electrochemical data acquisition (Bi-ECDAQ) system accurately and selectively detected SARS-CoV-2 Nucleocapsid protein (N-protein) in both spiked samples and clinical nasopharyngeal swab samples of COVID-19 patients within 30 min. The two working electrodes offered the limit of detection of 116 fg/mL and 150 fg/mL, respectively, with the dynamic detection range of 1-10,000 pg/mL and the sensitivity range of 2744-2936 Ω mL/pg.mm2 for the detection of N-protein. The potentiostat performed comparable or better than commercial Autolab potentiostats while it is significantly lower cost. The open-source Bi-ECDAQ presents a customizable and flexible approach towards addressing the need for rapid and accurate point-of-care electrochemical biosensors for the rapid detection of various diseases.