A Partition-based Mobile Crowd Sensing-enabled Task Allocation for Solar Insecticidal Lamp Internet of Things Maintenance

Solar Insecticidal Lamps Internet of Things (SIL-IoT) is a new green prevention and control technology for pest management. In the implementation of SIL-IoT to large-scale regions, two practical issues remain to be solved, i.e., i) scheduling the cleaning tasks of SILs periodically; and ii) minimizing the insecticidal efficiency reduction over time. As smartphones are widely available among farmers across the globe, Mobile Crowd Sensing (MCS) for agricultural data collection becomes a cost-effective and efficient solution by integrating participatory sensing based on a large group of individuals. This paper proposes an MCS-enabled framework to address the SIL Maintenance Problem (SILMP) and perform system analysis by considering both the partition structure of farmland and the insecticidal efficiency of SILs. In addition, considering the farmland’s practical natural geographical features, we propose dividing the regions of interest into numerous subareas, where each subarea can be considered a separate partition. Finally, we formulate the SILMP framework as two sub-problems, i.e., path planning and task selection, and propose two different methods to tackle each problem based on the concept of greedy algorithm. Simulation results show that our proposed methods have improved performance in the trade-off between task cost and insecticidal efficiency and outperform the three selected baseline algorithms.</p

<i>UBE3A</i> deletion enhances the efficiency of immunotherapy in non-small-cell lung cancer

Immunotherapy significantly improves the prognosis of advanced lung cancer. It has become an important treatment option for advanced lung cancer. However, there remain many limitations in clinical treatment, and only a small portion of patients can benefit from immunotherapy. Our study aimed to identify markers that can precisely forecast the efficacy of immunotherapy in patients. We analyzed a non-small-cell lung cancer (NSCLC) immune checkpoint inhibitor (ICI) cohort (n=240). We used this discovery cohort to identify CNVs in genes associated with immunotherapy. We further analyzed immune biomarkers and immune infiltration in The Cancer Genome Atlas (TCGA)-NSCLC cohort and the Gene Expression Omnibus (GEO) cohorts. By analyzing an ICI dataset from MSKCC, we found that progression-free survival (PFS) was improved after UBE3A deletion (UBE3A-del). The analysis results showed that UBE3A-del had higher immunocyte infiltration levels and higher expression levels of immune checkpoint biomarkers and affected the enrichment levels of immune signaling pathways. Our results suggest that UBE3A-del can be used as a predictive biomarker of NSCLC to screen for NSCLC patients who may benefit from ICI therapy.  Abbreviations: NSCLC: Non-small cell lung cancer; CNV: Copy number variation; ICIs: Immune checkpoint inhibitors; TCGA: The cancer genome atlas; GEO: Gene expression omnibus; GSEA: Gene set enrichment; PFS: Progression-free survival; OS: Overall survival; TMB: Tumor mutational burden; CTLA-4: Cytotoxic T lymphocyte antigen 4; PD-(L)1: Programmed cell death (ligand) 1; MSI: Microsatellite instability; dMMR: DNA mismatch repair; SCNAs: Somatic copy number alterations; TME: Tumor microenvironment; MSK-IMPACT: The Memorial Sloan Kettering-Integrated Mutation Profilng of Actionable; Cancer Targets; FDA: Food and Drug Administration; WES: Whole-exome sequencing; SNP: Single Nucleotide Polymorphisms; FDR: False discovery rate; DCR: Disease control rate; DDR: DNA damage response and repair; MDSCs: Myeloid-derived suppressor cells; FAO: Fatty acid oxidation</p

On enabling mobile crowd sensing for data collection in smart agriculture: a vision

Smart agriculture enables the efficiency and intelligence of production in physical farm management. Though promising, due to the limitation of the existing data collection methods, it still encounters few challenges required to be considered. Mobile crowd sensing (MCS) embeds three beneficial characteristics: 1) cost-effectiveness; 2) scalability; and 3) mobility and robustness. With the Internet of Things becoming a reality, smartphones are widely becoming available even in remote areas. Hence, both the MCS characteristics and the plug-and-play widely available infrastructure provide huge opportunities for MCS-enabled smart agriculture, opening up several new opportunities at the application level. In this article, we extensively evaluate agriculture mobile crowd sensing (AMCS) and provide insights for agricultural data collection schemes. In addition, we offer a comparative study with the existing agriculture data collection solutions and conclude that AMCS has significant benefits in terms of flexibility, collecting implicit data, and low-cost requirements. However, we note that AMCSs may still possess limitations regarding data integrity and quality to be considered a future work. To this end, we perform a detailed analysis of the challenges and opportunities that concerns MCS-enabled agriculture by putting forward seven potential applications of AMCS-enabled agriculture. Finally, we propose general research based on agricultural characteristics and discuss a special case based on the solar insecticidal lamp maintenance problem

On enabling mobile crowd sensing for data collection in smart agriculture: a vision

Smart agriculture enables the efficiency and intelligence of production in physical farm management. Though promising, due to the limitation of the existing data collection methods, it still encounters few challenges required to be considered. Mobile crowd sensing (MCS) embeds three beneficial characteristics: 1) cost-effectiveness; 2) scalability; and 3) mobility and robustness. With the Internet of Things becoming a reality, smartphones are widely becoming available even in remote areas. Hence, both the MCS characteristics and the plug-and-play widely available infrastructure provide huge opportunities for MCS-enabled smart agriculture, opening up several new opportunities at the application level. In this article, we extensively evaluate agriculture mobile crowd sensing (AMCS) and provide insights for agricultural data collection schemes. In addition, we offer a comparative study with the existing agriculture data collection solutions and conclude that AMCS has significant benefits in terms of flexibility, collecting implicit data, and low-cost requirements. However, we note that AMCSs may still possess limitations regarding data integrity and quality to be considered a future work. To this end, we perform a detailed analysis of the challenges and opportunities that concerns MCS-enabled agriculture by putting forward seven potential applications of AMCS-enabled agriculture. Finally, we propose general research based on agricultural characteristics and discuss a special case based on the solar insecticidal lamp maintenance problem

Data_Sheet_1_Rapid, accurate, and novel diagnostic technique for respiratory pathogens: Clinical application of loop-mediated isothermal amplification assay in older patients with pneumonia, a multicenter prospective observational study.PDF

BackgroundLoop-mediated isothermal amplification (LAMP) is a novel nucleic acid amplification method using only one type of enzyme that can amplify DNA with high specificity, efficiency and rapidity under isothermal conditions. Chips for Complicated Infection Detection (CCID) is based on LAMP. This study translate CCID into clinical application and evaluate its diagnostic value for pneumonia.MethodsEighty one older patients with pneumonia were prospectively enrolled from January 1 to July 23, 2021, and 57 sputum/airway secretion and 35 bronchoalveolar lavage fluid samples were collected and analyzed by CCID and conventional microbiological tests (CMTs). Samples were collected, transported, monitored, and managed by a multidisciplinary team using a sample management information system.ResultsCCID turnaround time was 50 min, and the detection limit was 500 copies/reaction. The percentage of positive samples was significantly higher using CCID than CMTs, especially for Klebsiella pneumoniae (odds ratio [OR], 9.0; 95% confidence interval [CI], 1.1–70.5; p ConclusionCCID allows the rapid and accurate detection of pneumonia in older patients. Moreover, this technique is less affected by previous antibiotic treatment and can improve patient care.</p

Presentation_1_Rapid, accurate, and novel diagnostic technique for respiratory pathogens: Clinical application of loop-mediated isothermal amplification assay in older patients with pneumonia, a multicenter prospective observational study.PPTX

BackgroundLoop-mediated isothermal amplification (LAMP) is a novel nucleic acid amplification method using only one type of enzyme that can amplify DNA with high specificity, efficiency and rapidity under isothermal conditions. Chips for Complicated Infection Detection (CCID) is based on LAMP. This study translate CCID into clinical application and evaluate its diagnostic value for pneumonia.MethodsEighty one older patients with pneumonia were prospectively enrolled from January 1 to July 23, 2021, and 57 sputum/airway secretion and 35 bronchoalveolar lavage fluid samples were collected and analyzed by CCID and conventional microbiological tests (CMTs). Samples were collected, transported, monitored, and managed by a multidisciplinary team using a sample management information system.ResultsCCID turnaround time was 50 min, and the detection limit was 500 copies/reaction. The percentage of positive samples was significantly higher using CCID than CMTs, especially for Klebsiella pneumoniae (odds ratio [OR], 9.0; 95% confidence interval [CI], 1.1–70.5; p ConclusionCCID allows the rapid and accurate detection of pneumonia in older patients. Moreover, this technique is less affected by previous antibiotic treatment and can improve patient care.</p

Data_Sheet_2_Rapid, accurate, and novel diagnostic technique for respiratory pathogens: Clinical application of loop-mediated isothermal amplification assay in older patients with pneumonia, a multicenter prospective observational study.PDF

BackgroundLoop-mediated isothermal amplification (LAMP) is a novel nucleic acid amplification method using only one type of enzyme that can amplify DNA with high specificity, efficiency and rapidity under isothermal conditions. Chips for Complicated Infection Detection (CCID) is based on LAMP. This study translate CCID into clinical application and evaluate its diagnostic value for pneumonia.MethodsEighty one older patients with pneumonia were prospectively enrolled from January 1 to July 23, 2021, and 57 sputum/airway secretion and 35 bronchoalveolar lavage fluid samples were collected and analyzed by CCID and conventional microbiological tests (CMTs). Samples were collected, transported, monitored, and managed by a multidisciplinary team using a sample management information system.ResultsCCID turnaround time was 50 min, and the detection limit was 500 copies/reaction. The percentage of positive samples was significantly higher using CCID than CMTs, especially for Klebsiella pneumoniae (odds ratio [OR], 9.0; 95% confidence interval [CI], 1.1–70.5; p ConclusionCCID allows the rapid and accurate detection of pneumonia in older patients. Moreover, this technique is less affected by previous antibiotic treatment and can improve patient care.</p