A Fast Solution Method for Large-scale Unit Commitment Based on Lagrangian Relaxation and Dynamic Programming

The unit commitment problem (UC) is crucial for the operation and market mechanism of power systems. With the development of modern electricity, the scale of power systems is expanding, and solving the UC problem is also becoming more and more difficult. To this end, this paper proposes a new fast solution method based on Lagrangian relaxation and dynamic program-ming. Firstly, the UC solution is estimated to be an initial trial UC solution by a fast method based on Lagrangian relaxation. This initial trial UC solution fully considers the system-wide con-straints. Secondly, a dynamic programming module is introduced to adjust the trial UC solution to make it satisfy the unit-wise constraints. Thirdly, a method for constructing a feasible UC solution is proposed based on the adjusted trial UC solution. Specifically, a feasibility-testing model and an updating strategy for the trial UC solution are established in this part. Numerical tests are implemented on IEEE 24-bus, IEEE 118-bus, Polish 2383-bus, and French 6468-bus systems, which verify the effec-tiveness and efficiency of the proposed method.Comment: 10 pages, journal paper, transaction

COVIDanno, COVID-19 annotation in human

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 19 (COVID-19), has caused a global health crisis. Despite ongoing efforts to treat patients, there is no universal prevention or cure available. One of the feasible approaches will be identifying the key genes from SARS-CoV-2-infected cells. SARS-CoV-2-infected in vitro model, allows easy control of the experimental conditions, obtaining reproducible results, and monitoring of infection progression. Currently, accumulating RNA-seq data from SARS-CoV-2 in vitro models urgently needs systematic translation and interpretation. To fill this gap, we built COVIDanno, COVID-19 annotation in humans, available at http://biomedbdc.wchscu.cn/COVIDanno/. The aim of this resource is to provide a reference resource of intensive functional annotations of differentially expressed genes (DEGs) among different time points of COVID-19 infection in human in vitro models. To do this, we performed differential expression analysis for 136 individual datasets across 13 tissue types. In total, we identified 4,935 DEGs. We performed multiple bioinformatics/computational biology studies for these DEGs. Furthermore, we developed a novel tool to help users predict the status of SARS-CoV-2 infection for a given sample. COVIDanno will be a valuable resource for identifying SARS-CoV-2-related genes and understanding their potential functional roles in different time points and multiple tissue types

Anti-PD-1 antibodies, a novel treatment option for advanced chemoresistant pulmonary lymphoepithelioma carcinoma

BackgroundPulmonary lymphoepithelioma-like carcinoma (LELC) exhibits a unique immune microenvironment, including high PD-L1 expression and abundant infiltrating-immune cells. However, the availability of PD-1/PD-L1 inhibitors in patients with LELC is still not determined.MethodsA total of 36 cases of pulmonary LELC treated with PD-1/PD-L1 inhibitors were reviewed, including 10 cases from our institute and 26 cases included from the literature. The Kaplan-Meier method and log-rank test were utilized to analyze the survival outcomes of LELC patients receiving immunotherapy, and the factors related to immunotherapy response were further examined.ResultsOf the 10 patients from our institute, the median age was 53.5 years, adrenal glands and distant lymph nodes were the most common metastatic sites, and 4 of 8 (50%) patients had a PD-L1 TPS ≥50%. The median progression-free survival and overall survival in patients from our institute and from the literature were 11.6 and 27.3 months, 17.2 months and not reached, respectively. In all 36 patients, the objective response rate was as high as 57.6%. Patients with higher PD-L1 expression were more likely to have a tumor response, but the association of PD-L1 expression with survival time remains to be determined.ConclusionsPD-1/PD-L1 inhibitors in patients with pulmonary LELC demonstrated a promising efficacy in retrospective cohorts, and deserve further validation in prospective studies administrating in front-line setting

Genetically engineered cell membrane-coated nanoparticles for antibacterial and immunoregulatory dual-function treatment of ligature-induced periodontitis

Purpose: In order to overcome the problem that conventional pharmacological treatments of periodontitis cannot effectively synergizing antimicrobial and immunomodulation, inspired by the critical role of toll-like receptor 4 (TLR4) in bacterial recognition and immune activation, we demonstrated a combined antibacterial-immunoregulatory strategy based on biomimetic nanoparticles.Methods: Functioned cell membranes and silk fibroin nanoparticles (SNs) loaded with minocycline hydrochloride (Mino) were used to prepare a biomimetic nanoparticle (MSNCs). SNs and MSNCs were characterized by Scanning Electron Microscope, size, zeta potential, dispersion index. At the same time, SNs were characterized by cell counting kit-8 and real-time Polymerase Chain Reaction (RT-PCR). TLR4-expressing cell membranes were characterized by RT-PCR and western blot (WB). Cell membrane coating was characterized by Transmission Electron Microscope (TEM), the Bradford staining and WB. Then, Laser confocal, flow cytometry and agar plate coating were evaluated in vitro with antibacterial effects, RT-PCR was simultaneously evaluated with immunoregulatory effects. Finally, Anti-inflammatory treatment of MSNCs was evaluated in a ligature-induced periodontitis (LIP) mouse model.Results: Successfully prepared cell membranes overexpressing TLR4 and constructed MSNCs. In vitro studies had shown that MSNCs effectively targeted bacteria via TLR4 and acted as molecular decoys to competitively neutralize lipopolysaccharide (LPS) in the microenvironment as well as inhibit inflammatory activation of macrophages. In vivo, MSNCs effectively attenuated periodontal tissue inflammation and alveolar bone loss in a LIP mouse model.Conclusion: MSNCs have good targeted antibacterial and immunoregulatory effects, and provide a new and effective strategy for the treatment of periodontitis and have good potential for application in various types of pathogenic bacterial infections

Electrical and magnetic properties of antiferromagnetic semiconductor MnSi2N4 monolayer

Two-dimensional antiferromagnetic semiconductors have triggered significant attention due to their unique physical properties and broad application. Based on first-principles calculations, a novel two-dimensional (2D) antiferromagnetic material MnSi2N4 monolayer is predicted. The calculation results show that the two-dimensional MnSi2N4 prefers an antiferromagnetic state with a small band gap of 0.26 eV. MnSi2N4 has strong antiferromagnetic coupling which can be effectively tuned under strain. Interestingly, the MnSi2N4 monolayer exhibits a half-metallic ferromagnetic properties under an external magnetic field, in which the spin-up electronic state displays a metallic property, while the spin-down electronic state exhibits a semiconducting characteristic. Therefore, 100% spin polarization can be achieved. Two-dimensional MnSi2N4 monolayer has potential application in the field of high-density information storage and spintronic devices

Enhanced Osseointegration of Hierarchically Structured Ti Implant with Electrically Bioactive SnO₂-TiO₂ Bilayered Surface

The poor osseointegration of Ti implant significantly compromise its application in load-bearing bone repair and replacement. Electrically bioactive coating inspirited from heterojunction on Ti implant can benefit osseointegration but cannot avoid the stress shielding effect between bone and implant. To resolve this conflict, hierarchically structured Ti implant with electrically bioactive SnO2–TiO2 bilayered surface has been developed to enhance osseointegration. Benefiting from the electric cue offered by the built-in electrical field of SnO2–TiO2 heterojunction and the topographic cue provided by the hierarchical surface structure to bone regeneration, the osteoblastic function of basic multicellular units around the implant is significantly improved. Because the individual TiO2 or SnO2 coating with uniform surface exhibits no electrical bioactivity, the effects of electric and topographic cues to osseointegration have been decoupled via the analysis of in vivo performance for the placed Ti implant with different surfaces. The developed Ti implant shows significantly improved osseointegration with excellent bone–implant contact, improved mineralization of extracellular matrix, and increased push-out force. These results suggest that the synergistic strategy of combing electrical bioactivity with hierarchical surface structure provides a new platform for developing advanced endosseous implants

Genome Sequencing of the Sweetpotato Whitefly \u3cem\u3eBemisia tabaci\u3c/em\u3e MED/Q

The sweetpotato whitefly Bemisia tabaci is a highly destructive agricultural and ornamental crop pest. It damages host plants through both phloem feeding and vectoring plant pathogens. Introductions of B. tabaci are difficult to quarantine and eradicate because of its high reproductive rates, broad host plant range, and insecticide resistance. A total of 791 Gb of raw DNA sequence from whole genome shotgun sequencing, and 13 BAC pooling libraries were generated by Illumina sequencing using different combinations of mate-pair and pair-end libraries. Assembly gave a final genome with a scaffold N50 of 437 kb, and a total length of 658 Mb. Annotation of repetitive elements and coding regions resulted in 265.0 Mb TEs (40.3%) and 20 786 protein-coding genes with putative gene family expansions, respectively. Phylogenetic analysis based on orthologs across 14 arthropod taxa suggested that MED/Q is clustered into a hemipteran clade containing A. pisum and is a sister lineage to a clade containing both R. prolixus and N. lugens. Genome completeness, as estimated using the CEGMA and Benchmarking Universal Single-Copy Orthologs pipelines, reached 96% and 79%. These MED/Q genomic resources lay a foundation for future \u27pan-genomic\u27 comparisons of invasive vs. noninvasive, invasive vs. invasive, and native vs. exotic Bemisia, which, in return, will open up new avenues of investigation into whitefly biology, evolution, and management

Prediction and Optimal Scheduling of Advertisements in Linear Television

Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of impressions in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue

Prediction and Optimal Scheduling of Advertisements in Linear Television

Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of impressions in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue