Streamlined Data Fusion: Unleashing the Power of Linear Combination with Minimal Relevance Judgments

Linear combination is a potent data fusion method in information retrieval tasks, thanks to its ability to adjust weights for diverse scenarios. However, achieving optimal weight training has traditionally required manual relevance judgments on a large percentage of documents, a labor-intensive and expensive process. In this study, we investigate the feasibility of obtaining near-optimal weights using a mere 20\%-50\% of relevant documents. Through experiments on four TREC datasets, we find that weights trained with multiple linear regression using this reduced set closely rival those obtained with TREC's official "qrels." Our findings unlock the potential for more efficient and affordable data fusion, empowering researchers and practitioners to reap its full benefits with significantly less effort.Comment: 12 pages, 8 figure

Intention-Aware Planner for Robust and Safe Aerial Tracking

The intention of the target can help us to estimate its future motion state more accurately. This paper proposes an intention-aware planner to enhance safety and robustness in aerial tracking applications. Firstly, we utilize the Mediapipe framework to estimate target's pose. A risk assessment function and a state observation function are designed to predict the target intention. Afterwards, an intention-driven hybrid A* method is proposed for target motion prediction, ensuring that the target's future positions align with its intention. Finally, an intention-aware optimization approach, in conjunction with particular penalty formulations, is designed to generate a spatial-temporal optimal trajectory. Benchmark comparisons validate the superior performance of our proposed methodology across diverse scenarios. This is attributed to the integration of the target intention into the planner through coupled formulations.Comment: 7 pages, 10 figures, submitted to 2024 IEEE International Conference on Robotics and Automation (ICRA

Multilevel Nitrogen Additions Alter Chemical Composition and Turnover of the Labile Fraction Soil Organic Matter via Effects on Vegetation and Microorganisms

Global nitrogen (N) deposition greatly impacts soil carbon sequestration. A 2- yr multiple N addition (0, 10, 20, 40, 80, and 160 kg N·ha- 1·yr- 1) experiment was conducted in alpine grassland to illustrate the mechanisms underlying the observed soil organic matter (SOM) dynamics on the Qinghai- Tibet Plateau (QTP). Labile fraction SOM (LF- SOM) fingerprints were characterized by pyrolysis- gas chromatography/tandem- mass spectrometry, and microbial functional genes (GeoChip 4.6) were analyzed in conjunction with LF- SOM fingerprints to decipher the responses of LF- SOM transformation to N additions. The significant correlations between LF- SOM and microbial biomass, between organic compounds in LF- SOM and compound degradation- related genes, and between LF- SOM and net ecosystem exchange implied LF- SOM were the main fraction utilized by microorganisms and the most sensitive fraction to N additions. The LF- SOM increased at the lowest N addition levels (10 and 20 kg N·ha- 1·yr- 1) and decreased at higher N addition levels (40 to 160 kg N·ha- 1·yr- 1), but the decrease of LF- SOM was weakened at 160 kg N·ha- 1·yr- 1 addition. The nonlinear response of LF- SOM to N additions was due to the mass balance between plant inputs and microbial degradation. Plant- derived compounds in LF- SOM were more sensitive to N addition than microbial- derived and aromatic compounds. It is predicted that when the N deposition rate increased by 10 kg N·ha- 1·yr- 1 on the QTP, carbon sequestration in the labile fraction may increase by nearly 170% compared with that under the current N deposition rate. These findings provide insight into future N deposition impacts on LF- SOM preservation on the QTP.Key PointsThe LF- SOM quantity increased at the lowest N additions (N10 and N20) and decreased from N40 to N160, but the decrease was weakened at the highest N addition (N160)Plant- derived compounds in LF- SOM were more sensitive to N addition than microbial- derived and aromatic compoundsThe organic compounds in LF- SOM were significantly correlated with compound degradation- related genesPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154963/1/jgrg21637_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154963/2/jgrg21637.pd

Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients

The global coronavirus disease 2019 (COVID-19) pandemic has lasted for over 2 years now and has already caused millions of deaths. In COVID-19, leukocyte pyroptosis has been previously associated with both beneficial and detrimental effects, so its role in the development of this disease remains controversial. Using transcriptomic data (GSE157103) of blood leukocytes from 126 acute respiratory distress syndrome patients (ARDS) with or without COVID-19, we found that COVID-19 patients present with enhanced leukocyte pyroptosis. Based on unsupervised clustering, we divided 100 COVID-19 patients into two clusters (PYRcluster1 and PYRcluster2) according to the expression of 35 pyroptosis-related genes. The results revealed distinct pyroptotic patterns associated with different leukocytes in these PYRclusters. PYRcluster1 patients were in a hyperinflammatory state and had a worse prognosis than PYRcluster2 patients. The hyperinflammation of PYRcluster1 was validated by the results of gene set enrichment analysis (GSEA) of proteomic data (MSV000085703). These differences in pyroptosis between the two PYRclusters were confirmed by the PYRscore. To improve the clinical treatment of COVID-19 patients, we used least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model based on differentially expressed genes between PYRclusters (PYRsafescore), which can be applied as an effective prognosis tool. Lastly, we explored the upstream transcription factors of different pyroptotic patterns, thereby identifying 112 compounds with potential therapeutic value in public databases

Molecular Cloning and Expression Analysis of the Endogenous Cellulase Gene MaCel1 in Monochamus alternatus

The purpose of this study was to characterize the endogenous cellulase gene MaCel1 of Monochamus alternatus, which is an important vector of Bursaphelenchus xylophilus, a pine wood nematode, which causes pine wilt disease (PWD). In this study, MaCel1 was cloned by rapid amplification of cDNA end (RACE), and its expression analyzed by RT-qPCR (real-time quantitative PCR detecting). A total of 1778 bp of cDNA was obtained. The encoding region of this gene was 1509 bp in length, encoding a protein containing 502 amino acids with a molecular weight of 58.66 kDa, and the isoelectric point of 5.46. Sequence similarity analysis showed that the amino acids sequence of MaCel1 had high similarity with the beta-Glucosinolate of Anoplophora glabripennis and slightly lower similarity with other insect cellulase genes (GH1). The beta-D-Glucosidase activity of MaCel1 was 256.02 +/- 43.14 U/L with no beta-Glucosinolate activity. MaCel1 gene was widely expressed in the intestine of M. alternatus. The expression level of MaCel1 gene in male (3.46) and female (3.51) adults was significantly higher than that in other developmental stages, and the lowest was in pupal stage (0.15). The results will help reveal the digestive mechanism of M. alternatus and lay the foundation for controlling PWD by controlling M. alternatus

Gut Bacterial Communities of Lymantria xylina and Their Associations with Host Development and Diet

The gut microbiota of insects has a wide range of effects on host nutrition, physiology, and behavior. The structure of gut microbiota may also be shaped by their environment, causing them to adjust to their hosts; thus, the objective of this study was to examine variations in the morphological traits and gut microbiota of Lymantria xylina in response to natural and artificial diets using high-throughput sequencing. Regarding morphology, the head widths for larvae fed on a sterilized artificial diet were smaller than for larvae fed on a non-sterilized host-plant diet in the early instars. The gut microbiota diversity of L. xylina fed on different diets varied significantly, but did not change during different development periods. This seemed to indicate that vertical inheritance occurred in L. xylina mutualistic symbionts. Acinetobacter and Enterococcus were dominant in/on eggs. In the first instar larvae, Acinetobacter accounted for 33.52% of the sterilized artificial diet treatment, while Enterococcus (67.88%) was the predominant bacteria for the non-sterilized host-plant diet treatment. Gut microbe structures were adapted to both diets through vertical inheritance and self-regulation. This study clarified the impacts of microbial symbiosis on L. xylina and might provide new possibilities for improving the control of these bacteria

Metabolic risk factors of cognitive impairment in young women with major psychiatric disorder

BackgroundCognitive performance improves clinical outcomes of patients with major psychiatric disorder (MPD), but is impaired by hyperglycemia. Psychotropic agents often induce metabolism syndrome (MetS). The identification of modifiable metabolic risk factors of cognitive impairment may enable targeted improvements of patient care.ObjectiveTo investigate the relationship between MetS and cognitive impairment in young women with MPD, and to explore risk factors.MethodsWe retrospectively studied women of 18–34 years of age receiving psychotropic medications for first-onset schizophrenia (SCH), bipolar disorder (BP), or major depressive disorder (MDD). Data were obtained at four time points: presentation but before psychotropic medication; 4–8 and 8–12 weeks of psychotropic therapy; and enrollment. MATRICS Consensus Cognitive Battery, (MCCB)—based Global Deficit Scores were used to assess cognitive impairment. Multiple logistic analysis was used to calculate risk factors. Multivariate models were used to investigate factors associated with cognitive impairment.ResultsWe evaluated 2,864 participants. Cognitive impairment was observed in 61.94% of study participants, and was most prevalent among patients with BP (69.38%). HbA1c within the 8–12 week-treatment interval was the most significant risk factor and highest in BP. Factors in SCH included pre-treatment waist circumference and elevated triglycerides during the 8–12 weeks treatment interval. Cumulative dosages of antipsychotics, antidepressants, and valproate were associated with cognitive impairment in all MPD subgroups, although lithium demonstrated a protect effect (all P < 0.001).ConclusionsCognitive impairment was associated with elevated HbA1c and cumulative medication dosages. Pre-treatment waist circumference and triglyceride level at 8–12 weeks were risk factors in SCH. Monitoring these indices may inform treatment revisions to improve clinical outcomes