Rethinking Item Importance in Session-based Recommendation

Session-based recommendation aims to predict users' based on anonymous sessions. Previous work mainly focuses on the transition relationship between items during an ongoing session. They generally fail to pay enough attention to the importance of the items in terms of their relevance to user's main intent. In this paper, we propose a Session-based Recommendation approach with an Importance Extraction Module, i.e., SR-IEM, that considers both a user's long-term and recent behavior in an ongoing session. We employ a modified self-attention mechanism to estimate item importance in a session, which is then used to predict user's long-term preference. Item recommendations are produced by combining the user's long-term preference and current interest as conveyed by the last interacted item. Experiments conducted on two benchmark datasets validate that SR-IEM outperforms the start-of-the-art in terms of Recall and MRR and has a reduced computational complexity

Field Experimental Study on Corrosion Mechanism of Well Lai 14-9

Casing corrosion is serious and the injection efficiency is considerably low due to high injecting water corrosion in Well Lai 14-9. Casing corrosion mechanism is retrieved through SEM observation, energy spectrum analysis, XRD analysis spectrum, TGA analysis of corrosion fouling. The results show casing corrosion mechanism varies with depths; casing corrosion is the result of the combined action of carbon dioxide, dissolved oxygen, sulfate-reducing bacteria and high salinity. To extend the life of casing, appropriate casing protection measures should be adopted, which can reduces the cost of production of the oilfield.Key words: Corrosion mechanism; Fouling; SEM observation; XRD analysis spectrum; TGA analysi

Potential Application of Copper Aspirinate in Preventing and Treating Thromboembolic Diseases

The efficacy of copper aspirinate against thrombotic diseases has been tested in animal models. The results show that copper aspirinate, following ig pretreatment for 7 days at 0.012mmol/kg markedly prolonged the bleeding time and inhibited the mortality induced by arachidonic acid (AA) in mice. On cereral ischemia model pretreatment with 0.018mmol/kg copper aspirinate ig significantly increased survival of animals and the density of intact hippocampal CA1 cells and decreased brain calcium concentration. Its anticerebral ischemia activity was superior to or equal to nimodipine. It is, therefore, suggested that copper aspirinate is very promising in becoming an antithrombotic drug in preventing and treating thrombotic diseases

Cerebroprotective Effects of Dimeric Copper(II) Bis(o-acetoxybenzoate) on Ischemia-reperfusion Injury in Gerbils

The cerebroprotective effects of copper aspirinate [dimeric copper(II) bis(o-acetoxybenzoate)] were investigated in gerbils subjected to 10-min global cerebral ischemia followed b 60-min reperfusion. The results showed that intragastric copper aspirinate (7.5, 15.0 and 30.0 mg Kg−1) markedly promoted the recovery of the electroencephalogram amplitude, attenuated the increase of lipid peroxide content and the decrease of superoxide dismutase activity in the cortex during ischemia-reperfusion injury. It suggested that copper aspirinate possesses potential neuroprotective properties, the mechanism of which might be related to an increase of the activity of endogenous superoxide dismutase

Generalized Rake Receiver for Spreading-IFDMA Systems

Abstract. Spreading-Interleaved Frequency Division Multiple Access (IFDMA) providing code domain multiplexing for one IFDMA channel shows improved spectrum efficiency and good compatibility with CDMA systems while maintaining advantages of IFDMA systems. A generalized Rake receiver for Spreading-IFDMA is proposed in this paper, which combines jointly derepetition, equalization, and de-spreading processing. Similar to the conventional CDMA systems, the guard interval in Spreading-IFDMA symbols is not necessary, which means that spectrum efficiency can be further improved over IFDMA systems. With digital simulations and performance analysis, the proposed generalized Rake receiver demonstrates better BER performance, robustness, and lower computational complexity

A prediction model using alternative splicing events and the immune microenvironment signature in lung adenocarcinoma

Background: Alternative splicing (AS) is a gene regulatory mechanism that drives protein diversity. Dysregulation of AS is thought to play an essential role in cancer initiation and development. This study aimed to construct a prognostic signature based on AS and explore the role in the tumor immune microenvironment (TIME) in lung adenocarcinoma. Methods: We analyzed transcriptome profiling and clinical lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq. Prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan–Meier survival analyses, and proportional hazards model. The context of TIME in lung adenocarcinoma was also analyzed. Gene and protein expression data of Cyclin-Dependent Kinase Inhibitor 2A (CDKN2A) were obtained from ONCOMINE and Human Protein Atlas. Splicing factor (SF) regulatory networks were visualized. Results: A total of 19,054 survival-related AS events in lung adenocarcinoma were screened in 1,323 genes. Exon skip (ES) and mutually exclusive exons (ME) exhibited the most and fewest AS events, respectively. Based on AS subtypes, eight AS prognostic signatures were constructed. Patients with high-risk scores were associated with poor overall survival. A nomogram with good validity in prognostic prediction was generated. AUCs of risk scores at 1, 2, and 3 years were 0.775, 0.736, and 0.759, respectively. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. Low-risk patients had a higher StromalScore, ImmuneScore, and ESTIMATEScore. AS-based risk score signature was positively associated with CD8+ T cells. CDKN2A was also found to be a prognostic factor in lung adenocarcinoma. Finally, potential functions of SFs were determined by regulatory networks. Conclusion: Taken together, our findings show a clear association between AS and immune cell infiltration events and patient outcome, which could provide a basis for the identification of novel markers and therapeutic targets for lung adenocarcinoma. SF networks provide information of regulatory mechanisms

Comparison of Efficacy of Deep Brain Stimulation of Different Targets in Parkinson's Disease: A Network Meta-Analysis

Background: Deep brain stimulation (DBS) is considered an effective treatment option for Parkinson's disease (PD). Several studies have demonstrated the efficacy of neurostimulation in patients with advanced PD. The subthalamic nucleus (STN), the internal globus pallidus (GPi), ventral intermediate nucleus (Vim), and pedunculopontine nucleus (PPN) are reportedly effective DBS targets for control of Parkinsonian tremors. However, there is no consensus on the ideal target for DBS in patients with Parkinson's disease. Only a few studies have directly compared the efficacy of DBS of the Vim, STN, and GPi. Therefore, we searched PubMed, Embase, Cochrane Library, and other databases for observational studies, extracted data on unified Parkinson's disease rating scale (UPDRS) scores and performed a comprehensive network meta-analysis of different strategies of DBS and compared the efficiency of DBS at different targets.Methods: Forest plot was used to examine the overall efficiency of DBS; cumulative probability value was used to rank the strategies under examination. A node-splitting model was employed to assess consistency of reported outcomes inconsistency. A total of 16 studies which focused on UPDRS improvement were included in the network meta-analysis.Results: By comparing the overall efficiency associated with each target, we confirmed the efficacy of DBS therapy in PD. Our findings revealed similar efficacy of DBS targeted at GPi and STN in the on-medication phase [GPi-3.9 (95% CI −7.0 to −0.96); STN-3.1 (−5.9 to −0.38)]; however, in the off-medication phase, Vim-targeted DBS was associated with better improvement in UPDRS scores and could be a choice as a DBS target for tremor-dominant Parkinsonism.Conclusions: Our findings will help improve clinical application of DBS

Trends and profiles of acute poisoning cases: a retrospective analysis

Acute poisoning is a significant public health concern. This retrospective study investigates trends in acute poisoning cases and explores the clinical and sociodemographic profiles associated with this condition. Medical data from 859 hospitalized patients diagnosed with acute poisoning between January 2017 and December 2022 were comprehensively analyzed. The descriptive statistical analysis revealed that 360 patients had underlying diseases, with depression being the most prevalent among them. Furthermore, urban areas accounted for 87.2% of the acute poisoning cases, indicating a higher incidence compared to rural areas. The substances implicated in acute poisoning incidents varied, with drugs of abuse being the most common (53.2%), followed by pesticides (22.2%), carbon monoxide (11.8%), and alcohol (5.4%). Suicide attempt/suicide emerged as the leading cause of acute poisoning incidents, accounting for 75.9% of cases, while poisoning accidents predominantly occurred within the home setting. Through chi-square tests, it was determined that risk factors for suicide attempt/suicide included female gender and underlying medical conditions. Temporal analysis showed that the total number of acute poisoning cases increased from 2017 to 2019 and decreased from 2019 to 2022. Notably, suicide-related cases exhibited an upward trend, with suicide attempt/suicide accounting for over 80% of all acute poisoning cases after 2020. This study contributes valuable insights into the trends, profiles, and risk factors associated with acute poisoning cases