Effect of geometric factors on the energy performance of high-rise office towers in Tianjin, China

To improve energy efficiency of office buildings in Tianjin, we select a prototypical high-rise office tower as an example and focus on the effect of geometric factors on building energy performance. These factors include the orientation, plane shape, floor area, plane shape factor (the ratio of the plane length to the plane width, only as regards to a rectangle-shaped plane), floor height, floor number and window-to-wall ratio. The simulation is performed in DesignBuilder, which integrates artificial lighting with instantaneous daylight during the energy simulation process. The geometric factors of the defined prototype are examined in both single-parameter and multi-parameter evaluations. As to the multi-parameter results, the energy saving rate can vary by up to 18.9%, and reducing the floor height is observed to be the most effective means of reducing annual total end-use energy consumption, followed by increasing the plane shape factor and reducing the floor area. The results can serve as a reference for passive design strategies related to geometric factors in the early design stage

Leveraging Key Information Modeling to Improve Less-Data Constrained News Headline Generation via Duality Fine-Tuning

Recent language generative models are mostly trained on large-scale datasets, while in some real scenarios, the training datasets are often expensive to obtain and would be small-scale. In this paper we investigate the challenging task of less-data constrained generation, especially when the generated news headlines are short yet expected by readers to keep readable and informative simultaneously. We highlight the key information modeling task and propose a novel duality fine-tuning method by formally defining the probabilistic duality constraints between key information prediction and headline generation tasks. The proposed method can capture more information from limited data, build connections between separate tasks, and is suitable for less-data constrained generation tasks. Furthermore, the method can leverage various pre-trained generative regimes, e.g., autoregressive and encoder-decoder models. We conduct extensive experiments to demonstrate that our method is effective and efficient to achieve improved performance in terms of language modeling metric and informativeness correctness metric on two public datasets.Comment: Accepted by AACL-IJCNLP 2022 main conferenc

Precision ion separation via self-assembled channels

: Selective nanofiltration membranes with accurate molecular sieving offer a solution to recover rare metals and other valuable elements from brines. However, the development of membranes with precise sub-nanometer pores is challenging. Here, we report a scalable approach for membrane fabrication in which functionalized macrocycles are seamlessly oriented via supramolecular interactions during the interfacial polycondensation on a polyacrylonitrile support layer. The rational incorporation of macrocycles enables the formation of nanofilms with self-assembled channels holding precise molecular sieving capabilities and a threshold of 6.6 ångström, which corresponds to the macrocycle cavity size. The resulting membranes provide a 100-fold increase in selectivity for Li+/Mg2+ separation, outperforming commercially available and state-of-the-art nanocomposite membranes for lithium recovery. Their performance is further assessed in high-recovery tests under realistic nanofiltration conditions using simulated brines or concentrated seawater with various Li+ levels and demonstrates their remarkable potential in ion separation and Li+ recovery applications

Modifiable factors for irritable bowel syndrome: Evidence from Mendelian randomisation approach

Background The potential modifiable factors influencing irritable bowel syndrome (IBS) have not been thoroughly documented. We aimed to systematically investigate the modifiable factors associated with IBS, while accounting for the impact of unobserved confounders and coexisting disorders. Methods Genetic correlation and Mendelian randomisation (MR) analyses were integrated to identify potential modifiable factors and coexisting disorders linked to IBS. Subsequently, multiresponse MR (MR 2) was employed to further examine these associations. Summary-level genome-wide association data were used. Modifiable factors and coexisting disorders (ie, gastrointestinal and psychiatric disorders) were identified based on evidence from cohort studies and meta-analysis. In all analyses, IBS was the primary outcome, while in the MR 2 analysis, coexisting disorders were also treated as outcomes alongside IBS. Results Most identified modifiable factors and coexisting disorders exhibited genetic correlations with IBS. MR analyses revealed strong causation between IBS and multisite chronic pain (OR=2.20, 95% CI 1.82 to 2.66), gastro-oesophageal reflux disease (OR=1.31, 95% CI 1.23 to 1.39), well-being spectrum (OR=0.17, 95% CI 0.13 to 0.21), life satisfaction (OR=0.31, 95% CI 0.25 to 0.38), positive affect (OR=0.30, 95% CI 0.24 to 0.37), neuroticism score (OR=1.20, 95% CI 1.16 to 1.25) and depression (OR=1.50, 95% CI 1.37 to 1.66). Additionally, smoking, alcohol frequency, college or university degree, intelligence, childhood maltreatment, frailty index, diverticular disease of the intestine and schizophrenia were suggestively associated with IBS. Robust associations were found between multisite chronic pain and both IBS and coexisting disorders. Conclusions Our study identified a comprehensive array of potential modifiable factors and coexisting disorders associated with IBS, supported by genetic evidence, including genetic correlation and multiple MR analyses. The presence of multisite chronic pain may offer a promising avenue for the concurrent prevention of IBS and its coexisting disorders