Data-Augmented and Retrieval-Augmented Context Enrichment in Chinese Media Bias Detection

With the increasing pursuit of objective reports, automatically understanding media bias has drawn more attention in recent research. However, most of the previous work examines media bias from Western ideology, such as the left and right in the political spectrum, which is not applicable to Chinese outlets. Based on the previous lexical bias and informational bias structure, we refine it from the Chinese perspective and go one step further to craft data with 7 fine-grained labels. To be specific, we first construct a dataset with Chinese news reports about COVID-19 which is annotated by our newly designed system, and then conduct substantial experiments on it to detect media bias. However, the scale of the annotated data is not enough for the latest deep-learning technology, and the cost of human annotation in media bias, which needs a lot of professional knowledge, is too expensive. Thus, we explore some context enrichment methods to automatically improve these problems. In Data-Augmented Context Enrichment (DACE), we enlarge the training data; while in Retrieval-Augmented Context Enrichment (RACE), we improve information retrieval methods to select valuable information and integrate it into our models to better understand bias. Extensive experiments are conducted on both our dataset and an English dataset BASIL. Our results show that both methods outperform our baselines, while the RACE methods are more efficient and have more potential

A Cullin-1 Based SCF E3 Ligase Complex Directs Two Distinct Modes of Neuronal Pruning in Drosophila Melanogaster

Ph.DDOCTOR OF PHILOSOPH

IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators

This study focuses on media bias detection, crucial in today's era of influential social media platforms shaping individual attitudes and opinions. In contrast to prior work that primarily relies on training specific models tailored to particular datasets, resulting in limited adaptability and subpar performance on out-of-domain data, we introduce a general bias detection framework, IndiVec, built upon large language models. IndiVec begins by constructing a fine-grained media bias database, leveraging the robust instruction-following capabilities of large language models and vector database techniques. When confronted with new input for bias detection, our framework automatically selects the most relevant indicator from the vector database and employs majority voting to determine the input's bias label. IndiVec excels compared to previous methods due to its adaptability (demonstrating consistent performance across diverse datasets from various sources) and explainability (providing explicit top-k indicators to interpret bias predictions). Experimental results on four political bias datasets highlight IndiVec's significant superiority over baselines. Furthermore, additional experiments and analysis provide profound insights into the framework's effectiveness

Single and Multiple-Band Bandpass Filters Using Bandstop Resonator Sections

In this paper, the design methodology and implementation of single-band and multiple-band elliptic function bandpass filters (BPFs) are presented, based on the concept of bandstop resonator (BSR) sections. One or more single-mode and multiple-mode BSRs can be dangled from a non-resonant node. Each BSR can generate one reflection zeroes (RZ) and one transmission zeroes (TZ). Multiple BSR sections are used to flexibly and independently control the location and bandwidth of the stop bands and therefore the same of the passbands. The method to design single- and multiple-band elliptic function BPFs has been detailed using a number of examples based on waveguide technology. For proof of concept, a 6th-order single-band BPF with six BSR&amp;#x00A0;&amp;#x003D;&amp;#x00A0;2 sections and a 3rd-order dual-band BPF using three BSR&amp;#x00A0;&amp;#x003D;&amp;#x00A0;3 sections are designed and fabricated monolithically using a selective-laser-melting (SLM) 3-D printing technique. Excellent agreement between simulated and measured results verifies the proposed design methodology and its versatility as well as the additive-manufacture approach.</p

In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line

To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQ™ quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway Analysis™ (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death

Viscoelastic solid-repellent coatings for extreme water saving and global sanitation

Water scarcity threatens over half of the world’s population, yet over 141 billion litres of fresh water are used globally each day for toilet flushing. This is nearly six times the daily water consumption of the population in Africa. The toilet water footprint is so large primarily because large volumes of water are necessary for the removal of human faeces; human faeces is viscoelastic and sticky in nature, causing it to adhere to conventional surfaces. Here, we designed and fabricated the liquid-entrenched smooth surface (LESS)—a sprayable non-fouling coating that can reduce cleaning water consumption by ~90% compared with untreated surfaces due to its extreme repellency towards liquids, bacteria and viscoelastic solids. Importantly, LESS-coated surfaces can repel viscoelastic solids with dynamic viscosities spanning over nine orders of magnitude (that is, three orders of magnitude higher than has previously been reported for other repellent materials). With an estimated 1 billion or more toilets and urinals worldwide, incorporating LESS coating into sanitation systems will have significant implications for global sanitation and large-scale wastewater reduction for sustainable water management

Factors affecting hotel visitors' usage of guest empowerment technology (GET)

The aim of this study is to determine the factors affecting the usage of Guest Empowerment Technologies (GET) in hotels among hotel visitors in Labuan, Malaysia. The research used multiple regression for data analysis across a sample of 225 respondents who stayed in hotel at least once in a year. Their participation was voluntarily. Results confirmed that the core factor affecting users' intention to use of GET is perceived usefulness. Meanwhile, all variables are proven to be significant to each other and perceived usefulness had the strongest influencing on the users' intention to use of GET. The findings provide additional information to the hotels for further understanding their consumers' characteristics in hotels. Having this information, the proposed framework can be use as the basis for further research

Replication and Meta-analysis of the Association between BDNF Val66Met Polymorphism and Cognitive Impairment in Patients Receiving Chemotherapy.

Cancer-related cognitive impairment (CRCI) adversely affects cancer patients. We had previously demonstrated that the BDNF Val66Met genetic polymorphism is associated with lower odds of subjective CRCI in the multitasking and verbal ability domains among breast cancer patients receiving chemotherapy. To further assess our previous findings, we evaluated the association of BDNF Val66Met polymorphism with subjective and objective CRCI in a temporally separate cohort of patients and pooled findings from both the original (n = 145) and current (n = 193) cohorts in a meta-analysis. Subjective CRCI was assessed using FACT-Cog. Objective CRCI was evaluated using computerized neuropsychological tests. Genotyping was carried out using Sanger sequencing. The association of BDNF Val66Met genotypes and CRCI was examined with logistic regression. A fixed-effect meta-analysis was conducted using the inverse variance method. In the meta-analysis (n = 338), significantly lower odds of CRCI were associated with Met allele carriers based on the global FACT-Cog score (OR = 0.52, 95% CI 0.29-0.94). Furthermore, Met allele carriers were at lower odds of developing impairment in the domains of memory (OR = 0.34, 95% CI: 0.17-0.70), multitasking (OR = 0.33, 95% CI: 0.18-0.59), and verbal ability (OR = 0.46, 95% CI: 0.24-0.88). Consistent with the previous study, lower odds of subjective CRCI among patients with the BDNF Met allele was observed after adjusting for potential confounders in the multitasking (OR = 0.30, 95% CI: 0.14-0.67) domain. In conclusion, carriers of the BDNF Met allele were protected against global subjective CRCI, particularly in the domains of memory, multitasking, and verbal ability. Our findings further contribute to the understanding of CRCI pathophysiology