Enabling Weak LLMs to Judge Response Reliability via Meta Ranking

Despite the strong performance of large language models (LLMs) across a wide range of tasks, they still have reliability issues. Previous studies indicate that strong LLMs like GPT-4-turbo excel in evaluating the reliability of responses from LLMs, but face efficiency and local deployment issues. Thus, to enable weak LLMs to effectively assess the reliability of LLM responses, we propose a novel cross-query-comparison-based method called $\textit{Meta Ranking}$ (MR). Unlike previous few-shot methods that solely based on in-context learning capabilities in LLMs, MR assesses reliability by pairwisely ranking the target query-response pair with multiple reference query-response pairs. We found that MR is highly effective in error detection for LLM responses, where weak LLMs, such as Phi-2, could surpass strong baselines like GPT-3.5-turbo, requiring only five reference samples and significantly improving efficiency. We further demonstrate that MR can enhance strong LLMs' performance in two practical applications: model cascading and instruction tuning. In model cascading, we combine open- and closed-source LLMs to achieve performance comparable to GPT-4-turbo with lower costs. In instruction tuning, we use MR for iterative training data filtering, significantly reducing data processing time and enabling LLaMA-7B and Phi-2 to surpass Alpaca-13B with fewer training tokens. These results underscore the high potential of MR in both efficiency and effectiveness.Comment: Preprint, under review. 28 page

Expression of SET Protein in the Ovaries of Patients with Polycystic Ovary Syndrome

Background. We previously found that expression of SET gene was up-regulated in polycystic ovaries by using microarray. It suggested that SET may be an attractive candidate regulator involved in the pathophysiology of polycystic ovary syndrome (PCOS). In this study, expression and cellular localization of SET protein were investigated in human polycystic and normal ovaries. Method. Ovarian tissues, six normal ovaries and six polycystic ovaries, were collected during transsexual operation and surgical treatment with the signed consent form. The cellular localization of SET protein was observed by immunohistochemistry. The expression levels of SET protein were analyzed by Western Blot. Result. SET protein was expressed predominantly in the theca cells and oocytes of human ovarian follicles in both PCOS ovarian tissues and normal ovarian tissues. The level of SET protein expression in polycystic ovaries was triple higher than that in normal ovaries (P<0.05). Conclusion. SET was overexpressed in polycystic ovaries more than that in normal ovaries. Combined with its localization in theca cells, SET may participate in regulating ovarian androgen biosynthesis and the pathophysiology of hyperandrogenism in PCOS

Effects of Foliar Selenite on the Nutrient Components of Turnip (Brassica rapa var. rapa Linn.)

We administered foliar applications of 50, 100, and 200 mg L−1 selenium (Se, selenite) on turnip (Brassica rapa var. rapa Linn.) and detected the changes in the main nutrient components in fleshy roots. Results showed that the foliar application of Se (IV) significantly increased the Se content in turnip, and Se (IV) positively affected the uptake of several mineral elements, including magnesium, phosphorus, iron, zinc, manganese, and copper. Se (IV) treatments also improved the synthesis of protein and multiple amino acids instead of crude fat and total carbohydrate in turnip, indicating that the foliar application of Se (IV) could enhance Se biofortification in turnip and promote its nutritional value. We recommended 50–100 mg L−1 Se treatment for foliar application on turnip based on the daily intake of Se for adults (96–139 μg person−1 day−1) and its favorable effects on the nutrient components of turnip

Coupling Coordination of Built-Up Land Intensity and Green Land-Use Efficiency in Hainan Island Based on Multi-Source Heterogeneous Data Fusion

Aligning urban land development intensity with green land-use efficiency (GLUE) is crucial for fostering high-quality regional growth. This study aims to examine the coupling and coordination between built-up land intensity (BUI) and GLUE by utilizing multi-source heterogeneous data for Hainan Island (2017, 2020). A coupling coordination degree model and Geographical Detector are applied to quantify BUI, GLUE, and their coupling coordination, while also identifying the underlying driving factors. The results reveal the following: (i) Following the Free Trade Port initiative, BUI increased by 15.8%, while GLUE grew by 4.9%; (ii) The BUI&ndash;GLUE system is still in an adjustment phase, with 94% of jurisdictions showing low coordination; (iii) The primary drivers of coupling have shifted from economic fundamentals to policy and institutional guidance, with their interactions demonstrating significant synergies. These findings suggest that policy-induced land expansion may outpace improvements in GLUE, potentially leading to an imbalance in the land system. This paper introduces an innovative Driver&ndash;Response&ndash;Feedback and Production&ndash;Living&ndash;Ecological (DRF&ndash;PLE) framework and develops a transferable diagnostic tool for evaluating land-use system sustainability in rapidly urbanizing regions

Selenium Accumulation Characteristics and Biofortification Potentiality in Turnip (Brassica rapa var. rapa) Supplied with Selenite or Selenate

Selenium (Se) is an essential trace element for humans. About 70% of the regions in China, including most of the Tibetan Plateau, are faced with Se deficiency problems. Turnip is mainly distributed around the Tibetan Plateau and is one of the few local crops. In the present study, we compared the absorption and translocation differences of Se (IV) selenite and Se (VI) selenate in turnip. The results showed that Se treatment, either by soil addition (0.2–2 mg Se kg−1 dry soil) or by foliar spraying (50–200 mg L−1 Se), could significantly increase the Se concentrations in turnips, and 0.5 mg Se (IV) or Se (VI) kg−1 dry matter in soils could improve the biomasses of turnips. Moreover, turnip absorbed significantly more Se (VI) than Se (IV) at the same concentration and also transferred much more Se (VI) from roots to leaves. Based on the Se concentrations, as well as the bioconcentration factors and translocation coefficients, we considered that turnip might be a potential Se indicator plant. Subsequently, we estimated the daily Se intake for adults based on the Se concentrations in turnip roots. The results indicated that Se (IV) should be more suitable as an artificial Se fertilizer for turnips, although the levels found in most samples in this study could cause selenosis to humans. In addition, we also estimated the optimum and maximum Se concentrations for treating turnips based on the linear relations between Se concentrations in turnip roots and Se treatment concentrations. The results provided preliminary and useful information about Se biofortification in turnips