One Embedder, Any Task: Instruction-Finetuned Text Embeddings

We introduce INSTRUCTOR, a new method for computing text embeddings given task instructions: every text input is embedded together with instructions explaining the use case (e.g., task and domain descriptions). Unlike encoders from prior work that are more specialized, INSTRUCTOR is a single embedder that can generate text embeddings tailored to different downstream tasks and domains, without any further training. We first annotate instructions for 330 diverse tasks and train INSTRUCTOR on this multitask mixture with a contrastive loss. We evaluate INSTRUCTOR on 70 embedding evaluation tasks (66 of which are unseen during training), ranging from classification and information retrieval to semantic textual similarity and text generation evaluation. INSTRUCTOR, while having an order of magnitude fewer parameters than the previous best model, achieves state-of-the-art performance, with an average improvement of 3.4% compared to the previous best results on the 70 diverse datasets. Our analysis suggests that INSTRUCTOR is robust to changes in instructions, and that instruction finetuning mitigates the challenge of training a single model on diverse datasets. Our model, code, and data are available at https://instructor-embedding.github.io.Comment: Accepted in ACL2023 Finding

Lemur: Harmonizing Natural Language and Code for Language Agents

We introduce Lemur and Lemur-Chat, openly accessible language models optimized for both natural language and coding capabilities to serve as the backbone of versatile language agents. The evolution from language chat models to functional language agents demands that models not only master human interaction, reasoning, and planning but also ensure grounding in the relevant environments. This calls for a harmonious blend of language and coding capabilities in the models. Lemur and Lemur-Chat are proposed to address this necessity, demonstrating balanced proficiencies in both domains, unlike existing open-source models that tend to specialize in either. Through meticulous pre-training using a code-intensive corpus and instruction fine-tuning on text and code data, our models achieve state-of-the-art averaged performance across diverse text and coding benchmarks among open-source models. Comprehensive experiments demonstrate Lemur's superiority over existing open-source models and its proficiency across various agent tasks involving human communication, tool usage, and interaction under fully- and partially- observable environments. The harmonization between natural and programming languages enables Lemur-Chat to significantly narrow the gap with proprietary models on agent abilities, providing key insights into developing advanced open-source agents adept at reasoning, planning, and operating seamlessly across environments. https://github.com/OpenLemur/Lemu

Strain Screening and Conditions Optimization in Microalgae-Based Monosodium Glutamate Wastewater (MSGW) Treatment

The wastewater generated from monosodium glutamate production displays distinctive features of elevated salinity, organic content, as well as nitrogen and phosphorus concentrations, and its indiscriminate disposal poses a significant threat to water quality and can cause detrimental impacts on aquatic ecosystems. The application of microalgae for monosodium glutamate wastewater (MSGW) treatment can result in simultaneous wastewater purification and biomass recovery. In this study, the algae species capable of thriving in diluted MSGW were screened, and the wastewater composition and growth conditions were optimized to obtain high algal biomass and nutrient removal rate. Among the tested species, Chlorella sp. FACHB-30 demonstrated superior potential for MSGW treatment and achieved a maximum specific growth rate of 0.28 d−1 and the highest COD removal rate of 61.50% over a 20-day cultivation period with trace metals supplementation in the wastewater. Moreover, the cultivation of Chlorella sp. FACHB-30 yielded considerable reductions in total phosphate (69.09%), total nitrogen (26.93%), and NH4+-N (51.91%) levels in the wastewater. The optimum conditions for achieving maximum algal density and highest nutrient removal were determined as light intensity of 150 μmol m−2s−1, inoculation concentration of 1 × 105 cells mL−1, and an iron concentration of 10−5 mol L−1. Finally, under the optimized conditions, the removal rates of total phosphate, total nitrogen, NH4+-N, and COD were determined to be 87.60%, 68.05%, 75.89%, and 77.96%, respectively. The findings of this study highlight the potential for enhancing the nutrient removal efficiency of microalgae-based MSGW treatment through the implementation of a combined approach that involves the selection of tolerant strains, optimization of cultivation conditions, and refinement of wastewater composition

Effects of Iron Valence on the Growth, Photosynthesis, and Fatty Acid Composition of Phaeodactylum tricornutum

Iron is a limiting factor that controls the phytoplankton biomass of the ocean and plays an important role in the lipid production of microalgae. Elucidating the effects of different iron valences on microalgae is helpful for their commercial production. We investigated the growth, photosynthesis, and fatty acid profile of the model diatom Phaeodactylum tricornutum cultured with depleted Fe, Fe2+, Fe2+/Fe3+, and Fe3+. Samples were taken every 24 h for 8 days, and their cell density, photosynthetic pigment content, chlorophyll fluorescence, total fatty acid content, and fatty acid composition were analyzed. The cell densities of the Fe2+ and Fe2+/Fe3+ groups were significantly higher than those of the control and Fe3+ groups (p < 0.05). They were 1.26 times and 1.23 times higher than those in the Fe-depleted group. The contents of chlorophyll a and c in the Fe2+ group were significantly higher than those in the Fe-depleted group (p < 0.05). The chlorophyll fluorescence results show that Fe2+ enhanced the photosynthesis of P. tricornutum to a greater extent than Fe3+. On the eighth day of harvest, Fv/Fm and Y(II) in the Fe2+ group were 0.672 and 0.476, respectively, being 1.10 and 1.19 times greater than those in the Fe3+ group and 1.15 and 1.33 times greater than those in the Fe-depleted group, respectively. Compared with the control group, the levels of saturated fatty acids of the Fe2+/Fe3+ and Fe3+ groups were significantly higher (p < 0.05) at 21.36 ± 1.24% and 21.20 ± 0.13%, respectively. The levels of polyunsaturated fatty acids of the Fe2+/Fe3+ group were significantly lower (p < 0.05) at 29.82 ± 2.75%. Our results show that P. tricornutum exhibited physiological plasticity, including changes in photosynthetic activities and shifts in fatty acid composition, in response to different iron valences and that Fe2+ was more beneficial to the biomass production of this species than Fe3+. These findings are applicable to the production of biomass and polyunsaturated fatty acids

A novel photoanode with three-dimensionally, hierarchically ordered nanobushes for highly efficient photoelectrochemical cells

A 3D hierarchically ordered nanobush structure is fabricated for use as a photoanode in photoelectrochemical cells. The photoanode structure has several favorable intrinsic characteristics, including high interface area, direct electron transport pathways, and engineered light scattering centers. Sensitization with CdS quantum dots is demonstrated, and this nanobush photoanode is expected to be advantageous also in solar cells

Psoriasis complicated with metabolic disorder is associated with traditional Chinese medicine syndrome types: a hospital-based retrospective case-control study

To explore the distribution law of traditional Chinese medicine (TCM) syndrome types in patients with psoriasis vulgaris complicated by metabolic disorders based on the same pathogenic factors as blood-heat and blood-stasis in the pathogenesis of psoriasis and metabolic disorders and to further analyze the correlation between adiponectin and the distribution law. From January 1, 2018, to December 31, 2019, patients diagnosed with psoriasis in the inpatient or outpatient department of Dermatology Ward of Shanghai Yueyang Hospital and normal participants who underwent physical examination in the physical examination center over the same period were retrospectively reviewed. Demographic data, medical history, metabolic disorder indices, and TCM syndrome indices of psoriasis patients and healthy volunteers were evaluated. We included 307 patients with psoriasis and 613 healthy controls. On analyzing past medical history, the proportion of overweight and obesity and the comorbidity of diabetes in the psoriasis group (53.42% and 14.66%) were significantly higher than in the control group (43.88% and 7.67%, respectively; P P P  TCM syndrome differentiation of psoriasis, especially the diagnosis of blood-stasis syndrome, prompts the early screening of patients with metabolic comorbidities. For patients with psoriasis with metabolic disorder, TCM for promoting blood circulation and removing blood stasis can be compatibly applied without contraindications. The trial was registered at ClinicalTrials.gov (Trial ID: NCT03942185).</p