AmericasNLI: Machine translation and natural language inference systems for Indigenous languages of the Americas.

Little attention has been paid to the development of human language technology for truly low-resource languages-i.e., languages with limited amounts of digitally available text data, such as Indigenous languages. However, it has been shown that pretrained multilingual models are able to perform crosslingual transfer in a zero-shot setting even for low-resource languages which are unseen during pretraining. Yet, prior work evaluating performance on unseen languages has largely been limited to shallow token-level tasks. It remains unclear if zero-shot learning of deeper semantic tasks is possible for unseen languages. To explore this question, we present AmericasNLI, a natural language inference dataset covering 10 Indigenous languages of the Americas. We conduct experiments with pretrained models, exploring zero-shot learning in combination with model adaptation. Furthermore, as AmericasNLI is a multiway parallel dataset, we use it to benchmark the performance of different machine translation models for those languages. Finally, using a standard transformer model, we explore translation-based approaches for natural language inference. We find that the zero-shot performance of pretrained models without adaptation is poor for all languages in AmericasNLI, but model adaptation via continued pretraining results in improvements. All machine translation models are rather weak, but, surprisingly, translation-based approaches to natural language inference outperform all other models on that task.

Distribution and accumulative pattern of tetracyclines and sulfonamides in edible vegetables of cucumber, tomato, and lettuce.

Veterinary antibiotics can be released to environment by the animals' excretions, which thereby poses human health and ecological risks. Six antibiotics (tetracycline, oxytetracycline, chlortetracycline, sulfamethazine, sulfamethoxazole, and sulfadimethoxine) at three concentrations (5, 10, and 20 mg kg(-1) soil) were employed in pots filled with a loamy sand upland soil. Three types of vegetable seedlings, including cucumber (Cucumis sativus), cherry tomato (Solanum lycopersicum), and lettuce (Lactuca sativa), were also cultivated during 45 d in the greenhouse. All antibiotics taken up by tested plants showed negative effects on growth. Relatively high levels of tetracyclines and sulfonamides (SAs) were detected in the nonedible parts, roots, and leaves of cucumber and tomato, but fruit parts accumulated them lower than acceptable daily intake. Indeed, cucumber roots accumulated SAs by up to 94.6% of total addition (at 5 mg kg(-1) soil).

Some biochemical parameters related to blood glucose mutation of total blood storage at the Central Institute of hematology and transfusion

The study was carried out in six stored blood by CPD-A1, at the first, 4th, 14th, 21st, 28th, 35th and 42nd days of the blood stored. The results showed that: The plasma glucose and pH; 2.3-DPG concentration were decreased, plasma lactat was increased gradually during blood stored by time, the difference was significantly than that in the first point of time with p<0.001. The plasma G-6-PD and PK activities were significantly decreased during blood stored by time.