Task irrelevant external cues can influence language selection in voluntary object naming: evidence from Hindi-English bilinguals

We examined if external cues such as other agents’ actions can influence the choice of language during voluntary and cued object naming in bilinguals in three experiments. Hindi– English bilinguals first saw a cartoon waving at a color patch. They were then asked to either name a picture in the language of their choice (voluntary block) or to name in the instructed language (cued block). The colors waved at by the cartoon were also the colors used as language cues (Hindi or English). We compared the influence of the cartoon’s choice of color on naming when speakers had to indicate their choice explicitly before naming (Experiment 1) as opposed to when they named directly on seeing the pictures (Experiment 2 and 3). Results showed that participants chose the language indicated by the cartoon greater number of times (Experiment 1 and 3). Speakers also switched significantly to the language primed by the cartoon greater number of times (Experiment 1 and 2). These results suggest that choices leading to voluntary action, as in the case of object naming can be influenced significantly by external non-linguistic cues. Importantly, these symbolic influences can work even when other agents are merely indicating their choices and are not interlocutors in bilingual communicatio

HIV and cancer registry linkage identifies a substantial burden of cancers in persons with HIV in India.

We utilized computerized record-linkage methods to link HIV and cancer databases with limited unique identifiers in Pune, India, to determine feasibility of linkage and obtain preliminary estimates of cancer risk in persons living with HIV (PLHIV) as compared with the general population.Records of 32,575 PLHIV were linked to 31,754 Pune Cancer Registry records (1996-2008) using a probabilistic-matching algorithm. Cancer risk was estimated by calculating standardized incidence ratios (SIRs) in the early (4-27 months after HIV registration), late (28-60 months), and overall (4-60 months) incidence periods. Cancers diagnosed prior to or within 3 months of HIV registration were considered prevalent.Of 613 linked cancers to PLHIV, 188 were prevalent, 106 early incident, and 319 late incident. Incident cancers comprised 11.5% AIDS-defining cancers (ADCs), including cervical cancer and non-Hodgkin lymphoma (NHL), but not Kaposi sarcoma (KS), and 88.5% non-AIDS-defining cancers (NADCs). Risk for any incident cancer diagnosis in early, late, and combined periods was significantly elevated among PLHIV (SIRs: 5.6 [95% CI 4.6-6.8], 17.7 [95% CI 15.8-19.8], and 11.5 [95% CI 10-12.6], respectively). Cervical cancer risk was elevated in both incidence periods (SIRs: 9.6 [95% CI 4.8-17.2] and 22.6 [95% CI 14.3-33.9], respectively), while NHL risk was elevated only in the late incidence period (SIR: 18.0 [95% CI 9.8-30.20]). Risks for NADCs were dramatically elevated (SIR > 100) for eye-orbit, substantially (SIR > 20) for all-mouth, esophagus, breast, unspecified-leukemia, colon-rectum-anus, and other/unspecified cancers; moderately elevated (SIR > 10) for salivary gland, penis, nasopharynx, and brain-nervous system, and mildly elevated (SIR > 5) for stomach. Risks for 6 NADCs (small intestine, testis, lymphocytic leukemia, prostate, ovary, and melanoma) were not elevated and 5 cancers, including multiple myeloma not seen.Our study demonstrates the feasibility of using probabilistic record-linkage to study cancer/other comorbidities among PLHIV in India and provides preliminary population-based estimates of cancer risks in PLHIV in India. Our results, suggesting a potentially substantial burden and slightly different spectrum of cancers among PLHIV in India, support efforts to conduct multicenter linkage studies to obtain precise estimates and to monitor cancer risk in PLHIV in India

CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion

Code completion models have made significant progress in recent years, yet current popular evaluation datasets, such as HumanEval and MBPP, predominantly focus on code completion tasks within a single file. This over-simplified setting falls short of representing the real-world software development scenario where repositories span multiple files with numerous cross-file dependencies, and accessing and understanding cross-file context is often required to complete the code correctly. To fill in this gap, we propose CrossCodeEval, a diverse and multilingual code completion benchmark that necessitates an in-depth cross-file contextual understanding to complete the code accurately. CrossCodeEval is built on a diverse set of real-world, open-sourced, permissively-licensed repositories in four popular programming languages: Python, Java, TypeScript, and C#. To create examples that strictly require cross-file context for accurate completion, we propose a straightforward yet efficient static-analysis-based approach to pinpoint the use of cross-file context within the current file. Extensive experiments on state-of-the-art code language models like CodeGen and StarCoder demonstrate that CrossCodeEval is extremely challenging when the relevant cross-file context is absent, and we see clear improvements when adding these context into the prompt. However, despite such improvements, the pinnacle of performance remains notably unattained even with the highest-performing model, indicating that CrossCodeEval is also capable of assessing model's capability in leveraging extensive context to make better code completion. Finally, we benchmarked various methods in retrieving cross-file context, and show that CrossCodeEval can also be used to measure the capability of code retrievers.Comment: To appear at NeurIPS 2023 (Datasets and Benchmarks Track

ContraGen: Effective Contrastive Learning For Causal Language Model

Despite exciting progress in large-scale language generation, the expressiveness of its representations is severely limited by the \textit{anisotropy} issue where the hidden representations are distributed into a narrow cone in the vector space. To address this issue, we present ContraGen, a novel contrastive learning framework to improve the representation with better uniformity and discrimination. We assess ContraGen on a wide range of downstream tasks in natural and programming languages. We show that ContraGen can effectively enhance both uniformity and discrimination of the representations and lead to the desired improvement on various language understanding tasks where discriminative representations are crucial for attaining good performance. Specifically, we attain $44\%$ relative improvement on the Semantic Textual Similarity tasks and $34\%$ on Code-to-Code Search tasks. Furthermore, by improving the expressiveness of the representations, ContraGen also boosts the source code generation capability with $9\%$ relative improvement on execution accuracy on the HumanEval benchmark.Comment: 10 page

Complementary feeding at 4 versus 6 months of age for preterm infants born at less than 34 weeks of gestation: a randomised, open-label, multicentre trial

Background Evidence on the optimal time to initiation of complementary feeding in preterm infants is scarce. We examined the effect of initiation of complementary feeding at 4 months versus 6 months of corrected age on weight for age at 12 months corrected age in preterm infants less than 34 weeks of gestation. Methods In this open-label, randomised trial, we enrolled infants born at less than 34 weeks of gestation with no major malformation from three public health facilities in India. Eligible infants were tracked from birth and randomly assigned (1:1) at 4 months corrected age to receive complementary feeding at 4 months corrected age (4 month group), or continuation of milk feeding and initiation of complementary feeding at 6 months corrected age (6 month group), using computer generated randomisation schedule of variable block size, stratified by gestation (30 weeks or less, and 31–33 weeks). Iron supplementation was provided as standard. Participants and the implementation team could not be masked to group assignment, but outcome assessors were masked. Primary outcome was weight for age Z-score at 12 months corrected age (WAZ12) based on WHO Multicentre Growth Reference Study growth standards. Analyses were by intention to treat. The trial is registered with Clinical Trials Registry of India, number CTRI/2012/11/003149. Findings Between March 20, 2013, and April 24, 2015, 403 infants were randomly assigned: 206 to receive complementary feeding from 4 months and 197 to receive complementary feeding from 6 months. 22 infants in the 4 month group (four deaths, two withdrawals, 16 lost to follow-up) and eight infants in the 6 month group (two deaths, six lost to follow-up) were excluded from analysis of primary outcome. There was no difference in WAZ12 between two groups: –1·6 (SD 1·2) in the 4 month group versus –1·6 (SD 1·3) in the 6 month group (mean difference 0·005, 95% CI –0·24 to 0·25; p=0·965). There were more hospital admissions in the 4 month group compared with the 6 month group: 2·5 episodes per 100 infant-months in the 4 month group versus 1·4 episodes per 100 infant-months in the 6 month group (incidence rate ratio 1·8, 95% CI 1·0–3·1, p=0·03). 34 (18%) of 188 infants in the 4 month group required hospital admission, compared with 18 (9%) of 192 infants in the 6 month group. Interpretation Although there was no evidence of effect for the primary endpoint of WAZ12, the higher rate of hospital admission in the 4 month group suggests a recommendation to initiate complementary feeding at 6 months over 4 months of corrected age in infants less than 34 weeks of gestation

Demographic, socio-economic, and cultural factors affecting fertility differentials in Nepal

<p>Abstract</p> <p>Background</p> <p>Traditionally Nepalese society favors high fertility. Children are a symbol of well-being both socially and economically. Although fertility has been decreasing in Nepal since 1981, it is still high compared to many other developing countries. This paper is an attempt to examine the demographic, socio-economic, and cultural factors for fertility differentials in Nepal.</p> <p>Methods</p> <p>This paper has used data from the Nepal Demographic and Health Survey (NDHS 2006). The analysis is confined to ever married women of reproductive age (8,644). Both bivariate and multivariate analyses have been performed to describe the fertility differentials. The bivariate analysis (one-way ANOVA) was applied to examine the association between children ever born and women's demographic, socio-economic, and cultural characteristics. Besides bivariate analysis, the net effect of each independent variable on the dependent variable after controlling for the effect of other predictors has also been measured through multivariate analysis (multiple linear regressions).</p> <p>Results</p> <p>The mean numbers of children ever born (CEB) among married Nepali women of reproductive age and among women aged 40-49 were three and five children, respectively. There are considerable differentials in the average number of children ever born according to women's demographic, socio-economic, and cultural settings. Regression analysis revealed that age at first marriage, perceived ideal number of children, place of residence, literacy status, religion, mass media exposure, use of family planning methods, household headship, and experience of child death were the most important variables that explained the variance in fertility. Women who considered a higher number of children as ideal (β = 0.03; p < 0.001), those who resided in rural areas (β = 0.02; p < 0.05), Muslim women (β = 0.07; p < 0.001), those who had ever used family planning methods (β = 0.08; p < 0.001), and those who had a child-death experience (β = 0.31; p < 0.001) were more likely to have a higher number of CEB compared to their counterparts. On the other hand, those who married at a later age (β = -0.15; p < 0.001), were literate (β = -0.05; p < 0.001), were exposed to both (radio/TV) mass media (β = -0.05; p < 0.001), were richest (β = -0.12; p < 0.001), and were from female-headed households (β = -0.02; p < 0.05) had a lower number of children ever born than their counterparts.</p> <p>Conclusion</p> <p>The average number of children ever born is high among women in Nepal. There are many contributing factors for the high fertility, among which are age at first marriage, perceived ideal number of children, literacy status, mass media exposure, wealth status, and child-death experience by mothers. All of these were strong predictors for CEB. It can be concluded that programs should aim to reduce fertility rates by focusing on these identified factors so that fertility as well as infant and maternal mortality and morbidity will be decreased and the overall well-being of the family maintained and enhanced.</p