Fluid and Electrolyte Management of Very Low Birth Weight Infants

Recent advances in medical knowledge and technology have markedly improved the survival rates of very low birth weight infants. Optimizing the neuro-developmental outcomes of these survivors has become an important priority in neonatal care, which includes appropriate management for achieving fluid and electrolyte balance. This review focuses on the principles of providing maintenance fluid to these infants, including careful assessment to avoid excessive fluid administration that may increase the risk of such neonatal morbidities as necrotizing enterocolitis, patent ductus arteriosus, and bronchopulmonary dysplasia (BPD). The review also describes the principles of fluid and electrolyte management of infants with BPD, which includes the strategy of providing adequate nutrition to promote normal growth

Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens

Recent psycholinguistic studies have drawn conflicting conclusions about the relationship between the quality of a language model and the ability of its surprisal estimates to predict human reading times, which has been speculated to be due to the large gap in both the amount of training data and model capacity across studies. The current work aims to consolidate these findings by evaluating surprisal estimates from Transformer-based language model variants that vary systematically in the amount of training data and model capacity on their ability to predict human reading times. The results show that surprisal estimates from most variants with contemporary model capacities provide the best fit after seeing about two billion training tokens, after which they begin to diverge from humanlike expectations. Additionally, newly-trained smaller model variants reveal a 'tipping point' at convergence, after which the decrease in language model perplexity begins to result in poorer fits to human reading times. These results suggest that the massive amount of training data is mainly responsible for the poorer fit achieved by surprisal from larger pre-trained language models, and that a certain degree of model capacity is necessary for Transformer-based language models to capture humanlike expectations.Comment: Findings of the Association for Computational Linguistics: EMNLP 202

Token-wise Decomposition of Autoregressive Language Model Hidden States for Analyzing Model Predictions

While there is much recent interest in studying why Transformer-based large language models make predictions the way they do, the complex computations performed within each layer have made their behavior somewhat opaque. To mitigate this opacity, this work presents a linear decomposition of final hidden states from autoregressive language models based on each initial input token, which is exact for virtually all contemporary Transformer architectures. This decomposition allows the definition of probability distributions that ablate the contribution of specific input tokens, which can be used to analyze their influence on model probabilities over a sequence of upcoming words with only one forward pass from the model. Using the change in next-word probability as a measure of importance, this work first examines which context words make the biggest contribution to language model predictions. Regression experiments suggest that Transformer-based language models rely primarily on collocational associations, followed by linguistic factors such as syntactic dependencies and coreference relationships in making next-word predictions. Additionally, analyses using these measures to predict syntactic dependencies and coreferent mention spans show that collocational association and repetitions of the same token largely explain the language models' predictions on these tasks.Comment: ACL 202

Sustainable farming with native rocks: the transition without revolution.

The development process which humanity passed through favored a series of conquests, reflected in the better quality of life and longevity, however, it also provoked upsets and severe transformation in the environment and in the human food security. Such process is driving the ecosystems to be homogeneous, and, therefore,the nutrients� supply, via nourishment. To change this panorama, the present work discusses the gains of incorporating the stonemeal technique as a strategic alternative to give back the essential fertile characteristics to the soils. This technology has the function of facilitating the rejuvenation of the soils and increasing the availability of the necessary nutrients to the full development of the plants which is a basic input for the proliferation of life in all its dimensions

Consumer Preference for Sustainable Tourism Certifications: A Choice Modeling Approach

Certifying tourism businesses as sustainable has been proposed as a means to connect the academic goals of ecotourism to the industry. One obstacle that impedes the development of widely recognized sustainable tourism certifications is the lack of knowledge regarding consumer preferences for these certifications. A better understanding of consumer desires is needed in order to create sustainable tourism certifications that will generate price premiums for certified businesses and thus accelerate the growth of certified businesses. This study uses a stated-preference choice modeling approach to examine consumer preference for sustainable tourism certifications amongst international tourists in Tanzania. Results suggest that certifications that emphasize environmental sustainability are more important to tourists than certifications that emphasize cultural or economic sustainability. Additionally, the more stringent certifications provide relatively little increase in consumer utility. The implications of the findings on the development of sustainable tourism certifications are discussed

Partially coherent ambiguity functions for depth-variant point spread function design

The ambiguity function (AF) provides a convenient way to model how a camera with a modified aperture responds to defocus. We use the AF to design an optimal aperture distribution, which creates a depth-variant point spread function (PSF) from a sparse set of desired intensity patterns at different focal depths. Prior knowledge of the coherence state of the light is used to constrain the optimization in the mutual intensity domain. We use an assumption of spatially coherent light to design a fixed-pattern aperture mask. The concept of a dynamic aperture mask that displays several aperture patterns during one image exposure is also suggested, which is modeled under an assumption of partially coherent light. Parallels are drawn between the optimal aperture functions for this dynamic mask and the eigenmodes of a coherent mode decomposition. We demonstrate how the space of design for a 3D intensity distribution of light using partially coherent assumptions is less constrained than under coherent light assumptions.United States. Air Force Office of Scientific Research (National Defense Science and Engineering Graduate (NDSEG) fellowship)United States. Defense Advanced Research Projects Agency (DARPA Young Faculty Award)Alfred P. Sloan Foundation (Research Fellowship

Metastatic seminoma and grade 1 follicular lymphoma presenting concurrently in a supraclavicular lymph node: a case report

An asymptomatic 67-year-old man presented with a left supraclavicular lymph node that enlarged over a 2-month period which was biopsied. Pathologic features were consistent with involvement by metastatic seminoma and follicular lymphoma, follicular pattern, grade 1 (of 3). Staging Positron Emission Tomography/Computed Tomography scans indicated several areas of enlarged lymph nodes. The patient completed chemotherapy with bleomycin, etoposide, and cisplatin chemotherapy. This is the first reported case of metastatic seminoma and follicular lymphoma occurring in the same lymph node. No obvious pathophysiologic link exists between these two malignancies and there are no shared common risk factors. Given the natural history of these two malignancies, if this patient develops recurrent lymphadenopathy, it will be difficult to identify whether the enlarged lymph nodes represent recurrent seminoma or follicular lymphoma without a biopsy of each pathologically enlarged node. Similarly, Fluorodeoxyglucose- Positron Emission Tomography is known to be active in both seminoma and follicular lymphoma, making this scan non-specific in this patient. Finally, this patient had no baseline elevation in any germ cell tumor marker. Thus, serum tumor markers cannot be relied upon as surrogates for response to chemotherapy or as identifiers of relapsed seminoma