Incorporating Auxiliary Data of Different Spatial Scales for Spatial Prediction of Soil Nitrogen Using Robust Residual Cokriging (RRCoK)

Auxiliary data has usually been incorporated into geostatistics for high-accuracy spatial prediction. Due to the different spatial scales, category and point auxiliary data have rarely been incorporated into prediction models together. Moreover, traditionally used geostatistical models are usually sensitive to outliers. This study first quantified the land-use type (LUT) effect on soil total nitrogen (TN) in Hanchuan County, China. Next, the relationship between soil TN and the auxiliary soil organic matter (SOM) was explored. Then, robust residual cokriging (RRCoK) with LUTs was proposed for the spatial prediction of soil TN. Finally, its spatial prediction accuracy was compared with that of ordinary kriging (OK), robust cokriging (RCoK), and robust residual kriging (RRK). Results show that: (i) both LUT and SOM are closely related to soil TN; (ii) by incorporating SOM, the relative improvement accuracy of RCoK over OK was 29.41%; (iii) by incorporating LUTs, the relative improvement accuracy of RRK over OK was 33.33%; (iv) RRCoK obtained the highest spatial prediction accuracy (RI = 43.14%). It is concluded that the recommended method, RRCoK, can effectively incorporate category and point auxiliary data together for the high-accuracy spatial prediction of soil properties.

The influence of melatonin on stress-induced ultramicroscopic changes of the neurons of the supraoptic nuclei of the rat hypothalamus

The aim: to study the effect of melatonin on the ultrastructural state of the supraoptic nuclei of the hypothalamus of rats under immobilization stress.Materials and methods. The experiments were performed on non-linear male white rats weighing 200-220 g. The animals were divided into 3 study series, in each of which the biomaterial was collected at 2 p.m. and at 2 a.m. using electron microscopic method. Long immobilization stress was simulated by keeping rats in special plastic penal cages for 6 hours daily for 7 consecutive days. Melatonin (Sigma, USA, 99.5% purification degree) at a dose of 0.5 mg/kg, in 1.0 ml of solvent (0.9% ethanol solution on physiologic saline) was injected daily, intraperitoneally.Results. When the animals were kept under the standard light regime, the ultrastructural organization of the hypothalamic nuclei at 2 p.m. indicated their low functional activity in comparison with the studies carried out at 2 a.m. Prolonged exposure of rats to immobilization stress was reflected in a significant rearrangement of the ultrastructural organization of supraoptic nuclei of the hypothalamus. The established changes can be considered as a manifestation of neurosecretory activity suppression, a decrease in neurosecretase production by hypothalamic neurons. Melatonin injections against the background of immobilization stress resulted in relative normalization of ultrastructural state of neurons of supraoptic nuclei of the hypothalamus of animals. In particular, studies at 2 a.m. revealed light neurosecretory cells containing a large nucleus, it was pyknotically altered. Karyolema invaginations, euchromatin dominance in the nucleus were observed. Heterogeneous changes were observed on the part of mitochondria. Enlarged tubules of granular endoplasmic reticulum were seen. At the same time, a small number of ribosomes and few hormonal granules were noticeable in neuroplasm. The mentioned picture of neurosecretory cells reflects a relative improvement in their electron microscopic state, which is evidenced by the appearance of neurosecretory granules. However, the ultrastructure of other organelles of the studied neurons indicates a depleted state caused by prolonged immobilization.Conclusions. 1. In animals under standard photoperiod conditions, the structural organization of supraoptic neurons of the hypothalamic nuclei during the nighttime of the experiment reflects the intensity of intracellular synthesizing processes (at 2 a.m.). A decrease in the activity of the structures under study is noted during the daytime. 2. Under immobilization stress, the ultrastructural organization of the above neurons indicates a pronounced disturbance of reactive nature with the signs of decreased functional ability of the structures and the phenomena of edema and destruction during the period of observation. 3. Melatonin injections against the background of immobilization stress led to a relative improvement in the ultrastructural state of the animals’ hypothalamic nuclei neurons, which is evidenced by the appearance of neurosecretory granules. However, the ultrastructure of other organelles of the studied neurons indicated a depleted state caused by prolonged immobilization.

Multimodal image and audio music transcription

Optical Music Recognition (OMR) and Automatic Music Transcription (AMT) stand for the research fields that aim at obtaining a structured digital representation from sheet music images and acoustic recordings, respectively. While these fields have traditionally evolved independently, the fact that both tasks may share the same output representation poses the question of whether they could be combined in a synergistic manner to exploit the individual transcription advantages depicted by each modality. To evaluate this hypothesis, this paper presents a multimodal framework that combines the predictions from two neural end-to-end OMR and AMT systems by considering a local alignment approach. We assess several experimental scenarios with monophonic music pieces to evaluate our approach under different conditions of the individual transcription systems. In general, the multimodal framework clearly outperforms the single recognition modalities, attaining a relative improvement close to $$40\%$$ 40 % in the best case. Our initial premise is, therefore, validated, thus opening avenues for further research in multimodal OMR-AMT transcription.

Evaluation of an mHealth-enabled hierarchical diabetes management intervention in primary care in China (ROADMAP): A cluster randomized trial

Background Glycemic control remains suboptimal in developing countries due to critical system deficiencies. An innovative mobile health (mHealth)-enabled hierarchical diabetes management intervention was introduced and evaluated in China with the purpose of achieving better control of type 2 diabetes in primary care. Methods and findings A community-based cluster randomized controlled trial was conducted among registered patients with type 2 diabetes in primary care from June 2017 to July 2019. A total of 19,601 participants were recruited from 864 communities (clusters) across 25 provinces in China, and 19,546 completed baseline assessment. Moreover, 576 communities (13,037 participants) were centrally randomized to the intervention and 288 communities (6,509 participants) to usual care. The intervention was centered on a tiered care team–delivered mHealth-mediated service package, initiated by monthly blood glucose monitoring at each structured clinic visit. Capacity building and quarterly performance review strategies upheld the quality of delivered primary care. The primary outcome was control of glycated hemoglobin (HbA1c; <7.0%), assessed at baseline and 12 months. The secondary outcomes include the individual/combined control rates of blood glucose, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C); changes in levels of HbA1c, BP, LDL-C, fasting blood glucose (FBG), and body weight; and episodes of hypoglycemia. Data were analyzed using intention-to-treat (ITT) generalized estimating equation (GEE) models, accounting for clustering and baseline values of the analyzed outcomes. After 1-year follow-up, 17,554 participants (89.8%) completed the end-of-study (EOS) assessment, with 45.1% of them from economically developed areas, 49.9% from urban areas, 60.5 (standard deviation [SD] 8.4) years of age, 41.2% male, 6.0 years of median diabetes duration, HbA1c level of 7.87% (SD 1.92%), and 37.3% with HbA1c <7.0% at baseline. Compared with usual care, the intervention led to an absolute improvement in the HbA1c control rate of 7.0% (95% confidence interval [CI] 4.0% to 10.0%) and a relative improvement of 18.6% (relative risk [RR] 1.186, 95% CI 1.105 to 1.267) and an absolute improvement in the composite ABC control (HbA1c <7.0%, BP <140/80 mm Hg, and LDL-C <2.6 mmol/L) rate of 1.9% (95% CI 0.5 to 3.5) and a relative improvement of 21.8% (RR 1.218, 95% CI 1.062 to 1.395). No difference was found on hypoglycemia episode and weight gain between groups. Study limitations include noncentralized laboratory tests except for HbA1c, and caution should be exercised when extrapolating the findings to patients not registered in primary care system. Conclusions The mHealth-enabled hierarchical diabetes management intervention effectively improved diabetes control in primary care and has the potential to be transferred to other chronic conditions management in similar contexts. Trial registration Chinese Clinical Trial Registry (ChiCTR) IOC-17011325.

An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource

Background Clear language makes communication easier between any two parties. A layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical terminology which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa. Objective Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the slow growth of these vocabularies. In this paper, we present an automatic method to enrich laymen’s vocabularies that has the benefit of being able to be applied to vocabularies in any domain. Methods Our entirely automatic approach uses machine learning, specifically Global Vectors for Word Embeddings (GloVe), on a corpus collected from a social media healthcare platform to extend and enhance consumer health vocabularies. Our approach further improves the consumer health vocabularies by incorporating synonyms and hyponyms from the WordNet ontology. The basic GloVe and our novel algorithms incorporating WordNet were evaluated using two laymen datasets from the National Library of Medicine (NLM), Open-Access Consumer Health Vocabulary (OAC CHV) and MedlinePlus Healthcare Vocabulary. Results The results show that GloVe was able to find new laymen terms with an F-score of 48.44%. Furthermore, our enhanced GloVe approach outperformed basic GloVe with an average F-score of 61%, a relative improvement of 25%. Furthermore, the enhanced GloVe showed a statistical significance over the two ground truth datasets with P < 0.001. Conclusions This paper presents an automatic approach to enrich consumer health vocabularies using the GloVe word embeddings and an auxiliary lexical source, WordNet. Our approach was evaluated used healthcare text downloaded from MedHelp.org, a healthcare social media platform using two standard laymen vocabularies, OAC CHV, and MedlinePlus. We used the WordNet ontology to expand the healthcare corpus by including synonyms, hyponyms, and hypernyms for each layman term occurrence in the corpus. Given a seed term selected from a concept in the ontology, we measured our algorithms’ ability to automatically extract synonyms for those terms that appeared in the ground truth concept. We found that enhanced GloVe outperformed GloVe with a relative improvement of 25% in the F-score.

Voice Activation for Low-Resource Languages

Voice activation systems are used to find a pre-defined word or phrase in the audio stream. Industry solutions, such as “OK, Google” for Android devices, are trained with millions of samples. In this work, we propose and investigate several ways to train a voice activation system when the in-domain data set is small. We compare self-training exemplar pre-training, fine-tuning a model pre-trained on another domain, joint training on both an out-of-domain high-resource and a target low-resource data set, and unsupervised pre-training. In our experiments, the unsupervised pre-training and the joint-training with a high-resource data set from another domain significantly outperform a strong baseline of fine-tuning a model trained on another data set. We obtain 7–25% relative improvement depending on the model architecture. Additionally, we improve the best test accuracy on the Lithuanian data set from 90.77% to 93.85%.

Stem Cell Therapy in Children With Sensorineural Hearing Loss: A Narrative Review

Context: One of the research areas is using stem cell transplantation for treating children’s sensorineural hearing loss. Preclinical studies and testing of the stem cell types have been performed in this field, and relative improvement has been achieved. Objectives: This narrative review has been prepared to study the advancements in hearing regeneration with stem cell transplantation. Data Sources: The English articles with full-text were searched in PubMed, Scopus, and Google scholar from 2000 to 2020 using keywords of sensory neural hearing loss and stem cell. Results: In 2018, the first human study was performed with stem cells from the human umbilical cord, which has promising results regarding the safety of the method and its positive effects on hearing. Conclusions: Autologous stem cell transplantation had induced relative improvement without serious adverse events in children with acquired sensorineural hearing loss. To obtain more evidence, further studies are required with larger sample sizes and in different patients groups.

Toward Automated Factchecking

In an effort to assist factcheckers in the process of factchecking, we tackle the claim detection task, one of the necessary stages prior to determining the veracity of a claim. It consists of identifying the set of sentences, out of a long text, deemed capable of being factchecked. This article is a collaborative work between Full Fact, an independent factchecking charity, and academic partners. Leveraging the expertise of professional factcheckers, we develop an annotation schema and a benchmark for automated claim detection that is more consistent across time, topics, and annotators than are previous approaches. Our annotation schema has been used to crowdsource the annotation of a dataset with sentences from UK political TV shows. We introduce an approach based on universal sentence representations to perform the classification, achieving an F1 score of 0.83, with over 5% relative improvement over the state-of-the-art methods ClaimBuster and ClaimRank. The system was deployed in production and received positive user feedback.

Comment on “Optimal Contract to Induce Continued Effort”

In this comment, we first use a counterexample to demonstrate that the optimal contract structure proposed in section 4 of Sun and Tian (2018) can be wrong when the two players’ discount rates are different. We then specify correct optimal contract structures, which involve generalizing the contract space to allow random termination. Numerical study with a wide range of model parameters illustrates that such a random termination only occurs sparingly in optimal contracts. Moreover, the suboptimality gap, measured by the relative improvement of the optimal contract over the best contract without random termination, is extremely small. This paper was accepted by Manel Baucells, decision analysis.

Scrutinizing the Clinical Symptoms and treatment Outcomes in a Case of Parasomnia with Sleepwalking Disorder Associated with Nocturnal Violence

The aim of this study was to investigate a case of sleepwalking associated with violence (non-REM parasomnias) and obstructive sleep apnea-hypopnea syndrome (OSAHS) following treatment strategies. Here we studied a 60-year-old man with family history of a wide range of sleep disorders. His quality of sleep, anxiety, depression, quality of life, and possibility of post-traumatic stress disorder (PTSD) were examined using the standard questionnaires upon pre-treatment, post-treatment, and follow-up phases of the study. The treatment plan comprised adherence to sleep hygiene measures, applying continuous positive airway pressure machine (CPAP) concurrently with eight sessions of weekly biofeedback therapy sessions. Standard over-night polysomnographic evaluations were done prior to and after the treatment. The present report comparatively highlights the patient’s sleep bioparameters, number of arousals, respiratory events, and periodic limb movements (PLM) during sleep stages in pre- and post-treatment studies. Prior to the intervention, the subject suffered from OSA, anxiety, minor depression, moderate quality of life and some degree of PTSD resulting in frequent episodes of sleepwalking associated with violence. After the intervention, there was a relative improvement in all indices. The apnea/hypopnea index (AHI) was 33.37 at the beginning of the intervention and decreased to 2.24 after 3 weeks of compliant CPAP therapy. The treatment protocol in this study resulted in complete improvement in some parameters such as PLM and OSAHS and relative improvement in others such as arousal instability and parasomnias including sleep walking associated with violence. The present study puts forward further insights into the possible relation between parasomnias and sleep disordered breathing with intermittent hypoxia. The above hypothesis deserves further investigations in future controlled studies.