Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-step crystallization and solid–solid transitions in binary colloidal mixtures

Significance Crystallization—the spontaneous formation of an ordered solid from a disordered fluid—has fascinated humankind for centuries. Contrary to longstanding theories, which predict that crystals form by a single nucleation event, recent experiments have shown that crystallization can traverse multiple intermediate states. In this paper, we observe a two-step crystallization pathway, in which a metastable crystal forms first and later transforms into another crystal with a different crystallographic symmetry. This transformation is diffusionless: The particles undergo coherent, local rearrangements. Using complementary computer simulations, we show that the two-step crystallization pathway is driven by competing thermodynamic forces and, thus, could be common to many physical systems. Crystallization is fundamental to materials science and is central to a variety of applications, ranging from the fabrication of silicon wafers for microelectronics to the determination of protein structures. The basic picture is that a crystal nucleates from a homogeneous fluid by a spontaneous fluctuation that kicks the system over a single free-energy barrier. However, it is becoming apparent that nucleation is often more complicated than this simple picture and, instead, can proceed via multiple transformations of metastable structures along the pathway to the thermodynamic minimum. In this article, we observe, characterize, and model crystallization pathways using DNA-coated colloids. We use optical microscopy to investigate the crystallization of a binary colloidal mixture with single-particle resolution. We observe classical one-step pathways and nonclassical two-step pathways that proceed via a solid–solid transformation of a crystal intermediate. We also use enhanced sampling to compute the free-energy landscapes corresponding to our experiments and show that both one- and two-step pathways are driven by thermodynamics alone. Specifically, the two-step solid–solid transition is governed by a competition between two different crystal phases with free energies that depend on the crystal size. These results extend our understanding of available pathways to crystallization, by showing that size-dependent thermodynamic forces can produce pathways with multiple crystal phases that interconvert without free-energy barriers and could provide approaches to controlling the self-assembly of materials made from colloids.
Mid-upper arm circumference as a screening tool for identifying adolescents with thinness

Abstract Objective: To evaluate the performance of mid-upper arm circumference (MUAC) to identify thinness in the late adolescence period (aged 15–19 years) in Ethiopia. Design: We conducted a school-based cross-sectional study. The receiver operating characteristics curve was used to examine the validity of MUAC compared with BMI Z-score to identify adolescents with thinness (BMI Z-score <−2 sd). Settings: Fifteen high schools (grade 9–12) located in Addis Ababa, Ethiopia. Participants: A total of 851 adolescent (456 males and 395 females) were included in the study. Results: The prevalence of thinness and severe thinness among high-school adolescents in Addis Ababa was 9·5 % (95 % CI 7·7, 11·7 %). The overall AUC for MUAC against BMI Z-score <−2 SD was 0·91 (95 % CI 0·88, 0·93). The optimal MUAC cut-offs to identify thinness were 23·3 cm for males and 22·6 cm for females. These cut-off points give high sensitivity and specificity for both males (a sensitivity of 87·9 % and a specificity of 75·9 %) and females (a sensitivity of 100 % and a specificity 88·2 %). Conclusions: MUAC has a comparable level of accuracy with BMI Z-score to identify thinness in adolescents aged 15–19 years. Hence, MUAC could be used as an alternative tool for surveillance and screening of thinness among adolescents aged 15–19 years. The optimum cut-off proposed by this study may incorrectly include a large number of adolescents when used in a relatively well-nourished population. In this situation, it would be necessary to choose a cut-off with greater positive predictive value.
Productivity and nutritive value of Brachiaria decumbens and performance of dairy heifers in a long‐term silvopastoral system

Silvopastoral system (SPS) has been suggested to ensure sustainability in animal production systems in tropical ecosystems. The objective of this study was to evaluate the productive and nutritive value traits of Brachiaria decumbens and performance of dairy heifers in SPS and open pasture (OP) during the summer and autumn of two consecutive years in the SPS and OP (17th and 18th years after establishment). Experimental design was a randomized complete block with two treatments (SPS and OP) and three replications in subdivided plots with repeated measures in time. There was reduction in the tiller population density, total and green forage mass, and total and green forage bulk density in the SPS when compared to the OP in the summer. In the autumn, no difference was observed between the systems. Shading in SPS increased crude protein content of the grass pasture by 25% and 33% when compared to the OP during the first and second experimental years, respectively, and reduced neutral detergent fibre content. However, it did not change acid detergent fibre or lignin content. OP provided higher stocking rate and weight gain per area than the SPS. Average daily gain was higher in the OP in the second experimental year. Severe shading conditions should be avoided, because in the long - term they may threaten the persistence and sustainability of pasture in the SPS. It is recommended to plant a low density of trees or implement management strategies of the tree component by either thinning or pruning over the years after planting.
Affective Conditioning on Hierarchical Attention Networks Applied to Depression Detection from Transcribed Clinical Interviews

In this work we propose a machine learning model for depression detection from transcribed clinical interviews. Depression is a mental disorder that impacts not only the subject's mood but also the use of language. To this end we use a Hierarchical Attention Network to classify interviews of depressed subjects. We augment the attention layer of our model with a conditioning mechanism on linguistic features, extracted from affective lexica. Our analysis shows that individuals diagnosed with depression use affective language to a greater extent than not-depressed. Our experiments show that external affective information improves the performance of the proposed architecture in the General Psychotherapy Corpus and the DAIC-WoZ 2017 depression datasets, achieving state-of-the-art 71.6 and 68.6 F1 scores respectively.
Hybrid Network Feature Extraction for Depression Assessment from Speech

A fast-growing area of mental health research is the search for speech-based objective markers for conditions such as depression. One vital challenge in the development of speech-based depression severity assessment systems is the extraction of depression-relevant features from speech signals. In order to deliver more comprehensive feature representation, we herein explore the beneﬁts of a hybrid network that encodes depression-related characteristics in speech for the task of depression severity assessment. The proposed network leverages self-attention networks (SAN) trained on low-level acoustic features and deep convolutional neural networks (DCNN) trained on 3D Log-Mel spectrograms. The feature representations learnt in the SAN and DCNN are concatenated and average pooling is exploited to aggregate complementary segment-level features. Finally, support vector regression is applied to predict a speaker’s Beck Depression Inventory-II score. Experiments based on a subset of the Audio-Visual Depressive Language Corpus, as used in the 2013 and 2014 Audio/Visual Emotion Challenges, demonstrate the effectiveness of our proposed hybrid approach.
Quantization Aware Training with Absolute-Cosine Regularization for Automatic Speech Recognition

Compression and quantization is important to neural networks in general and Automatic Speech Recognition (ASR) systems in particular, especially when they operate in real-time on resource-constrained devices. By using fewer number of bits for the model weights, the model size becomes much smaller while inference time is reduced signiﬁcantly, with the cost of degraded performance. Such degradation can be potentially addressed by the so-called quantization-aware training (QAT). Existing QATs mostly take into account the quantization in forward propagation, while ignoring the quantization loss in gradient calculation during back-propagation. In this work, we introduce a novel QAT scheme based on absolute-cosine regularization (ACosR), which enforces a prior, quantization-friendly distribution to the model weights. We apply this novel approach into ASR task assuming a recurrent neural network transducer (RNN-T) architecture. The results show that there is zero to little degradation between ﬂoating-point, 8-bit, and 6-bit ACosR models. Weight distributions further conﬁrm that in-training weights are very close to quantization levels when ACosR is applied.
Using State of the Art Speaker Recognition and Natural Language Processing Technologies to Detect Alzheimer's Disease and Assess its Severity

In this study, we analyze the use of state-of-the-art technologies for speaker recognition and natural language processing to detect Alzheimer’s Disease (AD) and to assess its severity predicting Mini-mental status evaluation (MMSE) scores. With these purposes, we study the use of speech signals and transcriptions. Our work focuses on the adaptation of state-of-the-art models for both modalities individually and together to examine its complementarity. We used x-vectors to characterize speech signals and pre-trained BERT models to process human transcriptions with different back-ends in AD diagnosis and assessment. We evaluated features based on silence segments of the audio ﬁles as a complement to x-vectors. We trained and evaluated our systems in the Interspeech 2020 ADReSS challenge dataset, containing 78 AD patients and 78 sex and age-matched controls. Our results indicate that the fusion of scores obtained from the acoustic and the transcript-based models provides the best detection and assessment results, suggesting that individual models for two modalities contain complementary information. The addition of the silence-related features improved the fusion system even further. A separate analysis of the models suggests that transcript-based models provide better results than acoustic models in the detection task but similar results in the MMSE prediction task.
Morphological Variation and Palynomorphology of Rosa laxa in Xinjiang, China

Rosa laxa is widely distributed in the Xinjiang Uygur Autonomous Region of China and is highly adaptable and rich in variation. In this study, we investigated the morphology, habitats, and palynomorphology of R. laxa botanical varieties from Xinjiang, China. In addition to R. laxa var. laxa, there were three other botanical varieties of R. laxa growing in southern Xinjiang, including var. mollis, var. kaschgarica, and var. tomurensis. Together, these four botanical varieties exhibited morphological variation, mainly in the morphology of prickles and the glandular trichome and in flower color. The pollen grains of the R. laxa botanical varieties, all medium in size (21.77–48.39 μm), came in three shapes: perprolate, prolate, and subspheroidal. Their pollen exine sculptures were characterized by either a striate-perforation pattern or striate pattern, but perforation varied in terms of diameter and density and striae varied in depth and density. Palynomorphological assessment showed that three types of evolution, i.e., primitive, transitive, and evolved, were present among R. laxa botanical varieties, and pollen dimorphism was observed in the same botanical variety. Perprolate pollen with a dense striate pattern was the most evolved type. Based on morphological and palynomorphological investigations, var. tomurensis was considered to be the most evolved one among the studied botanical varieties.
Limbal, low-grade myofibroblastic sarcoma: Case report and literature review

Low-grade myofibroblastic sarcoma is a relatively recently-described neoplasm of the myofibroblasts having a predilection for the head and neck region. Ophthalmic involvement is extremely rare. Limbal involvement has not yet been documented in the literature. We describe one such case involving the limbus of a 48-year-old Asian male.
Receiving a diagnosis of young onset dementia: Evidence-based statements to inform best practice

Introduction Better understanding of patient experience is an important driver for service improvements and can act as a lever for system change. In the United Kingdom, the patient experience is now a central issue for the National Health Service Commissioning Board, clinical commissioning groups and the providers they commission from. Traditionally, dementia care in the United Kingdom has focused predominantly on the individual experience of those with late onset dementia, while the voice of those with young onset dementia has been, comparatively, unheard. This study aims to improve the understanding of the personal experience of younger people undergoing investigation for dementia. Methods A modified Delphi approach was undertaken with 18 younger people with dementia and 18 supporters of people with young onset dementia. Questions were informed by a scoping review of the literature (O’Malley, M., Carter, J., Stamou, V., Lafontaine, J., & Parkes, J. (2019a). Receiving a diagnosis of young onset dementia: A scoping review of lived experiences. Ageing & Mental Health, 0(0), 1-12). Summary individual statements were refined over two rounds to a final list of 29 key statements. Results Twenty-seven of these statements were rated as absolutely essential or very important and included (1) for the general practitioner to identify dementia in younger people, (2) clinicians should be compassionate, empathic and respectful during the assessment and particularly sensitive when providing information about a diagnosis, and (3) remembering that receiving the diagnosis is a lot to absorb for a person with dementia and their supporter. Statistical analyses found no difference in the scoring patterns between younger people with dementia and supporters, suggesting similar shared experiences during the diagnostic process. Conclusion Understanding the uniquely personal experience of young people going through the process of diagnosis for dementia is essential to provide person-centred, needs-led, and cost-effective services. Patient’s values and experiences should be used to support and guide clinical decision-making.
Haplotypic characterization of the olive ridley turtle (Lepidochelys olivacea) in northwest Mexico: the northernmost limit of its distribution

espanolLa tortuga golfina (L. olivacea) tiene una distribucion pantropical. En el Pacifico oriental, los limites oficiales de su zona de reproduccion son la peninsula de Baja California y el sur de Sinaloa, en Mexico. La playa de Ceuta en Elota, Sinaloa, Mexico ha servido de sitio de proteccion para L. olivacea durante mas de tres decenios. En este estudio, se caracterizo geneticamente la poblacion de L. olivacea de la playa de Ceuta. Concretamente, se amplifico un fragmento de 712 pb de la region de control del ADNmt de 32 tortugas golfinas. Se identificaron ocho haplotipos (siete tras reducir a ~468 pb) y se incluyeron dos haplotipos nuevos (Lo–T7 y Lo–T8) y cinco haplotipos que se habian identificado anteriormente en otras playas de anidacion. El haplotipo Lo–T2 era dominante (~60%) en las muestras: h = 0,6048 (± 0,0974) y π = 0,002212 (± 0,001504). Si bien este estudio se realizo en el limite septentrional de la zona de anidacion de la tortuga golfina en el Pacifico oriental, el grupo estudiado presenta una diversidad genetica moderada y pertenece a una poblacion que, en la escala evolutiva, ha pasado recientemente por una expansion demografica. Debido a que la tortuga golfina del Pacifico oriental se considera resiliente a la variacion ambiental, es necesario estudiar las zonas de anidacion en el noroeste de Mexico. EnglishThe olive ridley sea turtle (L. olivacea) has a pantropical distribution. In the Eastern Pacific, the official limits of its reproduction area are south of the Baja California peninsula and south of Sinaloa, Mexico. Ceuta beach in Elota, Sinaloa, Mexico, has served as a protection site for L. olivacea for over three decades. In this study, the L. olivacea population from Ceuta beach was genetically characterized. Specifically, a 712–bp fragment from the control region of mtDNA was amplified from 32 olive ridley turtles. Eight haplotypes (seven after cutting to ~468 bp) were identified, and these included two novel haplotypes (Lo–T7 and Lo–T8) and five haplotypes that were previously identified in other nesting beaches. The Lo–T2 haplotype was dominant (~60%) in the samples: h = 0.6048 (± 0.0974) and π = 0.002212 (± 0.001504). Although this study was conducted in the northernmost limit of the olive ridley turtle nesting distribution in the eastern Pacific, the sampled group presents moderate genetic diversity and belongs to a population that, on an evolutionary scale, only recently underwent demographic expansion. Because the olive ridley turtle in the eastern Pacific is considered resilient to environmental variation, nesting area studies in northwest Mexico are necessary.
Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis

Background A substantial amount of COVID-19–related data is generated by Twitter users every day. Self-reports of COVID-19 symptoms on Twitter can reveal a great deal about the disease and its prevalence in the community. In particular, self-reports can be used as a valuable resource to learn more about common symptoms and whether their order of appearance differs among different groups in the community. These data may be used to develop a COVID-19 risk assessment system that is tailored toward a specific group of people. Objective The aim of this study was to identify the most common symptoms reported by patients with COVID-19, as well as the order of symptom appearance, by examining tweets in Arabic. Methods We searched Twitter posts in Arabic for personal reports of COVID-19 symptoms from March 1 to May 27, 2020. We identified 463 Arabic users who had tweeted about testing positive for COVID-19 and extracted the symptoms they associated with the disease. Furthermore, we asked them directly via personal messaging to rank the appearance of the first 3 symptoms they had experienced immediately before (or after) their COVID-19 diagnosis. Finally, we tracked their Twitter timeline to identify additional symptoms that were mentioned within ±5 days from the day of the first tweet on their COVID-19 diagnosis. In total, 270 COVID-19 self-reports were collected, and symptoms were (at least partially) ranked. Results The collected self-reports contained 893 symptoms from 201 (74%) male and 69 (26%) female Twitter users. The majority (n=270, 82%) of the tracked users were living in Saudi Arabia (n=125, 46%) and Kuwait (n=98, 36%). Furthermore, 13% (n=36) of the collected reports were from asymptomatic individuals. Of the 234 users with symptoms, 66% (n=180) provided a chronological order of appearance for at least 3 symptoms. Fever (n=139, 59%), headache (n=101, 43%), and anosmia (n=91, 39%) were the top 3 symptoms mentioned in the self-reports. Additionally, 28% (n=65) reported that their COVID-19 experience started with a fever, 15% (n=34) with a headache, and 12% (n=28) with anosmia. Of the 110 symptomatic cases from Saudi Arabia, the most common 3 symptoms were fever (n=65, 59%), anosmia (n=46, 42%), and headache (n=42, 38%). Conclusions This study identified the most common symptoms of COVID-19 from tweets in Arabic. These symptoms can be further analyzed in clinical settings and may be incorporated into a real-time COVID-19 risk estimator.
Expression dynamics of dehydration tolerance in the tropical plant Marchantia inflexa.

Tolerance to prolonged water deficit occurs along a continuum in plants, with dehydration and desiccation tolerance representing some of the most extreme adaptations to water scarcity. Although, dehydration and desiccation tolerance presumably vary among individuals of a single species, this variability remains largely unstudied. Here, we characterized expression dynamics throughout a dehydration - rehydration timecourse in six diverse genotypes of the dioecious liverwort Marchantia inflexa. We identified classical signatures of stress response in M. inflexa, including major changes in transcripts related to metabolism, expression of LEA and ELIP genes, and evidence of cell wall remodeling. However, we detected very little temporal synchronization of these responses across different genotypes of M. inflexa, which may be related to genotypic variation among samples, constitutive expression of dehydration associated transcripts, the sequestration of mRNAs in ribonucleoprotein partials prior to drying, or the lower tolerance of M. inflexa relative to most bryophytes studied to date. Our characterization of intraspecific variation in expression dynamics suggests that differences in the timing of transcriptional adjustments contribute to variation among genotypes, and that developmental differences impact the relative tolerance of meristematic and differentiated tissues. This work highlights the complexity and variability of water stress tolerance and underscores the need for comparative studies that seek to characterize variation in desiccation and dehydration tolerance.
Achiote (Bixa orellana) Lipophilic Extract, Bixin, and δ-tocotrienol Effects on Lifespan and Stress Resistance in Caenorhabditis elegans

Abstract The onset of many degenerative diseases related to aging has been associated with a decrease in the activity of antistress systems, and pharmacological interventions increasing stress resistance could be effective to prevent the development of such diseases. Achiote is a valuable source of carotenoid and tocotrienols, which have antioxidant activity. In this work, we explore the capacity of an achiote seed extract and its main compounds to modulate the lifespan and antistress responses on Caenorhabditis elegans, as well as the mechanisms involved in these effects. Achiote lipophilic extract, bixin, and δ-tocotrienol were applied on nematodes to carry out lifespan, stress resistance, and fertility assays. The achiote seed extract increased the median and maximum lifespan up to 35% and 27% and increased resistance against oxidative and thermal stresses without adverse effects on fertility. The beneficial effects were mimicked by a bixin+δ-tocotrienol mixture. All the effects on lifespan and stress resistance were independent of caloric restriction but dependent on the insulin/insulin growth factor-1 pathway. This study could provide insights for further research on a new beneficial use of this important crop in health and nutraceutical applications beyond its use as a source of natural pigments.