Miracle-dz/UniFAR-FTUs huggingface dataset:
“It’s Stable but Not Stable”: A Conceptual Framework of Subjective Housing Stability Definition Among Individuals with Co-occurring Mental Health and Substance Use Disorders

Abstract Objective: Despite increasing efforts to improve housing stability, research has largely defined housing stability in a narrow sense and heavily relied on objective measures, such as housing types and housing duration. The present study constructed a conceptual framework for a subjective housing stability definition from the perspectives of individuals with co-occurring mental health and substance use disorders and their behavioral health service providers. Methods: Following the principles of grounded theory, we collected and analyzed qualitative data through semistructured interviews with 24 individuals with serious mental illness and substance use problems and three focus groups with 22 behavioral health service providers. Results: We developed a conceptual framework with two domains of subjective housing stability: functional stability and experiential stability. The functional stability domain includes four theoretical concepts: meeting basic needs, housing quality, housing affordability, and housing permanence. The experiential stability domain includes four theoretical concepts: autonomy and independence, connectedness, safety, and supportiveness. Conclusions: The conceptual framework can inform future research, practices, and policies to move beyond focusing on merely providing housing to consider the diverse and underlying needs in improving housing stability and well-being among those experiencing or at risk of housing instability.
Soil moisture incidentally selects for microbes that facilitate locally adaptive plant response

While a plant's microbiome can facilitate adaptive phenotypes, the plant's role in selecting for these microbes is unclear. Do plants actively recruit microbes beneficial to their current environment, or are beneficial microbes only an incidental by-product of microbial adaptation? We addressed these questions through a multigeneration greenhouse experiment, selecting for either dry- or wet-adapted soil microbial communities, either with or without plants. After three plant generations, we conducted a full reciprocal transplant of each soil community onto wet- and dry-treated plants. We found that plants generally benefited from soil microbes, and this benefit was greater whenever their current watering conditions matched the microbes' historical watering conditions. Principally, the plant's presence was not necessary in the historical treatments for this environmental matching benefit to emerge. Moreover, we found microbes from droughted soils could better tolerate drought stress. Taken together, these results suggest that the moisture environment selects for microbes that benefit plants under those specific moisture conditions, and that these beneficial properties arise as a by-product of microbial adaptation to the watering environment and not as a co-adapting plant–microbe system. This work highlights that understanding the selective agents on these plant-associated microbes will lead to a better understanding of plant adaptation.
The effect of placentation type, litter size, lactation and gestation length on cancer risk in mammals

Reproduction is a central activity for all living organisms but is also associated with a diversity of costs that are detrimental for survival. Until recently, the cost of cancer as a selective force has been poorly considered. Considering 191 mammal species, we found cancer mortality was more likely to be detected in species having large, rather than low, litter sizes and long lactation lengths regardless of the placentation types. However, increasing litter size and gestation length are not per se associated with an enhanced cancer mortality risk. Contrary to basic theoretical expectations, the species with the highest cancer mortality were not those with the most invasive (i.e. haemochorial) placentation, but those with a moderately invasive (i.e. endotheliochorial) one. Overall, these results suggest that (i) high reproductive efforts favour oncogenic processes' dynamics, presumably because of trade-offs between allocation in reproduction effort and anti-cancer defences, (ii) cancer defence mechanisms in animals are most often adjusted to align reproductive lifespan, and (iii) malignant cells co-opt existing molecular and physiological pathways for placentation, but species with the most invasive placentation have also selected for potent barriers against lethal cancers. This work suggests that the logic of Peto's paradox seems to be applicable to other traits that promote tumorigenesis.
Ranging behaviours across ecological and anthropogenic disturbance gradients: a pan-African perspective of giraffe (Giraffa spp.) space use

Animal movement behaviours are shaped by diverse factors, including resource availability and human impacts on the landscape. We generated home range estimates and daily movement rate estimates for 149 giraffe (Giraffa spp.) from all four species across Africa to evaluate the effects of environmental productivity and anthropogenic disturbance on space use. Using the continuous time movement modelling framework and a novel application of mixed effects meta-regression, we summarized overall giraffe space use and tested for the effects of resource availability and human impact on 95% autocorrelated kernel density estimate (AKDE) size and daily movement. The mean 95% AKDE was 359.9 km2 and the mean daily movement was 14.2 km, both with marginally significant differences across species. We found significant negative effects of resource availability, and significant positive effects of resource heterogeneity and protected area overlap on 95% AKDE size. There were significant negative effects of overall anthropogenic disturbance and positive effects of the heterogeneity of anthropogenic disturbance on daily movements and 95% AKDE size. Our results provide unique insights into the interactive effects of resource availability and anthropogenic development on the movements of a large-bodied browser and highlight the potential impacts of rapidly changing landscapes on animal space-use patterns.
SER: Performance Evaluation of CNN Model Along with an Overview of Available Indic Speech Datasets, and Transition of Classifiers From Traditional to Modern Era

Speech emotion recognition (SER) is a rapidly evolving field in affective computing and human-computer interaction. In general, a SER system extracts and classifies prominent elements called features from a pre-processed speech signal to target the presence of speaker's certain emotion. This paper explores the utilization of deep learning classifiers in SER and surveys available datasets in both Indic and international languages. The paper highlights the significance of SER in enhancing human-computer interaction and presents deep learning as an effective approach to handle the complexity of speech signals. Various deep learning architectures, including Convolution Neural Networks (CNNs), Recurrent Neural Network (RNNs), and hybrid models, are analysed in terms of training methodology, and performance on benchmark datasets. Additionally, the paper conducts a comprehensive survey of publicly available datasets for speech emotion recognition, considering emotional categories, language diversity, recording conditions, and sample sizes. Challenges in adapting deep learning models to these datasets, such as data augmentation and cross-lingual transfer learning, are discussed. Moreover, the CNN based model is analysed on accuracy, precision, recall and F-1 score on Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset with the value 84%, 85%, 84% and 84% resp. The review concludes with key findings, emphasizing the strengths and limitations of deep learning classifiers for SER. It identifies the need for standardized evaluation protocols, exploration of transfer learning across languages, and development of robust and culturally diverse datasets as future research directions.
RADIOCARBON DATING OF GRASS-TEMPERED CERAMIC REVEALS THE EARLIEST POTTERY FROM SLOVAKIA PREDATES THE ARRIVAL OF FARMING

ABSTRACT In the absence of wood, bone, and other organics, one possible candidate for determining the age of a site is the radiocarbon (14C) dating of pottery. In central Europe during the Early Neolithic, pottery was ubiquitous and contained substantial quantities of organic temper. However, attempts at the direct dating of organic inclusions raises a lot of methodological issues, especially when several sources of carbon contribute to the resulting radiocarbon age. Hence an alternative approach to dating of the early pottery is necessary. Here, we present a novel method of bulk separation of organic content from the grass-tempered pottery from Santovka (Slovakia). The procedure is based on the consecutive application of three inorganic acids, dissolving clay, silica content, and low molecular or mobile fractions to separate organic inclusions added to the pottery matrix during the formation of vessels. Radiocarbon dates obtained with this method are coherent and produce the shortest time span compared to other pretreatment methods presented in this study. The paired dates of grass-tempered pots with the 14C age of lipids extracted from the same pots point to a difference of 400–600 14C yr, however they are in line with the site’s chronostratigraphic Bayesian model. Grass-tempered pottery from Santovka (Slovakia) is dated to the first half of the 6th millennium cal BC, making it the earliest pottery north of the Danube. It seems feasible that ceramic containers from Santovka were produced by hunter-gatherers, and pottery predated the arrival of farming in the Carpathian region by a couple of centuries.
The effects of boundary proximity on Kelvin–Helmholtz instability and turbulence

Abstract Studies of Kelvin–Helmholtz (KH) instability have typically modelled the initial flow as an isolated shear layer. In geophysical cases, however, the instability often occurs near boundaries and may therefore be influenced by boundary proximity effects. Ensembles of direct numerical simulations are conducted to understand the effect of boundary proximity on the evolution of the instability and the resulting turbulence. Ensemble averages are used to reduce sensitivity to small variations in initial conditions. Both the transition to turbulence and the resulting turbulent mixing are modified when the shear layer is near a boundary: the time scales for the onset of instability and turbulence are longer, and the height of the KH billow is reduced. Subharmonic instability is suppressed by the boundary because phase lock is prevented due to the diverging phase speeds of the KH and subharmonic modes. In addition, the disruptive influence of three-dimensional secondary instabilities on pairing is more profound as the two events coincide more closely. When the shear layer is far from the boundary, the shear-aligned convective instability is dominant; however, secondary central-core instability takes over when the shear layer is close to the boundary, providing an alternate route for the transition to turbulence. Both the efficiency of the resulting mixing and the turbulent diffusivity are dramatically reduced by boundary proximity effects.
Digit Preference and Avoidance in the Age Statistics of Some Recent African Censuses: Some Patterns and Correlates

Demographers have long known that the age data compiled by national population censuses are often subject to a number of limitations, particularly in countries that can be characterized as economically underdeveloped. In those instances where age statistics are inadequate, it can generally be attributed to one or both of two basic sources: (1) failure to report ages (especially for very young children who are often not thought of as full members of society); and (2) misstatements of ages that are reported. When the former occurs, and the proportion of unknown ages is significantly large, little can be done unless the demographer has access to other data that would provide a basis for a realistic distribution of unknowns among the population with ages known. In most cases, however, the problem of unknown ages is secondary; and it is errors in the ages reported that constitute the most serious source of bias in age data. Misstatements of age arise from a number of different sources, among the most common of which are ignorance of correct age; a tendency to understate at some ages while exaggerating at others particularly at the more advanced ages; either a conscious or subconscious preference for certain socially significant ages (such as 21 or 65 in the United States), and a corresponding avoidance of other ages (such as the "unlucky" 13); a general tendency to overselect ages ending in certain digits, such as 0, 2, 5 and 8; and finally, deliberate falsification of age reports for a variety of social, economic, political or purely individual motives. As a result of these tendencies, population age distributions often display a regular pattern of irregularity possessing such characteristics as: (a) a deficiency of infants and very young children; (b) overstatement of seniority among the very oldest ages; (c) overstatement of certain socially significant ages; and (d) overstatement at ages ending in certain preferred digits with a corresponding understatement of ages ending in other digits. ' This latter is the most common source of error in age reporting, and it leads to a pattern of successive "heaping" throughout an age distribution.2 The aim of the present paper is to examine the extent of digit preference and avoidance in the age statistics of recent African censuses, paying particular attention to identifying some of the social and economic correlates of age heaping.
The final outcome of an epidemic model with several different types of infective in a large population

We consider a stochastic model for the spread of an epidemic amongst a closed homogeneously mixing population, in which there are several different types of infective, each newly infected individual choosing its type at random from those available. The model is based on the carrier-borne model of Downton (1968), as extended by Picard and Lefèvre (1990). The asymptotic distributions of final size and area under the trajectory of infectives are derived as the initial population becomes large, using arguments based on those of Scalia-Tomba (1985), (1990). We then use our limiting results to compare the asymptotic final size distribution of our model with that of a related multi-group model, in which the type of each infective is assigned deterministically.
Ecological causes of uneven mammal diversity

The uneven distributions of species over geography (e.g., tropical versus temperate regions) and phylogeny (e.g., rodents and bats versus the aardvark) are prominent biological patterns for which causal interconnections remain enigmatic. Here we investigate this central issue for living mammals using time-sliced clades sampled from a comprehensive recent phylogeny (N=5,911 species, ∼70% with DNA) to assess how different levels of unsampled extinction impact the inferred causes of species richness variation. Speciation rates are found to strongly exceed crown age as a predictor of clade species richness at every time slice, rejecting a clock-like model in which the oldest clades are the most speciose. Instead, mammals that are low-vagility or daytime-active show the fastest recent speciation and greatest extant richness. This suggests primary roles for dispersal limitation leading to geographic speciation (peripatric isolation) and diurnal adaptations leading to ecological speciation (time partitioning). Rates of speciation are also faster in temperate than tropical lineages, but only among older clades, consistent with the idea that many temperate lineages are ephemeral. These insights, enabled by our analytical framework, offer straightforward support for ecological effects on speciation-rate variation among clades as the primary cause of uneven phylogenetic richness patterns.
The songbird lateral habenula projects to dopaminergic midbrain and is important for normal vocal development

Mistakes in performance feel disappointing, suggesting that brain pathways for aversive feedback may play a role in motor learning. Here we tested if the lateral habenula (LHb), an evolutionarily conserved part of the limbic system known in mammals to relay aversive feedback from ventral pallidum (VP) to ventral tegmental area (VTA) dopamine neurons, is involved in birdsong learning and production. By combining viral tract tracing and functional circuit mapping, we discovered that songbird LHb links VP and an auditory cortical area to singing-related DA neurons that signal song errors. As in mammals, VP stimulation activated LHb activity and LHb stimulation suppressed DA firing. To test this pathway’s role in learning we lesioned the LHb in juvenile zebra finches and recorded their songs in adulthood. Birds with the LHb lesioned as juveniles produced highly unusual vocalizations as adults, including prolonged high-pitch notes and species-atypical trills. These findings identify a songbird VP-LHb-VTA pathway with similar functional connectivity as mammals, expand the known territories of vocal learning circuits, and demonstrate that limbic circuits associated with disappointing outcomes are important for motor performance learning.
Stimulus-Specific Modulation is Enabled by Differential Serotonin Receptor Expression

Neural networks must be able to flexibly process information under different conditions. To this end, networks frequently rely on uniform expression of modulatory receptors by distinct classes of neurons to fine tune the computations supported by each neuronal class. In this study, we explore the consequences of heterogeneous, rather than uniform, serotonin (5-HT) receptor expression within a cell class for olfactory processing in Drosophila melanogaster. Here, we demonstrate that two distinct populations of olfactory output neurons (projection neurons, PNs) display heterogeneous receptor co-expression of all 5-HT receptors. Moreover, the PN populations that express distinct 5-HT receptors innervate different combinations of glomeruli, implying that the effects of 5-HT on these PNs may vary with their odor tuning. Furthermore, connectomic analyses reveal that PN subsets with different receptor profiles have little convergence upon downstream synaptic partners. Finally, 5-HT differentially modulates the odor-evoked responses of PNs with distinct receptor expression profiles and odor tuning. Overall, this implies that heterogeneous modulatory receptor expression enables differential tuning of activity within a neuronal class depending on the odor scene to which individual neurons respond.
Structural insights into a single semi-clathrate hydrate formed in a confined environment of porous protein crystal

Water behavior on protein surfaces influences protein structure and function. Antifreeze Proteins (AFPs) have been intensively studied in context of biological cytotechnology. AFPs inhibit growth of ice microcrystals by forming unique water-cluster networks which are influenced by protein surface morphology and hydrophobicity. Such unique water-cluster networks have been identified as semi-clathrate structures in crystals and are believed to be stabilized by intermolecular interactions within the confined environment. However, there is little atomic-level information about the process of formation of semi-clathrates and the structural units of water-clathrate networks. We identified a single semi-clathrate formed on the pore surface of ferritin crystal which has a structure similar to that of a natural AFP. Comparison of ferritin mutants and determination of temperature-dependent structures revealed that semi-clathrate water molecules on an ⍺-helix undergo structural alterations with increasing temperature. Lowering the temperature regenerates the semi-clathrate structure. Water molecules hydrogen-bonded to main chain carbonyl groups are stably immobilized at room temperature and serve as starting points for clathrate formation. These findings provide a mechanistic understanding of water networks in AFPs and guidelines for designing new cryomaterials.
Prolonging lung cancer response to EGFR inhibition by targeting the selective advantage of resistant cells

Non-small cell lung cancers (NSCLCs) treated with tyrosine kinase inhibitors (TKIs) of the epidermal growth factor receptor (EGFR) almost invariably relapse in the long term, due to the emergence of subpopulations of resistant cells. Here we show that the lack of sensitivity of these cells to EGFR-TKIs constitutes a vulnerability that can be potentially targeted. Through a DNA barcoding approach, we demonstrate that the clinically approved drug sorafenib specifically abolishes the selective advantage of EGFR-TKI-resistant cells, while preserving the response of EGFR-TKI-sensitive cells, thus resulting in overall inhibition of clonal evolution within the tumor cell mass population. Sorafenib is active against multiple mechanisms of resistance/tolerance to EGFR-TKIs and its effects depend on early inhibition of MAPK interacting kinase (MNK) activity and signal transducer and activator of transcription 3 (STAT3) phosphorylation, and later down-regulation of MCL1 and EGFR. Using several xenograft and allograft models to recapitulate different mechanisms and kinetics of acquired resistance, we show that the sorafenib-EGFR-TKI combination can substantially delay tumor growth and promote the recruitment of inflammatory cells. Together, our findings indicate that sorafenib can substantially prolong the response to EGFR-TKIs by targeting NSCLC capacity to adapt to treatment through the emergence of resistant cells.
Duchenne muscular dystrophy: disease mechanism and therapeutic strategies

Duchenne muscular dystrophy (DMD) is a severe, progressive, and ultimately fatal disease of skeletal muscle wasting, respiratory insufficiency, and cardiomyopathy. The identification of the dystrophin gene as central to DMD pathogenesis has led to the understanding of the muscle membrane and the proteins involved in membrane stability as the focal point of the disease. The lessons learned from decades of research in human genetics, biochemistry, and physiology have culminated in establishing the myriad functionalities of dystrophin in striated muscle biology. Here, we review the pathophysiological basis of DMD and discuss recent progress toward the development of therapeutic strategies for DMD that are currently close to or are in human clinical trials. The first section of the review focuses on DMD and the mechanisms contributing to membrane instability, inflammation, and fibrosis. The second section discusses therapeutic strategies currently used to treat DMD. This includes a focus on outlining the strengths and limitations of approaches directed at correcting the genetic defect through dystrophin gene replacement, modification, repair, and/or a range of dystrophin-independent approaches. The final section highlights the different therapeutic strategies for DMD currently in clinical trials.