bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ethnicity in Schools: Perceptions of Migrant Children from Central Asia in the Multicultural Environment of Russian Cities
Authors: Demintseva Ekaterina 
Published: June 2022

AbstractThis article analyzes phenomenon of “migrant schools” and “migrant classes” in schools that began to emerge in the 2010s in Siberian cities of Tomsk and Irkutsk. The study is based on 120 interviews with migrants and 36 express-interviews with parents of children from both local families and those that have migrated from Central Asia, as well as case studies of four schools in these two cities identified as “migrant” by local residents. Despite the ethnic diversity of these Siberian cities where most families themselves descend from migrants from other regions, the local population singles out new migrants from the countries of Central Asia as “others” in the urban space. While school administrations, teachers, and parents reproduce the narratives of tolerance and ethnic diversity, school segregation persists in these cities, manifested, among other things, in the emergence of “migrant” schools and “migrant classes” in schools. This study presents this segregation as an outcome of strategies pursued by school administrators and parents of both local and migrant children. In particular, creation of “migrant” classes in some schools is the school administrators’ response to the lack of adaptation programs for migrant children. I conclude that rather than assisting the socialization of migrant children, such schools reproduce their isolation from other pupils, limiting their ability to succeed in the future.
Should Animal Welfare Be Defined in Terms of Consciousness?
Authors: Birch Jonathan 
Published: June 2022

AbstractDefinitions of animal welfare often invoke consciousness or sentience. Marian Stamp Dawkins has argued that to define animal welfare this way is a mistake. In Dawkins’s alternative view, an animal with good welfare is one that is healthy and “has what it wants.” The dispute highlights a source of strain on the concept of animal welfare: consciousness-involving definitions are better able to capture the normative significance of welfare, whereas consciousness-free definitions facilitate the validation of welfare indicators. I reflect on how the field should respond to this strain, ultimately recommending against splitting the concept and in favor of consciousness-involving definitions.
Irreversible (One-hit) and Reversible (Sustaining) Causation
Authors: Ross Lauren N. , Woodward James F. 
Published: June 2022

AbstractThis paper explores a distinction among causal relationships that has yet to receive attention in the philosophical literature, namely, whether causal relationships are reversible or irreversible. We provide an analysis of this distinction and show how it has important implications for causal inference and modeling. This work also clarifies how various familiar puzzles involving preemption and over-determination play out differently depending on whether the causation involved is reversible.
BINARY SIGNED-DIGIT REPRESENTATIONS IN PAPERFOLDING
Authors: BATES BRUCE , BUNDER MARTIN , TOGNETTI KEITH 
Published: June 2022

AbstractWhen a page, represented by the interval
$[0,1]$
, is folded right over left
$n $
times, the right-hand fold contains a sequence of points. We specify these points using two different representation techniques, both involving binary signed-digit representations.
Subantarctic Mode Water Variations in the Three Southern Hemisphere Ocean Basins During 2004–2019
Authors: Wang Ran , Nan Feng , Yu Fei , Wang Bin 
Published: June 2022

AbstractSubantarctic mode water (SAMW) variations and their forcing mechanisms in the three Southern Hemisphere ocean basins are studied using Argo data and reanalysis products during the 2004–2019 period. In the Indian and Pacific Oceans, SAMW is characterized by potential vorticity (PV) minimums lower than 0.5 × 10−10 m−1 s−1. In the Atlantic Ocean, the PV minimum is generally lower than 1 × 10−10 m−1 s−1. The variations in SAMW thickness are significantly correlated with changes in the mixed layer depth (MLD) and show large differences among different ocean basins. The winter MLD in the Indian Ocean SAMW formation region is significantly positively correlated with the local wind stress curl (correlation coefficient = 0.61; 95% confidence level). In the Pacific and Atlantic SAMW formation regions, the variations in the winter MLD have significant negative correlations with the buoyancy flux; the correlation coefficients reach −0.57 and −0.67 (95% confidence level), respectively. These different mechanisms of the MLD variations in SAMW in the three ocean basins are related to the Southern Annular Mode (SAM) variation in winter. During positive (negative) SAM index periods, a strong positive (negative) wind stress curl anomaly occurs in association with a meridionally asymmetric westerly wind anomaly distribution. This phenomenon results in a corresponding MLD anomaly over the Indian Ocean SAMW formation region. In the Pacific and Atlantic SAMW formation regions, a negative (positive) westerly wind anomaly induces buoyancy gain (loss), leading to mixed layer shallowing (deepening) during positive (negative) SAM periods.
Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
Authors: Johnson J. Isaac , Sharman Glenn R. , Szymanski Eugene , Huang Xiao 
Published: June 2022

AbstractPetrography has long been used as a tool to decipher the sedimentary provenance of sand and sandstone based on relative proportions of detrital grain types. However, there is not yet a predictive framework that constrains the relationship between sand grain composition and the factors that influence it, including bedrock lithology, elevation, slope, basin area, precipitation, and temperature. We used a globally extensive modal point‐count data set of 3,522 Pleistocene to modern sand samples to train an inline series of random forest meta‐estimators to predict relative abundances of quartz (Q), feldspar (F), and lithic (L) grain types and eight subcompositions. The trained random forest models were fit to a global data set of fluvial watersheds to produce the global prediction of sand modal composition (GloPrSM) model which predicts Q‐F‐L of fluvially transported sediment. GloPrSM predicts quartz enrichment in low latitudes (35°N to 35°S), feldspar enrichment near plutonic and metamorphic crystalline terranes in middle to high latitudes, and lithic enrichment near modern and ancient collisional plate boundaries and flood basalts. Our analyses reveal that slope, temperature, and the relative abundance of exposed metamorphic and felsic to intermediate plutonic rocks are the most important predictors of Q‐F‐L composition. In addition, temperatures higher than 15°C and large drainage areas appear to promote quartz enrichment, while steeply sloping environments favor lithic enrichment. The GloPrSM model represents the first global‐scale estimate of fluvial sand compositional modes and illustrates that the spatial distribution of Q‐F‐L at Earth's surface can be predicted from the first‐order factors that generate sediment.
Temporal Effects of Monsoon Rainfall Pulses on Plant Available Nitrogen in a Chihuahuan Desert Grassland
Authors: Brown Renée F. , Sala Osvaldo E. , Sinsabaugh Robert L. , Collins Scott L. 
Published: June 2022

AbstractDrylands are often characterized by a pulse dynamics framework in which episodic rain events trigger brief pulses of biological activity and resource availability that regulate primary production. In the northern Chihuahuan Desert, growing season precipitation typically comes from monsoon rainstorms that stimulate soil microbial processes like decomposition, releasing inorganic nitrogen needed by plant processes. Compared to microbes, plants require greater amounts of soil moisture, typically from larger monsoon storms predicted to become less frequent and more intense in the future. Yet field‐based studies linking rainfall pulses with soil nutrient dynamics are rare. Consequently, little is known about how changes in rainfall patterns may affect plant available nitrogen in dryland soils, particularly across temporal scales. We measured daily and seasonal responses of soil inorganic nitrogen and related parameters to experimentally applied small frequent and large infrequent rain events throughout a summer growing season in a Chihuahuan Desert grassland. Contrary to long‐standing theories around resource pulse dynamics in drylands, nitrogen availability did not pulse following experimental rain events. Moreover, large infrequent events resulted in significantly less plant available nitrogen despite causing distinct pulses of increased soil moisture availability that persisted for several days. Overall, nitrogen availability increased over the growing season, especially following small frequent rain events that also stimulated some microbial ecoenzymatic activities. Our results suggest that projected changes in climate to fewer, larger rain events could significantly impact primary production in desert grasslands by decreasing plant available nitrogen when soil moisture is least limiting to plant growth.
LDL receptor-related protein 1 (LRP1), a novel target for opening the blood-labyrinth barrier (BLB)
Authors: Shi Xi , Wang Zihao , Ren Wei , Chen Long , Xu Cong , Li Menghua , Fan Shiyong , Xu Yuru , Chen Mengbing , Zheng Fanjun , Zhang Wenyuan , Zhou Xinbo , Zhang Yue , Qiu Shiwei , Wu Liyuan , Zhou Peng , Lv Xinze , Cui Tianyu , Qiao Yuehua , Zhao Hui , Guo Weiwei , Chen Wei , Li Song , Zhong Wu , Lin Jian , Yang Shiming 
Published: June 2022

AbstractInner ear disorders are a cluster of diseases that cause hearing loss in more than 1.5 billion people worldwide. However, the presence of the blood-labyrinth barrier (BLB) on the surface of the inner ear capillaries greatly hinders the effectiveness of systemic drugs for prevention and intervention due to the low permeability, which restricts the entry of most drug compounds from the bloodstream into the inner ear tissue. Here, we report the finding of a novel receptor, low-density lipoprotein receptor-related protein 1 (LRP1), that is expressed on the BLB, as a potential target for shuttling therapeutics across this barrier. As a proof-of-concept, we developed an LRP1-binding peptide, IETP2, and covalently conjugated a series of model small-molecule compounds to it, including potential drugs and imaging agents. All compounds were successfully delivered into the inner ear and inner ear lymph, indicating that targeting the receptor LRP1 is a promising strategy to enhance the permeability of the BLB. The discovery of the receptor LRP1 will illuminate developing strategies for crossing the BLB and for improving systemic drug delivery for inner ear disorders.
Automated recognition of pain in cats
Authors: Feighelstein Marcelo , Shimshoni Ilan , Finka Lauren R. , Luna Stelio P. L. , Mills Daniel S. , Zamansky Anna 
Published: June 2022

AbstractFacial expressions in non-human animals are closely linked to their internal affective states, with the majority of empirical work focusing on facial shape changes associated with pain. However, existing tools for facial expression analysis are prone to human subjectivity and bias, and in many cases also require special expertise and training. This paper presents the first comparative study of two different paths towards automatizing pain recognition in facial images of domestic short haired cats (n = 29), captured during ovariohysterectomy at different time points corresponding to varying intensities of pain. One approach is based on convolutional neural networks (ResNet50), while the other—on machine learning models based on geometric landmarks analysis inspired by species specific Facial Action Coding Systems (i.e. catFACS). Both types of approaches reach comparable accuracy of above 72%, indicating their potential usefulness as a basis for automating cat pain detection from images.
Combining ability and gene action for yield improvement in kenaf (Hibiscus cannabinus L.) under tropical conditions through diallel mating design
Authors: Al-Mamun Md , Rafii Mohd Y. , Misran Azizah Binti , Berahim Zulkarami , Ahmad Zaiton , Khan Md Mahmudul Hasan , Oladosu Yusuff 
Published: June 2022

AbstractNine morphologically distinct kenaf genotypes were hybridized to produce 36 hybrids following a half diallel mating design. The combining ability and gene action of 15 yield and yield components were assessed in hybrids and their parents across two environments. Except for the mid diameter and plant height traits, there were highly significant differences (p ≤ 0.01) between the environments and the interaction of genotype and environment. Additive gene effects were considerable for the inheritance of these traits, and the expression of these additive genes was heavily influenced by the environment. Significant differences were found for all studied traits for GCA except top diameter and SCA except plant height and top diameter, implying the presence of both additive and non-additive gene action for the inheritance of the concerned characters. For all features except top diameter and number of nodes, the magnitude of GCA variation was significantly higher than that of SCA variance, indicating the additive gene's predominance. The parental lines P1, P3 and P4 were outstanding general combiners for fiber yield and yield-related parameters. Considering combining ability and genetic analysis study, the crosses P1 × P4, P1 × P9, P2 × P3, P2 × P5, P4 × P6, P4 × P7, P4 × P9, P5 × P8, and P7 × P9 were found promising for their heterotic response to higher fiber yield, stick yield, seed yield and could be for future improvement in kenaf breeding programmes.
Maximum entropy models provide functional connectivity estimates in neural networks
Authors: Lamberti Martina , Hess Michael , Dias Inês , van Putten Michel , le Feber Joost , Marzen Sarah 
Published: June 2022

AbstractTools to estimate brain connectivity offer the potential to enhance our understanding of brain functioning. The behavior of neuronal networks, including functional connectivity and induced connectivity changes by external stimuli, can be studied using models of cultured neurons. Cultured neurons tend to be active in groups, and pairs of neurons are said to be functionally connected when their firing patterns show significant synchronicity. Methods to infer functional connections are often based on pair-wise cross-correlation between activity patterns of (small groups of) neurons. However, these methods are not very sensitive to detect inhibitory connections, and they were not designed for use during stimulation. Maximum Entropy (MaxEnt) models may provide a conceptually different method to infer functional connectivity. They have the potential benefit to estimate functional connectivity during stimulation, and to infer excitatory as well as inhibitory connections. MaxEnt models do not involve pairwise comparison, but aim to capture probability distributions of sets of neurons that are synchronously active in discrete time bins. We used electrophysiological recordings from in vitro neuronal cultures on micro electrode arrays to investigate the ability of MaxEnt models to infer functional connectivity. Connectivity estimates provided by MaxEnt models correlated well with those obtained by conditional firing probabilities (CFP), an established cross-correlation based method. In addition, stimulus-induced connectivity changes were detected by MaxEnt models, and were of the same magnitude as those detected by CFP. Thus, MaxEnt models provide a potentially powerful new tool to study functional connectivity in neuronal networks.
Using deep learning to detect digitally encoded DNA trigger for Trojan malware in Bio-Cyber attacks
Authors: Islam M. S. , Ivanov S. , Awan H. , Drohan J. , Balasubramaniam S. , Coffey L. , Kidambi S. , Sri-saan W. 
Published: June 2022

AbstractThis article uses Deep Learning technologies to safeguard DNA sequencing against Bio-Cyber attacks. We consider a hybrid attack scenario where the payload is encoded into a DNA sequence to activate a Trojan malware implanted in a software tool used in the sequencing pipeline in order to allow the perpetrators to gain control over the resources used in that pipeline during sequence analysis. The scenario considered in the paper is based on perpetrators submitting synthetically engineered DNA samples that contain digitally encoded IP address and port number of the perpetrator’s machine in the DNA. Genetic analysis of the sample’s DNA will decode the address that is used by the software Trojan malware to activate and trigger a remote connection. This approach can open up to multiple perpetrators to create connections to hijack the DNA sequencing pipeline. As a way of hiding the data, the perpetrators can avoid detection by encoding the address to maximise similarity with genuine DNAs, which we showed previously. However, in this paper we show how Deep Learning can be used to successfully detect and identify the trigger encoded data, in order to protect a DNA sequencing pipeline from Trojan attacks. The result shows nearly up to 100% accuracy in detection in such a novel Trojan attack scenario even after applying fragmentation encryption and steganography on the encoded trigger data. In addition, feasibility of designing and synthesizing encoded DNA for such Trojan payloads is validated by a wet lab experiment.
Influence of sintering temperatures on microstructure and electrochemical performances of LiNi0.93Co0.04Al0.03O2 cathode for high energy lithium ion batteries
Authors: Park Hye-Jin , Sim Seong-Ju , Jin Bong-Soo , Lee Seung-Hwan , Kim Hyun-Soo 
Published: June 2022

AbstractIn this study, we present a method for synthesizing Ni-rich LiNi0.93Co0.04Al0.03O2 (NCA) with a high-energy cathode material by the solid-phase method. The sintering temperature plays a very important role in the electrochemical performance of the LiNi0.93Co0.04Al0.03O2 since it affects the crystallinity and structural stability. Therefore, various sintering temperatures (660 °C/690 °C/720 °C/750 °C/780 °C/810 °C) are studied to get optimum electrochemical performances. The electrochemical performance of LiNi0.93Co0.04Al0.03O2 sintered at 720 °C shows the highest discharge capacity of 217.48 mAh g−1 with excellent Coulombic efficiency of 87.84% at 0.1 C. Moreover, the LiNi0.93Co0.04Al0.03O2 sintered at 720 °C exhibits excellent rate-capability (181.1 mAh g−1 at 2.0 C) as well as superior cycle stability (95.4% after 80 cycles at 0.5 C). This is because optimized sintering temperature leads to good structural stability with low cation disorder and residual lithium content.
Identification of selection signatures in Iranian dromedary and Bactrian camels using whole genome sequencing data
Authors: Khalkhali-Evrigh Reza , Hedayat Nemat , Ming Liang , Jirimutu  
Published: June 2022

AbstractThe Old World camels play an important role as one of the main food sources in large parts of Asia and Africa. Natural selection combined with artificial selection by human has affected parts of the domestic animal genome for adapting them to their habitats and meeting human needs. Here, we used whole genome sequencing data of 34 camels (including 14 dromedaries and 20 Bactrian camels) to identify the genomic signature of selection in the Iranian dromedary (ID) and Bactrian camels (IB). To detect the mentioned regions, we used two methods including population differentiation index (Fst) and cross-population extended haplotype homozygosity (XP-EHH) with 50 kb sliding window and 25 kb step size. Based on gene ontology analysis on the candidate genes identified for IB camels, we found GO terms associated with lung development, nervous system development, immune system and behavior. Also, we identified several genes related to body thermoregulation (ZNF516), meat quality (ANK1 and HSPA13), and high-altitude adaptation (OPA1) for IB camels. In the list of detected candidate genes under selection in ID camels, the genes related to energy metabolism (BDH1), reproduction (DLG1, IMMP2L and FRASI), long-term memory (GRIA1), kidney (SLC12A1), lung development (EMILIN2 and FBN1) and immunity (SOCS2, JAK1, NRROS and SENP1) were found. Our findings, along with further studies in this field, will strengthen our knowledge about the effect of selection on the camelid genome under different geographical, climatic and even cultural conditions.
LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data
Authors: Lall Snehalika , Ray Sumanta , Bandyopadhyay Sanghamitra 
Published: June 2022

AbstractA fundamental problem of downstream analysis of scRNA-seq data is the unavailability of enough cell samples compare to the feature size. This is mostly due to the budgetary constraint of single cell experiments or simply because of the small number of available patient samples. Here, we present an improved version of generative adversarial network (GAN) called LSH-GAN to address this issue by producing new realistic cell samples. We update the training procedure of the generator of GAN using locality sensitive hashing which speeds up the sample generation, thus maintains the feasibility of applying the standard procedures of downstream analysis. LSH-GAN outperforms the benchmarks for realistic generation of quality cell samples. Experimental results show that generated samples of LSH-GAN improves the performance of the downstream analysis such as feature (gene) selection and cell clustering. Overall, LSH-GAN therefore addressed the key challenges of small sample scRNA-seq data analysis.
Safety and effectiveness of underwater cold snare resection without submucosal injection of large non-pedunculated colorectal lesions
Authors: Yen Andrew W. , Leung Joseph W. , Koo Malcom , Leung Felix W. 
Published: June 2022

Abstract
Background and study aims Adverse events are uncommon with cold snaring, but cold techniques are generally reserved for lesions ≤ 9 mm out of concern for incomplete resection or inability to mechanically resect larger lesions. In a non-distended, water-filled lumen, colorectal lesions are not stretched, enabling capture and en bloc resection of large lesions. We assessed the effectiveness and safety of underwater cold snare resection (UCSR) without submucosal injection (SI) of ≥ 10 mm non-pedunculated, non-bulky (≤ 5 mm elevation) lesions with small, thin wire snares.
Patients and methods Retrospective analysis of an observational cohort of lesions removed by UCSR during colonoscopy. A single endoscopist performed procedures using a small thin wire (9-mm diameter) cold or (10-mm diameter) hybrid snare.
Results Fifty-three lesions (mean 15.8 mm [SD 6.9]; range 10–35 mm) were removed by UCSR from 44 patients. Compared to a historical cohort, significantly more lesions were resected en bloc by UCSR (84.9 % [45/53]; P = 0.04) compared to conventional endoscopic mucosal resection (EMR) (64.0 % [32/50]). Results were driven by high en bloc resection rates for 10– to 19-mm lesions (97.3 % [36/37]; P = 0.01). Multiple logistic regression analysis adjusted for potential confounders showed en bloc resection was significantly associated with UCSR compared to conventional EMR (OR 3.47, P = 0.027). Omission of SI and forgoing prophylactic clipping of post-resection sites did not result in adverse outcomes.
Conclusions UCSR of ≥ 10 mm non-pedunculated, non-bulky colorectal lesions is feasible with high en bloc resection rates without adverse outcomes. Omission of SI and prophylactic clipping decreased resource utilization with economic benefits. UCSR deserves further evaluation in a prospective comparative study.