Miracle-dz/UniFAR-FTUs huggingface dataset:
Status and Magnitude of Grey Wolf Conflict with Pastoral Communities in the Foothills of the Hindu Kush Region of Pakistan

Simple Summary Despite higher loss due to disease, human–carnivore conflicts over livestock depredation is one of the major problems in carnivore conservation, both locally and globally. Locals share negative attitudes towards the wolf due to conflicts over livestock depredation. Using semi-structured questionnaires, we found that grey wolf is in a serious conflict with the locals, causing economic loss to them at the expanse of its own life. The locals considered the species a serious threat to their livestock, causing them economic losses, and wanted to reduce or even eliminate it from their area. Respondents having larger herd size and higher dependency on livestock for earning livelihoods shared more negative attitudes towards the wolves. In our study area the economic loss of the locals due to livestock mortalities from diseases was higher than that from wolf depredation. Therefore, we suggested that vaccination of the livestock and compensation schemes will help to change the perception of locals towards wolf. Abstract Pastoralist–wolf conflict over livestock depredation is the main factor affecting conservation of grey wolf worldwide. Very limited research has been carried out to evaluate the pattern and nature of livestock depredation by wolf. This study aims to determine the status and nature of human–wolf conflict across different villages in the Hind Kush region of Pakistan during the period January 2016–December 2016. For this purpose, a total of 110 local male respondents from all walks of life were interviewed using a semi-structured questionnaire. The grey wolf was declared as a common species in the area by 51.3% of the locals with an annual sighting rate of 0.46 each. During the year (2016), a total of 358 livestock were lost to grey wolf predation and disease. Of the total livestock loss, grey wolf was held responsible for a total 101 livestock losses. Goat and sheep were the most vulnerable prey species as they accounted for 80 (79.2%) of the total reported depredations. Out of the total economic loss (USD 46,736, USD 424.87/household), grey wolf was accountable for USD 11,910 (USD 108.27 per household), while disease contributed 34,826 (USD 316.6 per household). High depredation was observed during the summer season 58.42% (n = 59) followed by spring and autumn. Unattended livestock were more prone to grey wolf attack during free grazing in forests. Most of the respondents (75.45%) showed aggressive and negative attitudes towards grey wolf. The herders shared more negative attitude (z = −3.21, p = 0.001) than businessman towards the species. Herders having larger herd size displayed more deleterious behavior towards wolves than those having smaller herd size. Active herding techniques, vaccinating livestock, educating locals about wildlife importance, and initiating compensating schemes for affected families could be helpful to decrease negative perceptions.
Surface Heterogeneity-Involved Estimation of Sample Size for Accuracy Assessment of Land Cover Product from Satellite Imagery

Sample size estimation is a key issue for validating land cover products derived from satellite images. Based on the fact that present sample size estimation methods account for the characteristics of the Earth’s subsurface, this study developed a model for estimating sample size by considering the scale effect and surface heterogeneity. First, we introduced a watershed with different areas to indicate the scale effect on the sample size. Then, by employing an all-subsets regression feature selection method, three landscape indicators describing the aggregation and diversity of the land cover patches were selected (from 14 indicators) as the main factors for indicating the surface heterogeneity. Finally, we developed a multi-level linear model for sample size estimation using explanatory variables, including the estimated sample size (n) calculated from the traditional statistical model, size of the test region, and three landscape indicators. As reference data for developing this model, we employed a case study in the Jiangxi Province using a 30 m spatial resolution global land cover product (Globeland30) from 2010 as a classified map, and national 30 m land use/cover change (LUCC) data from 2010 in China. The results showed that the adjusted square coefficient of R2 is 0.79, indicating that the joint explanatory ability of all predictive variables in the model to the sample size is 79%. This means that the predictability of this model is at a good level. By comparing the sample size NS obtained by the developed multi-level linear model and n as calculated from the statistics model, we find that NS is much smaller than n, which mainly contributes to the concerns regarding surface heterogeneity in this study. The validity of the established model is tested and is proven as effective in the Anhui Province. This indicates that the estimated sample size from considering the scale effect and spatial heterogeneity in this study achieved the same accuracy as that calculated from a probability statistical model, while simultaneously saving more time, labour, and money in the accuracy assessment of a land cover dataset.
Improving the Hydrolysis Rate of the Renewable Poly(hexamethylene sebacate) Through Copolymerization of a Bis(pyrrolidone)-Based Dicarboxylic Acid

In this work, we report on the synthesis of a series of polyesters based on 1,6-hexanediol, sebacic acid, and N,N’-dimethylene-bis(pyrrolidone-4-carboxylic acid) (BP-C2), of which the latter is derived from renewable itaconic acid and 1,2-ethanediamine. Copolymers with a varying amount of BP-C2 as dicarboxylic acid are synthesized using a melt-polycondensation reaction with the aim of controlling the hydrolysis rate of the polymers in water or under bioactive conditions. We demonstrate that the introduction of BP-C2 in the polymer backbone does not limit the molecular weight build-up, as polymers with a weight average molecular weight close to 20 kg/mol and higher are obtained. Additionally, as the BP-C2 moiety is excluded from the crystal structure of poly(hexamethylene sebacate), the increase in BP-C2 concentration effectively results in a suppression in both melting temperature and crystallinity of the polymers. Overall, we demonstrate that the BP-C2 moiety enhances the polymer’s affinity to water, effectively improving the water uptake and rate of hydrolysis, both in demineralized water and in the presence of a protease from Bacillus licheniformis.
Tumor Immune Microenvironment and Chemosensitivity Signature for Predicting Response to Chemotherapy in Gastric Cancer

An SVM (support vector machine) signature, integrating immune microenvironment and chemosensitivity-related immunohistochemistry features of tumor cells, functions as an independent prognosis predictor. The signature identifies a subgroup of patients with gastric cancer likely to benefit from adjuvant chemotherapy. Current gastric cancer staging alone cannot predict prognosis and adjuvant chemotherapy benefits in stage II and III gastric cancer. Tumor immune microenvironment biomarkers and tumor-cell chemosensitivity might add predictive value to staging. This study aimed to construct a predictive signature integrating tumor immune microenvironment and chemosensitivity-related features to improve the prediction of survival and adjuvant chemotherapy benefits in patients with stage II to III gastric cancer. We used IHC to assess 26 features related to tumor, stroma, and chemosensitivity in tumors from 223 patients and evaluated the association of the features with disease-free survival (DFS) and overall survival (OS). Support vector machine (SVM)–based methods were used to develop the predictive signature, which we call the SVM signature. Validation of the signature was performed in two independent cohorts of 445 patients. The diagnostic signature integrated seven features: CD3+ cells at the invasive margin (CD3 IM), CD8+ cells at the IM (CD8 IM), CD45RO+ cells in the center of tumors (CD45RO CT), CD66b+ cells at the IM (CD66b IM), CD34+ cells, periostin, and cyclooxygenase-2. Patients fell into low- and high-SVM groups with significant differences in 5-year DFS and OS in the training and validation cohorts (all P < 0.001). The signature was an independent prognosis indicator in multivariate analysis in each cohort. The signature had better prognostic value than various clinicopathologic risk factors and single features. High-SVM patients exhibited a favorable response to adjuvant chemotherapy. Thus, this SVM signature predicted survival and has the potential for identifying patients with stage II and III gastric cancer who could benefit from adjuvant chemotherapy.
Expanding our horizons: central pattern generation in the context of complex activity sequences

ABSTRACT Central pattern generators (CPGs) are central nervous system (CNS) networks that can generate coordinated output in the absence of patterned sensory input. For decades, this concept was applied almost exclusively to simple, innate, rhythmic movements with essentially identical cycles that repeat continually (e.g. respiration) or episodically (e.g. locomotion). But many natural movement sequences are not simple rhythms, as they include different elements in a complex order, and some involve learning. The concepts and experimental approaches of CPG research have also been applied to the neural control of complex movement sequences, such as birdsong, though this is not widely appreciated. Experimental approaches to the investigation of CPG networks, both for simple rhythms and for complex activity sequences, have shown that: (1) brief activation of the CPG elicits a long-lasting naturalistic activity sequence; (2) electrical stimulation of CPG elements alters the timing of subsequent cycles or sequence elements; and (3) warming or cooling CPG elements respectively speeds up or slows down the rhythm or sequence rate. The CPG concept has also been applied to the activity rhythms of populations of mammalian cortical neurons. CPG concepts and methods might further be applied to a variety of fixed action patterns typically used in courtship, rivalry, nest building and prey capture. These complex movements could be generated by CPGs within CPGs (‘nested’ CPGs). Stereotypical, non-motor, non-rhythmic neuronal activity sequences may also be generated by CPGs. My goal here is to highlight previous applications of the CPG concept to complex but stereotypical activity sequences and to suggest additional possible applications, which might provoke new hypotheses and experiments. Summary: Central pattern generation is a concept conventionally applied to neural control of simple, innate rhythmic movements. Here, I discuss how it can be applied to the control of complex, non-rhythmic, learned stereotypical activity sequences.
Quantitative real-time PCR assay for the rapid identification of the intrinsically multidrug-resistant bacterial pathogen Stenotrophomonas maltophilia

Stenotrophomonas maltophilia is emerging as an important cause of disease in nosocomial and community-acquired settings, including bloodstream, wound and catheter-associated infections. Cystic fibrosis (CF) airways also provide optimal growth conditions for various opportunistic pathogens with high antibiotic tolerance, including S. maltophilia . Currently, there is no rapid, cost-effective and accurate molecular method for detecting this potentially life-threatening pathogen, particularly in polymicrobial specimens, suggesting that its true prevalence is underestimated. Here, we used large-scale comparative genomics to identify a specific genetic target for S. maltophilia , with subsequent development and validation of a real-time PCR assay for its detection. Analysis of 167 Stenotrophomonas spp. genomes identified a conserved 4 kb region in S. maltophilia , which was targeted for Black Hole Quencher assay design. Our assay yielded the positive detection of 89 of 89 (100%) clinical S. maltophilia strains, and no amplification of 23 non- S. maltophilia clinical isolates. S. maltophilia was detected in 10 of 16 CF sputa, demonstrating the assay's utility for direct detection in respiratory specimens. The assay demonstrated good sensitivity, with limits of detection and quantitation on pure culture of ~10 and ~100 genome equivalents, respectively. Our assay provides a highly specific, sensitive and cost-effective method for the accurate identification of S. maltophilia , and will improve the diagnosis and treatment of this under-recognized pathogen by enabling its accurate and rapid detection from polymicrobial clinical and environmental samples.
Thromboprophylactic Efficacy and Safety of Anticoagulants After Arthroscopic Knee Surgery: A Systematic Review and Meta-Analysis

To examine the efficacy and safety of anticoagulants after knee arthroscopy (KA), PubMed, EMBASE, databases of Cochrane Central Register of Controlled Trials, and Chinese National Knowledge Infrastructure were searched up to August 2019 for randomized controlled trials (RCT). Seven RCTs including 4097 patients were demonstrated eligible according to the inclusion and exclusion criteria. The efficacy and safety of thromboprophylaxis were assessed and expressed using relative risk (RR) and 95% confidence intervals (95% CIs). The analysis of pooled data showed that anticoagulants group exhibited significant lower overall incidence of symptomatic and asymptomatic venous thromboembolism (VTE; RR = 0.35, 95% CIs: 0.22-0.55, P < .00001), significant higher incidence of all bleeding events (RR = 1.42, 95% CIs: 1.08-1.86, P = .01) compared to control group. However, no significant difference was found in terms of incidence of symptomatic VTE (RR = 0.43, 95% CIs: 0.15-1.21, P = .11) and incidence of major bleeding events (RR = 1.87, 95% CIs: 0.40-8.67, P = .42). The pooled number needed to treat to prevent one symptomatic or asymptomatic VTE was 26, while the pooled number needed to harm to cause one major bleeding event was 869. These results show that anticoagulants can effectively reduce the overall risk of VTE after KA; however, the increased risk of bleeding should be fully considered. Further studies are required to address the risk–benefit calculus and cost-effectiveness of anticoagulants after KA.
Metabolomic Profiling and Cytotoxic Tetrahydrofurofuran Lignans Investigations from Premna odorata Blanco

Metabolomic profiling of different Premna odorata Blanco (Lamiaceae) organs, bark, wood, young stems, flowers, and fruits dereplicated 20, 20, 10, 20, and 20 compounds, respectively, using LC–HRESIMS. The identified metabolites (1–34) belonged to different chemical classes, including iridoids, flavones, phenyl ethanoids, and lignans. A phytochemical investigation of P. odorata bark afforded one new tetrahydrofurofuran lignan, 4β-hydroxyasarinin 35, along with fourteen known compounds. The structure of the new compound was confirmed using extensive 1D and 2D NMR, and HRESIMS analyses. A cytotoxic investigation of compounds 35–38 against the HL-60, HT-29, and MCF-7 cancer cell lines, using the MTT assay showed that compound 35 had cytotoxic effects against HL-60 and MCF-7 with IC50 values of 2.7 and 4.2 µg/mL, respectively. A pharmacophore map of compounds 35 showed two hydrogen bond acceptor (HBA) aligning the phenoxy oxygen atoms of benzodioxole moieties, two aromatic ring features vectored on the two phenyl rings, one hydrogen bond donor (HBD) feature aligning the central hydroxyl group and thirteen exclusion spheres which limit the boundaries of sterically inaccessible regions of the target’s active site.
Transcriptome-Based SNP Discovery and Validation in the Hybrid Zone of the Neotropical Annual Fish Genus Austrolebias

The genus Austrolebias (Cyprinodontiformes: Rivulidae) represents a specious group of taxa following annual life cycles in the neotropical ichthyofauna. They live in temporary ponds and each generation must be completed in a few months, depending on environmental stochasticity. Annual fish survive the dry season through diapausing eggs buried in the substrate of these ponds. A hypothesized bimodal hybrid zone between two taxa of the genus, A. charrua and A. reicherti from Dos Patos Merin lagoon system, was recently proposed based on genetics and morphological analyses. However, hundreds of additional nuclear molecular markers should be used to strongly support this hypothesized bimodal pattern. In the present paper, we conducted RNA-seq-based sequencing of the transcriptomes from pools of individuals of A. charrua, A. reicherti and their putative natural hybrids from the previously characterized hybrid zone. As a result, we identified a set of 111,725 SNP (single nucleotide polymorphism) markers, representing presumably fixed allelic differences among the two species. The present study provided the first panel of 106 SNP markers as a single diagnostic multiplex assay and validated their capacity to reconstruct the patterns of the hybrid zone between both taxa. These nuclear markers combined with Cytb gene and morphological analyses detected a population structure in which some groups among the hybrid swarms showed different level of introgression towards one or the other parental species according to their geographic distribution. High-quality transcriptomes and a large set of gene-linked SNPs should greatly facilitate functional and population genomics studies in the hybrid zone of these endangered species.
Phylogenetic Analysis of Lednice Orthobunyavirus

Lednice virus (LEDV) has been detected in Culex modestus mosquitoes in several European countries within the last six decades. In this study, phylogenetic analyses of the complete genome segments confirm that LEDV belongs to the Turlock orthobunyavirus (Orthobunyavirus, Peribunyaviridae) species and is closely related to Umbre, Turlock, and Kedah viruses.
On the use of Action Units and fuzzy explanatory models for facial expression recognition

Facial expression recognition is related to the automatic identification of affective states of a subject by computational means. Facial expression recognition is used for many applications, such as security, human-computer interaction, driver safety, and health care. Although many works aim to tackle the problem of facial expression recognition, and the discriminative power may be acceptable, current solutions have limited explicative power, which is insufficient for certain applications, such as facial rehabilitation. Our aim is to alleviate the current limited explicative power by exploiting explainable fuzzy models over sequences of frontal face images. The proposed model uses appearance features to describe facial expressions in terms of facial movements, giving a detailed explanation of what movements are in the face, and why the model is making a decision. The model architecture was selected to keep the semantic meaning of the found facial movements. The proposed model can discriminate between the seven basic facial expressions, obtaining an average accuracy of 90.8±14%, with a maximum value of 92.9±28%.
Radiation drives the evolution of orthotopic xenografts initiated from glioblastoma stem-like cells.

A consequence of the intratumor heterogeneity (ITH) of glioblastoma (GB) is the susceptibility to treatment driven evolution. To determine the potential of radiotherapy to influence GB evolution we used orthotopic xenografts initiated from CD133+ GB stem-like cells (GSCs). Towards this end, orthotopic xenografts grown in nude mice were exposed to a fractionated radiation protocol that resulted in a significant increase in animal survival. Brain tumors from control and irradiated mice were then collected at morbidity and compared in terms of growth pattern, clonal diversity and genomic architecture. In mice that received fractionated radiation, tumors were less invasive with more clearly demarcated borders and tumor core hypercellularity as compared to controls suggesting a fundamental change in tumor biology. Viral integration site analysis indicated a reduction in clonal diversity in the irradiated tumors implying a decrease in intratumor heterogeneity. Changes in clonal diversity were not detected after irradiation of GSCs in vitro suggesting that the radiation-induced reduction in intratumor heterogeneity was dependent on the brain microenvironment. Whole exome sequencing revealed differences in mutation patterns between control and irradiated tumors, which included modifications in the presence and clonality of driver mutations associated with GB. Moreover, changes in the distribution of mutations as a function of subpopulation size between control and irradiated tumors were consistent with subclone expansion and contraction, i.e. subpopulation evolution. Taken together, these results indicate that radiation drives the evolution of the GSC-initiated orthotopic xenografts and suggest that radiation-driven evolution may have therapeutic implications for recurrent GB.
Development of a Class-C Power Amplifier with Diode Expander Architecture for Point-of-Care Ultrasound Systems

Point-of-care ultrasound systems are widely used in ambulances and emergency rooms. However, the excessive heat generated from ultrasound transmitters has an impact on the implementation of piezoelectric transducer elements and on battery consumption, thereby affecting the system’s sensitivity and resolution. Non-linear power amplifiers, such as class-C amplifiers, could substitute linear power amplifiers, such as class-A amplifiers, which are currently used in point-of-care ultrasound systems. However, class-C power amplifiers generate less output power, resulting in a reduction of system sensitivity. To overcome this issue, we propose a new diode expander architecture dedicated to power amplifiers to reduce the effects of sinusoidal pulses toward the power supply. Thus, the proposed architecture could increase the input pulse amplitudes applied to the main transistors in the power amplifiers, hence increasing the output voltage of such amplifiers. To verify the proposed concept, pulse-echo responses from an ultrasonic transducer were tested with the developed class-C power amplifier using a resistor divider and the designed diode expander architecture. The peak-to-peak amplitude of the echo signals of the ultrasonic transducers when using a class-C power amplifier with a diode expander architecture (2.98 Vp–p) was higher than that for the class-C power amplifier with a resistor divider architecture (2.51 Vp–p). Therefore, the proposed class-C power amplifier with diode expander architecture is a potential candidate for improving the sensitivity performance of piezoelectric transducers for point-of-care ultrasound systems.
Automated Brain Tumor Segmentation Using Multimodal Brain Scans: A Survey Based on Models Submitted to the BraTS 2012–2018 Challenges

Reliable brain tumor segmentation is essential for accurate diagnosis and treatment planning. Since manual segmentation of brain tumors is a highly time-consuming, expensive and subjective task, practical automated methods for this purpose are greatly appreciated. But since brain tumors are highly heterogeneous in terms of location, shape, and size, developing automatic segmentation methods has remained a challenging task over decades. This paper aims to review the evolution of automated models for brain tumor segmentation using multimodal MR images. In order to be able to make a just comparison between different methods, the proposed models are studied for the most famous benchmark for brain tumor segmentation, namely the BraTS challenge [1]. The BraTS 2012-2018 challenges and the state-of-the-art automated models employed each year are analysed. The changing trend of these automated methods since 2012 are studied and the main parameters that affect the performance of different models are analysed.