Miracle-dz/UniFAR-FTUs huggingface dataset:
The Seasonality of Mesoscale Eddy Intensity in the Southeastern Tropical Indian Ocean

The seasonality of mesoscale eddy intensity in the southeastern tropical Indian Ocean (SETIO) is investigated using the latest eddy dataset and marine hydrological reanalysis data. The results show that the eddy intensity in an area to the southwest coast of the Java Island has prominent seasonality—eddies in this area are relatively weak during the first half of the year but tend to enhance in August and peak in October. Further analysis reveals that the strong eddies in October are actually developed from the ones mainly formed in July to September, and the barotropic instability and baroclinic instability are the key dynamics for eddy development, but each plays a different role at different development stages. The barotropic instability resulting from the horizontal shear of surface current plays an important role in the early stage of eddy development. However, in the late development stage, the baroclinic instability induced by the sloping pycnocline becomes the major energy contributor of eddy development.
Deciphering the Effects and Mechanisms of Yi-Fei-San-Jie-pill on Non-Small Cell Lung Cancer With Integrating Network Target Analysis and Experimental Validation

Non-small cell lung cancer (NSCLC), which accounts for 85% of lung cancer cases, calls for better therapy. Yi-Fei-San-Jie-pill (YFSJ), a well-applicated traditional Chinese medicine formula, was reported to be effective in the treatment of NSCLC. However, its anti-tumor mechanism still needs to be fully elucidated. Herein, a reliable preclinical orthotopic but not subcutaneous model of NSCLC in mice was established to evaluate the anti-cancer properties and further validate the mechanisms of YFSJ. A bioinformatic analysis was executed to identify the potential targets and key pathways of YFSJ on NSCLC. In detail, the anti-tumor effect of YFSJ and the autophagy inhibitor 3-MA was evaluated according to the tumor fluorescence value and comparison of different groups’ survival times. As a result, YFSJ markedly decreased tumor size and prolonged survival time in contrast with those in the orthotopic model group (p < 0.05), and it also significantly regulated the protein expression levels of apoptosis- and autophagy-related proteins. In conclusion, this study provides convincing evidence that YFSJ could inhibit the growth of tumors and prolong the survival time of tumor-bearing mice based on the NSCLC orthotopic model, and its anti-tumor effect was closely associated with the promotion of apoptosis and interference of autophagy coupled with regulation of immune infiltration.
Automatic Tumor Grading on Colorectal Cancer Whole-Slide Images: Semi-Quantitative Gland Formation Percentage and New Indicator Exploration

Tumor grading is an essential factor for cancer staging and survival prognostication. The widely used the WHO grading system defines the histological grade of CRC adenocarcinoma based on the density of glandular formation on whole-slide images (WSIs). We developed a fully automated approach for stratifying colorectal cancer (CRC) patients’ risk of mortality directly from histology WSI relating to gland formation. A tissue classifier was trained to categorize regions on WSI as glands, stroma, immune cells, background, and other tissues. A gland formation classifier was trained on expert annotations to categorize regions as different degrees of tumor gland formation versus normal tissues. The glandular formation density can thus be estimated using the aforementioned tissue categorization and gland formation information. This estimation was called a semi-quantitative gland formation ratio (SGFR), which was used as a prognostic factor in survival analysis. We evaluated gland formation percentage and validated it by comparing it against the WHO cutoff point. Survival data and gland formation maps were then used to train a spatial pyramid pooling survival network (SPPSN) as a deep survival model. We compared the survival prediction performance of estimated gland formation percentage and the SPPSN deep survival grade and found that the deep survival grade had improved discrimination. A univariable Cox model for survival yielded moderate discrimination with SGFR (c-index 0.62) and deep survival grade (c-index 0.64) in an independent institutional test set. Deep survival grade also showed better discrimination performance in multivariable Cox regression. The deep survival grade significantly increased the c-index of the baseline Cox model in both validation set and external test set, but the inclusion of SGFR can only improve the Cox model less in external test and is unable to improve the Cox model in the validation set.
Post-surgery Rehabilitative Intervention Based on Imitation Therapy and Mouth-Hand Motor Synergies Provides Better Outcomes in Smile Production in Children and Adults With Long Term Facial Paralysis

Rehabilitation after free gracilis muscle transfer (smile surgery, SS) is crucial for a functional recovery of the smiling skill, mitigating social and psychological problems resulting from facial paralysis. We compared two post-SS rehabilitation treatments: the traditional based on teeth clenching exercises and the FIT-SAT (facial imitation and synergistic activity treatment). FIT-SAT, based on observation/imitation therapy and on hand-mouth motor synergies would facilitate neuronal activity in the facial motor cortex avoiding unwanted contractions of the jaw, implementing muscle control. We measured the smile symmetry on 30 patients, half of whom after SS underwent traditional treatment (control group, CG meanage = 20 ± 9) while the other half FIT-SAT (experimental group, EG meanage= 21 ± 14). We compared pictures of participants while holding two postures: maximum and gentle smile. The former corresponds to the maximal muscle contraction, whereas the latter is strongly linked to the control of muscle strength during voluntary movements. No differences were observed between the two groups in the maximum smile, whereas in the gentle smile the EG obtained a better symmetry than the CG. These results support the efficacy of FIT-SAT in modulating the smile allowing patients to adapt their smile to the various social contexts, aspect which is crucial during reciprocal interactions.
CGRP and the Calcitonin Receptor are Co-Expressed in Mouse, Rat and Human Trigeminal Ganglia Neurons

The neuropeptide calcitonin gene-related peptide (CGRP) is expressed in the trigeminal ganglia, a key site in craniofacial pain and migraine. CGRP potently activates two receptors: the CGRP receptor and the AMY1 receptor. These receptors are heterodimers consisting of receptor activity-modifying protein 1 (RAMP1) with either the calcitonin receptor-like receptor (CLR) to form the CGRP receptor or the calcitonin receptor (CTR) to form the AMY1 receptor. The expression of the CGRP receptor in trigeminal ganglia has been described in several studies; however, there is comparatively limited data available describing AMY1 receptor expression and in which cellular subtypes it is found. This research aimed to determine the relative distributions of the AMY1 receptor subunit, CTR, and CGRP in neurons or glia in rat, mouse and human trigeminal ganglia. Antibodies against CTR, CGRP and neuronal/glial cell markers were applied to trigeminal ganglia sections to investigate their distribution. CTR-like and CGRP-like immunoreactivity were observed in both discrete and overlapping populations of neurons. In rats and mice, 30–40% of trigeminal ganglia neurons displayed CTR-like immunoreactivity in their cell bodies, with approximately 78–80% of these also containing CGRP-like immunoreactivity. Although human cases were more variable, a similar overall pattern of CTR-like immunoreactivity to rodents was observed in the human trigeminal ganglia. CTR and CGRP appeared to be primarily colocalized in small to medium sized neurons, suggesting that colocalization of CTR and CGRP may occur in C-fiber neurons. CGRP-like or CTR-like immunoreactivity were not typically observed in glial cells. Western blotting confirmed that CTR was expressed in the trigeminal ganglia of all three species. These results confirm that CTR is expressed in trigeminal ganglia neurons. The identification of populations of neurons that express both CGRP and CTR suggests that CGRP could act in an autocrine manner through a CTR-based receptor, such as the AMY1 receptor. Overall, this suggests that a trigeminal ganglia CTR-based receptor may be activated during migraine and could therefore represent a potential target to develop treatments for craniofacial pain and migraine.
Cariprazine Use in Combination With a Mood Stabilizer in First Episode Mania

Background Cariprazine's efficacy and safety have been previously tested in adult patients with acute mania associated with bipolar I disorder, but there is no available data in FEM. The objective of this study is to assess the efficacy and safety of cariprazine in combination with a mood stabilizer in treating FEM as well as to evaluate patients' adherence to the treatment. Methods FEM patients were recruited from the acute inpatient unit at Lleida University Hospital Santa Maria, between January and June 2021. Their symptoms were evaluated using the Young Mania Rating Scale (YMRS) and the Clinical Global Impressions–Severity (CGI-S) scale at admission and at discharge. Akathisia was assessed using the Barnes Akathisia Rating Scale. Patient adherence to medication treatment was assessed 30 days after discharge using the Morisky, Green and Levine Medication Adherence Scale. Socio-demographic and clinical information were further collected. Results Eleven patients with FEM were involved, seven women and four men. Their mean age was 26.00+/-6.37 years. Mean hospitalization was 17.36+/−4.7 days. Cariprazine was combined with a mood stabilizer: lithium in seven patients and divalproex in four. Mean YMRS change from baseline was −24.55+/−7.5 and the mean CGI-S change from baseline was −2.55+/−0.82. Regarding adverse events, two (18.2%) patients presented with akathisia. At the 30-day treatment-adherence assessment, six (54.5%) patients were adherent and four (36.4%) had moderate adherence. Conclusion In this sample, cariprazine in combination with mood stabilizers proved to be safe and effective in the treatment of FEM with more than half the patients being adherent to treatment. Therefore, cariprazine add-on is a good choice for promoting the long-term adherence of patients, thus minimizing the risk of relapse and improving prognosis.
Right Ventricle to Pulmonary Artery Coupling Predicts the Risk Stratification in Patients With Systemic Sclerosis-Associated Pulmonary Arterial Hypertension

Background Pulmonary arterial hypertension (PAH) is a serious complication of systemic sclerosis (SSc). PAH has high mortality, and risk assessment is critical for proper management. Whether the right ventricle to pulmonary artery (RV-PA) coupling accurately assesses risk status and predicts prognosis in patients with SSc-associated PAH has not been investigated. Methods Between March 2010 and July 2018, 60 consecutive patients with SSc-associated PAH diagnosed by right heart catheterization were enrolled prospectively, and the mean follow-up period was 52.9 ± 27.0 months. The RV-PA coupling was assessed by the ratio of tricuspid annular plane systolic excursion (TAPSE) and pulmonary artery systolic pressure (PASP) which was obtained by transthoracic echocardiography. The simplified risk stratification strategy was applied to assess the risk level of participants, and the endpoint was a composite of all-cause death and clinical worsening. Results The receiver operating characteristic (ROC) curve of the ability to determine high-risk patients identified the optimal cut-off value of the TAPSE/PASP ratio as 0.194 mm/mmHg, and the ratio appeared to be a reliable indicator in the stratification of patients with high risk (area under the curve = 0.878, ROC P-value = 0.003), which showed the highest positive likelihood ratio (LR) (5.4) and the lowest negative LR (0) among a series of echocardiographic parameters. The TAPSE/PASP ratio was an independent predictive factor (HR = 0.01, 95% CI: 0.00–0.77, P = 0.037) for the composite endpoint, and patients with a TAPSE/PASP ratio >0.194 had a better overall survival for both the composite endpoint (log-rank χ2 = 5.961, P = 0.015) and all-cause mortality (log-rank χ2 = 8.004, P = 0.005) compared to the patients with a TAPSE/PASP ≤ 0.194. Conclusion RV-PA coupling assessed by the TAPSE/PASP ratio provides added value as a straightforward and non-invasive approach for predicting risk stratification of patients with SSc-associated PAH. Meanwhile, a lower TAPSE/PASP ratio identified a subgroup with worse prognosis.
Living in an imbalanced world

Classification is one of the most fundamental tasks in the machine learning and data mining communities. One of the most common challenges faced when trying to perform classification is the class imbalance problem. The introduction of class imbalance into the classification problem poses serious and interesting challenges which must be met in order to provide knowledge. An orthogonal problem to class imbalance arises due to concept drift in data streams. Due to the complexity of each of the issues—much less both in tandem—the combination of class imbalance and concept drift are very understudied. In this dissertation we discuss classification in an imbalanced world from a variety of angles. First, we propose methods to overcome class imbalance in its simplest incarnation. In subsequent chapters, we remove restrictions in order to provide novel solutions and insights. By the end of this dissertation, we will present a wide variety of solutions to the class imbalance problem, including the combination of class imbalance and concept drift. Before beginning, however, we present intuitive (and mathematical) definitions of class imbalance and concept drift, as well as an overview of the state of the art methods in each community.
A Comparison of Post-Processed Variables Used by the Tri-Service Version of the Integrated Weather Effects Decision Aid

Abstract : The U.S. Army Research Laboratory (ARL) has developed a red-amber-green mission-planning aid for Army commanders to advise them when and where the environmental conditions currently exceed or are forecasted to exceed levels of marginal or severe impact to their systems, operations, or personnel. A Tri-service version of the software has been developed and fielded on Air Force and Navy systems. Meteorological data is provided to the Tri-Service Integrated Weather Effects Decision Aid (T-IWEDA) from both the Weather Research and Forecasting (WRF) model and -degree Global Forecast System (GFS) output. Once the model output is received, many of the weather variables needed by the T-IWEDA rules are developed by both Air Force Weather Agency (AFWA) and ARL in their post-processing software so that mission planning can be achieved based on the weather conditions. This report looks at the different and unique approaches to solving forecasting challenges such as clouds, icing, and turbulence.
Andrubis: Android Malware Under the Magnifying Glass

The smartphone industry has been one of the fastest growing technological areas in recent years. Naturally, the considerable market share of the Android OS and the diversity of app distribution channels besides the official Google Play Store has attracted the attention of malware authors. To deal with the increasing numbers of malicious Android apps in the wild, malware analysts typically rely on analysis tools to extract characteristic information about an app in an automated fashion. While the importance of such tools has been addressed by the research community [8], [25], [26], [28], the resulting prototypes remain limited in terms of analysis capabilities and availability. In this paper we present ANDRUBIS, a completely automated, publicly available and comprehensive analysis system for Android applications. ANDRUBIS combines static analysis techniques with dynamic analysis on both Dalvik VM and system level, as well as several stimulation techniques to increase code coverage.
Antibiosis to Spodoptera frugiperda (Lepidoptera: Noctuidae) in chickpea genotypes

Abstract Chickpeas (Cicer arietinum L.) belong to the Fabaceae family and are one of the most grown crops in the world and an important source of protein for humans. Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae) is a polyphagous pest that causes significant crop damage. The objective of this study was to examine antibiosis to S. frugiperda in chickpea genotypes. The following genotypes were studied: Jamu 96 and Blanco Sinaloa 92 (Mexico); Nacional 29 (Cuba); BG 1392 (Spain), and BRS Kalifa, BRS Cristalino, BRS Toro, Nacional 27, 004UP, 003UP, BRS Cícero, and BRS Aleppo (Brazil). The chickpea genotypes influenced the biological parameters of S. frugiperda, of which larval period, larval weight, and pupal period were most affected. Nacional 29 caused high mortality in the larval and pupal stages of S. frugiperda. The larvae on BRS Aleppo had the longest larval stage, lowest weight, and longest pupal stage. The genotypes Nacional 29, Nacional 27, and BRS Cícero showed antibiosis resistance to S. frugiperda. These genotypes could be used as a source of resistance to S. frugiperda in conjunction with other methods of pest control in integrated pest management programs for chickpea crops. These resistant genotypes could also be used as donor sources in breeding programs for insect resistance.
Identification and analysis of chemosensory genes encoding odorant-binding proteins, chemosensory proteins and sensory neuron membrane proteins in the antennae of Lissorhoptrus oryzophilus

Abstract The rice water weevil, Lissorhoptrus oryzophilus Kuschel (Coleoptera: Curculionidae), is a destructive pest that causes damage to rice crops worldwide. The olfactory system is critical for host or mate location by weevils, but only limited information about the molecular mechanism of olfaction-related behaviour has been reported in this insect. In this study, we conducted SMRT-seq transcriptome analysis and obtained 54,378 transcripts, 38,706 of which were annotated. Based on these annotations, we identified 40 candidate chemosensory genes, including 31 odorant-binding proteins (OBPs), six chemosensory proteins (CSPs) and three sensory neuron membrane proteins (SNMPs). Phylogenetic analysis showed that LoryOBPs, LoryCSPs and LorySNMPs were distributed in various clades. The results of tissue expression patterns indicated that LoryOBPs were highly abundant in the antennae, whereas LoryCSPs were highly abundant not only in the antennae but also in the abdomen, head and wings. Our findings substantially expand the gene database of L. oryzophilus and may serve as a basis for identifying novel targets to disrupt key olfactory genes, potentially providing an eco-friendly strategy to control this pest in the future.
Education Disparity in Chicago Public High Schools

The purpose of this paper is to delve into the Chicago public high school system to extract information on demographics and academics. The methods used are common in machine learning and discrete mathematics and seek to bring helpful visualizations and interpretations of education disparity. Not only is the goal to analyze the current state but also how these demographic and academic factors have changed over time for certain school groups. This can accomplish this using graphical models and create visualizations to show key factors and how the change over time. In addition, one can see how the COVID-19 pandemic has aﬀected schools in this system. Lastly, the correlations between these factors will be presented along with discussion.
Targeting Ribosome Biogenesis in Cancer: Lessons Learned and Way Forward

Simple Summary Cells need to produce ribosomes to sustain continuous proliferation and expand in numbers, a feature that is even more prominent in uncontrollably proliferating cancer cells. Certain cancer cell types are expected to depend more on ribosome biogenesis based on their genetic background, and this potential vulnerability can be exploited in designing effective, targeted cancer therapies. This review provides information on anti-cancer molecules that target the ribosome biogenesis machinery and indicates avenues for future research. Abstract Rapid growth and unrestrained proliferation is a hallmark of many cancers. To accomplish this, cancer cells re-wire and increase their biosynthetic and metabolic activities, including ribosome biogenesis (RiBi), a complex, highly energy-consuming process. Several chemotherapeutic agents used in the clinic impair this process by interfering with the transcription of ribosomal RNA (rRNA) in the nucleolus through the blockade of RNA polymerase I or by limiting the nucleotide building blocks of RNA, thereby ultimately preventing the synthesis of new ribosomes. Perturbations in RiBi activate nucleolar stress response pathways, including those controlled by p53. While compounds such as actinomycin D and oxaliplatin effectively disrupt RiBi, there is an ongoing effort to improve the specificity further and find new potent RiBi-targeting compounds with improved pharmacological characteristics. A few recently identified inhibitors have also become popular as research tools, facilitating our advances in understanding RiBi. Here we provide a comprehensive overview of the various compounds targeting RiBi, their mechanism of action, and potential use in cancer therapy. We discuss screening strategies, drug repurposing, and common problems with compound specificity and mechanisms of action. Finally, emerging paths to discovery and avenues for the development of potential biomarkers predictive of therapeutic outcomes across cancer subtypes are also presented.
Rearranging ‘indivisible’ Blocks for Community Detection

Unattributed social networks are more complicated, and it tends not to determine the best division by over-optimizing a theoretical measure for unsupervised algorithms. Nowadays, communities strongly overlap due to the fact that people strongly interact, which makes community detection even more challenging. The paper develops a new algorithm by rearranging ‘indivisible’ blocks (RaidB). In RaidB, we first initialize ‘indivisible’ blocks by disjoint <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="sun-ieq1-3173271.gif"/></alternatives></inline-formula>-clique blocks in a network, and then these blocks are rearranged by moving nodes from one block to another based on maximizing modularity to uncover non-overlapping communities. For identifying overlapping communities, the above blocks are further rearranged, i.e., each block is subdivided and expanded to determine sub-blocks by introducing a dynamic linear threshold (DLT) model for influence interpenetration, and we finally determine a division from these sub-blocks with the minimum size that can cover the network. We compare RaidB with the existing state of the art methods for non-overlapping and overlapping community detection. The results show that RaidB tends to achieve better performance especially on sparse networks with unobvious communities and networks with strongly overlapping communities.