Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypothalamic Proopiomelanocortin Is Necessary for Normal Glucose Homeostasis in Female Mice

The arcuate nucleus of the hypothalamus is a key regulator of energy balance and glucose homeostasis. In particular, arcuate proopiomelanocortin (POMC) neurons inhibit food intake, stimulate energy expenditure and increase glucose tolerance. The interruption of insulin or glucose signaling in POMC neurons leads to glucose intolerance without changing energy homeostasis. Although it was previously shown that POMC neurons are necessary for normal glucose homeostasis, the participation of POMC neuropeptide, by mechanisms independent of energy balance, remains to be demonstrated. To study the role of POMC in the regulation of glucose homeostasis, we performed glucose and insulin tolerance tests in non-obese mice lacking hypothalamic POMC expression. We found that POMC deficiency leads to glucose intolerance and insulin resistance in female mice before the onset of obesity or hyperphagia. Conversely, POMC deficiency does not impair glucose homeostasis in non-obese male mice. Interestingly, females completely normalize both glucose and insulin tolerance after genetic POMC restoration. Next, to further study sex dimorphism of POMC neurons regarding glucose homeostasis, we measured glucose-elicited changes in C-FOS by performing immunofluorescence in brain slices of POMC-EGFP mice. Remarkably, we found that glucose-induced C-FOS expression in POMC neurons is more than 3-fold higher in female than in male mice. Altogether, our results reveal a key role of arcuate POMC in the regulation of glucose homeostasis in females. Since POMC reactivation completely reverses the diabetogenic phenotype, arcuate POMC could be a potential target for diabetes therapy.
Modelling distributed Erlang within a single node

This paper was motivated by a challenge we faced while re-architecting a critical component in Klarna's software stack. We wanted to increase our confidence about correctness aspects of a new distributed algorithm, developed for an Erlang system at the very core of Klarna's business. Reasoning about the correctness of concurrent Erlang systems is a difficult task, but tools exist that can help, for instance, Concuerror. However, our algorithm was intimately linked to distributed Erlang's behaviours, which are not supported by Concuerror. The solution we came up with was to design and implement vnet, a modelling library which can be used to simulate the behaviour of distributed Erlang nodes within a single Erlang node. We discuss aspects of vnet showing its capabilities and limitations. We also report on two case studies, showing how vnet can be used to prototype, test and verify simple and advanced distributed Erlang systems. We finally demonstrate that we were able to find errors and verify properties in the systems of our case studies, using Concuerror.
Efficient 2D-3D Matching for Multi-Camera Visual Localization

Visual localization, i.e., determining the position and orientation of a vehicle with respect to a map, is a key problem in autonomous driving. We present a multi-camera visual inertial localization algorithm for large scale environments. To efficiently and effectively match features against a pre-built global 3D map, we propose a prioritized feature matching scheme for multi-camera systems. In contrast to existing works, designed for monocular cameras, we (1) tailor the prioritization function to the multi-camera setup and (2) run feature matching and pose estimation in parallel. This significantly accelerates the matching and pose estimation stages and allows us to dynamically adapt the matching efforts based on the surrounding environment. In addition, we show how pose priors can be integrated into the localization system to increase efficiency and robustness. Finally, we extend our algorithm by fusing the absolute pose estimates with motion estimates from a multi-camera visual inertial odometry pipeline (VIO). This results in a system that provides reliable and drift-less pose estimation. Extensive experiments show that our localization runs fast and robust under varying conditions, and that our extended algorithm enables reliable real-time pose estimation.
Add-on Yoga Therapy for Social Cognition in Schizophrenia: A Pilot Study

Background: Yoga as a mind–body therapy is useful in lifestyle-related disorders including neuropsychiatric disorders. In schizophrenia patients, yoga has been shown to significantly improve negative symptoms, functioning, and plasma oxytocin level. Aim: The aim of the study was to study the effect of add-on yoga therapy on social cognition in schizophrenia patients. Materials and Methods: In a single pre-post, study design, 15 schizophrenia patients stabilized on antipsychotic medication for 6 weeks were assessed for social cognition (theory of mind, facial emotion recognition, and social perception [SP]) and clinical symptoms (negative and positive symptoms and social disability) before and after twenty sessions of add-on yoga therapy. Results: There was a significant improvement in the social cognition composite score after 20 sessions of yoga (t[13] = −5.37, P≤ 0.001). Clinical symptoms also reduced significantly after twenty sessions of yoga. Conclusion: Results are promising to integrate yoga in clinical practice, if proven in well-controlled clinical trials.
Portable Implementation of Postquantum Encryption Schemes and Key Exchange Protocols on JavaScript-Enabled Platforms

Quantum computers have the potential to solve some difficult mathematical problems efficiently and thus will inevitably exert a more significant impact on the traditional asymmetric cryptography. The National Institute of Standards and Technology (NIST) has opened a formal call for the submission of proposals of quantum-resistant public-key cryptographic algorithms to set the next-generation cryptography standards. Compared to powerful machines with ample amount of hardware resources such as racks of servers and IoT devices, including the massive number of microcontrollers, smart terminals, and sensor nodes with limited computing capacity, should also have some postquantum cryptography features for security and privacy. To ensure the correct execution of encryption algorithms on any platforms, the portability of implementation becomes more important. As distinguished from C/C++, JavaScript is a popular cross-platform language that can be used for the web applications and some hardware platforms directly, and it could be one of the solutions of portability. Therefore, we investigate and implement several recent lattice-based encryption schemes and public-key exchange protocols including Lizard, ring-Lizard, Kyber, Frodo, and NewHope in JavaScript, which are the active candidates of postquantum cryptography due to their applicabilities and efficiencies. We show and compare the performance of our JavaScript implementation on web browsers, embedded device Tessel2, Android phone, and several JavaScript-enabled platforms on PC and Mac. Our work shows that implementing lattice-based cryptography on JavaScript-enabled platforms is achievable and results in desirable portability.
Preparation, optimisation, and in vitro–in vivo evaluation of febuxostat ternary solid dispersion

Abstract The research aimed to prepare febuxostat (FEB) solid dispersion through solvent evaporation. Optimised solid dispersion composed of FEB, polyvinylpyrrolidone (PVP K30) and poloxamer at a ratio of 1:3:3 was characterised. Powder X-ray diffraction (XRD) and differential scanning calorimetry (DSC) indicated FEB was transformed from crystalline into the amorphous state in solid dispersion and scanning electron microscopy (SEM) revealed the morphology. Fourier transform infrared spectroscopy (FT-IR) suggested the interactions formed between FEB and polymers. A remarkable increase was observed of the optimised formulation in saturation solubility, dissolution studies (96.17 ± 0.79% in pH 6.0), and bioavailability (Cmax 18.25 ± 2.44 vs. 7.72 ± 0.48 μg/mL and AUC0–∞ 53.62 ± 7.63 vs. 34.76 ± 2.45 μg·h/mL). Besides, the FEB solid dispersion showed great stability after 90 days storage. Thus, the present study supports the rationality of PVP K30 and poloxamer188 as co-carriers for the preparation of FEB solid dispersion.
Partial Mechanical Unloading of the Heart Disrupts L-Type Calcium Channel and Beta-Adrenoceptor Signaling Microdomains

Introduction: We investigated the effect of partial mechanical unloading (PMU) of the heart on the physiology of calcium and beta-adrenoceptor-cAMP (βAR-cAMP) microdomains. Previous studies have investigated PMU using a model of heterotopic-heart and lung transplantation (HTHAL). These studies have demonstrated that PMU disrupts the structure of cardiomyocytes and calcium handling. We sought to understand these processes by studying L-Type Calcium Channel (LTCC) activity and sub-type-specific βAR-cAMP signaling within cardiomyocyte membrane microdomains. Method: We utilized an 8-week model of HTHAL, whereby the hearts of syngeneic Lewis rats were transplanted into the abdomens of randomly assigned cage mates. A pronounced atrophy was observed in hearts after HTHAL. Cardiomyocytes were isolated via enzymatic perfusion. We utilized Förster Resonance Energy Transfer (FRET) based cAMP-biosensors and scanning ion conductance microscopy (SICM) based methodologies to study localization of LTCC and βAR-cAMP signaling. Results: β2AR-cAMP responses measured by FRET in the cardiomyocyte cytosol were reduced by PMU (loaded 28.51 ± 7.18% vs. unloaded 10.84 ± 3.27% N,n 4/10-13 mean ± SEM ∗p < 0.05). There was no effect of PMU on β2AR-cAMP signaling in RII_Protein Kinase A domains. β1AR-cAMP was unaffected by PMU in either microdomain. Consistent with this SICM/FRET analysis demonstrated that β2AR-cAMP was specifically reduced in t-tubules (TTs) after PMU (loaded TT 0.721 ± 0.106% vs. loaded crest 0.104 ± 0.062%, unloaded TT 0.112 ± 0.072% vs. unloaded crest 0.219 ± 0.084% N,n 5/6-9 mean ± SEM ∗∗p < 0.01, ∗∗∗p < 0.001 vs. loaded TT). By comparison β1AR-cAMP responses in either TT or sarcolemmal crests were unaffected by the PMU. LTCC occurrence and open probability (Po) were reduced by PMU (loaded TT Po 0.073 ± 0.011% vs. loaded crest Po 0.027 ± 0.006% N,n 5/18-26 mean ± SEM ∗p < 0.05) (unloaded TT 0.0350 ± 0.003% vs. unloaded crest Po 0.025 N,n 5/20-30 mean ± SEM NS #p < 0.05 unloaded vs. loaded TT). We discovered that PMU had reduced the association between Caveolin-3, Junctophilin-2, and Cav1.2. Discussion: PMU suppresses’ β2AR-cAMP and LTCC activity. When activated, the signaling of β2AR-cAMP and LTCC become more far-reaching after PMU. We suggest that a situation of ‘suppression/decompartmentation’ is elicited by the loss of refined cardiomyocyte structure following PMU. As PMU is a component of modern device therapy for heart failure this study has clinical ramifications and raises important questions for regenerative medicine.
Improving Sexual Health Education Programs for Adolescent Students through Game-Based Learning and Gamification

An effective innovative pedagogy for sexual health education is required to meet the demands of technology savvy digital natives. This study investigates the extent to which game-based learning (GBL) and gamification could improve the sexual health education of adolescent students. We conducted a randomized control trial of GBL and gamification experimental conditions. We made a comparison with traditional teaching as a control condition in order to establish differences between the three teaching conditions. The sexual health education topics were delivered in a masked fashion, 40-min a week for five weeks. A mixed-method research approach was uses to assess and analyze the results for 120 students from a secondary school in Dar Es Salaam, Tanzania. Students were divided into groups of 40 for each of the three teaching methods: GBL, gamification, and the control group (the traditional teaching method). The average post-test scores for GBL (Mean = 79.94, SD = 11.169) and gamification (Mean = 79.23, SD = 9.186) were significantly higher than the control group Mean = 51.93, SD = 18.705 (F (2, 117) = 54.75, p = 0.001). Overall, statistically significant differences (p ≤ 0.05) were found for the constructs of Motivation, Attitude, Knowledge, and Engagement (MAKE). This study suggests that the two innovative teaching approaches can be used to improve the sexual health education of adolescent students. The methods can potentially contribute socially, particularly in improving sexual health behaviour and adolescents’ knowledge in regions plagued by years of sexual health problems, including HIV/AIDS.
Segmentation of the lumen and media-adventitial borders in intravascular ultrasound images using a geometric deformable model

This study presents a geometric deformable model-based segmentation approach to segmentation of the intima and media-adventitial (MA) borders in sequential intravascular ultrasound (IVUS) images. The initial estimation of the vessel borders was done manually only for the first frame of each sequence. After the border initialisation, pre-processing including edge preservation, noise reduction, and dead zone preservation was successively performed on each IVUS frame. To improve segmentation performance, the image masks were determined preliminarily by local binary pattern-based mask initialisation. Then, the inner and outer borders were approximated using a modified distance regularised level set evolution model. The results showed superior performance of the suggested approach for estimating intima and MA layers from the IVUS images. The corresponding correlation coefficients of area, vessel perimeter, maximum vessel diameter, and maximum lumen diameter were r = 0.782, r = 0.716, r = 0.956, and r = 0.874 for the 20 MHz images, respectively, and r = 0.990, r = 0.995, r = 0.989, and r = 0.996 for the 45 MHz images, respectively. In addition, linear regression analysis indicated that the manual segmentation had significantly high similarity at r > 0.967 and r > 0.993 for 20 and 45 MHz images, respectively.
Function-Aware Anomaly Detection Based on Wavelet Neural Network for Industrial Control Communication

Function control, which is an essential link in industrial automation, is undergoing a growing integration with ICTs (Information Communication Technologies) because of the flexible manufacturing and convenient interoperability in CPSs (Cyber-Physical Systems). However, it has also brought the increasing dangers of cyberattacks caused by malicious or intentional industrial process control exploitations. In order to effectively detect these cyber intrusions and anomalies, this paper proposes a function-aware anomaly detection approach based on WNN (Wavelet Neural Network), which perceives the abnormal function control changes in industrial control communication. By appropriately extracting the time-related function control characteristics from industrial communication packets, this approach builds an optimized wavelet neural network to model the normal function control behaviors and calculates the detection threshold to differentiate the aberrant industrial process control activities. Additionally, a real-world control system, whose communication protocol is Modbus/TCP, is simulated to furnish the analyzed function control data. According to the experimental results, we fully demonstrate this approach has the fine detection accuracy and adequate real-time capability.
Analysis of bZIP Transcription Factor Family and Their Expressions under Salt Stress in Chlamydomonas reinhardtii

The basic leucine-region zipper (bZIP) transcription factors (TFs) act as crucial regulators in various biological processes and stress responses in plants. Currently, bZIP family members and their functions remain elusive in the green unicellular algae Chlamydomonas reinhardtii, an important model organism for molecular investigation with genetic engineering aimed at increasing lipid yields for better biodiesel production. In this study, a total of 17 C. reinhardtii bZIP (CrebZIP) TFs containing typical bZIP structure were identified by a genome-wide analysis. Analysis of the CrebZIP protein physicochemical properties, phylogenetic tree, conserved domain, and secondary structure were conducted. CrebZIP gene structures and their chromosomal assignment were also analyzed. Physiological and photosynthetic characteristics of C. reinhardtii under salt stress were exhibited as lower cell growth and weaker photosynthesis, but increased lipid accumulation. Meanwhile, the expression profiles of six CrebZIP genes were induced to change significantly during salt stress, indicating that certain CrebZIPs may play important roles in mediating photosynthesis and lipid accumulation of microalgae in response to stresses. The present work provided a valuable foundation for functional dissection of CrebZIPs, benefiting the development of better strategies to engineer the regulatory network in microalgae for enhancing biofuel and biomass production.
Look before you leap: the role of negative urgency in appraisals of ambiguous and unambiguous scenarios in individuals high in generalized anxiety disorder symptoms

ABSTRACT Negative interpretation bias, the propensity to make threatening interpretations of ambiguous information, is associated with symptoms of generalized anxiety disorder (GAD). Apart from its relationship with intolerance of uncertainty (IU), little is known about what explains the presence of this cognitive bias in GAD. One factor may be negative urgency (NU), the tendency to take rash action when distressed, which is related to GAD symptoms and to cognitive biases in nonclinical populations. The aim of the present study was to examine the relationship between NU and interpretation bias in individuals high in GAD symptoms (N = 111). IU, trait anxiety, and other forms of impulsivity were examined concurrently as competing correlates of interpretation bias. Greater NU and IU were found to be unique correlates of greater threatening interpretations of ambiguous scenarios. Greater NU was also a unique correlate of greater threatening interpretations of negative and positive scenarios. No other forms of impulsivity were uniquely related to interpretation bias. The findings suggest that greater NU may have a role in the tendency for individuals high in GAD symptoms to make threatening interpretations in response to ambiguous scenarios, overtly threatening situations, and situations without indication of threat or danger. Theoretical implications of these findings are discussed.
Flooding-based segmentation for contactless hand biometrics oriented to mobile devices

Segmentation is a crucial stage in hand biometric recognition due to its direct influence on the feature extraction process. The actual trend toward contactless biometrics adds new challenges to traditional defiances, which are mainly related to the capturing conditions and the limitations on computational resources. Traditional methods do not succeed when variable capturing conditions are imposed and methods which are able to deal with daily-life situations are, in general, computationally expensive. In this study, a competitive flooding-based segmentation method oriented to mobile devices is proposed in order to achieve a compromised solution between accuracy and computational resources consumption. The method has been evaluated using images coming from five different databases which cover a wide spectrum of capturing conditions, one of them recorded as a part of this study. The results have been compared with other two well known segmentation techniques in terms of both accuracy and computation time.
Discharge of patients with an acute upper gastrointestinal bleed from the emergency department using an extended Glasgow-Blatchford Score

Objective To use an extended Glasgow-Blatchford Score (GBS) cut-off of ≤1 to aid discharge of patients presenting with acute upper gastrointestinal bleeding (AUGIB) from emergency departments. Background The GBS accurately predicts the need for intervention and death in AUGIB, and a cut-off of 0 is recommended to identify patients for discharge without endoscopy. However, this cut-off is limited by identifying a low percentage of low-risk patients. Extension of the cut-off to ≤1 or ≤2 has been proposed to increase this proportion, but there is controversy as to the optimal cut-off and little data on performance in routine clinical practice. Methods Dual-centre study in which patients with AUGIB and GBS ≤1 were discharged from the emergency department without endoscopy unless there was another reason for admission. Retrospective analysis of associated adverse outcome defined as a 30-day combined endpoint of blood transfusion, intervention or death. Results 569 patients presented with AUGIB from 2015 to 2018. 146 (25.7%) had a GBS ≤1 (70, GBS=0; 76, GBS=1). Of these, 103 (70.5%) were managed as outpatients, and none had an adverse outcome. GBS ≤1 had a negative predictive value=100% and the GBS had an area under receiver operator characteristic (AUROC)=0.89 (95% CI 0.86 to 0.91) in predicting adverse outcomes. In 2008–2009, prior to risk scoring (n=432), 6.5% of patients presenting with AUGIB were discharged safely from the emergency department in comparison with 18.1% (p<0.001) in this cohort. A GBS cut-off ≤2 was associated with an adverse outcome in 8% of cases. Conclusion GBS of ≤1 is the optimal cut-off for the discharge of patients with an AUGIB from the emergency department.
Implementing resource-aware safe assembly for kernel probes as a dependently-typed DSL

We present construction of resource-aware safe typed assembly language as an EDSL in dependently-typed Idris language. We use this assembly language to compile Linux kernel probes — small pieces of instrumentation code injected directly into the kernel and thus having to satisfy strict safety properties. We believe that the techniques presented can be generally applied to embedding a typed assembly language into a functional language with dependent types.
A Classifier Ensemble for Offensive Text Detection

Offensive posts are a constant nuisance in many Web platforms. As a consequence, there has been growing interest in devising methods to automatically identify such posts. In this paper, we present Hate2Vec -- an approach for detecting offensive comments on the Web. Hate2Vec relies on a classifier ensemble. The base learners include: (i) a lexicon-based classifier which leverages the semantic relatedness of word embeddings; (ii) a logistic regression classifier based on comment embeddings; (iii) and a standard bag-of-words (BOW) classifier based on unigram features. Our experiments with datasets in English and Portuguese have yielded high classification results (F-measure above 0.9) and significantly outperformed a traditional BOW classifier.