Miracle-dz/UniFAR-FTUs huggingface dataset:
FC‐ACGAN‐based data augmentation for terahertz time‐domain spectral concealed hazardous materials identification

Terahertz (THz) wave is an electromagnetic wave with a frequency between far infrared ray and millimeter wave, which is widely used in hazardous material detection for its waveband fingerprint spectroscopy. THz time‐domain spectroscopy technology based on deep learning can be used for nondestructive detection of various hazardous materials by recognizing the fingerprint spectrum of substances. However, due to the high cost of collecting spectral data, training samples are not easy to obtain and scarce for classification models, which leads to poor training effectiveness and low accuracy of classification. To address this problem, a fully connected layer‐based auxiliary classifier generative adversarial network (FC‐ACGAN) data augmentation method is proposed in this paper, we realized the generator and discriminator with fully connected layers to fit original data distribution better and generate data with higher quality. First, THz time‐domain spectral data from seven flammable liquids were augmented using Mixup and FC‐ACGAN, and then we fed the generated data set and expanded data set into Residual Network (ResNet), convolutional neural network, fully convolutional network, and multilayer perceptron for training. It is demonstrated that our method can solve the overfitting of models because of insufficient data. Compared with direct training on original data set, the accuracy of models using augmented data set improved by 5.1325% on average, which is 3.15% higher than that using Mixup. Furthermore, we experimented on expanded data set with ResNet long short‐term memory for classification, the final accuracy reaches 99.42% on average, which is 1.09% higher than that using the original data set.
The death of argument - fallacies in agent based reasoning

I Metatheoretical Questions. - 1. Who Cares About the Fallacies? - 2. The Necessity of Formalism. - 3. The Informal Core of Formal Logic. - II Threats and Intimidation. - 4. Ad Baculum and Pascal's Wager. - 5. Appeal to Force. - III Arguments Involving Reference to Persons. - 6. Dialectical Blindspots. - 7. Ad Hominem. - 8. And so Indeed are Perfect Cheat. - IV Pragma-Dialectics. - 9. Pragma-Dialectics. - 10. Buttercups, GNP's and Quarks. - 11. Unifying the Fallacies? - V Intractable Disagreement. - 12. Standoffs in Public Policy. - 13. Standoffs and Demoralization. - VI How to Interpret Arguments. - 14. Charity: Can We Find it a Home? - 15. Missing Premisses. - VII Analogy. - 16. By Parity of Reasoning. - 17. Verdi is the Puccini of Music. - VIII Induction. - 18. Secundum Quid. - 19. Hasty Generalization. - 20. The Problem of Abduction. - Epilogue: The Way Ahead? - References.
The proper motion of stars in dwarf galaxies: distinguishing central density cusps from cores

We show that measuring the proper motion of ∼2000 stars within a dwarf galaxy, with an uncertainty of 1 km/s at most, can establish whether the Dark Matter (DM) density profile of the dwarf has a central core or cusp. We derive these limits by building mock star catalogues similar to those expected from future astrometric Theia-like missions and including celestial coordinates, radial velocity and proper motion of the stars. The density field of the DM halo of the dwarf is sampled from an extended Navarro-Frank-White (eNWF) spherical model, whereas the number density distribution of the stars is a Plummer sphere. The velocity field of the stars is set according to the Jeans equations. A Monte Carlo Markov Chain algorithm applied to a sample of N ≳ 2000 stars returns unbiased estimates of the eNFW DM parameters within $10\%$ of the true values and with 1σ relative uncertainties ≲ 20%. The proper motions of the stars lift the degeneracy among the eNFW parameters which appears when the line-of-sight velocities alone are available. Our analysis demonstrates that, by estimating the log-slope of the mass density profile estimated at the half-light radius, a sample of N = 2000 stars can distinguish between a core and a cusp at more than 8σ. Proper motions also return unbiased estimates of the dwarf mass profile with 1σ uncertainties that decrease, on average, from 2.65 dex to 0.15 dex when the size of the star sample increases from N = 100 to N = 6000 stars. The measure of the proper motions can thus strongly constrain the distribution of DM in nearby dwarfs and provides fundamental contribution to understanding the nature and the properties of DM.
In vitro anti-inflammatory and wound healing properties of Andrographis echioides and Andrographis paniculata

Andrographis echioides (L.) is an annual herbaceous plant in the family Acanthaceae. Anti-inflammatory is the property of a substance or treatment that reduces inflammation or swelling. Antioxidants are substances that can prevent or slow damage to cells caused by free radicals, unstable molecules that the body produces as a reaction to environmental and other pressures. They are sometimes called "free-radical scavengers. Therefore, it is of interest to analyse the anti-inflammatory and antioxidant properties of Andrographis echioides and Andrographis paniculata. Protease inhibitor activity was done by bovine serum albumin was added to 100µl of plant sample with increase in concentrations (100-500µg/ml). Invitro antioxidant activity was done by DPPH free radical scavenging assay. 200 µL of 0.1 mM DPPH prepared in methanol was added to 100 µL of the plant extract with increase in concentration. Based on the results from the present study, it can be concluded that A.echioides is found to be a good natural antioxidant source and A. paniculata is found to be a good anti-inflammatory source. However, both the plant A.echioides and A.paniculata have these properties. Data shows that both A.echioides and A. paniculata have potential anti-inflammatory and antioxidant activity which could be due to the presence of bioactive compounds present in the plant extracts.
High-dose MRI-Guided Adaptive Radiation Therapy for Locally Recurrent Pancreatic Cancer

Introduction: The prognosis of recurrent pancreatic cancer is poor even after curative resection. There have been no reports of MRI-guided radiation therapy for locally recurrent pancreatic cancer after curative resection and chemotherapy. Case Presentation: A 66-year-old man with pancreatic cancer was referred to our institution for local recurrence after failure of surgical resection and second-line chemotherapy. He did not want to undergo further chemotherapy, so high-dose MRI-guided adaptive radiation therapy was performed in daily doses of 2.5 Gy to a total dose of 70 Gy over a period of 5.5 weeks. Three months after radiation therapy, the recurrent tumors disappeared and his CA19-9 level was within normal range without chemotherapy. There were no adverse events during treatment and three months of follow-up. Conclusions: High-dose MRI-guided adaptive radiation therapy may be safe and useful for locally recurrent pancreatic cancer.
Observations of the Circumstellar Water 110→101 and Ammonia 10→00 Lines in IRC +10216 by the Odin Satellite

Submillimeter lines of H2O and NH3 have been detected in the carbon star IRC +10216 (CW Leo) with the Odin submillimeter satellite. The detection of the J = 110 → 101 557 GHz line of ortho-H2O confirms the earlier detection in the same source with SWAS. The detection of the JK = 10 → 00 572 GHz line represents the first observation of the ground-state rotational transition of NH3 in a stellar envelope. By fitting a molecular line transfer model to the observed lines, we derive an ortho-H2O abundance of 2.4 × 10-6, which is consistent with estimates from the SWAS observation. The derived ortho-NH3 abundance of 1 × 10-6 relative to H2 is significantly higher than those derived from 24 GHz inversion transitions and is slightly higher than those from vibrational transitions in the infrared band. The high H2O and NH3 abundances in the carbon-rich star IRC +10216 underscore shortcomings in the conventional gas-phase LTE and non-LTE chemical models.
Which child to which school? How local politicians shape catchment areas, school choice and diversity

Growing global debates surrounding parental school choice underscore the relevance of school place allocation. While there is much research on school choice, the enactment of such allocation policy is rarely analysed. Responding to this research gap, this article investigates how local politicians in Berlin put public primary school place allocation into practice. Building on approaches of policy enactment and policy field analysis, this article examines the ‘doing’ of Berlin primary school place allocation with the concurrency of catchment areas and parental school choice. Methodologically, this article draws on semi-structured interviews with three inner-city district school department heads in Berlin. Using qualitative content analysis, their political objectives, scope and strategies are analysed. The findings demonstrate that local politicians can interpret the allocation process in line with their political objectives. Consequently, there is surprising variation between the districts’ enactment of primary school place allocation policy. Policymakers’ political preferences for either school choice or social diversity are influential, as is the local context (e.g. school place shortages). The study highlights the importance of local actors and identifies three political strategies used to influence school place allocation, which might inform local politicians’ strategies elsewhere.
Macroeconomic Indicators and CO2 Emissions in the EU Region

Macroeconomic Indicators and CO 2 Emissions in the EU Region. 24(61), pp. 817-830. Abstract The anthropogenic emissions of carbon dioxide into the atmosphere are one of the problems facing mankind on a global scale. Therefore, the governments of many countries are making efforts to reduce CO 2 emissions through regulatory measures. Environmental pollution from CO 2 emissions is not only an environmental problem, but also an economic one. Therefore, the authors focus on conducting a multi-econometric study of the impact of macroeconomic factors (gross domestic product, exports, imports, inflation, and unemployment) on CO 2 emissions in the EU region. Systematization, empirical comparative analysis, and econometric modeling (determining the relationships between indicators) were the research methods applied in our research. The results, which were carried out based on statistical data for the period 1970-2020 in the EU, confirmed the existence of dependence of carbon dioxide emissions on macroeconomic indicators such as gross domestic product, exports, imports, inflation, and unemployment. To know whether to reduce or maintain allowable CO 2 emissions, governments can use multivariate regression models to optimize, monitor, and forecast their macroeconomic indicators.
Interpreting discrete choice models based on best-worst data: A matter of framing

Best worst choice response tasks have become increasingly popular as a means of increasing the amount of information captured from respondents undertaking stated preference experiments. In analysis, best worst data is often exploded to provide additional pseudo observations which may aid in model estimation. Recent studies however have questioned many of the underlying assumptions which typically accompany best worst studies, such as the symmetry of preferences across the best and worst responses as well as assumptions about equal error variances across the two response types. This paper first provides a detailed description of the various best worst tasks that have appeared within the literature before arguing that violations of preference symmetry and homogeneity of error variance should be the norm. This is because in asking respondent to choose their most and least preferred option out of a set of alternatives reflects different response frames, one positive and one negative, and behaviourally there exists no reason why one would assume that the preferences (and error variances) obtained from one type of question should precisely mirror that of the other. Using an empirical case study, the impact of the framing of these questions is examined. Finally, the argument put forward is that best-worst data should be treated in a similar to data fusion methods, where one combines two different sources of discrete choice data.
Role of Ultrasonography in the Diagnosis of Wilms’ Tumour

Background. Wilms’ tumour or nephroblastoma is the most common renal malignancy encountered in the paediatric population. Imaging findings are of great importance to the surgeon, the oncologist and the radiologist in the diagnosis and the staging and surveillance of this tumour. Material and Methods. This study was carried out as a 10-year retrospective study of patients who were diagnosed with Wilms’ tumour. Results. The study included 12 boys and 11 girls. Ultrasound and computed tomography were performed in all cases. Ultrasonography was found to be superior to the CT examination when approximating the antero-posterior and transverse diameters; the computer-tomographic examination is cited as superior for estimating the invasion of nephroblastomas. Conclusions: Ultrasound has been shown to be effective in detecting the rupture of the renal capsule, tumour calcifications and invasion of the renal vein, pelvis and ureter. However, ultrasound cannot replace CT in the detection of lymphadenopathy and the invasion of adjacent organs.
Impact of Maternal Obesity on the Gestational Metabolome and Infant Metabolome, Brain, and Behavioral Development in Rhesus Macaques

Maternal gestational obesity is associated with elevated risks for neurodevelopmental disorder, including autism spectrum disorder. However, the mechanisms by which maternal adiposity influences fetal developmental programming remain to be elucidated. We aimed to understand the impact of maternal obesity on the metabolism of both pregnant mothers and their offspring, as well as on metabolic, brain, and behavioral development of offspring by utilizing metabolomics, protein, and behavioral assays in a non-human primate model. We found that maternal obesity was associated with elevated inflammation and significant alterations in metabolites of energy metabolism and one-carbon metabolism in maternal plasma and urine, as well as in the placenta. Infants that were born to obese mothers were significantly larger at birth compared to those that were born to lean mothers. Additionally, they exhibited significantly reduced novelty preference and significant alterations in their emotional response to stress situations. These changes coincided with differences in the phosphorylation of enzymes in the brain mTOR signaling pathway between infants that were born to obese and lean mothers and correlated with the concentration of maternal plasma betaine during pregnancy. In summary, gestational obesity significantly impacted the infant systemic and brain metabolome and adaptive behaviors.
Edge-partitions of sparse graphs and their applications to game coloring

In this note, we prove that every graph with maximum average degree less than 32 (resp. 30 , 32 , 70 ) admits an edge-partition into a forest and a subgraph of maximum degree 1 (resp. 2, 3, 4). This implies that these graphs have game coloring number at most 5, 6, 7, 8, respectively.
Chitosan-Based Scaffolds for Facilitated Endogenous Bone Re-Generation

Facilitated endogenous tissue engineering, as a facile and effective strategy, is emerging for use in bone tissue regeneration. However, the development of bioactive scaffolds with excellent osteo-inductivity to recruit endogenous stem cells homing and differentiation towards lesion areas remains an urgent problem. Chitosan (CS), with versatile qualities including good biocompatibility, biodegradability, and tunable physicochemical and biological properties is undergoing vigorously development in the field of bone repair. Based on this, the review focus on recent advances in chitosan-based scaffolds for facilitated endogenous bone regeneration. Initially, we introduced and compared the facilitated endogenous tissue engineering with traditional tissue engineering. Subsequently, the various CS-based bone repair scaffolds and their fabrication methods were briefly explored. Furthermore, the functional design of CS-based scaffolds in bone endogenous regeneration including biomolecular loading, inorganic nanomaterials hybridization, and physical stimulation was highlighted and discussed. Finally, the major challenges and further research directions of CS-based scaffolds were also elaborated. We hope that this review will provide valuable reference for further bone repair research in the future.
Spontaneous Pneumothorax in a Patient with Systemic Lupus Erythematosus and Recent Infection with Coronavirus

A 50-year-old woman with a history of systemic lupus erythematosus and a recent infection with COVID-19 presented to the emergency department with acute shortness of breath twice in 10 days. She was diagnosed with myopericarditis attributed to COVID-19 infection (first admission), and chest X-ray revealed a small left-sided pneumothorax, pericardial effusion (second admission), with no mediastinal shift or other signs of tension. Computed tomography confirmed these results and revealed a few small cysts in the right lung. An echocardiogram demonstrated normal heart anatomy and filling dynamics. The patient was diagnosed with simple pneumothorax and ongoing myopericarditis managed with colchicine, ibuprofen, and low-dose prednisolone. The patient responded to treatment and was discharged. Pneumothorax association with COVID-19 is reported in a small number of publications, but the association is less clear with SLE. Our patient may have been predisposed to developing pneumothorax after COVID-19 infection due to her existing connective tissue disorder.
Spat~ : A Spatial Processor for Musicians and Sound Engineers

Spat~ is a real-time spatial processing software which runs on the Ircam Music Workstation in the Max graphical signal processing environment. It provides a library of elementary modules (pan-pots, equalizers, reverberators.) linkable into a compact processor integrating the localization of sound events together with the manipulation of room acoustical quality. This processor can be configured for various reproduction formats over loudspeaker or headphones, and controlled through a higher-level user interface including perceptual attributes derived from psychoacoustical research. Applications include studio recording and computer music, virtual reality or variable acoustics in rooms.
Multimodal Physiological Signals and Machine Learning for Stress Detection by Wearable Devices

Wearable technology is growing in popularity, and wearable devices, such as smartwatches, are used in many applications, from fitness tracking and activity recognition to health monitoring. As the affordability and popularity of such devices increase, so does the amount of personal and unique data that they provide. At the same time, advantages in microprocessor and memory technology enable multiple physiological signal sensors integrated into wearable devices to collect personal and unique data. After the data is extracted, machine learning classification algorithms can help investigate the insights of the data. In this work, we examine the performance of a real-time stress detection system based on physiological signals collected from wearable devices. Specifically, three physiological signals, electrodermal activity (EDA), electrocardiogram (ECG), and photoplethysmo-graph (PPG) that can be collected through smartwatches, are examined for stress classification. Six machine learning methods are used for the classification in a post-acquisition phase, at a computer, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest, Naive Bayes, Logistic Regression, and Stacking Ensemble Learning (SEL). Data from two publicly available datasets are used for training and testing. We examine the accuracy of each modality and the combination of all modalities. According to evaluation results, EDA has the best accuracy when SEL is used for classification. Also, the accuracy of EDA outperforms the other signals and combinations, in comparison with any of the other machine learning approaches, for both datasets. EDA collected from the wearable device has a great potential to be used for a real-time stress detection system.
Implications of Polyploidy and Ploidy Alterations in Hepatocytes in Liver Injuries and Cancers

Polyploidy, a condition in which more than two sets of chromosomes are present in a cell, is a characteristic feature of hepatocytes. A significant number of hepatocytes physiologically undergo polyploidization at a young age. Polyploidization of hepatocytes is enhanced with age and in a diseased liver. It is worth noting that polyploid hepatocytes can proliferate, in marked contrast to other types of polyploid cells, such as megakaryocytes and cardiac myocytes. Polyploid hepatocytes divide to maintain normal liver homeostasis and play a role in the regeneration of the damaged liver. Furthermore, polyploid hepatocytes have been shown to dynamically reduce ploidy during liver regeneration. Although it is still unclear why hepatocytes undergo polyploidization, accumulating evidence has revealed that alterations in the ploidy in hepatocytes are involved in the pathophysiology of liver cirrhosis and carcinogenesis. This review discusses the significance of hepatocyte ploidy in physiological liver function, liver injury, and liver cancer.
NEW DESIGN ALGORITHM AND RELIABILITY TESTING OF SOLAR POWERED NEAR-SPACE FLIGHT VEHICLE FOR DEFENSE AND SECURITY

Broadband telecommunications have become the key factor for economic growths around the world, but rural and hard to reach areas are missing out on the opportunity. To overcome this problem, we propose a pseudo-satellite system where telecommunication devices are carried on a perpetually flying solar aircraft cruising at stratospheric altitude. Our aircraft will combine lighter-than-air technology to augment the lift from the wing. Every major components contributing to the aircraft total weight has been considered, resulting in a range of design solutions. We chose wing span and aspect ratio of 50m and 13 respectively, from which other specifications of the aircraft were fixed to. Our design solution has been validated by power and weight balance analysis. System reliability has been demonstrated by Monte Carlo simulation.
Enhanced laser trimming of thin film resistors dedicated to snubber for high power IGBT modules

This paper reveals a durable trimming condition of thin film resistors as a part of snubber circuits in high power electronic modules including IGBT converters. Our previous study clarified that the maximum voltage to apply to the resistors is limited by thermal destruction of the resistors due to the pulsed power injection. With careful failure analysis and surface observations, this paper provides an additional insight that dimensions of the indispensable trimming patterns affect the thermal destruction. Electro-thermal analysis results show that the optimized dimensions of the trimmed shapes can suppress temperature rise of the most critical area up to one sixth compared to the most pessimistic shape.