Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of 128 Dual Source Computed Tomography Angiography Imaging for Detection of Cerebral Aneurysm – Retrospective Study

Background: Multislice computed tomography (CT) has great potential for use in vascular studies. Multislice 128 slice CT angiography is an excellent non-invasive screening test in the assessment of intracranial aneurysms, both on a per-aneurysm and per-patient basis. Purpose: The aim of the study was to evaluate non-invasive CT angiography (CTA) on 128 dual sources CT scan for detecting the aneurysm in spontaneous cases of subarachnoid bleed. Materials and Methods: We evaluated 51 cases with spontaneous subarachnoid bleed by 128 slice dual-source CT in digital subtraction angiography (DSA) CT brain angiography protocol for the detection of aneurysms. The analysis of the scan for aneurysm detection was performed using 2D, multi-planar reconstructions, volume rendered techniques, and 3D maximum intensity projection. Aneurysms were evaluated for size, location, and other imaging characteristics. Patients with subarachnoid bleeds who were negative for aneurysm were further evaluated by the DSA. Result: Fifty-one patients with age group of 23–85 (mean age 53.60 ± 13.76 years) were investigated. In 42 patients, aneurysms were identified in CT angiography, and their comprehensive evaluation such as location, size, and neck direction status were appropriately done, and information guided the neurosurgeons/interventionist for the proper management. Nine cases that were negative for aneurysm were also negative in DSA. Conclusion: The faster high-resolution multislice 128 slice dual-source CT scan allows for non-invasive, safer, and accurate identification of cerebral aneurysms and accurately determines their size, morphology, and location. Specificity and sensitivity of 128 dual-source CT angiography in DSA protocol are near to the DSA which is the gold standard.
AUTHORSHIP VERIFICATION OF TWEETS CROSS TOPICS USING WEIGHTED WORD VECTORS SIMILARITY

Authorship Verification (AV) is one of the interesting topics that had developed rapidly and distinctly since the middle of the 19th century. With the social media era, there is always a problem in determining whether a given tweet, post, or comment was written by a certain user or not. We are proposing a new approach to verify if a tweet belongs to a claimed user. Our proposed method utilizes the benefits of one-shot learning. It is based on vectors similarity which depends on Term Frequency–Inverse Document Frequency (TF-IDF) and word embedding for better verification accuracy. After comparisons, our proposed approach outperforms existing methods in the case of cross topics.
Kinetics of the tin‐catalyzed reactions of phenyl isocyanate with ureas

The initial rates have been determined for the second-order equilibrium reaction of phenyl isocyanate with a series of phenyl-substituted 1,1-pentamethylene-3-phenyl ureas in the presence of butyltin trichloride catalyst in chlorobenzene at 60°C. These results were compared with the rates of reaction of phenyl isocyanate with 1,1-di-n-butyl-3-phenylurea, 1,3-diphenyl-1-methylurea, N-phenylbenzamide, methyl-N-phenyl carbamate, and 1-butanol. The activation energy for the butyltin trichloride-catalyzed reaction of phenyl isocyanate and 1,1-pentamethylene-3-phenylurea was 12 kcal. /mole. At 60°C. this reaction was approximately 11 times as fast as the reverse reaction. The rate of the reaction of phenyl isocyanate and 1,1-pentamethylene-3-phenylurea was directly proportional to the concentration of butyltin trichloride. The activity of this catalyst was 28 times as great as that of triethyltin chloride. Dibutyltin dilaurate, dibutyltin diacetate, dibutylin dichloride, tributyltin chloride, tetramethyltin, trimethyltin bromide, triethyltin fluoride, and 1,2,4-trimethylpiperazine were not catalysts for these reactions. The ureas formed solid complexes with stannic chloride and with butyltin trichloride in which the tin compounds were coordinated through the carbonyl oxygen. A tentative reaction mechanism has been proposed, which involves nucleophilic attack of the urea on the isocyanate through an intermediate ternary complex. The stannic chloride-catalyzed reaction of ureas with isocyanates at room temperature has been shown to have wide application.
Thoracic radiotherapy in small cell lung cancer—a narrative review

Small-cell lung cancer (SCLC) represents 10–15% of all lung cancers and has a poor prognosis. Thoracic radiotherapy plays a central role in current SCLC management. Concurrent chemoradiotherapy (CTRT) is the standard of care for localised disease (stage I−III, limited-stage, LS). Definitive thoracic radiotherapy may be offered in metastatic patients (stage IV, extensive stage, ES-SCLC) after chemotherapy. For LS-SCLC, the gold standard is early accelerated hyperfractionated twice-daily CTRT (4 cycles of cisplatin etoposide, starting with the first or second chemotherapy cycle). Modern radiation techniques should be used with involved-field radiotherapy based on baseline CT and PET/CT scans. In ES-SCLC, thoracic radiotherapy should be discussed in cases of initial bulky mediastinal disease/residual thoracic disease not progressing after induction chemotherapy. This strategy was however not assessed in recent trials establishing chemo-immunotherapy as the standard first line treatment in ES-SCLC. Future developments include technical radiotherapy advances and the incorporation of new drugs. Thoracic irradiation is delivered more precisely given technical developments (IMRT, image-guided radiotherapy, stereotactic radiotherapy), reducing the risks of severe adverse events. Stereotactic ablative radiotherapy may be discussed in rare early stage (T1 to 2, N0) inoperable patients. A number of current clinical trials are investigating immunoradiotherapy. In this review, we highlight the current role of thoracic radiotherapy and describe ongoing research in the integration of biological surrogate markers, advanced radiotherapy technologies and novel drugs in SCLC patients.
Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images

As AI-based medical devices are becoming more common in imaging fields like radiology and histology, interpretability of the underlying predictive models is crucial to expand their use in clinical practice. Existing heatmap-based interpretability methods such as GradCAM only highlight the location of predictive features but do not explain how they contribute to the prediction. In this paper, we propose a new interpretability method that can be used to understand the predictions of any black-box model on images, by showing how the input image would be modified in order to produce different predictions. A StyleGAN is trained on medical images to provide a mapping between latent vectors and images. Our method identifies the optimal direction in the latent space to create a change in the model prediction. By shifting the latent representation of an input image along this direction, we can produce a series of new synthetic images with changed predictions. We validate our approach on histology and radiology images, and demonstrate its ability to provide meaningful explanations that are more informative than GradCAM heatmaps. Our method reveals the patterns learned by the model, which allows clinicians to build trust in the model's predictions, discover new biomarkers and eventually reveal potential biases.
Stroke patients experience many mental and functional problems

Background: The aim of this work was to investigate the influence of transcranial direct current stimulation (TDCS) on improving depression in stroke patients. Subjects and Methods: forty hemiparetic stroke patients from both sexes represent the sample of this study. The patients' ages ranged from 45 to 60 years with a mean value of 55.475 ± 4.01 years. Patients were assigned randomly into two groups equal in number; the study group A and the control group B. The study group A treated by the prescribed medications for depression as the control group B in addition to transcranial direct current stimulation for 30 minutes, three times per week for one month in addition to physical therapy program. The control group B treated by the prescribed medication only and sham transcranial direct current stimulation in addition to physical therapy program. Depression was evaluated by Hamilton Depression scale pre and post treatment in both groups and quality of life was evaluated by The Stroke Specific Quality Of Life scale. Results: results of this study revealed a significant improvement in all different parameters in study group A P ≤ 0.05; over the control group B. Comparison of post treatment results of both groups showed that transcranial direct current stimulation used in study group A showed significant improvement in post stroke depression and Stroke Specific Quality Of Life than group B. Conclusion: transcranial direct current stimulation has significant effect on treatment of depression and Stroke Specific Quality Of Life in stroke patients.
ACUTE ORAL TOXICITY STUDY OF AQUEOUS

Blumea virens, belonging to family Asteraceae, is found abundantly in tropical and subtropical zones of Asia, especially in India. The consumption of whole plant has been reported to produce mortality in animals in Kerala. Thus, the present study was undertaken to evaluate the in vivo acute oral toxicity of aqueous and methanolic extract of Blumea virens in Sprague Dawley rats as per OECD guidelines 425. Limit test was conducted at a dose of 2000 mg/Kg. The animals administered with the aqueous and methanolic extract did not produce any related signs of toxicity or mortality during the 14-day observation period. Gross and histopathology was performed at the end of the study. Methanolic extract evinced hepatotoxicity and pulmonary toxicity to the animal whereas no abnormalities were detected with aqueous extract. Phytochemical analysis of the plant methanolic extract revealed presence of steroids, alkaloids, flavonoids, tannins, diterpenes, triterpenes and glycosides whereas aqueous extract revealed presence of steroids, alkaloids, flavonoids, diterpenes and glycosides.
FTRLIM results for OAEI 2020

FTRLIM is a distributed framework that is designed for large-scale instance matching. The FTRLIM framework leverages the blocking algorithm to generate candidate instance pairs, and applies the follow-the-regularized-leader model to determine whether candidate instance pairs are matched. FTRLIM participated in the SPIMBENCH Track of OAEI 2020, and achieved the fastest matching eﬃciency both in SANDBOX and MAINBOX, as well as the competitive matching quality.
Head Injuries from the Vulnerable Road User Injury Prevention Alliance (VIPA): Effect of Vehicle Type on Head Contact Location

Kohoyda-Inglis, E.H. Trager, C. Kohoyda-Inglis, S. Holcombe, S. Ejima all work at the University of Michigan, International Center for Automotive Medicine. F. Roth and A. Schneider work at Audi AG, Global Safety Affairs. J. Joyner works at General Motors, Global Vehicle Safety. B. Mueller works at the Insurance Institute for Highway Safety. Nick Ables works at Hyundai Mostor Group. Timothy Keon works for the Subaru Corporation. Abstract Several efforts to mitigate vulnerable road user (VRU) injury in motor vehicle crashes are ongoing. VRU head injuries are among the most common and severe. Descriptive findings from the Vulnerable Road User Injury Prevention Alliance’s current research efforts are reported in this study. Results include relational graphics of impact locations on vehicles with isometric and wrap documentations, strike density, impact speeds and kinematic patterns. The distribution maps of VRU-vehicle impact zones show that the most common contact occurred on the front right corner area of the vehicles for those that sustained a head injury. The forward projection trajectory type occurred at lower impact speeds with multipurpose vehicles (MPVs) and trucks, while wrap trajectories and roof vaults occurred at higher relative speeds. A higher proportion of VRU head/face contacts occurred beyond the hood surface (i.e. cowl, windshield) in passenger cars (84%) when compared to MPVs (44%) and trucks (50%). This analysis of pedestrian head/face strike locations on vehicles is the most current real-time surveillance of VRU crashes in the United States.
Antifeedant Activity of Nanoemulsion Formulation of Arugula Eruca sativa Oil on Elm Leaf Beetle Xanthogaleruca luteola (Coleoptera: Chrysomelidae)

The antifeedant activity of nanoemulsion formulation of arugula Eruca sativa Mill. oil was studied against elm leaf beetle Xanthogaleruca luteola (Müller)(Col.:Chrysomelidae) under laboratory conditions at 25±1oC, 75±5% RH, and LD 16:8 hours. Ingestive LC50 values of the oil were studied in third instar larvae. Then, physiological parameters were evaluated following 24, 48, and 72 hours post feeding at LC50 level. LC50 values 24, 48 and 72 hours after application were 4.940, 3.791, and 2.938 mg mL, respectively. Arugula oil at LC50 level decreased the nutritional indices including efficiency of conversion of ingested food, relative growth rate, efficiency of conversion of digested food, and relative consumption rate, but increased feeding deterrence index significantly 72 hours post feeding. Nutritional reserves such as total carbohydrate, protein, and lipid contents and also digestive enzymes containing lipase, α-amylase, and protease activity were decreased showing post-ingestive toxicity. The activity of the detoxifying enzyme glutathione Stransferase was increased, indicating that this enzyme may be involved in detoxification of arugula oil, but general esterase did not change significantly. In general, it can be concluded that arugula oil possess antifeedant activity against X. luteola under laboratory condition. It seems that arugula oil has a great potential to be used as effective botanical pesticides. However, further studies such as greenhouse and field experiments are necessary before recommendation and commercialization process.
Examining the adequacy of MFI multiple lending directive in India : A study of slum dwellers ’ loan-related choices

The Indian Financial Inclusion efforts have been quite paradoxical. While a significant number of households in the country is yet to have access to formal credit, many parts of the country have already experienced crises of over-borrowing, resulting in huge defaults. Although Indian financial inclusion experts have faced multiple setbacks in their efforts to push credit into low-income households, their pursuit has remained relentless. In order to put a plug on rising non-performing assets, the Reserve Bank of India (RBI) issued new directives for non-banking financial companies – micro finance institutions (NBFC-MFIs) in December 2011, with further modifications in August 2012, restricting the borrower’s freedom in a bid to control over-indebtedness. However, we reason that with mostly illiterate and vulnerable customers, and with informational asymmetries in the micro-credit markets, people with a tendency to cheat can still defect, while credit-worthy households may be denied loans at a time of need, and rogue MFIs may pre-empt good customers from other MFIs. Therefore, we study the borrowing behaviour of slum-dwelling households in the city of Pune. We find that the RBI directives are inadequate in containing over-borrowing. We reason that this would be true elsewhere in the country as well. Through a logit model, we find that household characteristics predict over-borrowing behaviour, but only to moderate levels. Since monitoring of microloans is not feasible and not all borrower attributes are observable, we suggest that the RBI should amend these restrictions and allow MFIs to decide their own course of action after obtaining client loan information from credit information companies (CIC). ----------JEL Classifications – G2, D1, D8, I3 Abbreviations CIC – Credit Information Company MFI – Micro Finance Institution NBFC – Non Banking Financial Company NPA – Non Performing Asset RBI – Reserve Bank of India
Identifying Authorship Style in Malicious Binaries: Techniques, Challenges & Datasets

Attributing a piece of malware to its creator typically requires threat intelligence. Binary attribution increases the level of difficulty as it mostly relies upon the ability to disassemble binaries to identify authorship style. Our survey explores malicious author style and the adversarial techniques used by them to remain anonymous. We examine the adversarial impact on the state-of-the-art methods. We identify key findings and explore the open research challenges. To mitigate the lack of ground truth datasets in this domain, we publish alongside this survey the largest and most diverse meta-information dataset of 15,660 malware labeled to 164 threat actor groups.
Measurement-induced criticality as a data-structure transition

We employ unsupervised learning tools to identify the dynamical phases and their measurement-induced transitions in quantum systems subject to the combined action of unitary evolution and stochastic local measurements. Speciﬁcally, we show that the principal component analysis and the intrinsic dimension estimation provide order parameters that directly locate the transition and the critical exponents in the classical encoding data space. Finally, we test our approach on stabilizer circuits as proof of principle, ﬁnding robust agreement with previous studies.
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning

While designing inductive bias in neural architectures has been widely studied, we hypothesize that transformer networks are flexible enough to learn inductive bias from suitable generic tasks. Here, we replace architecture engineering by encoding inductive bias in the form of datasets. Inspired by Peirce's view that deduction, induction, and abduction are the primitives of reasoning, we design three synthetic tasks that are intended to require the model to have these three abilities. We specifically design these tasks to be synthetic and devoid of mathematical knowledge to ensure that only the fundamental reasoning biases can be learned from these tasks. This defines a new pre-training methodology called"LIME"(Learning Inductive bias for Mathematical rEasoning). Models trained with LIME significantly outperform vanilla transformers on four very different large mathematical reasoning benchmarks. Unlike dominating the computation cost as traditional pre-training approaches, LIME requires only a small fraction of the computation cost of the typical downstream task. The code for generating LIME tasks is available at https://github.com/tonywu95/LIME.
Spectral representations of characteristic functions of discrete probability laws

We consider discrete probability laws on the real line, whose characteristic functions are separated from zero. In particular, this class includes arbitrary discrete infinitely divisible laws and lattice probability laws, whose characteristic functions have no zeroes on the real line. We show that characteristic functions of such laws admit spectral L\'evy--Khinchine type representations. We also apply the representations of such laws to obtain limit and compactness theorems with convergence in variation to probability laws from this class. Thus we generalize the corresponding results from the recent papers by Lindner, Pan, Sato, and by Khartov.
Disk Tearing: Numerical Investigation of Warped Disk Instability

We present numerical simulations of misaligned disks around a spinning black hole covering a range of parameters. Previous simulations have shown that disks that are strongly warped by a forced precession—in this case, the Lense–Thirring effect from the spinning black hole—can break apart into discrete disks or rings that can behave quasi-independently for short timescales. With the simulations we present here, we confirm that thin and highly inclined disks are more susceptible to disk tearing than thicker disks or those with lower inclination, and we show that lower values of the disk viscosity parameter lead to instability at lower warp amplitudes. This is consistent with detailed stability analysis of the warped disk equations. We find that the growth rates of the instability seen in the numerical simulations are similar across a broad range of parameters, and are of the same order as the predicted growth rates. However, we did not find the expected trend of growth rates with viscosity parameter. This may indicate that the growth rates are affected by numerical resolution, or that the wavelength of the fastest-growing mode is a function of local disk parameters. Finally, we also find that disk tearing can occur for disks with a viscosity parameter that is higher than predicted by a local stability analysis of the warped disk equations. In this case, the instability manifests differently, producing large changes in the disk tilt locally in the disk, rather than the large changes in disk twist that typically occur in lower-viscosity disks.
Dynamical Masses and Stellar Evolutionary Model Predictions of M Stars

In this era of Gaia and ALMA, dynamical stellar mass measurements, derived from spatially and spectrally resolved observations of the Keplerian rotation of circumstellar disks, provide benchmarks that are independent of observations of stellar characteristics and their uncertainties. These benchmarks can then be used to validate and improve stellar evolutionary models, the latter of which can lead to both imprecise and inaccurate mass predictions for pre-main-sequence, low-mass (≤0.5 M ⊙) stars. We present the dynamical stellar masses derived from disks around three M stars (FP Tau, J0432+1827, and J1100–7619) using ALMA observations of 12CO (J = 2–1) and 13CO (J = 2–1) emission. These are the first dynamical stellar mass measurements for J0432+1827 and J1100–7619 (0.192 ± 0.005 M ⊙ and 0.461 ± 0.057 M ⊙, respectively) and the most precise measurement for FP Tau (0.395 ± 0.012 M ⊙). Fiducial stellar evolutionary model tracks, which do not include any treatment of magnetic activity, agree with the dynamical stellar mass measurement of J0432+1827 but underpredict the mass by ∼60% for FP Tau and by ∼80% for J1100–7619. Possible explanations for the underpredictions include inaccurate assumptions of stellar effective temperature, undetected binarity for J1100–7619, and that fiducial stellar evolutionary models are not complex enough to represent these stars. In the former case, the stellar effective temperatures would need to be increased by amounts ranging from ∼40 to ∼340 K to reconcile the fiducial stellar evolutionary model predictions with the dynamically measured masses. In the latter case, we show that the dynamical masses can be reproduced using results from stellar evolutionary models with starspots, which incorporate fractional starspot coverage to represent the manifestation of magnetic activity. Folding in low-mass M stars from the literature and assuming that the stellar effective temperatures are imprecise but accurate, we find tentative evidence of a relationship between fractional starspot coverage and observed effective temperature for these young, cool stars.