Miracle-dz/UniFAR-FTUs huggingface dataset:
Addressing Key Gaps in Existing Longitudinal Research and Establishing a Pathway Forward for Firearm Violence Prevention Research

ABSTRACT The main purpose of this article and this special section is to encourage greater attention to the key gaps that exist in our understanding of the epidemiology of adolescent firearm violence and to provide a pathway forward for future longitudinal research that will inform prevention efforts. This increased attention is especially salient given: (a) firearms are the leading cause of death for adolescents and emerging adults in the United States, with the majority of these deaths due to interpersonal violence; (b) significant health and social disparities with regards to the populations that are most affected by interpersonal firearm violence have been documented; and, (c) limitations in federal research funding during the past 30 years have created a deficit of knowledge about key risk and protective factors necessary to inform evidence-based prevention efforts. We discuss the implications of the articles in this special edition for existing and novel prevention programs. We also identify key considerations for future epidemiological research, including the need for a greater focus on collecting longitudinal data among nationally representative samples enriched with subgroups of at-risk youth, the need to examine the role of protective factors and mediating variables within existing and novel theoretical models of firearm risk behaviors, the need to examine key factors across all levels of the socio-ecological model, and the need to incorporate novel and innovative research designs, methods and analyses.
Exploring the antecedents of entrepreneurship success in information technology firms in Nigeria

ABSTRACT We examine four antecedents of IT entrepreneurship success in Nigeria. Particularly, two of the investigated antecedents are general human capital factors (i.e., having experience with entrepreneurial parents and business training) and the other two (IT education and spirituality) are specific to IT entrepreneurship and the Nigerian context. In a quantitative study of 167 IT entrepreneurs in Nigeria, we found that the general factors are more important determinants of success among IT entrepreneurs in Nigeria than the specific ones. There is corroboration between our findings and the developed economy literature which provides ample evidence of a positive relationship between having experience with entrepreneurial parents and entrepreneurship success. Before our findings, limited knowledge existed on the complexity of this orthodoxy in developing markets such as Nigeria. Our result did not show any significant correlation between formal education in the IT field and IT entrepreneurial success. Our paper contributes to the discourse on the antecedents of entrepreneurship success by focusing on IT entrepreneurship from a developing country context. This is particularly critical when one considers the importance of IT entrepreneurship towards economic diversification in Nigeria. The unique theoretical contribution of our paper lies in its introduction of the specific antecedents (constructs), IT-education and spirituality, even though they were not found as significant determinants of entrepreneurship success in the Nigerian context. Our findings imply that national entrepreneurial policy should be tailored to exploit the inherent benefits of experience with entrepreneurial parents and effectively blend it with factors such as business school education and other forms of relevant training in the areas of social competence.
Development and Validation of UV Derivative Spectrophotometric Method for Determination of Atorvastatin in Tablets

A zero-, first-, second-, and third-order derivative UV spectrophotometric method for determination of atorvastatin in tablets has been proposed. The proposed method was linear (linear range from 0.002 to 0.040 mg mL -1 ; r = 0.999), accurate (mean recovery 100.0%), and precise (mean CV = 1.20%). The obtained results were compared to those obtained by HPLC method (column: Lichrospher C-18 (Merck), mobile phase: water-acetonitrile (48:52, v/v) pH 2.0 adjusted with 80% orthophosphoric acid; spectrophotometric detection at 245 nm). No statistically significant differences between the results obtained by both methods were observed.
Investigation of BaSO4-KPO3-Na2B4O7 Low-Melting Glass System as a Basis for Synthesis of a Glass-Solder Material

The possibility of using the compositions of BaSO4-KPO3-Na2B4O7 system as a glass-solder (frit) material was shown. A glass formation region has been established in BaSO4-KPO3-Na2B4O7 system which is located in the borate-phosphate part of the concentration triangle and occupies ~41% of the triangle area. The concentration dependences of linear thermal expansion coefficient (TCLE), the softening temperature and the glass transition temperature was determined and discussed. It is established that the glass formation region, the concentration dependences of TCLE and technological temperatures values are significantly closer to those for CaSO4-KPO3-Na2B4O7 system than for MgSO4-KPO3-Na2B4O7 system. That may point out at the similar effect barium sulphate and calcium sulphate doping in the sulphate-phosphate-borate systems.
TAPHONOMIC ANALYSIS OF THE PALEOENTOMOFAUNA ASSEMBLAGE FROM THE CENOZOIC OF THE FONSECA BASIN, SOUTHEASTERN BRAZIL

Abstract: The Fonseca Formation (Eocene–Oligocene boundary, Minas Gerais, Brazil) is well known for its paleoflora, especially of flowering plants. The richness of this insect-bearing fossil locality is significantly less well understood, but we can shed light on the insect paleocommunity. One hundred and eight fossil insect specimens were examined and separated into four grades based on their preservational quality. We conducted analyses of taphonomic features, including body orientation, size, articulation, and chemical composition. Our results reveal differences in the body articulation of the insects. The fully articulated specimens apparently did not experience extensive flotation time at the water-air interface, whereas for partially articulated and disarticulated specimens the opposite is true. These taphonomic features would be acquired during the biostratinomy stage, and not early diagenesis. We also employed high resolution techniques (SEM-EDS and Raman spectroscopy) to understand their fossilization potential. Our chemical data suggest that the Fonseca insects are preserved as organic remains in carbonaceous compressions. Thus, chitin biomolecules most likely were transformed into more resistant biopolymers during diagenesis. This interpretation may also imply that the carbonaceous material originated from the insect itself. In this study, we document new discoveries and also provide future prospects for study of the Fonseca Formation.
Breast reconstruction after breast cancer surgery – persistent pain and quality of life 1–8 years after breast reconstruction

Abstract Objectives To assess the long-term outcome of breast reconstructions with special focus on chronic postsurgical pain (CPSP) in a larger cohort of breast cancer survivors. Methods A cross-sectional study on 121 women with mastectomy and breast reconstruction after mean 2 years 4 months follow up. The mean time from breast reconstruction to the follow-up visit was 4 years 2 months. We studied surveys on pain (Brief Pain Inventory, BPI and Douleur Neuropathique 4, DN4), quality of life (RAND-36 health survey), sleep (insomnia severity questionnaire, ISI), mood (Beck’s Depression Index, BDI; Hospital Anxiety and Depression Scale, HADS), and a detailed clinical sensory status. Patients were divided into three groups: abdominal flap (Deep inferior epigastric perforator flap, DIEP; Free transverse rectus abdominis flap, fTRAM, and Pedicled transverse rectus abdominis flap, pTRAM), dorsal flap (Latissimus dorsi flap, LD and Thoracodorsal artery perforator flap, TDAP), and other (Transverse myocutaneous gracilis flap, TMG; implant). Clinically meaningful pain was defined ≥ 4/10 on a numeric rating scale (NRS). We used patients’ pain drawings to localize the pain. We assessed preoperative pain NRS from previous data. Results 106 (87.6%) of the patients did not have clinically meaningful persistent pain. We found no statistically significant difference between different reconstruction types with regards to persistent pain (p=0.40), mood (BDI-II, p=0.41 and HADS A, p=0.54) or sleep (p=0.14), respectively. Preoperative pain prior to breast reconstruction surgery correlated strongly with moderate or severe CPSP. Conclusions Moderate to severe CPSP intensity was present in 14% of patients. We found no significant difference in the prevalence of pain across different reconstruction types. Preoperative pain associated significantly with postoperative persistent pain.
Direct Optical Observation of Band-Edge Excitons, Band Gap, and Fermi Level in Degenerate Semiconducting Oxide Nanowires In2O3

Direct optical evidence of Burstein–Moss shift (BMS) in conduction band of cubic c-In2O3 nanowires is reported herein. The optical property of degenerate semiconducting oxide c-In2O3 has been investigated by thermoreflectance (TR) spectroscopy. Low-temperature TR spectra clearly show a series of band-edge excitons for c-In2O3. The threshold energy for the exciton series was determined. One transition feature of direct gap caused by BMS was detected in all TR spectra from 20 to 300 K. The Femi-level (EF) energy above conduction-band edge (EC) is determined to be EF – EC ≈ 92 meV. The energy value causes a calculated electron density of ∼2.1 × 1019 cm–3. The direct gap of c-In2O3 with BMS is 3.43 eV at 300 K. Free exciton, bound exciton complexes, donor–acceptor pair transition, and defect emissions have been evaluated by photoluminescence (PL) measurements from 10 to 300 K. Photoresistivity change (i.e., 5.71 × 10–2 → 4.85 × 10–2 Ω-cm) under the illumination of halogen lamp (5 mW·cm–2) for c-In2O3 thin-fil.
A Journey Through Android App Analysis: Solutions and Open Challenges

Users can today download a wide variety of apps ranging from simple toy games to sophisticated business-critical apps. They rely on these apps daily to perform diverse tasks, some of them related to sensitive information such as their finance or health. Ensuring high-quality, reliable, and secure apps is thus key. In the TruX research group of the interdisciplinary center for Security, Reliability, and Trust (SnT) of the University of Luxembourg, we are working for about 10 years to deliver practical techniques, tools, and other artifacts (such as repositories) making the analysis of Android apps possible. In this paper, we will briefly introduce our key contributions in both (1) Android app static analysis to detect security issues, and (2) Android Malware Detection with machine learning. We will conclude by listing several open challenges that we are currently facing towards improving the analysis and security of Android apps.
Omegaflow: a high-performance dependency-based architecture

This paper investigates how to better track and deliver dependency in dependency-based cores to exploit instruction-level parallelism (ILP) as much as possible. To this end, we first propose an analytical performance model for the state-of-art dependency-based core, Forwardflow, and figure out two vital factors affecting its upper bound of performance. Then we propose Omegaflow,a dependency-based architecture adopting three new techniques, which respond to the discovered factors. Experimental results show that Omegaflow improves IPC by 24.6% compared to the state-of-the-art design, approaching the performance of the OoO architecture with an ideal scheduler (94.4%) without increasing the clock cycle and consumes only 8.82% more energy than Forwardflow.
HyQuas: hybrid partitioner based quantum circuit simulation system on GPU

Quantum computing has shown its strong potential in solving certain important problems. Due to the intrinsic limitations of current real quantum computers, quantum circuit simulation still plays an important role in both research and development of quantum computing. GPU-based quantum circuit simulation has been explored due to GPU's high computation capability. Despite previous efforts, existing quantum circuit simulation systems usually rely on a single method to improve poor data locality caused by complex quantum entanglement. However, we observe that existing simulation methods show significantly different performance for different circuit patterns. The optimal performance cannot be obtained only with any single method. To address these challenges, we propose HyQuas, a \textbf{Hy}brid partitioner based \textbf{Qua}ntum circuit \textbf{S}imulation system on GPU, which can automatically select the suitable simulation method for different parts of a given quantum circuit according to its pattern. Moreover, to make better support for HyQuas, we also propose two highly optimized methods, OShareMem and TransMM, as optional choices of HyQuas. We further propose a GPU-centric communication pipelining approach for effective distributed simulation. Experimental results show that HyQuas can achieve up to 10.71 x speedup on a single GPU and 227 x speedup on a GPU cluster over state-of-the-art quantum circuit simulation systems.
Bran: Reduce Vulnerability Search Space in Large Open Source Repositories by Learning Bug Symptoms

Software is continually increasing in size and complexity, and therefore, vulnerability discovery would benefit from techniques that identify potentially vulnerable regions within large code bases, as this allows for easing vulnerability detection by reducing the search space. Previous work has explored the use of conventional code-quality and complexity metrics in highlighting suspicious sections of (source) code. Recently, researchers also proposed to reduce the vulnerability search space by studying code properties with neural networks. However, previous work generally failed in leveraging the rich metadata that is available for long-running, large code repositories. In this paper, we present an approach, named Bran, to reduce the vulnerability search space by combining conventional code metrics with fine-grained repository metadata. Bran locates code sections that are more likely to contain vulnerabilities in large code bases, potentially improving the efficiency of both manual and automatic code audits. In our experiments on four large code bases, Bran successfully highlights potentially vulnerable functions, outperforming several baselines, including state-of-art vulnerability prediction tools. We also assess Bran's effectiveness in assisting automated testing tools. We use Bran to guide syzkaller, a known kernel fuzzer, in fuzzing a recent version of the Linux kernel. The guided fuzzer identifies 26 bugs (10 are zero-day flaws), including arbitrary writes and reads.
A practical tile size selection model for affine loop nests

Loop tiling for locality is an important transformation for general-purpose and domain-specific compilation as it allows programs to exploit the benefits of deep memory hierarchies. Most code generation tools with the infrastructure to perform automatic tiling of loop nests rely on auto-tuning to find good tile sizes. Tile size selection models proposed in the literature either fall back to modeling complex non-linear optimization problems or tackle a narrow class of inputs. Hence, a fast and generic tile size selection model is desirable for it to be adopted into compiler infrastructures like those of GCC, LLVM, or MLIR. In this paper, we propose a new, fast and lightweight tile size selection model that considers temporal and spatial reuse along dimensions of a loop nest. For an n-dimensional loop nest, we determine the tile sizes by calculating the zeros of a polynomial in a single variable of degree at most n. Our tile size calculation model also accounts for vectorizability of the innermost dimension. We demonstrate the generality of our approach by selecting benchmarks from various domains: linear algebra kernels, digital signal processing (DSP) and image processing. We implement our tile size selection model in PolyMage (a domain-specific language and compiler for image processing pipelines) and Pluto (state-of-the-art polyhedral auto-parallelizer). Implementing the model in PolyMage allows us to extend it to DSP and linear algebra domains and also incorporate idiom recognition phases so that optimized vendor-specific library implementations could be utilized whenever profitable. Our experiments demonstrate a significant geomean performance gain of 2.2x over Matlab on benchmarks from the DSP domain. For PolyBench, we obtain a geomean speedup of 1.04x (maximum speedup of 1.3x) over Pluto.
Design of Gaussian Similarity Measure for Network Anomaly Detection

Identifying intrusion in networks is one of the important concerns in computer networks. The task of dimensionality reduction and choice of classifier plays an important role in network intrusion detection. Dimensionality reduction should make sure that the efficacy of classifier on reduced dimensionality data is atleast retained if not improved. In this paper, we suggest a similarity function which can be used to find similarity between any two network elements expressed as vectors. The similarity measure is designed to make sure that the attribute distribution is taken into account for finding similarity value.
Oscillatory flow between concentric spheres driven by an electromagnetic force

Abstract The time-dependent flow driven by electromagnetic forcing of an electrolytic fluid in the gap of a concentric spheres set-up is studied experimentally and theoretically. The driving Lorentz force is generated by the interaction of an alternating current radially injected through electrodes located at the equatorial zone of the spheres and a dipolar magnetic field produced by a permanent magnet inside the inner sphere. Experimentally, the time-dependent flows were explored in the laminar regime with a Reynolds number ${Re} = 640$ and different forcing frequencies, which resulted in oscillatory Reynolds numbers ranging from $28$ to $2820$. Velocity profiles in the equatorial line between spheres were obtained with particle image velocimetry. Given the symmetry of the problem at the equatorial plane, asymptotic and approximate solutions for the azimuthal velocity are obtained for the limiting cases of low-${Re}_{\omega }$ (in real arguments) and high-${Re}_{\omega }$ (in complex arguments). Furthermore, a general methodology is proposed in such a way that an exact solution for the problem is obtained. The analytical solutions reproduce the main characteristic behaviour of the flow. An estimation of the oscillatory boundary layer due to the electromagnetic forcing is obtained through the exact solution. A full three-dimensional numerical model, that introduces the dipolar magnetic field and the radial dependency of the applied current, is able to quantitatively reproduce both the analytical solutions and the experimental measurements. Additionally, numerical results show a resonant behaviour of the flow when the forcing frequency is approximately ${Re}_{\omega } \approx 560$.
Aggressiveness of Care at the End-of-Life in Cancer Patients and Its Association With Psychosocial Functioning in Bereaved Caregivers

Study Registration https://www.drks. de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00022837,DRKS00022837. Background Intensified oncological treatment for advanced cancer patients at the end-of-life has been specified as aggressiveness of care (AOC) and increased over the past decades. The aims of this study were to 1) determine the frequency of AOC in Central Europe, and 2) investigate differences in mental health outcomes in bereaved caregivers depending on whether the decedent had experienced AOC or not. Materials and methods We conducted a cross-sectional study in a large tertiary comprehensive cancer care center in Germany. Bereaved caregivers provided information about (a) treatment within the last month of life of the deceased cancer patient and (b) their own mental health status, i.e., decision regret, complicated grief, depression, and anxiety. After multiple imputation of missing data, differences in mental health outcomes between AOC-caregivers and non-AOC-caregivers were analyzed in a multivariate analysis of variances. Results We enrolled 298 bereaved caregivers of deceased cancer patients. AOC occurred in 30.9% of all patients. In their last month of life, 20.0% of all patients started a new chemotherapy regimen, and 13.8% received ICU-treatment. We found differences in mental health outcomes between bereaved AOC- and non-AOC-caregivers. Bereaved AOC caregivers experienced significantly more decision regret compared to non-AOC caregivers (Cohen’s d = 0.49, 95% CI [0.23, 0.76]). Conclusion AOC occurs frequently in European health care and is associated with poorer mental health outcomes in bereaved caregivers. Future cohort studies should substantiate these findings and explore specific trajectories related to AOC. Notwithstanding, shared-decision making at end-of-life should increasingly account for both patients’ and caregivers’ preferences.
Write Like You: Synthesizing Your Cursive Online Chinese Handwriting via Metric‐based Meta Learning

In this paper, we propose a novel Sequence‐to‐Sequence model based on metric‐based meta learning for the arbitrary style transfer of online Chinese handwritings. Unlike most existing methods that treat Chinese handwritings as images and are unable to reflect the human writing process, the proposed model directly handles sequential online Chinese handwritings. Generally, our model consists of three sub‐models: a content encoder, a style encoder and a decoder, which are all Recurrent Neural Networks. In order to adaptively obtain the style information, we introduce an attention‐based adaptive style block which has been experimentally proven to bring considerable improvement to our model. In addition, to disentangle the latent style information from characters written by any writers effectively, we adopt metric‐based meta learning and pre‐train the style encoder using a carefully‐designed discriminative loss function. Then, our entire model is trained in an end‐to‐end manner and the decoder adaptively receives the style information from the style encoder and the content information from the content encoder to synthesize the target output. Finally, by feeding the trained model with a content character and several characters written by a given user, our model can write that Chinese character in the user's handwriting style by drawing strokes one by one like humans. That is to say, as long as you write several Chinese character samples, our model can imitate your handwriting style when writing. In addition, after fine‐tuning the model with a few samples, it can generate more realistic handwritings that are difficult to be distinguished from the real ones. Both qualitative and quantitative experiments demonstrate the effectiveness and superiority of our method.