Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Capital Injections with the Risk of Ruin: A Stochastic Differential Game of Impulse Control and Stopping Approach.

We consider an investment problem in which an investor performs capital injections to increase the liquidity of a firm for it to maximise profit from market operations. Each time the investor performs an injection, the investor incurs a fixed transaction cost. In addition to maximising their terminal reward, the investor seeks to minimise risk of loss of their investment (from a possible firm ruin) by exiting the market at some point in time. We show that the problem can be reformulated in terms of a new stochastic differential game of control and stopping in which one of the players modifies a (jump-)diffusion process using impulse controls and an adversary chooses a stopping time to end the game. We show that the value of this game can be computed by solving a double obstacle problem described by a quasi-variational inequality. We then characterise the value of the game via a set of HJBI equations, considering both games with zero-sum and non-zero-sum payoff structures. Our last result demonstrates that the solution to the investment problem is recoverable from the Nash equilibrium strategies of the game.
Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems

This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions.
Development and characterization of an oral multispecies biofilm implant flow chamber model

Peri-implant infections are the most common cause of implant failure in modern dental implantology. These are caused by the formation of biofilms on the implant surface and consist of oral commensal and pathogenic bacteria, which harm adjacent soft and hard tissues and may ultimately lead to implant loss. In order to improve the clinical situation, there has to be a better understanding of biofilm formation on abiotic surfaces. Therefore, we successfully developed a system to cultivate an oral multispecies biofilm model in a flow chamber system, optimized for the evaluation of biofilm formation on solid materials by direct microscopic investigation. The model contains four relevant oral bacterial species: Streptococcus oralis, Actinomyces naeslundii, Veillonella dispar and Porphyromonas gingivalis in ratios similar to the native situation. The reliability of the developed “Hanoverian Oral Multispecies Biofilm Implant Flow Chamber” (HOBIC) model was verified. Biofilm volume and live/dead distribution within biofilms were determined by fluorescence staining and confocal laser scanning microcopy (CLSM). The individual species distribution was analyzed using quantitative real time PCR with propidium monoazide pretreatment (PMA-qRT-PCR) and by urea-NaCl fluorescence in situ hybridization (urea-NaCl-FISH). This in vitro model may be used to analyze biofilm formation on dental implants in more detail and to develop future implant systems with improved material properties.
From one incision to one port: The surgical technique and the evolution of segmentectomy in patients with pulmonary tuberculosis

Objectives We retrospectively reviewed the evolution of segmentectomy for pulmonary tuberculosis (TB) and the feasibility of multi- and single-incision video-assisted thoracoscopic segmentectomy. Methods Of 348 patients undergoing surgery for TB, the medical records of 121 patients undergoing segmentectomy between January 1996 and November 2015 were reviewed. Clinical information and computed tomography (CT) image characteristics were investigated and analyzed. Results Eighteen patients underwent direct or intended thoracotomy. Sixty-four underwent video-assisted thoracoscopic segmentectomy (VATS), including 53 multi-incision thoracoscopic segmentectomy (MITS), and 11 single-incision thoracoscopic segmentectomy (SITS). Thirty-nine were converted to thoracotomy. The intended thoracotomy group had more operative blood loss (p = 0.005) and hospital stay (p = 0.001) than the VATS group although the VATS group had higher grade of cavity (p = 0.007). The intended thoracotomy group did not differ from converted thoracotomy in operative time, blood loss, or hospital stay, and the grade of pleural thickening was higher in the converted thoracotomy group (p = 0.001). The converted thoracotomy group had more operative blood loss, hospital stay, and complication rate than the MITS group (p = 0.001, p<0.001, and p = 0.009, respectively). The MITS group had lower pleural thickening, peribronchial lymph node calcification, cavity, and tuberculoma grading than the converted thoracotomy group (p<0.001, p = 0.001, 0.001, and 0.017, respectively). The SITS group had lower grading in pleural thickening, peribronchial lymph node calcification, and aspergilloma grading than the converted thoracotomy group (p = 0.002, 0.010, and 0.031, respectively). Four patients in the intended thoracotomy group and seven in the converted thoracotomy group had complications compared with three patients in the MITS and two in the SITS group. Risk factors of conversion were pleural thickening and peribronchial lymph node calcification. Conclusion Although segmentectomy is technically challenging in patients with pulmonary TB, it could be safely performed using MITS or SITS and should be attempted in selected patients. Its efficacy for medical treatment failure needs investigation.
Evolutionary Process of Zi Rime Change in North Henan Province : Perspectives of Linguistic Geography

This paper makes an attempt to explain the origin and evolutionary process of zi rime change in north Henan Province, mainly from the geographical distribution of zi forms in Hebi area. Based on the investigation into the relationship between the typological distribution and the geographical features, as well as the related historical events of immigrants in Ming Dynasty, the author argues that the degenerated affix of zi rime change in north Henan Province is originated from suffix , and the idea of ‘tou’ origin is not that convincing. Apart from the establishment of evolutionary chain, this paper also discusses the lenition chain In the author’s point of view, this change is due to the tendency to preserve the semantic function of zi suffix, which forces the segmental affix to be more prominent when it merges into the stem rime in the later stages of the evolution.
Joint Effect of Carotid Plaque and C‐Reactive Protein on First‐Ever Ischemic Stroke and Myocardial Infarction?

Background The joint effect of atherosclerosis and CRP (C‐reactive protein) on risk of ischemic stroke (IS) and myocardial infarction (MI) has been sparsely studied. The aim of this study was to explore whether CRP mediates the risk of events in subjects with prevalent carotid plaque, examine synergism, and test whether CRP and carotid plaque add to risk prediction beyond traditional risk factors. Methods and Results CRP and carotid total plaque area (TPA) were measured in 10 109 participants in the Tromsø Study from 1994 to 2008. Incident IS (n=671) and MI (n=1079) were registered until December 31, 2013. We calculated hazard ratios (HRs) of MI and IS according to categories of CRP (<1, 1–3, and >3 mg/L) and plaque status (no plaque and TPA below and above median) in Cox proportional hazard models with time‐varying covariates. Multivariable‐adjusted CRP >3 versus <1 mg/L was associated with risk of IS (HR, 1.84; 95% confidence interval, 1.49–2.26) and MI (HR, 1.46; 95% confidence interval, 1.23–1.73). TPA above median versus no plaque was associated with risk for IS (HR, 1.65; 95% confidence interval, 1.36–2.01) and MI (HR, 1.64; 95% confidence interval, 1.41–1.92). In participants with plaque, adjustment for CRP minimally attenuated the risk estimates. The highest incidence rates for MI and IS were seen in the group with both CRP >3 mg/L and TPA is above the median. TPA and CRP combined added to risk prediction beyond traditional risk factors. Conclusions The simultaneous presence of subclinical atherosclerosis and elevated CRP was associated with increased risk of IS and MI. The combined assessment of subclinical atherosclerosis and inflammatory biomarkers may improve cardiovascular disease risk stratification.
Seek and Push: Detecting Large Traffic Aggregates in the Dataplane

High level goals such as bandwidth provisioning, accounting and network anomaly detection can be easily met if high-volume traffic clusters are detected in real time. This paper presents Elastic Trie, an alternative to approaches leveraging controller-dataplane architectures. Our solution is a novel push-based network monitoring approach that allows detection, within the dataplane, of high-volume traffic clusters. Notifications from the switch to the controller can be sent only as required, avoiding the transmission or processing of unnecessary data. Furthermore, the dataplane can iteratively refine the responsible IP prefixes allowing a controller to receive a flexible granularity information. We report and discuss an evaluation of our P4-based prototype, showing our solution to be able to detect (with 95% of precision), hierarchical heavy hitters and superspreaders using less than 8KB or 80KB of active memory respectively. Finally, Elastic Trie can identify changes in the network traffic patterns, symptomatic of Denial-of-Service attack events.
#phramacovigilance - Exploring Deep Learning Techniques for Identifying Mentions of Medication Intake from Twitter

Mining social media messages for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions of drug usage and analyzing expression of sentiments related to drugs. Most of these studies are based on aggregated results from a large population rather than specific sets of individuals. In order to conduct studies at an individual level or specific cohorts, identifying posts mentioning intake of medicine by the user is necessary. Towards this objective, we train different deep neural network classification models on a publicly available annotated dataset and study their performances on identifying mentions of personal intake of medicine in tweets. We also design and train a new architecture of a stacked ensemble of shallow convolutional neural network (CNN) ensembles. We use random search for tuning the hyperparameters of the models and share the details of the values taken by the hyperparameters for the best learnt model in different deep neural network architectures. Our system produces state-of-the-art results, with a micro- averaged F-score of 0.693.
Highly ordered molecular rotor matrix on a nanopatterned template: titanyl phthalocyanine molecules on FeO/Pt(111)

Molecular rotors, motors and gears play important roles in artificial molecular machines, in which rotor and motor matrices are highly desirable for large-scale bottom-up fabrication of molecular machines. Here we demonstrate the fabrication of a highly ordered molecular rotor matrix by depositing nonplanar dipolar titanyl phthalocyanine (TiOPc, C32H16N8OTi) molecules on a Moiré patterned dipolar FeO/Pt(111) substrate. TiOPc molecules with O atoms pointing outwards from the substrate (upward) or towards the substrate (downward) are alternatively adsorbed on the fcc sites by strong lateral confinement. The adsorbed molecules, i.e. two kinds of molecular rotors, show different scanning tunneling microscopy images, thermal stabilities and rotational characteristics. Density functional theory calculations clarify that TiOPc molecules anchoring upwards with high adsorption energies correspond to low-rotational-rate rotors, while those anchoring downwards with low adsorption energies correspond to high-rotational-rate rotors. A robust rotor matrix fully occupied by low-rate rotors is fabricated by depositing molecules on the substrate at elevated temperature. Such a paradigm opens up a promising route to fabricate functional molecular rotor matrices, driven motor matrices and even gear groups on solid substrates.
Supplementary note : Palimpsest : an R package for studying mutational and structural variant signatures along clonal evolution in cancer

S1. Mutational signature analysis Palimpsest allows both de novo analysis of mutational signatures and quantification of previously described signatures. In both cases, a set of base substitutions from a tumor series is first imported from a VCF file and each mutation is assigned to one of 96 mutation categories, defined by the 6 substitution types multiplied by 16 possible trinucleotide contexts (Alexandrov et al., 2013). We can then represent the mutational catalog of the n tumors as a mutation
A Review of Systematic Risk Estimation on the JSE

This paper reviews some recent developments in the area of beta estimation on the JSE. it turns out that the dual phenomena of extreme thin trading and mild segmentation between the industrial and mining boards on the JSE impact on the techniques used for efficient beta estimation. On the basis of a simulation study as well as an empirical investigation, the trade-to-trade approach to beta estimation with a Bayesian adjustment has shown itself to be superior to other thin trading correction procedures. Further evidence of the perceived segmentation between the industrial and mining sectors of the JSE is revealed in the pricing of securities. As a consequence it is argued that the relevant Financial and Industrial or Mining Index should be used as a market proxy for beta estimation. The non-normality of security returns and possible time variance of security betas is also discussed in the context of the JSE.
Inter-specific and ontogenic differences in δ13C and δ15N values and Hg and Cd concentrations in cephalopods

Chemical tracers (e.g. stable isotopes or trace metals) are increasingly used to study trophic ecology and feeding habits of marine organisms and various factors can affect their values. The aim of the present study was to provide information on ontogenic effects on stable carbon and nitrogen values (δ 13 C and δ 15 N) and on cadmium (Cd) and mercury (Hg) concentrations in 5 cephalo- pod species from the Bay of Biscay (North-East Atlantic Ocean). To this end, individuals belonging to 3 species showing the widest range of sizes were analysed for muscle δ 13 C and δ 15 N values and mus- cle Hg, and digestive gland Cd concentrations. Results showed that stable isotope ratios allowed dis- crimination of specific feeding strategies during ontogenesis. Segregation between 5 cephalopod species in terms of trophic ecology was also evidenced (different isotopic niches). In contrast, Hg con- centrations varied over the same order of magnitude in these 5 cephalopod species, despite higher levels in the benthic octopus Eledone cirrhosa. Consistently, Hg concentrations followed the same ontogenic pattern and increased with increasing body size/age of cephalopods. Finally, Cd concen- trations varied over 3 orders of magnitude among the 5 species. Despite possible effects of physiol- ogy in terms of metal bioaccumulation, Cd concentrations were likely to reflect specific feeding pref- erences or feeding zones and ontogenic variability within a single species. Thus, ontogenic effects have to be taken into account when stable isotope ratios of carbon and nitrogen or trace metals are used as ecological tracers; the best recommendation being to focus on a given class age.
Automatic digital modulation recognition based on stacked sparse autoencoder

In this paper, a modulation recognition algorithm based on Stacked sparse Auto-Encoder (SSAE) is proposed for the classification of common digitally modulated signals. To this end, a set of eight features including, two instantaneous features and six higher order cumulants features are extracted from the intercepted signal; these features are then fed to the SSAE for classification. Unlike the majority of classifiers used in AMR algorithms, which relies only on the supervised learning scenario, the stacked sparse autoencoder benefits from both, unsupervised and supervised learning approaches. In fact, the main advantage of the SSAE is that it can automatically learn new features to separate the input data during the unsupervised pre-training phase. These new features are used as initialization parameters in the supervised training phase to enhance the convergence of the SSAE to optimal results, as well as improve the noise resistance of the eight features extracted before. Results show that the overall success rate reach 100 % at 5dB SNR. The performance of the proposed algorithm is compared to an SVM-based method, and it is found that the probability of correct classification in our method is considerably improved.
Translating Web Search Queries into Natural Language Questions

Users often query a search engine with a specific question in mind and often these queries are keywords or sub-sentential fragments. For example, if the users want to know the answer for "What's the capital of USA", they will most probably query "capital of USA" or "USA capital" or some keyword-based variation of this. For example, for the user entered query "capital of USA", the most probable question intent is "What's the capital of USA? ". In this paper, we are proposing a method to generate well-formed natural language question from a given keyword-based query, which has the same question intent as the query. Conversion of keyword-based web query into a well-formed question has lots of applications, with some of them being in search engines, Community Question Answering (CQA) website and bots communication. We found a synergy between query-to-question problem with standard machine translation(MT) task. We have used both Statistical MT (SMT) and Neural MT (NMT) models to generate the questions from the query. We have observed that MT models perform well in terms of both automatic and human evaluation.
Metrics analysis based on call graph of class methods

Evaluating software quality is a significant step in the process of developing software. Object-oriented metrics is an important way for software quality assessment and defect prediction. However, the existing object-oriented metric methods are difficult to reflect the complexity of software and vulnerabilities from the level of classes' method call relationship. A method is proposed in this paper, firstly we construct a call graph according to different classes methods call relationship in the system, and then three new software metrics are defined and analyzed by the call graph. The results of experiment indict that the metrics can reflect the complexity of software systems. These metrics can provide recommendations for evaluating software quality from the call graph.
Multiple objects tracking based on multiple information integration

Multi-target tracking algorithm often fail when targets are covered, or move fast, and it cannot be recovered from the failure. To solve this problem, firstly we use multiple information which integrate the target motion information and shape information. Based on the Fisher Criteria, we make the distance between same targets as close as possible which the distance between different targets far away. Secondly, the single target tracker based on strong discriminative ability and the Kalman predictor can track accurately when the target is covered or moves fast. The experimental results show that our multi-target tracking algorithm can track target in occlusion or in fast moving accurately in real time.
Feature extraction and segmentation in medical images by statistical optimization and point operation approaches

Feature extraction is a critical preprocessing step, which influences the outcome of the entire process of developing significant metrics for medical image evaluation. The purpose of this paper is firstly to compare the effect of an optimized statistical feature extraction methodology to a well designed combination of point operations for feature extraction at the preprocessing stage of retinal images for developing useful diagnostic metrics for retinal diseases such as glaucoma and diabetic retinopathy. Segmentation of the extracted features allow us to investigate the effect of occlusion induced by these features on generating stereo disparity mapping and 3-D visualization of the optic cup/disc. Segmentation of blood vessels in the retina also has significant application in generating precise vessel diameter metrics in vascular diseases such as hypertension and diabetic retinopathy for monitoring progression of retinal diseases.
Stunting at 24 Months Is Not Related to Incidence of Overweight through Young Adulthood in an Urban South African Birth Cohort.

Background The role that childhood stunting plays in the development of overweight and obesity later in life is not well understood, particularly in adolescence and young adulthood, because most studies have only followed up through midchildhood. Objective The objective of this study was to examine the relation between stunting and age-specific patterns of overweight and obesity incidence from early childhood to young adulthood in the context of a country in the process of the nutrition transition while these children were growing up. Methods We analyzed data from 895 participants in the Birth-to-Twenty Plus Cohort (Bt20+), an urban South African birth cohort initiated in 1990. Anthropometric data were collected at multiple ages and participants were included if they provided height at age 24 mo and ≥1 measure of body mass index [BMI; weight (kg)/height (m)2] in each of the following time periods: 4-8 y, 11-12 y, 13-15 y, 16-18 y, and 22-24 y. We defined stunting at age 24 mo as height-for-age z score <2 and overweight as BMI z score (BMIZ) >1 in childhood (4-8 y) and adolescence (11-12 y, 13-15 y, and 16-18 y) and BMI ≥25 in young adulthood (22-24 y). We compared BMI, BMIZ, and the prevalence of overweight by stunting status, stratified by sex. Results Our sample was 93% black and 51% female. The prevalence of stunting at 24 mo was 26% in males and 19% in females. In young adulthood, the prevalence of overweight and obesity was 15.5% (men) and 47.5% (women). Among both males and females, neither mean BMI nor a combined measure of overweight and obesity in any subsequent period differed by stunting status at 24 mo (P ≥ 0.05). Conclusion Stunting at 24 mo was not related to the risk of overweight or obesity in this cohort. Stunting may not be an important contributor to the increasing obesity rates in urban South Africa.