Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolomic Analysis in Neurocritical Care Patients

Metabolomics is the analytical study of metabolites in biological matrices using high-throughput profiling. Traditionally, the metabolome has been studied to identify various biomarkers for the diagnosis and pathophysiology of disease. Over the last decade, metabolomic research has grown to include the identification of prognostic markers, the development of novel treatment strategies, and the prediction of disease severity. In this review, we summarized the available evidence on the use of metabolome profiling in neurocritical care populations. Specifically, we focused on aneurysmal subarachnoid hemorrhage, traumatic brain injury, and intracranial hemorrhage to identify the gaps in the current literature and to provide direction for future studies. A primary literature search of the Medline and EMBASE databases was conducted. Upon removing duplicate studies, abstract screening and full-text screening were performed. We screened 648 studies and extracted data from 17 studies. Based on the current evidence, the utility of metabolomic profiling has been limited due to inconsistencies amongst studies and a lack of reproducible data. Studies identified various biomarkers for diagnosis, prognosis, and treatment modification. However, studies evaluated and identified different metabolites, resulting in an inability to compare the study results. Future research towards addressing the gaps in the current literature, including reproducing data on the use of specific metabolite panels, is needed.
Communication-Efficient Inner Product Private Join and Compute with Cardinality

Private join and compute (PJC) is a paradigm where two parties owing their private database securely join their databases and compute a function over the combined database. Inner product PJC, introduced by Lepoint et al. (Asiacrypt’21), is a class of PJC that has a wide range of applications such as secure analysis of advertising campaigns. In this computation, two parties, each of which has a set of identifier-value pairs, compute the inner product of the values after the (inner) join of their databases with respect to the identifiers. They proposed inner product PJC protocols that are specialized for the unbalanced setting where the input sizes of both parties are significantly different and not suitable for the balanced setting where the sizes of two inputs are relatively close. We propose an inner product PJC protocol that is much more efficient than that by Lepoint et al. for balanced inputs in the setting where both parties are allowed to learn the intersection size additionally. Our protocol can be seen as an extension of the private intersection-sum protocol based on the decisional Diffie-Hellman assumption by Ion et al. (EuroS&P’20) and is especially communication-efficient as the private intersection-sum protocol. In the case where both input sizes are 216, the communication cost of our inner-product PJC protocol is 46 × less than that of the inner product PJC protocol by Lepoint et al.
Response and receptivity of the hypersonic boundary layer past a wedge to free-stream acoustic, vortical and entropy disturbances

This paper analyses the response and receptivity of the hypersonic boundary layer over a wedge to free-stream disturbances including acoustic, vortical and entropy fluctuations. Due to the presence of an attached oblique shock, the boundary layer is known to support viscous instability modes whose eigenfunctions are oscillatory in the far field. These modes acquire a triple-deck structure. Any of three elementary types of disturbance with frequency and wavelength on the triple-deck scales interacts with the shock to generate a slow acoustic perturbation, which is reflected between the shock and the wall. Through this induced acoustic perturbation, vortical and entropy free-stream disturbances drive significant velocity and temperature fluctuations within the boundary layer, which is impossible when the shock is absent. A quasi-resonance was identified, due to which the boundary layer exhibits a strong response to a continuum of high-frequency disturbances within a narrow band of streamwise wavenumbers. Most importantly, in the vicinity of the lower-branch neutral curve the slow acoustic perturbation induced by a disturbance of suitable frequency and wavenumbers is in exact resonance with a neutral eigenmode. As a result, the latter can be generated directly by each of three types of free-stream disturbance without involving any surface roughness element. The amplitude of the instability mode is determined by analysing the disturbance evolution through the resonant region. The fluctuation associated with the eigenmode turns out to be much stronger than the free-stream disturbances due to the resonant nature of excitation, and in the case of acoustic disturbances, to the well-known amplification effect of a strong shock. Moreover, excitation at the neutral position means that the instability mode grows immediately without undergoing any decay, or missing any portion of the unstable region. All these indicate that this new mechanism is particularly efficient. The boundary-layer response and coupling coefficients are calculated for typical values of parameters.
Formation with Non-Collision Control Strategies for Second-Order Multi-Agent Systems

This article tackles formation control with non-collision for a multi-agent system with second-order dynamics. The nested saturation approach is proposed to solve the well-known formation control problem, allowing us to delimit the acceleration and velocity of each agent. On the other hand, repulsive vector fields (RVFs) are developed to avoid collisions among the agents. For this purpose, a parameter depending on the distances and velocities among the agents is designed to scale the RVFs adequately. It is shown that when the agents are at risk of collision, the distances among them are always greater than the safety distance. Numerical simulations and a comparison with a repulsive potential function (RPF) illustrate the agents’ performance.
Risk Factors for Death or Cardiovascular Events after Acute Coronary Syndrome in Patients with Myeloproliferative Neoplasms

Patients with myeloproliferative neoplasms (MPNs) are at increased risk of cardiovascular disease (CVD), including acute coronary syndrome (ACS). However, data on long-term outcomes of patients with MPN who have had ACS and risk factors for all-cause death or CV events post-ACS hospitalization are lacking. We conducted a single-center study of 41 consecutive patients with MPN with ACS hospitalization after MPN diagnosis. After a median follow-up of 80 months after ACS hospitalization, 31 (76%) experienced death or a CV event (myocardial infarction, ischemic stroke, or heart failure hospitalization). After multivariable Cox proportional hazards regression, index ACS within 12 months of MPN diagnosis (HR 3.84, 95% CI 1.44–10.19), WBC ≥ 20 K/µL (HR 9.10, 95% CI 2.71–30.52), JAK2 mutation (HR 3.71, 95% CI 1.22–11.22), and prior CVD (HR 2.60, 95% CI 1.12–6.08) were associated with increased death or CV events. Further studies are warranted to improve cardiovascular outcomes in this patient population.
Injectable Hyaluronan-Based Thermoresponsive Hydrogels for Dermatological Applications

Most marketed HA-based dermal fillers use chemical cross-linking to improve mechanical properties and extend their lifetime in vivo; however, stiffer products with higher elasticity require an increased extrusion force for injection in clinical practice. To balance longevity and injectability, we propose a thermosensitive dermal filler, injectable as a low viscosity fluid that undergoes gelation in situ upon injection. To this end, HA was conjugated via a linker to poly(N-isopropylacrylamide) (pNIPAM), a thermosensitive polymer using “green chemistry”, with water as the solvent. HA-L-pNIPAM hydrogels showed a comparatively low viscosity (G′ was 105.1 and 233 for Candidate1 and Belotero Volume®, respectively) at room temperature and spontaneously formed a stiffer gel with submicron structure at body temperature. Hydrogel formulations exhibited superior resistance against enzymatic and oxidative degradation and could be administered using a comparatively lower injection force (49 N and >100 N for Candidate 1 and Belotero Volume®, respectively) with a 32G needle. Formulations were biocompatible (viability of L929 mouse fibroblasts was >100% and ~85% for HA-L-pNIPAM hydrogel aqueous extract and their degradation product, respectively), and offered an extended residence time (up to 72 h) at the injection site. This property could potentially be exploited to develop sustained release drug delivery systems for the management of dermatologic and systemic disorders.
Quality Assessment and Classiﬁcation of Feedstock for Bioenergy Applications Considering ISO 17225 Standard on Solid Biofuels

: Biomass materials play a key role in the renewable energy market as they can serve as a suitable alternative to fossil fuels. However, the quality of the material entering bioenergy plants is often a cause of technical concern. Biomass quality assessment is crucial not only for energy characterization but also for environmental and operational aspects. The goal of this study is to characterize and classify the biomasses used by Italian power plants with reference to the quality classes stated by the ISO standard 17225:2021. A further objective is to verify the ability of the standard to classify heterogeneous and speciﬁc biomasses. In this study, more than 900 biomass samples were analyzed. The samples were collected from several Italian power plants with >5 MWe between 2010 and 2020, and the most important physical and chemical parameters were analyzed according to the international standards of reference. The results of the analyses were collected in a large dataset used for subsequent statistical analyses. Statistical analyses applied are Principal Component Analysis and Pearson correlation maps, which showed that the ash content is a fundamental and ideal parameter to assess the biomass quality. Results obtained demonstrate that herbaceous biomasses are of low quality mainly due to the high ash content; a relatively low ash content was found for woody biomasses.
Associations of polygenic risk scores with posttraumatic stress symptom trajectories following combat deployment

Abstract Background Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment. Method US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data. Results Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06–1.43) and 1.18 (1.02–1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01–1.25) and 1.16 (1.04–1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03–1.31)]. No other associations were statistically significant. Conclusions Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.
Synthesis of Brominated Lactones Related to Mycalin A: Selective Antiproliferative Activity on Metastatic Melanoma Cells and Inhibition of the Cell Migration

Starting from D-xylonolactone and D-ribonolactone, several five-membered bromolactones, related to the C1–C5 portion of mycalin A lactone, have been synthesized. The bromination of D-ribonolactone with HBr/AcOH, without a subsequent transesterification step, has been studied for the first time, giving us most of the acetylated lactones investigated in the present study. For each compound, where possible, both the C-3 alcohol and the corresponding acetate were prepared. Evaluation of their anti-tumor activity showed that all the acetates possess a good cytotoxicity towards human melanoma (A375), human cervical adenocarcinoma (HeLa) and human metastatic melanoma (WM266) cancer cells, comparable or even higher than that displayed by the original mycalin A lactone. Lactone acetates derived from D-ribonolactone showed the higher selectivity of action, exhibiting a strong cytotoxicity on all the tested tumor cells but only a limited toxicity on healthy human dermal fibroblast (HDF) cells, used as a control. Wound healing assays showed that two of these substances inhibit the migration of the WM266 cells.
Swift observations of 1RXS J180408.9-342058; return to quiescence

INTEGRAL detected a X-ray burst on April 16, 2012 at a position consistent with the position of an unidentified source 1RXS J180408.9-342058, and tentatively it was assumed that the burst is associated with the same source (Atel # 4050). To further monitor the X-ray activity of the source, we performed a follow-up observation using the Swift satellite. 1RXS J180408.9-342058 was observed using Swift in photon counting mode for an exposure time of 1.3 ks, on April 30, 2012 at UT 19:12.
Combining Data from Airborne Spatially Distributed Modes of Radar Imaging in Small-Sized Airborne Radars

A method has been developed for combining radar data collected in bistatic and monostatic modes of aviation monitoring based on small-sized airborne radars (AR) of a twoposition spatially distributed system implemented on the basis of integrated radar image processing (RI). A spatially distributed system is proposed that implements monostatic and bistatic modes of formation of two radar stations of the observed territory from two different viewing angles. These two modes of radar formation are combined on the basis of the method of combining different-angle radar information, which makes it possible to increase the resolution of the resulting RI being formed, which is impossible to obtain one AR from one angle.
Generalized semi-Markov schemes and open queueing networks

Generalized semi-Markov schemes were devised to give a versatile general model embracing queueing networks and similar systems of practical importance, and they have proved particularly successful in uniting many disparate results on insensitivity. However, it turns out that, although closed queueing networks are expressible as GSMS, open networks are not, and that the insensitivity results for such networks are not therefore strictly within their scope. In this paper, it is shown that, as one might hope, open networks can be realized as limits of a suitable sequence of closed networks in such a way that the insensitivity properties of the GSMS are transferred to the open network in the limit, and thus that open networks too can, in a sense, be considered to be GSMS. However, it appears from the technical nature of the arguments involved that, despite this close relationship between GSMS and open networks, it may nonetheless be simpler to treat them separately when constructing the proofs of theorems.
Design of a Subarray Configuration for Multifunction Radars Using a Nested Optimization Scheme

ABSTRACT An optimization scheme for the design of a subarray configuration applicable to multifunction radars is presented in this article. For the efficient design of the subarray configuration, a genetical swarm optimization is combined with a K-means clustering scheme that partitions antenna elements into homogeneous groups. By utilizing the proposed optimization scheme, an array antenna that consists of 5,120 radiating elements is restructured to 32 subarrays. In addition, optimization of the subarray design was also conducted for two different design cases in which the numbers of elements in the subarrays are both unequal and equal. The subarrays are configured irregularly to avoid the creation of grating lobes in the radiation pattern. The peak sidelobe levels of digitally scanned beams are increased by 4.6 dB on average compared to those without scanning.
Learning Security Awareness in Email Communication Using a Platform for Digital Skill Teaching

Despite emails having been a standard technology since the 1970s, they are still indispensable in daily communication and the number of sent emails continues to rise year by year. This technology is not limited to business, it is also used in education, entertainment, or personal correspondence. Emails are also present in the everyday life of children: they are required to join websites, social networks or to participate in school -especially in homeschooling. However, emails are also associated with disadvantages such as spam, phishing, or malware. To engage children in security awareness we developed the DigiSkill platform, which provides interactive educational experiences. It consists of modules such as email or browser simulations, to increase the student’s digital skills. In this research, we evaluated the tool with 52 secondary school students to observe their knowledge on security awareness in the context of email usage and to help gain a better understanding. Therefore, we conducted an in-class evaluation with a tool intervention and related pre- and post-activities. We observed different characteristics in emails that students use for classification and identified common misconceptions. We found that students follow an intensely visual approach, which means the visual representation of an email has a strong impact on the level of suspicion students have. We aim to provide educators with a tool to improve the security awareness skills of their students and to discuss educational possibilities in this field with our research findings.
LOBIN: In-Network Machine Learning for Limit Order Books

Machine learning is driving the evolution of algorithmic trading, but the demands for fast execution speed remain. Although both aim to increase profitability, embedding more powerful machine learning approaches and lowering trading latencies are hard to achieve simultaneously. Offloading machine learning inference to programmable network devices, also referred to as in-network machine learning, provides a delicate balance between the two ends of this trade-off. In this paper, we present LOBIN, providing machine learning based market prediction using high-frequency market data feeds. LOBIN builds limit order books and conducts inference within programmable switches. Compared with server-based solutions, LOBIN predicts future stock price movements with lower latency, higher throughput, and a minor impact on machine learning performance.
Depth-integrated equations for entraining granular flows in narrow channels

Abstract Flowing over erodible beds, channelized granular avalanches can alter their volume by entraining or detraining basal grains. In detail, entrainment results from a gradual adjustment of stress and velocity profiles over depth, bringing bed material past yield (and vice versa for detrainment). To capture this process, we propose new depth-integrated equations that balance kinetic energy in addition to mass and momentum. The equations require a local granular rheology, assumed viscoplastic, but no extra erosion law. Entrainment rates are instead deduced from the depth-integrated layer dynamics. To check the approach, we obtain solutions for non-equilibrium heap flows, and compare them with experiments conducted in a seesaw channel.
A Note on Completely and Absolutely Monotone Functions

Abstract The solutions of a certain class of first order linear differential equations are shown to be either completely or absolutely monotone depending on the nature of its coefficients. This is a simple theorem which is used to deduce a number of new and interesting results dealing with the complete and absolute monotonicity of functions. In particular, a partial answer is supplied to a question posed by Askey and Pollard: “When is completely monotone? ”
Investigating The Factors That Influence Kazakh Female Students' Interest In STEM Careers Using Machine Learning Techniques

The underrepresentation of women in STEM fields is a global problem that demands urgent attention, and Kazakhstan is no exception. Despite efforts to close the gender gap in STEM education, only 32% of undergraduate students in Kazakhstan's STEM programs are female, indicating that more needs to be done to address this issue. To tackle this problem, a groundbreaking study was conducted using machine learning techniques to analyze a dataset of female high school students in Kazakhstan. The innovative use of machine learning allowed the researchers to extract patterns and identify the most influential factors that shape Kazakh female students' interest in STEM careers. This is a step forward in the field, as the use of machine learning to address this issue is rare. The study's findings highlighted the importance of self-efficacy, parental support, and the availability of role models in STEM fields as key factors that influence Kazakh female high school students' interest in STEM careers. Based on these findings, programs that focus on increasing self-efficacy, parental involvement and support, and exposure to successful STEM professionals and role models can be implemented to encourage more female students to pursue STEM careers.
Ground state solutions for semilinear time-harmonic Maxwell equations

This paper is concerned with the time-harmonic semilinear Maxwell equation: ∇ × (∇ × u) + λu = f(x, u) in Ω with the boundary condition ν × u = 0 on ∂Ω, where Ω ⊂ ℝ3 is a simply connected, smooth, bounded domain with connected boundary and ν : ∂Ω → ℝ3 is the exterior normal. Here ∇ × denotes the curl operator in ℝ3 and the boundary condition holds when Ω is surrounded by a perfect conductor. By using the generalized Nehari manifold method due to Szulkin and Weth [Handbook of Nonconvex Analysis and Applications (International Press, Somerville, 2010), pp. 597–632] and some new techniques, existence of ground state solutions for above equation is established under some generic conditions on f.
Two-Factor Commissioning for Thread Protocol

Thread is a wireless protocol built based on the IEEE 802.15. 4 standard to enable IPv6-based, low-power, and reliable mesh topology for IoT systems. Thread commissioning allows new IoT devices to join the network by validating their credentials. Security of the commissioning process is crucial because it is the gateway to entering the Thread network. Its vulnerabilities could affect the entire IoT system and cause physical and financial damage. Literature review and vulnerability assessments point to the possible security risks on commissioning, such as credentials leakage, password-guessing attacks, and infringement of counterfeit devices through Datagram Transport Layer Security (DTLS) handshake. To mitigate the security threats, we proposed QR code encryption and additional layers of authentication with one-time random keys and login attempts controller in commissioning. The proposed solutions were analysed with different security test cases and proved that they could restrict the counterfeit devices from establishing DTLS communication and slow down password-guessing attacks.