Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence Of Malaria Among Blood Donors in The National Center for Blood Transfusion and Research in Sana’a Yemen

Background: Malaria has been killing millions of people worldwide. World Health Organization estimates that there are 300 million to 500 million of people infected with malaria. Therefore, the aim of this study is to explore the prevalence of malaria parasites among the blood donors attending the National Center for Blood Transfusion and Research in Sana’a, Yemen over a period of 6 months. Methods: Data collected from the National Center for Blood Transfusion and Research records for the year of 2012 and 2020. Secondary data were taken from 12.000 donors from 2012 and 18,000 from 2020. The records contain the patient’s number, blood bag, type of examination: cassette and confirmatory tests such as ELISA and type of malaria test. Results: In 2020, there were 814 Malaria-infected blood donors (97.8%), whereas, in 2012, there were only18 Malariainfected blood donors (2.2%). The male donors more infected (99.2%) than female donors (0.8%). The number of donors with blood group O+ were the highest infected people (50.4%), while the least infected donors is AB- (0.1%). The number of infected people with Plasmodium falciparum (24%) is the highest compared with other types of malaria (4%). The most packed cell volume (PCV) ratio among donor was 49%, the lowest PCV ratio in donors is 95% and 60% respectively. Conclusion: The study showed that the war played a significant role in increasing the number of people suffering from malaria and that the situation is worsening due to lack of awareness, migration and weak economic conditions.
Oscillatory Characteristics of Shallow Open Cavities in Supersonic Flow

Numerical simulations and experiments were carried out to investigate the unsteady flow in a two-dimensional rectangular open cavity with emphasis on the effects of length-to-depth ratio on the shear-layer development and cavity drag. The cavity was exposed to a supersonic flow of Mach 2. The results of the simulations were compared and analyzed with experimental data. Detailed predictions of flow features and frequencies showed a good agreement with the experiments. Particularly, the results indicated how the cavity flowfield changes when the length-to-depth ratio of the cavity is changed. Below a certain value of length-to-depth ratio, self-sustained periodic oscillations are strong and coherent, and the cavity drag is low. Beyond this value, the oscillations are weak, frequencies are mostly broadband, and the drag is high. This transition was found to occur for a cavity of length-to-depth ratio of 5. The investigation has also explored features of cavity shear-layer development, hitherto unexplained, a.
Short-range visible light ranging and detecting system using illumination light emitting diodes

A visible light object ranging and detecting system utilising light emitting diodes (LEDs) is proposed and investigated. The LEDs are used not only as illuminating devices but also as ranging and detecting sensors. LED is intensity modulated with a predetermined sinusoid signal at a certain frequency with an initial phase. After propagation, the backscatter signals from the object are received and detected. The direction of the object is estimated by an optical imaging receiver. The distance between the object and the LED is obtained based on a differential phase-shift measurement. The theoretical model of the system is derived and evaluated, and the fundamental channel characteristics of the proposed system are simulated and analysed. The numerical results show that with a proper design, the presence or position of an object can be identified with a detection range of up to ~6 m, with an estimation error as small as ~5 cm for the system employing commercially available illumination LEDs.
Reinforcement Learning Approach for SF Allocation in LoRa Network

LoRa technology is widely used to build wireless networks in various Internet of Things (IoT) applications. As the increased popularity of IoT, LoRa also gains tremendous attention in recent years. In most of the LoRa networks, the Aloha protocol is employed to send packets which may easily lead to collisions. Thanks to the orthogonality of spreading factor (SF) in modulate technique, a potential solution is obtained for this collision issue in the LoRa network. In this study, a reinforcement learning (RL)-based method called LR-RL is proposed to assign SF properly to alleviate collisions. The idea of LR-RL is mainly derived from the mathematical model of SF-channel traffic equilibrium, which indicates that SF with higher data rate must undertake more packet loads. Based on the system model, several similar methods, such as LR-opt-pro, LR-greedy, and LR-RL, are put forward successively. The LR-RL algorithm owns the best performance in terms of packet collision rate (PCR). In addition, we carry out simulations to evaluate the performance of LR-RL in both one-hop and LoRa-Mesh networks. Results show that LR-RL has lower PCR than other SF allocation methods. Moreover, practical experiments are also conducted to verify the performance. All the experiments exhibit that LR-RL is a desirable method to reduce packet collisions in the LoRa network.
Extremely Accurate, Generic and Tractable Exponential Bounds for the Gaussian Q Function With Applications in Communication Systems

In this letter, we apply the Fejer’s Rule of interpolatory integration in a modified manner to obtain a very generic, tractable and extremely accurate approximation for the Gaussian <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> function. We further show the utility of the proposed approximation by simplifying the error performance metrics like average symbol error probability (ASEP) of popular digital modulation techniques over a very useful <inline-formula> <tex-math notation="LaTeX">$\kappa -\mu $ </tex-math></inline-formula> shadowed fading channel. This eliminates the need of mathematical softwares which require very high processing power (a constraint at the receiver side) yielding simplified and cost effective receiver’s design. In addition, an insight on the asymptotic ASEP (and diversity order thereof) is also highlighted in this letter.
The CoralHydro2k database: a global, actively curated compilation of coral δ18O and Sr ∕ Ca proxy records of tropical ocean hydrology and temperature for the Common Era

Abstract. The response of the hydrological cycle to anthropogenic climate change, especially across the tropical oceans, remains poorly understood due to the scarcity of long instrumental temperature and hydrological records. Massive shallow-water corals are ideally suited to reconstructing past oceanic variability as they are widely distributed across the tropics, rapidly deposit calcium carbonate skeletons that continuously record ambient environmental conditions, and can be sampled at monthly to annual resolution. Climate reconstructions based on corals primarily use the stable oxygen isotope composition (δ18O), which acts as a proxy for sea surface temperature (SST), and the oxygen isotope composition of seawater (δ18Osw), a measure of hydrological variability. Increasingly, coral δ18O time series are paired with time series of strontium-to-calcium ratios (Sr/Ca), a proxy for SST, from the same coral to quantify temperature and δ18Osw variability through time. To increase the utility of such reconstructions, we present the CoralHydro2k database, a compilation of published, peer-reviewed coral Sr/Ca and δ18O records from the Common Era (CE). The database contains 54 paired Sr/Ca–δ18O records and 125 unpaired Sr/Ca or δ18O records, with 88 % of these records providing data coverage from 1800 CE to the present. A quality-controlled set of metadata with standardized vocabulary and units accompanies each record, informing the use of the database. The CoralHydro2k database tracks large-scale temperature and hydrological variability. As such, it is well-suited for investigations of past climate variability, comparisons with climate model simulations including isotope-enabled models, and application in paleodata-assimilation projects. The CoralHydro2k database is available in Linked Paleo Data (LiPD) format with serializations in MATLAB, R, and Python and can be downloaded from the NOAA National Center for Environmental Information's Paleoclimate Data Archive at https://doi.org/10.25921/yp94-v135 (Walter et al., 2022).
The Role of CSR Disclosure as Moderation on the Relationship between Environmental Performance and Corporate Financial Performance

This paper presents an analysis of the literature concerning whether environmental performance can improve financial performance of Manufacturing Companies in the Miscellaneous Industry Participating in Performance Rating Rating Program in Environmental Management PROPER. Then look at the extent to which the role of corporate social responsibility (CSR) can strengthen the relationship between environmental performance and financial performance of companies in the manufacturing sector and various industries. The sample we use in this study are manufacturing companies in the Miscellaneous Industry listed in the Indonesia Stock Exchange (IDX) and participating in PROPER for the 2016-2019 period with 16 observations. In conducting data analysis, we applied WarpPLS version 7.0 software which will evaluate the outer model and inner model. The company's financial performance variables are measured using the return on equity (ROE) and net profit margin (NPM) ratios, while the environmental performance variable is measured using the PROPER rating and CSR is measured by the CSR index. The provisional assumption of this study shows that (1) environmental performance cannot improve the financial performance of companies in the manufacturing sector and various industries, (2) CSR disclosure is not able to strengthen the relationship between environmental performance and the financial performance of companies in the manufacturing sector and various industries.
Event-Triggered Prespecified Performance Control for Steer-by-Wire Systems With Input Nonlinearity

This paper addresses the prescribed tracking performance control problem for uncertain steer-by-wire (SbW) systems with input nonlinearity (including dead-zone and actuator fault) and the limitation of controller-area-network (CAN) bandwidth. An adaptive interval type-2 fuzzy logic system (IT2 FLS) is introduced to approximate the lumped model uncertainty, and a switching event-triggering mechanism (ETM) is applied to save the communication resources. Combining the backstepping approach and barrier Lyapunov function techniques, a prescribed tracking performance control method is proposed for SbW systems, where the initial values of state errors are no longer required in the controller design. Theoretical analysis shows that the tracking error can converge to the predefined residual set within preset time instead of the time tending infinite, while the closed-loop system is semi-globally stable. Simulations and vehicle experiments are presented to verify the effectiveness of the proposed control method.
Assessment of Behavioral Impacts and Socio-Economic Status stand of Blockchain Games to Undergraduate Students in Metro Manila

Virtual Economies continue to be a global phenomenon, and cryptocurrency is prominent in this process, and it can be attained by playing blockchains. The rise of non-fungible tokens (NFTs) is also increasing the demand for Ethereum. Thus, these features encourage many people to earn money while playing it that even young people (most likely undergraduate students) invest. There is no doubt that it is a good business for financial risk and problems, it also provides much more significant opportunities and applications. Somehow the notions of blockchain technology provides some negative outcomes, specifically in the behavioral aspects of them. In this paper, the researchers focused on socioeconomic status and behavioral aspects of the players and considered these two as the factors in their perspective about the blockchain games. The results on socioeconomic shows that most of them are playing because of financial problems and sees this as an opportunity to have an income. The results on Behavioral impacts through pareto analysis shows that most respondents suffer from the negative impact of playing blockchain games, 66% of the respondents has lack of sleep, 53.5% less focus in studies, 39.5% less interactive and more. Tukey method is also use to analysis whether which questions is significantly important in terms of obtaining and analysis the results from the survey conducted. In conclusion the socioeconomic stand is likely to affect their perspective in the blockchain games and shows that these games can lead to addiction because of the time spend in playing, the anxiety with the game and other negative outcomes.
Quantitative analysis of Cr in soil using laser induced breakdown spectroscopy combined with relevance vector machine method

The laser induced breakdown spectroscopy (LIBS) technology coupled with a principal component analysis and relevance vector machine (PCA-RVM) was used for rapidly detect the concentration of heavy metal Cr in soil. The PCA-RVM was obtained by optimizing the relevance vector machine (RVM) with PCA.LIBS spectrum of 14 soil samples with different concentration of elements were collected and used for the model training and prediction. 10 of those were selected as training sample sets to build the PCA-RVM model, and the others as test sample sets for model evaluation. Comparing with the prediction results of PCA-RVM model with that obtained using RVM and support vector machines (SVM) model, the analytical accuracy improved by 84.17% to RVM and 92.62% to SVM at the maximum, respectively. Indicating that the PCA-RVM model can effectively improve the detection accuracy and repeatability of LIBS analysis of elemental concentration in soil.
SERS performance of silver nanoparticle/reduced graphene oxide-coated filter membranes

Abstract Polyvinylidene fluoride (PVDF), polyamide (Nylon) and anodic aluminum oxide (AAO) filter membranes were coated with in-situ synthesized silver nanoparticle/reduced graphene oxide (AgNP/rGO) nanocomposite by vacuum filtration, and surface-enhanced Raman scattering (SERS) performance of the prepared substrates was investigated using Rhodamine 6G (R6G) as a probe molecule. Analyte solutions were applied by drop casting and penetrated into the flexible PVDF and Nylon-based substrates within minutes, enabling very fast SERS measurements; however, this step took up to 2 hrs in the rigid AAO-based substrate. Scanning electron microscopy and Energy-dispersive X-ray spectroscopy mapping results showed that filter membrane surfaces were completely covered with AgNP/rGO nanocomposite at which AgNPs were uniformly distributed on rGO flakes; however, some large, partially reduced or unreduced GO flakes decorated with AgNP agglomerates (AgNP/GO) were also observed. Higher SERS signals were generally obtained from these AgNP/GO flakes compared to the AgNP/rGO coated regions, since they contain higher amount of oxygen-rich functional groups which enabled a higher chemical and electromagnetic enhancement in SERS signals. All the substrates could detect 10−7 M R6G even after being stored in a vacuum desiccator for 3 months, indicating that AgNP/rGO coated filter membranes are promising as stable SERS substrates thanks to their long shelf life.
In Vitro and In Vivo Improvement of Islet Quality and Transplantation Successes following Islet Treatment with Biomaterials in Diabetic Rats

Background Loss of islet survival and function, caused by native niche disruption and oxidative stress induction during mechanical and enzymatic isolation, limits the effectiveness of islet transplantation. Reconstitution of islet microenvironment, vascularization, and decreased oxidative stress with biomaterials may improve islet quality and graft outcomes. We investigated effects of two biomaterials, platelet-rich plasma and pancreatic islets homogenate combination on islet recovery and quality by evaluating in vitro islet survival, secretory function, and oxidative stress parameters and assessing in vivo transplantation outcomes. Methods In vitro, islet viability and secretory function of isolated islets were assessed after 24 h and 72 h incubation with biomaterials. Also, oxidative stress markers were measured once after isolation and 24 h after incubation with biomaterials. For evaluating in vivo effects, cultured islets for 24 h were transplanted into subscapular space of diabetic rat kidney, and outcomes were analyzed by measuring serum glucose and insulin concentrations, glucose tolerance test, level of oxidative parameters, and pancreatic gene expression. Results Treating islets with biomaterials significantly increased their viability and secretory function, reduced MDA level, and elevate SOD and CAT activity. Decreased level of glucose and MDA improved insulin level, increased SOD activity, and also enhanced pdx1 and insulin gene expression in diabetic rats after islet transplantation. Conclusions Biomaterials used in the present study should be consider as beneficial materials for increasing islet transplantation outcome. These materials may hamper transplantation limitation to some extent.
Diagnosis of observation, background and analysis‐error statistics in observation space

Most operational assimilation schemes rely on linear estimation theory. Under this assumption, it is shown how simple consistency diagnostics can be obtained for the covariances of observation, background and estimation errors in observation space. Those diagnostics are shown to be nearly cost‐free since they only combine quantities available after the analysis, i.e. observed values and their background and analysis counterparts in observation space. A first application of such diagnostics is presented on analyses provided by the French 4D‐Var assimilation. A procedure to refine background and observation‐error variances is also proposed and tested in a simple toy analysis problem. The possibility to diagnose cross‐correlations between observation errors is also investigated in this same simple framework. A spectral interpretation of the diagnosed covariances is finally presented, which allows us to highlight the role of the scale separation between background and observation errors. Copyright © 2005 Royal Meteorological Society
On the Statistical Performance of the Generalized Power Method for Angular Synchronization

The problem of angular synchronization with its numerous applications has attracted intense research recent years. Motivated by its optimal estimation error in the sense of Cram\'er-Rao inequality, two approaches have been recently developed to compute the maximum likelihood estimator. One is the semidefinite relaxation and the other is to directly solve the non-convex maximum likelihood optimization by the \emph{generalized power method}. In this paper, we focus on the latter and take a new perspective by directly studying the estimation error of the iterates. We show that the $\ell_2$- and $\ell_\infty$-errors decrease geometrically as the algorithm proceeds. In particular, the $\ell_2$-error decreases to the Cram\'er-Rao lower bound, under the least restrictive noise level requirement compared with prior works.
Obstruction primaire à la déformation

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Gender climate in rheumatology peer review

Gender climate in rheumatology peer review Renil Sinu Titus, Pavel Ovseiko , Lisa Traboco , Tayyeba Khursheed , Latika Gupta * Seth G.S. Medical College and K.E. M. Hospital, Acharya Donde Marg, Parel, Mumbai, India Radcliffe Department of Medicine, University of Oxford, Oxford, UK Department of Medicine, Section of Rheumatology, St. Luke’s Medical Center-Global City, Taguig, Philippines Department of Rheumatology, Pakistan Institute of Medical Sciences, Islamabad, Pakistan Department of Rheumatology, Royal Wolverhampton Trust, Wolverhampton, UK City Hospital, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK Division of Musculoskeletal and Dermatological Sciences, Centre for Musculoskeletal Research, School of Biological Sciences, University of Manchester, Manchester, UK *Correspondence to: Latika Gupta, Department of Rheumatology, Royal Wolverhampton Trust, Wolverhampton WV10 0QP, UK. E-mail: drlatikagupta@gmail.com R.S. T. and P.O. contributed equally.
Robust 600 V GaN high electron mobility transistor technology on GaN-on-Si with 400 V, 5 µs load-short-circuit withstand capability

A 600 V normally-ON GaN high-electron mobility transistor (HEMT) technology with an intrinsic specific ON resistance Ron · A = 500 mΩ·mm2 and a breakdown voltage of BVdss ∼ 1100 V is described. A novel high-power 30-A-class GaN-Si MOSFET cascode device with a back-side source Si laterally diffused MOSFET (LDMOSFET) and an embedded clamp diode are employed to enable the GaN HEMT to withstand 400 V and a more than 5 µs load short circuit condition, as required in switching inverter applications. Considerations for improvement of the GaN lateral HEMT short-circuit withstand capability are addressed.
Approach of shot-boundary detection based on texture and histogram feature fusion

The shot change detection is a basic and important technology in video retrieval.There are some basic algorithms for detecting abrupt shot change in digital video,including the template-matching algorithm,the histogram algorithm,etc.,but they cannot always attain high precision in practical detecting.Hence,an approach of shot-boundary detection by fusing feature was proposed.HSV histogram is a common and effective method for shot boundary detection.In this paper,texture analysis was obtained by wavelet transformation and then was integrated with the HSV histogram.Finally,the shots were detected by the technology of a sliding window.Experimental result shows that this proposed approach can detect abrupt shot effectively and has a satisfied result in gradual shot transition detection.
Health effects of ionising radiation in paediatrics undergoing either cardiac fluoroscopy or modern radiotherapy (The HARMONIC project)

The use of ionising radiation (IR) for medical diagnosis and treatment procedures has had a major impact on the survival of paediatric patients. Although the benefits of these techniques lead to efficient health care, evaluation of potential associated long-term health effects is required. HARMONIC aims to better understand the increased risk of cancer and non-cancer effects after exposure to medical IR in children with cancer treated with modern external beam radiotherapy (EBRT) – radiation energy in MeV range – and in children with cardiac defects diagnosed and treated with cardiac fluoroscopy procedures (CFP) – radiation energy in keV range. The project investigates, among survivors of paediatric cancer, potential endocrine dysfunction, cardiovascular and neurovascular damage, health-related quality of life and second (and subsequent) primary cancer (SPC). The cardiac component builds a pooled cohort of approximately 90 000 paediatric patients who underwent CFP during childhood and adolescence to investigate cancer risk following exposure to IR and explore the potential effects of conditions predisposing to cancer. HARMONIC develops software tools to allow dose reconstruction in both EBRT and CFP to enable epidemiological investigations and future optimisation of treatments. With the creation of a biobank of blood and saliva samples, HARMONIC aims to provide a mechanistic understanding of radiation-induced adverse health effects and identify potential biomarkers that can predict these effects.