Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Stroke Burden in Ghana: A Comprehensive Systematic Review Protocol

IntroductionThere is a lack of data summarizing the current burden of stroke in Ghana. The establishment of data on the current burden, incidence, and mortality of stroke in this country may guide decision-making toward interventions to curb the stroke burden. This protocol aims to describe the methods for a systematic review of the literature on the incidence, prevalence, and mortality of strokes in Ghana.Methods and Design We will perform a comprehensive search strategy of relevant abstracts and articles published from 1st May 2013 to 31st May 2020, related to prevalence or incidence or mortality in Ghana. Relevant articles will be searched from electronic databases including MEDLINE (PubMed), CINAHL (EBSCO), Web of Science, and PsycINFO (EBSCOhost). Full text of eligible studies will be included if they estimated one of the following epidemiological measures: burden, incidence and mortality. Studies that will meet the eligibility criteria will be assess for overall study quality, reliability and risk of bias, using design-specific criteria. We will appraise the included studies' reporting and methodology quality and perform a quantitative summary of reported outcomes where applicable.DiscussionExisting knowledge on the incidence or prevalence, or mortality of strokes in Ghana are limited. This review aims to present relevant information that will inform local policy on cardiovascular diseases and future research. The final report of this protocol, in the form of a scientific paper, will be published in a peer-reviewed journal and findings will be submitted to relevant health authorities. We also plan to update the review in the future to monitor changes and guide health service and policy solutions.Trial registration number: https://doi.org/10.17605/OSF.IO/MW3H8
Energy-Efficient Co-Design of Power Scheduling for State Estimation Over a Stochastic Delayed Network

In this article, the scheduling problem over a delayed network is investigated. Different from the existing literature, we propose a hybrid stochastic model which incorporates both delay and packet loss. Based on this proposed model, an energy-efficient co-design problem is considered under power-limited scenarios. A global optimal offline solution is presented explicitly. Aided by arriving information feedback, we propose an online schedule based on an absolute threshold. The optimality of our proposed schemes and thresholds selection is theoretically analyzed. Meanwhile, we have extended the conclusions of the single-system case to the multisystem case. Optimal strategies from both offline and online perspectives are provided with rigorous proof, respectively. The stability condition is given for the estimator to converge in an infinite-time horizon. The comparisons between offline and online strategies are proved the global superiority of the online strategy to the offline one. Numerical simulations have validated the correctness and superiority of our proposed algorithms.
Nonoverlapped Sampling for Hyperspectral Imagery: Performance Evaluation and a Cotraining-Based Classification Strategy

For hyperspectral imagery (HSI) classification, most of the studies focus on how to improve the classification accuracy, while the influence of sampling strategy for classification performance attracts little attention. For now, random sampling (RS) is the most adopted strategy. That is, for a hyperspectral image, a certain number of labeled samples are randomly selected as the training set, and the remaining labeled samples are taken as the test set. However, the RS strategy will produce over optimistic results when used for performance evaluation because of the overlap between training set and test set. Though spectral-spatial classification methods benefit most from the RS strategy, the pixel-wise classification methods can also benefit from it because of the high spectral correlation between training and test samples. However, in practical applications, the RS strategy is not feasible. Because the training and test samples are often collected from different locations. In this situation, the correlation between training and test samples will decrease dramatically and the performance of HSI classification methods will be affected. In this article, a nonoverlapped sampling method is adopted to reduce the correlation between training and test samples and different classic classification methods are evaluated. Experimental results show that the classification performance of all methods drops a lot when nonoverlapped sampling strategy is adopted. After the analysis of some important factors for HSI classification, we also propose a cotraining-based classification method to relief the influence of sampling strategy and obtains much better performance compared with those classic spectral-spatial classification methods.
All-Polarized Wideband Rectenna With Enhanced Efficiency Within Wide Input Power and Load Ranges

The efficiency of a rectenna varies under the influences of receiving polarization tilt angle, operating frequency, input power, and load value in different applications. Yet, no reported rectenna can realize stable efficiency when all these factors vary within a wide range. To solve this problem, an all-polarized rectenna is proposed in this article, composed of a dual-input rectifier and a dual-polarized (DP) antenna. By introducing a novel six-port coupler, the rectifier maintains stable efficiency at wideband, wide input power, and dc load ranges. Moreover, the efficiency of the rectifier keeps stable when the antenna receives power at different polarization tilt angles. Accordingly, a DP antenna with extended bandwidth and 3-dB beamwidth is implemented. Finally, the rectenna is formed. The prototype can maintain beyond 70% of the peak efficiency from 1.7 to 2.5 GHz. At a power density as low as 1 μW/cm2, efficiency can reach 24.4%. Furtherly, the rectenna is demonstrated by forming a battery-less digital clock. The clock can be powered wirelessly by a WiFi router or cellular base station with maximum distances of 1 or 70 m respectively. Besides, the clock can successfully function under significant transmitting-direction deviation or polarization misalignment between the power source and the rectenna.
The effect of lactate/albumin ratio on mortality in patients with sepsis

The aim of study was to evaluate the lactate/ albumin ratio, procalcitonin (ProCT) and C reactive protein (CRP) levels in patients with sepsis. For the study, 207 patients with sepsis who were treated in intensive care between January 1st, 2016 and January 1st, 2021 were analyzed retrospectively. The patients’ age, sex, diagnosis for hospitalization, lactate levels during the admission (lactate 1) and discharge (lactate 2), CRP, ProCT and albumin, levels registered in patients’ files were recorded from the hospital automation system and their effect on the mortality was statistically analyzed. The patients were grouped as those aged older than 65 and younger than 65, and those with and without mortality. The study included 207 patients diagnosed with sepsis (96 female, 111 male). ProCT levels were found significantly higher in the group older than 65 in the present study. In this study, according to the data obtained, there was no difference in lactate1/albumin and lactate2/albumin ratio in terms of age groups and sex. However, lactate1/albumin and lactate2/ albumin ratio were significantly higher in the group with mortality than the group without mortality. According to our ROC analysis results; The AUC for lactate1, lactate2, lactate1/albumin and lactate2/albumin ratio was 0.649, 0.680, 0.690, 0.771, respectively. The lactate/albumin ratio is a readily available parameter with consistently better prognostic performance than initial serum lactate for in-hospital mortality in adult patients with sepsis. Raised lactate/ albumin ratio showed significant association with increased mortality in patients with sepsis.
Antibacterial Effects of Crude Lectin Fraction Bioactive Compound of Red Macroalgae P. palmata and H. glandiforme from Southern Coast Java Island, Gunungkidul, Yogyakarta, Indonesia

Lectins or carbohydrate-binding proteins, are widely distributed in nature and also good candidates in such prospecting of algae. It may have been considered that binding specificity of lectins to some carbohydrates provokes to produce many unique biological activities, including cell agglutination, mitogenic activity, antibacterial activity and antitumor activity. The aim of this study was to determine the antibacterial effect of crude lectins fractions from red macro algae collected from the southern coast of Java island, Gunung Kidul Regency, Yogyakarta Indonesia. The.Crude lectin fraction showed no antibacterial activity against gram-negative bacteria because most of bacteria cells surface contain of mannan glycoprotein and the sample has no specificity to bind this glycoprotein type. Crude lectin fraction tested also have no antibacterial effect aginst gram positife bacteria because only binding specifically to N-glycan specifically as well as O-glycan.
Identifying Inorganic Turbidity in Water Samples as Potential Loss Factor During Nucleic Acid Extraction: Implications for Molecular Fecal Pollution Diagnostics and Source Tracking

Molecular diagnostic methods are increasingly applied for food and environmental analysis. Since several steps are involved in sample processing which can affect the outcome (e.g., adhesion of DNA to the sample matrix, inefficient precipitation of DNA, pipetting errors and (partial) loss of the DNA pellet during DNA isolation), quality control is essential at all processing levels. In soil microbiology, particular attention has been paid to the inorganic component of the sample matrix affecting DNA extractability. In water quality testing, however, this aspect has mostly been neglected so far, although it is conceivable that these mechanisms have a similar impact. The present study was therefore dedicated to investigate possible matrix effects on results of water quality analysis. Field testing in an aquatic environment with pronounced chemo-physical gradients [total suspended solids (TSS), inorganic turbidity, total organic carbon (TOC), and conductivity] indicated a negative association between DNA extractability (using a standard phenol/chloroform extraction procedure) and turbidity (spearman ρ = −0.72, p < 0.001, n = 21). Further detailed laboratory experiments on sediment suspensions confirmed the hypothesis of inorganic turbidity being the main driver for reduced DNA extractability. The observed effects, as known from soil samples, were also indicated to result from competitive effects for free charges on clay minerals, leading to adsorption of DNA to these inorganic particles. A protocol modification by supplementing the extraction buffer with salmon sperm DNA, to coat charged surfaces prior to cell lysis, was then applied on environmental water samples and compared to the standard protocol. At sites characterized by high inorganic turbidity, DNA extractability was significantly improved or made possible in the first place by applying the adapted protocol. This became apparent from intestinal enterococci and microbial source tracking (MST)-marker levels measured by quantitative polymerase chain reaction (qPCR) (100 to 10,000-fold median increase in target concentrations). The present study emphasizes the need to consider inorganic turbidity as a potential loss factor in DNA extraction from water-matrices. Negligence of these effects can lead to a massive bias, by up to several orders of magnitude, in the results of molecular MST and fecal pollution diagnostics.
Entropy-based network traffic anomaly classification method resilient to deception

Entropy-based network traffic anomaly detection techniques are attractive due to their simplicity and applicability in a real-time network environment. Even though flow data provide only a basic set of information about network communications, they are suitable for efficient entropy-based anomaly detection techniques. However, a recent work reported a serious weakness of the general entropy-based anomaly detection related to its susceptibility to deception by adding spoofed data that camouflage the anomaly. Moreover, techniques for further classification of the anomalies mostly rely on machine learning, which involves additional complexity. We address these issues by providing two novel approaches. Firstly, we propose an efficient protection mechanism against entropy deception, which is based on the analysis of changes in different entropy types, namely Shannon, R? nyi, and Tsallis entropies, and monitoring the number of distinct elements in a feature distribution as a new detection metric. The proposed approach makes the entropy techniques more reliable. Secondly, we have extended the existing entropy-based anomaly detection approach with the anomaly classification method. Based on a multivariate analysis of the entropy changes of multiple features as well as aggregation by complex feature combinations, entropy-based anomaly classification rules were proposed and successfully verified through experiments. Experimental results are provided to validate the feasibility of the proposed approach for practical implementation of efficient anomaly detection and classification method in the general real-life network environment.
Adaptive Multi-Scale HyperNet with Bi-Direction Residual Attention Module for Scene Text Detection

Scene text detection is an important step in the scene text reading system. There are still two problems during the existing text detection methods: (1) The small receptive of the convolutional layer in text detection is not sufficiently sensitive to the target area in the image; (2) The deep receptive of the convolutional layer in text detection lose a lot of spatial feature information. Therefore, detecting scene text remains a challenging issue. In this work, we design an effective text detector named Adaptive Multi-Scale HyperNet (AMSHN) to improve texts detection performance. Specifically, AMSHN enhances the sensitivity of target semantics in shallow features with a new attention mechanism to strengthen the region of interest in the image and weaken the region of no interest. In addition, it reduces the loss of spatial feature by fusing features on multiple paths, which significantly improves the detection performance of text. Experimental results on the Robust Reading Challenge on Reading Chinese Text on Signboard (ReCTS) dataset show that the proposed method has achieved the state-of-the-art results, which proves the ability of our detector on both particularity and universality applications.
Network Coding for K-Repetition in Grant-Free Random Access

In this work, we consider reliable transmissions for grant-free random access (GFRA) when machine-type communication (MTC) devices have a message of multiple short data packets to transmit. An existing approach is based on <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula>-repetition for reliable transmissions. In order to improve the reliability, a random network coding based scheme is proposed, where each device in GFRA employs random network coding to transmit packets that are linear combinations of its original packets. To shed light on the performance behaviors of the conventional <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula>-repetition and proposed schemes, we derive their error probabilities and provide an indicative analysis. Simulation results validate our derivations and show that the proposed scheme by exploiting random network coding can perform significantly better than conventional <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula>-repetition one.
Analisis Model Faktor Kualitas Functional Suitability dan Security pada Sistem Informasi Payroll

Pemberian gaji merupakan salah satu bentuk kompensasi yang diberikan kepada pegawai yang telah melaksanakan tugas dan kewajibannya pada suatu pekerjaan. Pemberian gaji dilakukan secara rutin oleh suatu organisasi, bersifat kritikal dan sensistif. Oleh karenanya diperlukanlah suatu system yang dapat mengolah data penggajian dengan benar. System penggajian ini dikenal dengan system informasi payroll. Karena system ini akan digunakan terus menerus pada organisasi sehingga perlu diperhatikan kehandalannya dari berbagai aspek seperti kelengkapan fungsionalnya, kebenaran informasi dan komputasi yang dihasilkan, serta aspek keamanan dari aplikasi tersebut. Salah satu cara yang dapat dilakukan adalah dengan melakukan evaluasi terhadap kualitas dari system informasi payroll yang telah dibangun. Untuk melakukan evaluasi tersebut dibutuhkanlah suatu model kualitas untuk mengevaluasi system informasi payroll. Berdasarkan analisis yang telah dilakukan berdasarkan kriteria system informasi payroll dan model kualitas International Organization for Standardization and International Electrotechnical Commision 25010(ISO/IEC 25010) Product Quality Model, diperolehlah hasil berupa model kualitas untuk factor kualitas functional suitability dan security pada system informasi payroll. Setiap factor kualitas yang diusulkan juga terdapat kriteria yang dapat digunakan untuk mengevaluasi setiap factor kualitas tersebut. Selain itu diperoleh juga bahwa seluruh sub factor functional suitability dan security memberikan pengaruh signifikan pada system informasi payroll sehingga termasuk kedalam kriteria yang telah diusulkan
Improving Sakura Block Quality as Feed Supplement to Optimize Rumen Fermentation Products and Nutrients Digestibility In Vitro

| The purpose of this research was to formulize the best sakura block enriched with earthworm flour by utilizing palm kernel cake as a substitute for corn in optimizing rumen fermentation products and nutrient digestibility in vitro. This research used a completely randomized design with 6 treatments and 3 replications namely the commercial sakura block as control (P0), and sakura block with palm kernel cake and earthworm flour of 0% (P1), 2% (P2), 4% (P3), 6% (P4) and 8% (P5). Result: The findings of the study showed that the higher the earthworm flour in the sakura block, the higher the crude protein content and the total digestible nutrient of the sakura block. However, optimal NH 3 , VFA, acetate, propionate, and butyrate were obtained in the treatment of sakura block with palm kernel cake and 6% earthworm flour. Although the average digestibility of dry matter, organic matter, and protein in vitro in the research was quite high, there was no difference between treatments. It was concluded that sakura block with palm kernel cake and 6% earthworm flour resulted in the best to optimize rumen fermentation products.
Comparison of neutrophil CD64 and monocytic HLA-DR with existing biomarkers for the diagnosis and prognosis of sepsis

Background We measured the expression of serum procalcitonin (PCT), quantitative C-reactive protein (QCRP), neutrophil CD64 (nCD64) and monocytic HLA-DR (mHLA-DR) sequentially in patients admitted to the intensive care unit (ICU) and correlated the expression of these biomarkers to predict development of sepsis and its outcome. Methods Consenting adult patients of more than 18 years of age, who developed sepsis during an observation period of 20 days with a sequential organ failure assessment score (SOFA) score ≥ 2 or those who already had sepsis at admission to the ICU were included. SOFA score, serum PCT, QCRP, nCD64 and mHLA-DR assays were recorded on the first and third day of admission to the ICU. A total of 27 sepsis cases and 24 controls (all admitted to the ICU) were included in the study. Results SOFA score, serum PCT, QCRP, nCD64 were significantly higher and mHLA-DR was significantly lower in cases compared to controls, both on day 1 and day 3. There was no significant difference in any of the parameters between day 1 and day 3. PCT and nCD64, both with sensitivity of 77.8% and specificity of 70.8% (95% CI, 0.73–0.95), had the best predictive value for diagnosing sepsis. Lower mHLA-DR (< 5000/cell) was associated with higher mortality among cases. Conclusions Serum PCT and nCD64 are the best biomarkers with similar sensitivity and specificity in detecting sepsis. mHLA-DR could have a role in prognosis as lower levels were associated with higher mortality.
Weed interference and control in sugar beet (Beta vulgaris L.)

: Two filed experiments were carried out at Tamya Agricultural Research Station, Agricultural Research Center, El-Fayoum Governorate (Middle Egypt) in both successive winter growing seasons of 2016/17 and 2017/18 to determine the effect of some weed control treatments on yield, yield components, quality of sugar beet (and its associated weeds. The randomized complete blocks design with four replications was used in these experiments. The major weed species associated sugar beet crop in field experiments in both seasons were Avena spp . , Phalaris spp . as annual grassy weeds, Brassica nigra L., Chenopodium sp., Sonchus oleraceus L., Medicago polymorpha L ., Melilotus indica L., Anagallus arvensis , Ammi majus L., Euphorbia helioscopia and Rumex dentatus L. as annual broad-leaved weeds. All weed control treatments statistically significant reduced dry weight of weeds (g/m 2 ) in both seasons at 75 and 105 days after planting (DAP). Hand hoeing three times recorded the lowest value of dry weight of weeds in both seasons.
Lie symmetries of Generalized Equal Width wave equations

Lie symmetry analysis of differential equations proves to be a powerful tool to solve or atleast to reduce the order and non-linearity of the equation. The present article focuses on the solution of Generalized Equal Width wave (GEW) equation using Lie group theory. Over the years, different solution methods have been tried for GEW but Lie symmetry analysis has not been done yet. At first, we obtain the infinitesimal generators, commutation table and adjoint table of Generalized Equal Width wave (GEW) equation. After this, we find the one dimensional optimal system. Then we reduce GEW equation into non-linear ordinary differential equation (ODE) by using the Lie symmetry method. This transformed equation can take us to the solution of GEW equation by different methods. After this, we get the travelling wave solution of GEW equation by using the Sine-cosine method. We also give graphs of some solutions of this equation.
Phenological synchrony and seasonality of tree species in a fragmented landscape in the Colombian Andes

Introduction: In Neotropical forests with high seasonality, climatic variables generally exert a strong influence on plant phenology. Objetive: To describe the reproductive phenology of eight tree species in a fragmented forest landscape, as well as to evaluate the seasonality and their phenological synchrony. Methods: The observations were performed over two years on the foothills of Los Farallones de Cali National Park, in southwestern Colombia. We applied circular statistics to detect seasonal trends, calculate intraspecific synchrony and identify correlations between phenophases and climatic variables. Results: Flowering and fruiting were significantly seasonal in most species. The flowering and fruiting patterns were annual (e.g. Henriettea seemannii, Ocotea aurantiodora, Schefflera morototoni, Lacistema aggregatum) or sub-annual (e.g. Eugenia cf. egensis, Erythroxylum citrifolium, Miconia minutiflora, M. rubiginosa). The open flower and mature fruit phenophases at the community level were continual and bimodal. Each species had high intraspecific population synchrony of open flowers and ripe fruits. Precipitation, relative humidity, temperature and solar irradiance were correlated to flowering and fruiting peaks, except in E. cf. egensis. Conclusions: The annual species showed high phenological synchrony, although the rainfall regime showed variations between years; thus, they seem to be less sensitive to climatic variation than the sub-annual species. Our results indicate that climatic variables partially control the flowering and fruiting rhythms of the eight tree species in this study.