Miracle-dz/UniFAR-FTUs huggingface dataset:
The Dietary Intake and Practices of Adolescent Girls in Low- and Middle-Income Countries: A Systematic Review

In many low- and middle-income countries (LMICs) the double burden of malnutrition is high among adolescent girls, leading to poor health outcomes for the adolescent herself and sustained intergenerational effects. This underpins the importance of adequate dietary intake during this period of rapid biological development. The aim of this systematic review was to summarize the current dietary intake and practices among adolescent girls (10–19 years) in LMICs. We searched relevant databases and grey literature using MeSH terms and keywords. After applying specified inclusion and exclusion criteria, 227 articles were selected for data extraction, synthesis, and quality assessment. Of the included studies, 59% were conducted in urban populations, 78% in school settings, and dietary measures and indicators were inconsistent. Mean energy intake was lower in rural settings (1621 ± 312 kcal/day) compared to urban settings (1906 ± 507 kcal/day). Self-reported daily consumption of nutritious foods was low; on average, 16% of girls consumed dairy, 46% consumed meats, 44% consumed fruits, and 37% consumed vegetables. In contrast, energy-dense and nutrient-poor foods, like sweet snacks, salty snacks, fast foods, and sugar-sweetened beverages, were consumed four to six times per week by an average of 63%, 78%, 23%, and 49% of adolescent girls, respectively. 40% of adolescent girls reported skipping breakfast. Along with highlighting the poor dietary habits of adolescent girls in LMIC, this review emphasizes the need for consistently measured and standardized indicators, and dietary intake data that are nationally representative.
Progression from acute to chronic hepatitis B is more common in older adults

ABSTRACT PURPOSE The rate of progression of acute Hepatitis B (HBV) to chronic disease is quoted as <10%. The purpose of this study was to determine the rate of progression from acute to chronic HBV in Northern Ireland (NI), assessing the influence of age, gender and biochemical parameters. METHODS All “acute” HBV cases diagnosed in NI between 2011 and 2015 were reviewed. Inclusion criteria: 1). positive HBsAg and positive HBV core IgM; 2). in the absence of positive HBV core IgM, positive HBsAg with a recent negative HBsAg. Patient age, HBsAg, HBV core IgM, peak bilirubin and peak ALT were recorded, along with date and result of repeat HbsAg testing. Mann-Whitney U test was used to compare mean age, peak ALT and bilirubin between clearing and non-clearing groups. Fisher’s exact test was used to compare progression to chronicity according to gender and age less than or greater than 50yrs. RESULTS Of 80 identified cases, 4 incorrectly categorised cases were excluded. Of the remaining 76, (15 female (mean age 37.27yr), 61 male (mean age 47.39yr)) follow-up data was available for 71 patients (15 female (mean age 37.27yr), 56 male (48.59yr)). All female patients cleared HBV. 42 of 61 males cleared HBV (p=0.0313). Overall the chronicity rate was 18.42% The mean age of those clearing the virus was 43.88 years, versus 55.64 years for those going on to develop chronic HBV (Mann-Whitney U test, z= -2.68, p=0.0037). Clearance rate was 83.72% in patients aged <50yrs and 63.64% in patients 50yrs (p=0.0068). Mean peak ALT (U/L) and peak bilirubin (µmol/L) for the clearing group were 2130 and 174 respectively compared to 656 and 100 for the non-clearing group (z= -3.51, p=0.0002, z= -2.35, p=0.009). CONCLUSION Our results suggest a higher than expected rate of progression from acute to chronic HBV with a significantly higher risk for those over 50yrs. This suggests a need to revise information provided to older patients with acute HBV regarding the likelihood of progression.
Building Blocks for a Millimeter-Wave Multiport Multicast Chip-to-Chip Interconnect Based on Dielectric Waveguides

A multichip multiport communication network technology is proposed based on a network of dielectric waveguides. For optimum performance and best versatility, a combination of high-permittivity dielectric slab waveguide and low-permittivity flexible dielectric rod waveguide is proposed. Additional building blocks are a dielectric waveguide Y junction and transitions between waveguide types as well as between chip and waveguide. The resulting multichip multicast multiport interconnect network features low overall transmission loss and small chip-area consumption for the chip-to-waveguide transitions. Measurement results for all components are presented for frequency bands around 60 GHz and around 100 GHz. The insertion loss of the transition from on-chip microstrip line to dielectric slab waveguide, extracted from end-to-end measurements, is 3.3 dB around 60 GHz and 2.2 dB around 100 GHz. Experimental four-terminal networks, each comprising four chip-to-waveguide transitions and two dielectric waveguide Y junctions, show measured end-to-end insertion loss (including pass through two Y junctions and two chip-to-waveguide transitions) of 21 dB (around 60 GHz, covering 26-mm distance) and of 17 dB (around 100 GHz, covering 20-mm distance), respectively. These values outperform wireless interconnects by far and emphasize the performance and versatility of the proposed approach for chip-to-chip multicast multiport interconnects.
Towards State-of-the-art Baselines for Vietnamese Multi-document Summarization

Text summarization is challenging, but an interesting task of natural language processing. While this task has been widely studied in English, it is still an early stage in Vietnamese. This paper introduces an investigation of extractive summarization methods in Vietnamese. To do that, we implement and compare several well-known summarization methods in three directions: unsupervised, supervised, and deep learning. We validate the performance of the methods on two Vietnamese datasets. According to experimental results, we find two interesting points. Firstly, learning-to-rank methods achieve promising ROUGE-scores in many cases. Particularly, one of them surpasses the state-of-the-art unsupervised learning method. Secondly, formulating the scoring step in the form of learning-to-rank benefits the selection step.
Comparity Study of Traditional and Nature Inspired Routing Algorithms for Mobile Adhoc Network

Mobile Adhoc Networks (MANET) is infrastructureless based wireless network which enable peoples to communicate, exchange and share information between them in easy and efficient manner. MANET is one the most popular and important types of wireless networks that used in the mobile communication systems. Moreover, the operation of this kind of wireless networks rely on routing protocols. In MANET, the routing protocols are used to establish the data path in multi-hop fashion between the end nodes. The primary aim of such routing protocol is to transmit the data packets even if the link changes. The designing of routing protocols is one of the interesting research area and challenging task because of limited resources such as bandwidth, storage, transmission range and battery power. Though a number of routing solutions (proactive, reactive and hybrid) have been proposed aiming to fulfill some of these QoS requirements but it is hard to support all the requirements at the same time. Therefore, the routing protocols in MANET have become one of the key important research directions in the last decades. This article provides the brief comparity analysis of classical based routing protocols (AODV and S-AODV) and nature inspired algorithms (SARA and PAR).
The Yellow Stripe-Like (YSL) Gene Functions in Internal Copper Transport in Peanut

Copper (Cu) is involved in fundamental biological processes for plant growth and development. However, Cu excess is harmful to plants. Thus, Cu in plant tissues must be tightly regulated. In this study, we found that the peanut Yellow Stripe-Like family gene AhYSL3.1 is involved in Cu transport. Among five AhYSL genes, AhYSL3.1 and AhYSL3.2 were upregulated by Cu deficiency in peanut roots and expressed mainly in young leaves. A yeast complementation assay suggested that the plasma membrane-localized AhYSL3.1 was a Cu-nicotianamine complex transporter. High expression of AhYSL3.1 in tobacco and rice plants with excess Cu resulted in a low concentration of Cu in young leaves. These transgenic plants were resistant to excess Cu. The above results suggest that AhYSL3.1 is responsible for the internal transport of Cu in peanut.
Safety Consideration for Emerging Wireless Technologies-Evaluations of Temperature Rise in Eyes for RF Radiations up to 10 GHz

The study of temperature rise distribution in the human eye under plane electromagnetic wave exposure up to 10 GHz is presented in this paper. The effects of different frequencies and different blood perfusion rates of sclera to thermal calculations are investigated by finite difference method. The results reveal that the changes in the thermal parameter produce a maximum relative standard deviation of ~15% in the temperature rise in lens.
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks

Understanding the loss surface of neural networks is essential for the design of models with predictable performance and their success in applications. Experimental results suggest that sufficiently deep and wide neural networks are not negatively impacted by suboptimal local minima. Despite recent progress, the reason for this outcome is not fully understood. Could deep networks have very few, if at all, suboptimal local optima? or could all of them be equally good? We provide a construction to show that suboptimal local minima (i.e., non-global ones), even though degenerate, exist for fully connected neural networks with sigmoid activation functions. The local minima obtained by our construction belong to a connected set of local solutions that can be escaped from via a non-increasing path on the loss curve. For extremely wide neural networks of decreasing width after the wide layer, we prove that every suboptimal local minimum belongs to such a connected set. This provides a partial explanation for the successful application of deep neural networks. In addition, we also characterize under what conditions the same construction leads to saddle points instead of local minima for deep neural networks.
Joyce's Messianism: Dante, Negative Existence, And The Messianic Self

In his study of negative existence and how it affects James Joyce's principal characters, Gian Balsamo joins the ongoing debate about the Irish writer's relationship to Dante and considers the centrality of messianism to that relationship. Finding in Dante a negative poetics that becomes a model for Joyce, Balsamo suggests that the inception and cessation of life - two occurrences that conventionally are deemed impossible to experience personally and directly - typically frame the existential experiences of Joyce's main characters. Balsamo perceives Stephen, Leopold, and Shem as messianic figures because they rebel against this convention, clustering their lives around the very events of inception and burial. Balsamo traces the engagement of each of the three characters in a negative existence immune from the rules and limitations of ordinary experience. Each struggles to express rather than exorcise the fecundity of his own mortality; each reinvents his biography as involving the pivotal transaction of one death - be it a mother's, a son's, or even that of his own body - in return for catharsis. Drawing on the writings of Giambattista Vico, Saint Augustine, Emile Durkheim, and Noam Chomsky, Balsamo challenges the current debate by identifying the messianic thread that ties together the biographies of Joyce's three characters. Faced with the fissure between history and poetic vocation, Stephen embraces the sacrificial poetry of silence. Faced with the domestic squalor provoked by the loss of his son, Leopold renews at every meal the cathartic exchange of food and semen. Faced with a destiny of death and decomposition, Shem reenacts the tradition of the medieval cycle drama, stretching his own body like a parchment on a cross and then rubricating it like a sacred manuscript.
Do Androgens Modulate the Pathophysiological Pathways of Inflammation? Appraising the Contemporary Evidence

The role of testosterone in the pathophysiology of inflammation is of critical clinical importance; however, no universal mechanism(s) has been advanced to explain the complex and interwoven pathways of androgens in the attenuation of the inflammatory processes. PubMed and EMBASE searches were performed, including the following key words: “testosterone”, “androgens”, “inflammatory cytokines”, “inflammatory biomarkers” with focus on clinical studies as well as basic scientific studies in human and animal models. Significant benefits of testosterone therapy in ameliorating or attenuating the symptoms of several chronic inflammatory diseases were reported. Because anti–tumor necrosis factor therapy is the mainstay for the treatment of moderate-to-severe inflammatory bowel disease; including Crohn’s disease and ulcerative colitis, and because testosterone therapy in hypogonadal men with chronic inflammatory conditions reduce tumor necrosis factor-alpha (TNF-α), IL-1β, and IL-6, we suggest that testosterone therapy attenuates the inflammatory process and reduces the burden of disease by mechanisms inhibiting inflammatory cytokine expression and function. Mechanistically, androgens regulate the expression and function of inflammatory cytokines, including TNF-α, IL-1β, IL-6, and CRP (C-reactive protein). Here, we suggest that testosterone regulates multiple and overlapping cellular and molecular pathways involving a host of immune cells and biochemical factors that converge to contribute to attenuation of the inflammatory process.
Comparative Analysis of Intra-Algorithm Parallel Multiobjective Evolutionary Algorithms: Taxonomy Implications on Bioinformatics Scenarios

Parallelism has become a recurrent tool to support computational intelligence and, particularly, evolutionary algorithms in the solution of very complex optimization problems, especially in the multiobjective case. However, the selection of parallel evolutionary designs often represents a difficult question due to the multiple variables that must be considered to attain an accurate exploitation of hardware resources, along with their influence in solution quality. This work looks into this issue by conducting a comparative performance analysis of intra-algorithm parallel multiobjective evolutionary algorithms running on shared-memory configurations. We consider different design trends including A) generational approaches based on measurements of solution quality plus diversity, B) generational approaches based on measurements of solution quality exclusively, and C) non-generational approaches. Following these trends, a total of six representative algorithms are applied to tackle a challenging bioinformatics problem as a case study, phylogenetic reconstruction. Experimentation on real-world scenarios point out the main advantages and weaknesses of each design, outlining guidelines for the selection of methods according to the characteristics of the employed hardware, evolutionary properties, and the parallelism exploitation capabilities of the evaluated approaches.
Phylogenomic Analysis of the Gammaproteobacterial Methanotrophs (Order Methylococcales) Calls for the Reclassification of Members at the Genus and Species Levels

The order Methylococcales constitutes the methanotrophs – bacteria that can metabolize methane, a potent greenhouse gas, as their sole source of energy. These bacteria are significant players in the global carbon cycle and can produce value-added products from methane, such as biopolymers, biofuels, and single-cell proteins for animal feed, among others. Previous studies using single-gene phylogenies have shown inconsistencies in the currently established taxonomic structure of this group. This study aimed to determine and resolve these issues by using whole-genome sequence analyses. Phylogenomic analysis and the use of similarity indexes for genomic comparisons – average amino acid identity, digital DNA–DNA hybridization (dDDH), and average nucleotide identity (ANI) – were performed on 91 Methylococcales genomes. Results suggest the reclassification of members at the genus and species levels. Firstly, to resolve polyphyly of the genus Methylomicrobium, Methylomicrobium alcaliphilum, “Methylomicrobium buryatense,” Methylomicrobium japanense, Methylomicrobium kenyense, and Methylomicrobium pelagicum are reclassified to a newly proposed genus, Methylotuvimicrobium gen. nov.; they are therefore renamed to Methylotuvimicrobium alcaliphilum comb. nov., “Methylotuvimicrobium buryatense” comb. nov., Methylotuvimicrobium japanense comb. nov., Methylotuvimicrobium kenyense comb. nov., and Methylotuvimicrobium pelagicum comb. nov., respectively. Secondly, due to the phylogenetic affinity and phenotypic similarities of Methylosarcina lacus with Methylomicrobium agile and Methylomicrobium album, the reclassification of the former species to Methylomicrobium lacus comb. nov. is proposed. Thirdly, using established same-species delineation thresholds (70% dDDH and 95% ANI), Methylobacter whittenburyi is proposed to be a later heterotypic synonym of Methylobacter marinus (89% dDDH and 99% ANI). Also, the effectively but not validly published “Methylomonas denitrificans” was identified as Methylomonas methanica (92% dDDH and 100% ANI), indicating that the former is a later heterotypic synonym of the latter. Lastly, strains MC09, R-45363, and R-45371, currently identified as M. methanica, each represent a putative novel species of the genus Methylomonas (21–35% dDDH and 74–88% ANI against M. methanica) and were reclassified as Methylomonas sp. strains. It is imperative to resolve taxonomic inconsistencies within this group, first and foremost, to avoid confusion with ecological and evolutionary interpretations in subsequent studies.
The Effects of Filgrastim on Complications of Patients with Cerebral Hemorrhage Due To Head Trauma

BACKGROUND: Filgrastim, a neopogen brand, is a blood-forming agent and a natural protein in the body that plays a role in stimulating the growth of white blood cells and protecting them against infectious agents. To the best of knowledge, human and animal specimens have shown the effect of Filgrastim on treating brain injuries regarding bone marrow transfusion into the blood, neuroprotection, stimulation of neurons for forming new neural networks and reducing the risk of bacterial infections. AIM: This study aimed to investigate the effect of Filgrastim on the prognosis of a cerebral haemorrhage in patients with traumatic brain injury. METHODS: This study was conducted as a clinical trial, in which the initial diagnosis of patients with cerebral haemorrhage due to head trauma was performed with a clinical examination and CT scan. After the patient arrives at the emergency room, the patient’s initial examination is performed, and blood tests are taken from the patient. Moreover, CBC values (Hb, Platelet, Hematocrit) were checked and recorded in the checklist. The intervention group received 150 mcg/day Filgrastim injected subcutaneously for 4 days. Furthermore, patients in the control group received the same amount of sterile water. At the end of the treatment period, blood tests were performed again in all patients, and their results were then recorded. All data were analysed by SPSS v.21 software package. RESULTS: Our findings revealed that the mean volume of bleeding in the intervention group based on CT scan was significantly reduced after four days as compared to the control group. Moreover, the mean score of consciousness and muscular strength of patients in the intervention group was significantly higher than the control group. Also, WBCs in the intervention group exhibited a significant increase after four days of intervention, while platelet and hematocrit levels in the intervention group decreased significantly compared to the control group. CONCLUSION: Regarding the results, the therapeutic application of filtration is considered to be effective. Given the lack of serious complications of the proposed dosages, the use of this drug can be suggested.
Element Around a Thin Cylinder

The design analysis for a cylindrical conformal PIFA antenna for mounting on a thin conducting cylinder is presented. The thin cylinder means that standard groundplane principles do not apply for antenna design, and that the antenna configurations must be evaluated numerically. The. factor and fractional bandwidths are used here to guide the design. This antenna has good potential for electrically thin cylindrical structures such as found on unmanned aerial vehicles, drones, bicycles, and some radio masts.
The Impacts Mechanism of Controlling System in Hospital on Quality of Care: From Process and Outcome Perspectives

Considering complex environment of hospital, the implementation of information systems occurs lots of obstacles which impairs its effectiveness and efficiency in medical process. In other words, there exists lots of poor interactions between human and information system use, such as the overload work volume and medical errors resulting from inappropriate behavior with new technology. Thus, we use quality control system, an augmented system of electronic medical records, to explore the complementary impacts of information system to enhance the effectiveness of information system us. Our study extracted physicians' scores evaluated by the controlling system automatically at a large urban hospital in China. To examine relationship between controlling system and healthcare organizational outcomes, we construct the fixed effect model. Our results reveal an interesting progression over time in how process standardization forming from controlling system affects physician performance and patient benefits. Our findings contribute to both theoretical and practical Implications, in particular the new insight of behavior change in healthcare and policy directions.
Efficient Instance Selection Based on Spatial Abstraction

Machine learning approaches have been applied in huge volumes of data. In order to deal with this big data, techniques for instance selection have been applied for reducing the data to a manageable volume and, consequently, for reducing the computational resources that are necessary to apply machine learning approaches. In this paper, we propose an efficient approach for instance selection called ISDSP. It adopts the notion of spatial partition for efficiently splitting the dataset in sets of similar instances. In a second step, the algorithm selects a representative instance of each of the densest spatial partitions that were previously identified. The approach was evaluated on 15 well-known datasets used in a classification task, and its performance was compared to those of 6 state-of-the-art algorithms, considering two measures: accuracy and reduction. All the obtained results show that, in general, the proposed approach provides a good trade-off between accuracy and reduction, with a significantly lower running time, when compared with other approaches.
Estimating network structure from unreliable measurements

Most empirical studies of networks assume that the network data we are given represent a complete and accurate picture of the nodes and edges in the system of interest, but in real-world situations this is rarely the case. More often the data only specify the network structure imperfectly -- like data in essentially every other area of empirical science, network data are prone to measurement error and noise. At the same time, the data may be richer than simple network measurements, incorporating multiple measurements, weights, lengths or strengths of edges, node or edge labels, or annotations of various kinds. Here we develop a general method for making estimates of network structure and properties using any form of network data, simple or complex, when the data are unreliable, and give example applications to a selection of social and biological networks.