Miracle-dz/UniFAR-FTUs huggingface dataset:
Great Wall-like Water-based Switchable Frequency Selective Rasorber with Polarization Selectivity

A water-based switchable frequency selective rasorber with polarization selectivity using the Great Wall structures is presented in this paper. The proposed structure comprises a container containing horizontal and vertical channels enabling dividable injection of water, and a cross-gap FSS. The novelty of the design lies in its switchability among four different operating states by injecting water or not into the water channels. When the container is empty, the structure acts as a polarization-intensive FSS with a -0.42 dB insertion loss passband at 3.75 GHz. When the horizontal channel is filled with water and there is no water in the vertical channel, this structure can be used as an FSR with single polarization selectivity. The FSR with -10 dB absorption band from 6.8 GHz to 18.8 GHz only allows certain polarized electromagnetic (EM) waves to pass at 3.1 GHz with an insertion loss of -0.78 dB, while another polarized EM wave cannot pass. When the container is full of water, the structure operates as an absorber with a reflection band below the absorption band, where neither of polarization EM waves can transmit. Besides, a reconfigurable water-based FSR automatic control system is built to achieve state switching and temperature constancy of the water within the container. Ultimately, a prototype of the presented design is fabricated, simulated and measured to verify the feasibility. This work has potential application in radome design to realize the out-of-band RCS reduction.
The Latest Drugs in Development That Reduce Intraocular Pressure in Ocular Hypertension and Glaucoma

Abstract Glaucoma causes irreversible vision loss, with elevated intraocular pressure (IOP) being the only known modifiable risk factor. There are a variety of medical and interventional options for lowering IOP; however, despite these treatments, glaucoma continues to be a leading cause of visual impairment. Further research continues to strive for treatment options with improved side effect profiles, additional IOP-lowering effects, and ease of use. This review provides a brief summary of current IOP-lowering therapies and then outlines pipeline ocular hypotensive agents, their mechanisms of action, benefits, and side effect profiles. Advancements are seen within currently used eye drop classes such as prostaglandin analogues, Rho kinase inhibitors and nitric oxide donors, whilst there are also new drug classes, such as tyrosine protein kinase activators. Most developing drugs are topical drop formulations, with a number already having entered Phase III trials. Alternative drug delivery methods are also in development and will be briefly discussed. Pharmacological and drug delivery developments continue to provide glaucoma patients and clinicians with new options and the promise of better outcomes, particularly in terms of improved tolerance and reduced frequency of dosing.
Association Between Serum Calcium and Phosphorus Levels and Insulin-Like Growth Factor-1 in Chinese Children and Adolescents with Short Stature

Objective The aim of this study was to investigate the effect of serum calcium and phosphorus levels on the insulin-like growth factor 1 (IGF-1) in Chinese children and adolescents with short stature. Methods In this cross-sectional analysis, the clinical data of 747 children with height below –2 SD who were evaluated at the Department of Endocrinology, Affiliated Hospital of Jining Medical University from March 1, 2013, to February 28, 2019, were selected. Anthropometric and biochemical indicators were measured. The relationship between the serum calcium and phosphorus levels and IGF-1 was analysed. Results The univariate analysis results showed that serum calcium or phosphorus was significantly associated with IGF-1 SDS. In addition, after adjusting for possible confounding factors, a linear relationship between serum calcium and IGF-1 SDS and a non-linear relationship between serum phosphorus and IGF-1 SDS were observed by smooth curve fitting. The results of the fully adjusted linear regression showed that serum calcium was positively associated with IGF-1 SDS (β 1.07, 95% CI 0.21, 1.92; p = 0.015). In the multivariate piecewise linear regression, when the serum phosphorus level was greater than 1.26 mmol/L, the IGF-1 SDS increased with the increase in serum phosphorus (β 1.92, 95% CI 1.36, 2.48; p < 0.001). However, we did not observe a significant relationship when the serum phosphorus level was less than 1.26 mmol/L (p = 0.223). Conclusion This study demonstrated that in Chinese children and adolescents with short stature, circulating calcium and phosphorus concentrations may be associated with the regulation of IGF-1 levels, and this relationship merits further investigation.
Congenital vaginal atresia: about an uncommon case

Congenital vaginal atresia is a rare congenital abnormality of the female reproductive tract due to a failure of canalisation in the urogenital sinus. We report the uncommon case of a 14-year-old girl with a primary amenorrhea associated to a cyclical pelvic pain, in whom examination objectified a vaginal cup that replaced the introitus. Ultrasound examination and magnetic resonance imaging (MRI) revealed atresia of the lower third of the vagina. The diagnosis of partial vaginal aplasia on functional uterus was retained, the patient had a perineal vaginoplasty. The evolution was satisfactory with regular cycles and improvement of pelvic pain. The decline is three years. Congenital vaginal atresia is a rare malformation classically and clinically pictured as a primary amenorrhea with chronic cyclic pelvic pain. Diagnosis is based on clinical examination and imaging. The MRI is designed to assess the importance of atresia and guide surgical management while the surgical technique aims to restore the integrity of the utero-vaginal tract and to increase the possibility of pregnancy for these patients.
Adversarial Attack on Facial Recognition using Visible Light

The use of deep learning for human identification and object detection is becoming ever more prevalent in the surveillance industry. These systems have been trained to identify human body's or faces with a high degree of accuracy. However, there have been successful attempts to fool these systems with different techniques called adversarial attacks. This paper presents a final report for an adversarial attack using visible light on facial recognition systems. The relevance of this research is to exploit the physical downfalls of deep neural networks. This demonstration of weakness within these systems are in hopes that this research will be used in the future to improve the training models for object recognition. As results were gathered the project objectives were adjusted to fit the outcomes. Because of this the following paper initially explores an adversarial attack using infrared light before readjusting to a visible light attack. A research outline on infrared light and facial recognition are presented within. A detailed analyzation of the current findings and possible future recommendations of the project are presented. The challenges encountered are evaluated and a final solution is delivered. The projects final outcome exhibits the ability to effectively fool recognition systems using light.
A panoramic survey of natural language processing in the Arab world

The term natural language refers to any system of symbolic communication (spoken, signed or written) without intentional human planning and design. This distinguishes natural languages such as Arabic and Japanese from artificially constructed languages such as Esperanto or Python. Natural language processing (NLP) is the sub-field of artificial intelligence (AI) focused on modeling natural languages to build applications such as speech recognition and synthesis, machine translation, optical character recognition (OCR), sentiment analysis (SA), question answering, dialogue systems, etc. NLP is a highly interdisciplinary field with connections to computer science, linguistics, cognitive science, psychology, mathematics and others. Some of the earliest AI applications were in NLP (e.g., machine translation); and the last decade (2010-2020) in particular has witnessed an incredible increase in quality, matched with a rise in public awareness, use, and expectations of what may have seemed like science fiction in the past. NLP researchers pride themselves on developing language independent models and tools that can be applied to all human languages, e.g. machine translation systems can be built for a variety of languages using the same basic mechanisms and models. However, the reality is that some languages do get more attention (e.g., English and Chinese) than others (e.g., Hindi and Swahili). Arabic, the primary language of the Arab world and the religious language of millions of non-Arab Muslims is somewhere in the middle of this continuum. Though Arabic NLP has many challenges, it has seen many successes and developments. Next we discuss Arabic's main challenges as a necessary background, and we present a brief history of Arabic NLP. We then survey a number of its research areas, and close with a critical discussion of the future of Arabic NLP.
Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network

Heterogeneous information network (HIN) has been widely used to characterize entities of various types and their complex relations. Recent attempts either rely on explicit path reachability to leverage path-based semantic relatedness or graph neighborhood to learn heterogeneous network representations before predictions. These weakly coupled manners overlook the rich interactions among neighbor nodes, which introduces an early summarization issue. In this paper, we propose GraphHINGE (Heterogeneous INteract and aggreGatE), which captures and aggregates the interactive patterns between each pair of nodes through their structured neighborhoods. Specifically, we first introduce Neighborhood-based Interaction (NI) module to model the interactive patterns under the same metapaths, and then extend it to Cross Neighborhood-based Interaction (CNI) module to deal with different metapaths. Next, in order to address the complexity issue on large-scale networks, we formulate the interaction modules via a convolutional framework and learn the parameters efficiently with fast Fourier transform. Furthermore, we design a novel neighborhood-based selection (NS) mechanism, a sampling strategy, to filter high-order neighborhood information based on their low-order performance. The extensive experiments on six different types of heterogeneous graphs demonstrate the performance gains by comparing with state-of-the-arts in both click-through rate prediction and top-N recommendation tasks.
Characterization and Derivation of Heard-Of Predicates for Asynchronous Message-Passing Models

In distributed computing, multiple processes interact to solve a problem together. The main model of interaction is the message-passing model, where processes communicate by exchanging messages. Nevertheless, there are several models varying along important dimensions: degree of synchrony, kinds of faults, number of faults. This variety is compounded by the lack of a general formalism in which to abstract these models. One way to bring order is to constrain these models to communicate in rounds. This is the setting of the Heard-Of model, which captures many models through predicates on the messages sent in a round and received on time. Yet, it is not easy to define the predicate that captures a given operational model. The question is even harder for the asynchronous case, as unbounded message delay means the implementation of rounds must depend on details of the model. This paper shows that characterising asynchronous models by heard-of predicates is indeed meaningful. This characterization relies on delivered predicates, an intermediate abstraction between the informal operational model and the heard-of predicates. Our approach splits the problem into two steps: first extract the delivered model capturing the informal model, and then characterize the heard-of predicates that are generated by this delivered model. For the first part, we provide examples of delivered predicates, and an approach to derive more. It uses the intuition that complex models are a composition of simpler models. We define operations like union, succession or repetition that make it easier to derive complex delivered predicates from simple ones while retaining expressivity. For the second part, we formalize and study strategies for when to change rounds. Intuitively, the characterizing predicate of a model is the one generated by a strategy that waits for as much messages as possible, without blocking forever.
Anadromous Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) as a Host for Argulus pugettensis (Crustacea, Branchiura): Parasite Prevalence, Intensity and Distribution

Abstract Coastal cutthroat trout [Oncorhynchus clarkii clarkii (Richardson, 1836)] from the marine waters of Puget Sound, WA, was documented as a new host for the ectoparasite Argulus pugettensis (Dana, 1852). The prevalence of A. pugettensis was 66% (49 of 74) on cutthroat trout and 0% (0 of 55) on coho salmon [O. kisutch (Walbaum, 1792)] collected during the winter of 2017/2018. Infestations occurred most frequently on the dorsal surface, with intensities ranging from 1 to 26 argulids per fish (mean intensity 3.94 ± 4.93 S.D.). In contrast, the prevalence of the common salmon louse [Lepeophtheirus salmonis (Krøyer, 1837)] was 72% for cutthroat trout and 31% for coho salmon. Relative to other native salmonids, little is known regarding the status, ecology and threats for coastal cutthroat trout. New information reported here is a first step in understanding the relationship between this wild, native trout and infestations by parasitic sea lice and should be followed by future studies aimed to identify population level consequences.
Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory

Longitudinal data are necessary to reveal changes within the same individual as they age. However, rarely will a single cohort capture data throughout the lifespan. We describe in detail the steps needed to develop life-course trajectories from cohorts that cover different and overlapping periods of life. Such independent studies are likely from heterogenous populations which raises several challenges including: data harmonisation (deriving new harmonised variables from differently measured variables by identifying common elements across all studies); systematically missing data (variables not measured are missing for all participants of a cohort); and model selection with differing age ranges and measurement schedules. We illustrate how to overcome these challenges using an example which examines the effects of parental education, sex, and ethnicity on weight trajectories. Data were from five prospective cohorts (Belarus and four UK regions), spanning from birth to early adulthood during differing calendar periods. Key strengths of our approach include modelling trajectories over wide age ranges, sharing of information across studies and direct comparison of the same parts of the life-course in different geographical regions and time periods. We also introduce a novel approach of imputing individual-level covariates of a multilevel model with a nonlinear growth trajectory and interactions.
Diabetes and Mortality Among 1.6 Million Adult Patients Screened for SARS-CoV-2 in Mexico

Background: Whether diabetes is associated with COVID-19-related mortality remains unclear. Methods: In this retrospective case-series study we examined the risk of death associated with self-reported diabetes in symptomatic adult patients with laboratory-confirmed COVID-19 who were identified through the System of Epidemiological Surveillance of Viral Respiratory Disease in Mexico from January 1 through November 4, 2020. Survival time was right-censored at 28 days of follow-up. Results: Among 757,210 patients with COVID-19 included in the study, 120,476 (16%) had diabetes and 80,616 died. Patients with diabetes had a 49% higher relative risk of death than those without diabetes (Cox proportional-hazard ratio; 1.49 (95% confidence interval [CI], 1.47-1.52), adjusting for age, sex, smoking habit, obesity, hypertension, immunodeficiency, and cardiovascular, pulmonary, and chronic renal disease. The relative risk of death associated with diabetes decreased with age (P=0.004). The hazard ratios were 1.66 (1.58-1.74) in outpatients and 1.14 (1.12-1.16) in hospitalized patients. The 28-day survival for inpatients with and without diabetes was, respectively, 73.5% and 85.2% for patients 20-39 years of age; 66.6% and 75.9% for patients 40-49 years of age; 59.4% and 66.5% for patients 50-59 years of age; 50.1% and 54.6% for patients 60-69 years of age; 42.7% and 44.6% for patients 70-79 years of age; and 38.4% and 39.0% for patients 80 years of age or older. In patients without COVID-19 (878,840), the adjusted hazard ratio for mortality was 1.78 (1.73-1.84). Conclusion: In symptomatic adult patients with COVID-19 in Mexico, diabetes was associated with higher mortality. This association decreased with age.
Complete Genome Sequences of Allofrancisella inopinata SYSU YG23 and Allofrancisella frigidaquae SYSU 10HL1970, Isolated from Water from Cooling Systems in China

Near neighbors to the causative agent of tularemia, Francisella tularensis, isolated from diverse sources, have been reported in recent years. In this announcement, we present the complete sequence of the circular chromosome of one of the closest neighboring genera of Francisella, the type strains of Allofrancisella inopinata and Allofrancisella frigidaquae. ABSTRACT Near neighbors to the causative agent of tularemia, Francisella tularensis, isolated from diverse sources, have been reported in recent years. In this announcement, we present the complete sequences of circular chromosomes of one of the closest neighboring genera of Francisella (i.e., the type strains of Allofrancisella inopinata and Allofrancisella frigidaquae).
Expression levels of the tetratricopeptide repeat protein gene ttc39b covary with carotenoid-based skin colour in cichlid fish

Carotenoid pigments play a major role in animal body colouration, generating strong interest in the genes involved in the metabolic processes that lead from their dietary uptake to their storage in the integument. Here, we used RNA sequencing (RNA-Seq) to test for differentially expressed genes in a taxonomically replicated design using three pairs of related cichlid fish taxa from the genera Tropheus and Aulonocara. Within each pair, taxa differed in terms of red and yellow body colouration, and high‐performance liquid chromatography (HPLC) analyses of skin extracts revealed different carotenoid profiles and concentrations across the studied taxa. Five genes were differentially expressed in all three yellow–red skin contrasts (dhrsx, nlrc3, tcaf2, urah and ttc39b), but only the tetratricopeptide repeat protein-coding gene ttc39b, whose gene product is linked to mammalian lipid metabolism, was consistently expressed more highly in the red skin samples. The RNA-Seq results were confirmed by quantitative PCR. We propose ttc39b as a compelling candidate gene for variation in animal carotenoid colouration. Since differential expression of ttc39b was correlated with the presence/absence of yellow carotenoids in a previous study, we suggest that ttc39b is more likely associated with the concentration of total carotenoids than with the metabolic formation of red carotenoids.
Changes in Vegetation Cover of Yukon River Drainages in Interior Alaska: Estimated from MODIS Greenness Trends, 2000 to 2018

Abstract Trends and transitions in the growing season MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in ecosystems of the Yukon River basin in interior Alaska. Statistical analysis of changes in the NDVI time series was conducted using the “Breaks for Additive Seasonal and Trend” method (BFAST). This structural change analysis indicated that NDVI breakpoints and negative 18-yr trends in vegetation greenness over the years since 2000 could be explained in large part by the impacts of severe wildfires, commonly affecting shrubland and forested ecosystems at relatively low elevations (< 300 m). At least one NDVI breakpoint was detected at 29% of the MODIS pixels within the Yukon River basin study area. The warmest and wettest years in the study time period were found to be associated with a sizeable fraction (30%) of NDVI breakpoints. Among pixels with no NDVI breakpoints detected, both forest and shrubland trends were strongly skewed toward positive trend values. Results from gradual NDVI trend analysis supported the hypothesis that air temperature warming has enhanced the rates of (unburned) vegetation growth in shrubland and woodlands across interior Alaska over the past two decades.
Green approach for fabrication of chitosan‐neem gum polyelectrolyte stabilized penta and hexagonal nanoparticles and in‐vitro cytotoxic potential toward breast cancer (MCF‐7) cells

The present investigation aimed to utilize chitosan‐neem gum polysaccharide (Ch‐NGP) polyelectrolyte complex for the fabrication of hexagonal and pentagonal nanoparticles using antisolvent precipitation method. Fabricated nanoparticles were found in the range of 63.1 to 447.2 nm with the entrapment efficiency of 76.80 ± 1.28 to 89.82 ± 2.32%. A nonlinear correlation between the independent variable and response was observed after the regression coefficient based linearity analysis. Drug release was carried out using the egg membrane and tomato membrane as a biological barrier. All the formulations show peculiar release pattern viz. initial immediate release, followed by sustained release and final burst release of the drug. Similarity factor analysis easily showed a significant difference in drug release patterns when the egg membrane and tomato membrane were utilized as biological barriers (S˂50). Anticancerous effect against breast cancer cells line (MCF‐7) shows better control over cell growth when etoricoxib loaded nanoparticles were used in place of pure etoricoxib. Particle size growth analysis elicits that significantly no “Ostwald ripening” was observed after 45 days. It can be concluded from the findings of the experiments that Ch‐NGP polyelectrolyte functionalized hexagonal and pentagonal nanoparticles can be utilized for passive targeting of tumor cells due to its unique properties.
Investigating the Role of Personalization When Creating Relaxing Playlists

More than just a common habit or pastime of people, listening to music is often used as a way to facilitate listeners to achieve a certain mental state or to perform specific activities. Among the most common activities performed when listening to music is relaxation. According to findings from the area of music therapy, a good musical choice for relaxation needs personalization. However, until now, many studies in the area of Music Information Retrieval (MIR) have focused on only identifying general characteristics of music according to certain contexts. Thus, this paper focuses on expanding the findings of music therapy, considering aspects of musicology and a large amount of data. To this end, we: (i) explore more than 60 thousand handcrafted playlists of almost 5 thousand users; (ii) create a user preference model based on high and low-level features of the songs and (iii) analyze the differences between the users' preferences. The results of our analysis suggest that personalization plays a key role in the playlists created by the users. With this work, we want to pave the way and encourage the improvement of context-aware music recommender systems or other MIR concepts like user behavior analysis.