Miracle-dz/UniFAR-FTUs huggingface dataset:
Atopic Eczema: Genetic Associations and Potential Links to Developmental Exposures

Atopic eczema (AE), or atopic dermatitis (AD), is a common inflammatory skin disease with a disrupted epidermal barrier and an allergic immune response. AD/AE is prominently characterized by a symptomatic itch and transient skin lesions. Infants compose a significant percentage affected. Two models have been proposed to explain AD/AE skin pathology: the gut microbiome-focused inside-outside model and the outside-inside model concentrating on the disrupted skin barrier/skin microbiome. Gene disruptions contributing to epidermal structure, as well as those in immune system genes, are implicated. Over 30 genes have been linked to AD/AE with Flg and Tmem79/Matt alterations being common. Other linked disruptions are in the interleukin-1 family of cytokines/receptors and the TH2 gene family of cytokines. Inheritable epigenetic modifications of the genes or associated proteins may also be involved. Skin barrier disruption and the allergic immune response have been the main foci in mechanistic studies of AD/AE, but the role of the environment is becoming more apparent. Thus, an examination of in utero exposures could be very helpful in understanding the heterogeneity of AD/AE. Although research is limited, there is evidence that developmental exposure to environmental tobacco smoke or phthalates may impact disease. Management for AD/AE includes topical corticosteroids and calcineurin inhibitors, which safely facilitate improvements in select individuals. Disease heterogeneity warrants continued research not only into elucidating disease mechanism(s), via identification of contributing genetic alterations, but also research to understand how/when these genetic alterations occur. This may lead to the cure that those affected by AD/AE eagerly await.
Lossless Compression Decoders for Bitstreams and Software Binaries Based on High-Level Synthesis

As the density of field-programmable gate arrays continues to increase, the size of configuration bitstreams grows accordingly. Compression techniques can reduce memory size and save external memory bandwidth. To accelerate the configuration process and reduce the software startup time, four open-source lossless compression decoders developed using high-level synthesis techniques are presented. Moreover, in order to balance the objectives of compression ratio, decompression throughput, and hardware resource overhead, various improvements and optimizations are proposed. Full bitstreams and software binaries have been collected as a benchmark, and 33 partial bitstreams have also been developed and integrated into the benchmark. Evaluations of the synthesizable compression decoders are demonstrated on a Xilinx ZC706 board, showing higher decompression throughput than those of the existing lossless compression decoders using our benchmark. The proposed decoders can reduce software startup time by up to 31.23% in embedded systems and 69.83% reduction of reconfiguration time for partial reconfigurable systems.
Memory Support for Adults with Alzheimer’s Disease: Applications for Speech-language Pathologists

Alzheimer’s disease (AD) is the most common form of dementia and is known to cause progressive and severely debilitating impairments in cognition, especially in memory. Deficits in memory and cognition are clearly reflected in the communication of people diagnosed with this progressive, degenerative, incurable disease, placing speech-language pathologists as important members of a care team for adults with AD. Speech-language pathologists provide treatment to support memory, and therefore communication, in people with AD through direct and indirect methods. Some examples of memory supportive strategies include spaced-retrieval learning, the use of external memory aids and assistive technology, Montessori methods, and manipulations to the physical and communicative environment. As the number of people with AD in America is projected to triple by 2050, knowledge of these effective memory supports to improve communication and quality of life among people with Alzheimer’s disease is essential. It is important to consider these effective interventions and supports when forming policy regarding access and delivery of health care to older adults, development and management of environments where they reside, and education of their caregivers. This literature review will explore recent evidence-based literature regarding direct and indirect treatment of memory for adults with Alzheimer’s disease, illustrate the relationship between these findings and the development of policy, and relate the significance of these findings relative to the scope of practice and the role of the speech-language pathologist.
A Clash of Old and New Scientific Concepts in Toxicity, with Important Implications for Public Health

Background A core assumption of current toxicologic procedures used to establish health standards for chemical exposures is that testing the safety of chemicals at high doses can be used to predict the effects of low-dose exposures, such as those common in the general population. This assumption is based on the precept that “the dose makes the poison”: higher doses will cause greater effects. Objectives We challenge the validity of assuming that high-dose testing can be used to predict low-dose effects for contaminants that behave like hormones. We review data from endocrinology and toxicology that falsify this assumption and summarize current mechanistic understanding of how low doses can lead to effects unpredictable from high-dose experiments. Discussion Falsification of this assumption raises profound issues for regulatory toxicology. Many exposure standards are based on this assumption. Rejecting the assumption will require that these standards be reevaluated and that procedures employed to set health standards be changed. The consequences of these changes may be significant for public health because of the range of health conditions now plausibly linked to exposure to endocrine-disrupting contaminants. Conclusions We recommend that procedures to establish acceptable exposure levels for endocrine-disrupting compounds incorporate the inability for high-dose tests to predict low-dose results. Setting acceptable levels of exposure must include testing for health consequences at prevalent levels of human exposure, not extrapolations from the effects observed in high-dose experiments. Scientists trained in endocrinology must be engaged systematically in standard setting for endocrine-disrupting compounds.
Iron: The Forgotten Driver of Nitrous Oxide Production in Agricultural Soil

In response to rising interest over the years, many experiments and several models have been devised to understand emission of nitrous oxide (N2O) from agricultural soils. Notably absent from almost all of this discussion is iron, even though its role in both chemical and biochemical reactions that generate N2O was recognized well before research on N2O emission began to accelerate. We revisited iron by exploring its importance alongside other soil properties commonly believed to control N2O production in agricultural systems. A set of soils from California's main agricultural regions was used to observe N2O emission under conditions representative of typical field scenarios. Results of multivariate analysis showed that in five of the twelve different conditions studied, iron ranked higher than any other intrinsic soil property in explaining observed emissions across soils. Upcoming studies stand to gain valuable information by considering iron among the drivers of N2O emission, expanding the current framework to include coupling between biotic and abiotic reactions.
Noninteractive Localization of Wireless Camera Sensors with Mobile Beacon

Recent advances in the application field increasingly demand the use of wireless camera sensor networks (WCSNs), for which localization is a crucial task to enable various location-based services. Most of the existing localization approaches for WCSNs are essentially interactive, i.e., require the interaction among the nodes throughout the localization process. As a result, they are costly to realize in practice, vulnerable to sniffer attacks, inefficient in energy consumption and computation. In this paper, we propose LISTEN, a noninteractive localization approach. Using LISTEN, every camera sensor node only needs to silently listen to the beacon signals from a mobile beacon node and capture a few images until determining its own location. We design the movement trajectory of the mobile beacon node, which guarantees to locate all the nodes successfully. We have implemented LISTEN and evaluated it through extensive experiments. Both the analytical and experimental results demonstrate that it is accurate, cost-efficient, and especially suitable for WCSNs that consist of low-end camera sensors.
Ecological effect of airborne particulate matter on plants

Atmospheric particulate matter is a mixture of diverse elements. Deposition of particulate matter to vegetated surfaces depends on the size distribution of these particles and, to a lesser extent, on the chemistry. Effects of particulate matter on vegetation may be associated with the reduction in light required for photosynthesis and an increase in leaf temperature due to changed surface optical properties. Changes in energy exchange are more important than the diffusion of gases into and out of leaves which is influenced by dust load, color and particle size. Alkaline dust materials may cause leaf surface injury while other materials may be taken up across the cuticle. A more probable route for metabolic uptake and impact on vegetation and ecosystems is through the rhizosphere. Interception of dusts by vegetation makes an important contribution to the improvement of air quality in the vicinity of vegetation. Although the effect of particulate matter on ecosystem is linked to climate change, there is little threat due to un-speciated particulate matter on a regional scale.
Research Progress on Design Methods for Missile Integrated Guidance and Control

The design for missile integrated guidance control is to combine the missile guidance and control circuit into one loop. According to the relative motion of the missile and target, the control command is directly obtained to further improve the guidance and control precision. This paper summarizes the domestic and foreign research progress on the design methods of missile integrated guidance control in recent years, studies and summarizes its advantages and disadvantages, and analyzes the main problems and development trend of missile integrated guidance and control design.
Prevalence of HPV infection among females in the United States.

CONTEXT Human papillomavirus (HPV) infection is estimated to be the most common sexually transmitted infection. Baseline population prevalence data for HPV infection in the United States before widespread availability of a prophylactic HPV vaccine would be useful. OBJECTIVE To determine the prevalence of HPV among females in the United States. DESIGN, SETTING, AND PARTICIPANTS The National Health and Nutrition Examination Survey (NHANES) uses a representative sample of the US noninstitutionalized civilian population. Females aged 14 to 59 years who were interviewed at home for NHANES 2003-2004 were examined in a mobile examination center and provided a self-collected vaginal swab specimen. Swabs were analyzed for HPV DNA by L1 consensus polymerase chain reaction followed by type-specific hybridization. Demographic and sexual behavior information was obtained from all participants. MAIN OUTCOME MEASURES HPV prevalence by polymerase chain reaction. RESULTS The overall HPV prevalence was 26.8% (95% confidence interval [CI], 23.3%-30.9%) among US females aged 14 to 59 years (n = 1921). HPV prevalence was 24.5% (95% CI, 19.6%-30.5%) among females aged 14 to 19 years, 44.8% (95% CI, 36.3%-55.3%) among women aged 20 to 24 years, 27.4% (95% CI, 21.9%-34.2%) among women aged 25 to 29 years, 27.5% (95% CI, 20.8%-36.4%) among women aged 30 to 39 years, 25.2% (95% CI, 19.7%-32.2%) among women aged 40 to 49 years, and 19.6% (95% CI, 14.3%-26.8%) among women aged 50 to 59 years. There was a statistically significant trend for increasing HPV prevalence with each year of age from 14 to 24 years (P<.001), followed by a gradual decline in prevalence through 59 years (P = .06). HPV vaccine types 6 and 11 (low-risk types) and 16 and 18 (high-risk types) were detected in 3.4% of female participants; HPV-6 was detected in 1.3% (95% CI, 0.8%-2.3%), HPV-11 in 0.1% (95% CI, 0.03%-0.3%), HPV-16 in 1.5% (95% CI, 0.9%-2.6%), and HPV-18 in 0.8% (95% CI, 0.4%-1.5%) of female participants. Independent risk factors for HPV detection were age, marital status, and increasing numbers of lifetime and recent sex partners. CONCLUSIONS HPV is common among females in the United States. Our data indicate that the burden of prevalent HPV infection among females was greater than previous estimates and was highest among those aged 20 to 24 years. However, the prevalence of HPV vaccine types was relatively low.
Maximal Repetition and Zero Entropy Rate

Maximal repetition of a string is the maximal length of a repeated substring. This paper investigates maximal repetition of strings drawn from stochastic processes. Strengthening previous results, two new bounds for the almost sure growth rate of maximal repetition are identified: an upper bound in terms of conditional Rényi entropy of order <inline-formula> <tex-math notation="LaTeX">$\gamma >1$ </tex-math></inline-formula> given a sufficiently long past and a lower bound in terms of unconditional Shannon entropy (<inline-formula> <tex-math notation="LaTeX">$\gamma =1$ </tex-math></inline-formula>). Both the upper and the lower bound can be proved using an inequality for the distribution of recurrence time. We also supply an alternative proof of the lower bound which makes use of an inequality for the expectation of subword complexity. In particular, it is shown that a power-law logarithmic growth of maximal repetition with respect to the string length, recently observed for texts in natural language, may hold only if the conditional Rényi entropy rate given a sufficiently long past equals zero. According to this observation, natural language cannot be faithfully modeled by a typical hidden Markov process, which is a class of basic language models used in computational linguistics.
Detection of subclinical vitamin K deficiency in neurosurgery with PIVKA-II

Abstract Vitamin K is known for supporting the carboxylation of hepatic coagulation proteins. Levels of proteins induced by vitamin K absence for factor II (PIVKA-II) reflect hypocarboxylated prothrombin and can be used to detect subclinical vitamin K deficiency. The aim of this study was to determine the prevalence of perioperative subclinical vitamin K deficiency among neurosurgical patients using PIVKA-II and investigate the existence of any correlation to standard coagulation assays. Also, the antitumor effects of vitamin K were reviewed. Thirty-five patients undergoing brain tumor resection were included. Blood samples were drawn preoperatively, at the end of surgery and in the morning after surgery. In addition to PIVKA-II, factor II and the Owren and Quick prothrombin times were analyzed. Seventeen of 35 patients had elevated PIVKA-II levels before surgery, which continued to be above normal range postoperatively. Median PIVKA-II and Owren prothrombin time (PT-INR) were increased on the morning day 1 postoperatively compared to before surgery, whereas Quick end-stage prothrombin time (EPT) decreased and factor II was unaffected. Postoperative complications were connected to high PIVKA-II increases. Positive correlations between PIVKA-II and factor II and body mass index (BMI) were found. In conclusion, PIVKA-II was increased in many patients preoperatively and then increased by the morning following surgery. Standard coagulation assays were largely non-pathological. Correlations were demonstrated between PIVKA-II and factor II and BMI. The effect of perioperative treatment with different vitamin K supplements should be investigated in future studies, as well as clinical trials evaluating their antitumor effects.
Receiver-initiated dynamic duty cycle scheduling schemes for underwater wireless sensor networks

The unique characteristics of underwater wireless sensor networks (UWSN) pose many constraints in transmission of data packets and energy efficiency is one of them. The battery powered underwater acoustic nodes require sophisticated protocols to control the nodes' active and sleep periods in order to increase the nodes lifetime. In the terrestrial networks a number of variants of Receiver Initiated MAC (RI-MAC) protocols utilize the nodes active and sleep cycles with the aim to improve the energy efficiency of the overall network. Motivated by the significance of less costly and energy efficient RI-MAC protocol, we present its two variants for the UWSN. In the first protocol, Duty Cycle Scheduling based on Residual Energy (RidE), each sender node to adjust its duty-cycle based on its residual energy. In the second protocol, Duty Cycle scheduling based on Next Wake-up Time (NeWT), each node calculates its duty cycle according to the duty cycle of last awake node, this allows the nodes to avoid any data collision and utilize their sleep modes efficiently to conserve their energy. The simulation results show that, RidE alleviates the need of additional re-transmissions as all the sender nodes overhear the communication with the receiver and plan their communication accordingly at the cost of additional energy consumption. Whereas, in NeWT energy consumption is minimized as the nodes stay awake for shorter period.
Quince Seed Lyophilized Biopolymer as a Medicinal Remedy: Study of Mechanical Properties of the Powder and Tablets

Background: Quince seed mucilage biopolymer (QSMB), famous for ameliorating coughs and controlling asthma symptoms, has not been processed by scientific methods and rules into a local oral tablet. Objectives: The purpose of this study was to investigate and compare the mechanical properties of QSMB with different size fractions of the mucilage powder, dried by oven or by freeze drying, to achieve a tablet. Materials and Methods: The granules dried by oven and freezing processes were classified into different size fractions (212 - 1700 µm) by sieve analyses. The tablets were prepared by a wet granulation method using deionized water. The physical and mechanical properties were tested and compared for the oven- and freeze-dried granules. Samples were compressed into troche tablets weighing 800 ± 6.9 mg and the packing fraction, tensile strength, friability, and hardness of the oven- and freeze-dried tablets were evaluated and compared. Results: The results showed that density of the powder prepared by the cold lyophilized method was about 20% less than that using the warm oven method. Compressibility and Hausner ratio values were 8 to 10 for compressibility and 0.9 to 1 for the Hausner ratio, and were different about 20 and 10%, respectively, for the two methods of drying. The tensile strength values decreased slightly from 1.65 ± 0.15 to 1.30 ± 0.1 for warm and 1.7 ± 0.3 to 1.45 ± 0.2 for cold drying, following an increase in granule sizes from 212 to 1700. This pattern also occurred for the friability, although in both cases the differences were not statistically significant (P > 0.05). The packing fraction significantly increased (P < 0.05) from 0.75 ± 0.2 to 0.82 ± 0.3 and 0.87 ± 0.2 to 0.96 ± 0.2 for the oven- and freeze-dried methods following an increase in the granule sizes. Conclusions: There seems to be a higher degree of consolidation for the compacts formed by larger particles of the freeze-dried mucilage, probably due to a plastic deformation and fragmentation processes, compared to those from smaller granules.
Plasma microRNA‐based signatures to predict 3‐year postoperative recurrence risk for stage II and III gastric cancer

Our aim was to identify plasma microRNA (miRNA)‐based signatures to predict 3‐year postoperative recurrence risk for patients with stage II and III gastric cancer (GC), so as to provide insights for individualized adjuvant therapy. Plasma miRNA expression was investigated in three phases, involving 407 patients recruited from three centers. ABI miRNA microarray and TaqMan Low Density Array were adopted in the discovery phase to identify potential miRNAs. Quantitative reverse‐transcriptase polymerase chain reaction was used to assess the expression of selected miRNAs. Logistic regression models were constructed in the training set (n = 170) and validated in the validation set (n = 169). Receiver operating characteristic analyses, survival analyses and subgroup analyses were further used to assess the accuracy of the models. We identified a 7 miRNA classifier and 7miR + pathological factors index that provided high predictive accuracy of GC recurrence (area under the curve = 0.725 and 0.841 in the training set; and 0.627 and 0.771 in the validation set). High‐risk patients defined by the signatures had significantly shorter disease‐free survival and overall survival than low‐risk patients. The 7 miRNA classifier is an independent prognostic factor, and could add predictive value to traditional prognostic factors. Subgroup analyses revealed the satisfactory performance persisted regardless of stage, and the two models both displayed high accuracy in stage IIA patients. In conclusion, identified microRNA signature may potentially provide some additional benefit for prediction of disease recurrence in patients with stage II and III GC.
Looking at Mondrian's Victory Boogie-Woogie: What Do I Feel?

Abstract artists use non-figurative elements (i.e. colours, lines, shapes, and textures) to convey emotions and often rely on the titles of their various compositions to generate (or enhance) an emotional reaction in the audience. Several psychological works observed that the metadata (i.e., titles, description and/or artist statements) associated with paintings increase the understanding and the aesthetic appreciation of artworks. In this paper we explore if the same metadata could facilitate the computational analysis of artworks, and reveal what kind of emotional responses they awake. To this end, we employ computer vision and sentiment analysis to learn statistical patterns associated with positive and negative emotions on abstract paintings. We propose a multimodal approach which combines both visual and metadata features in order to improve the machine performance. In particular, we propose a novel joint flexible Schatten p- norm model which can exploit the sharing patterns between visual and textual information for abstract painting emotion analysis. Moreover, we conduct a qualitative analysis on the cases in which metadata help improving the machine performance.
Acoustic Features for Music Emotion Recognition and System Building

We are faced with a massive growth of musical data in the form of digital files. Accurate metadata labeling of music archives is necessary in order to make digital music searchable and to be efficiently organized, not only by file name or song title but in deeper detail, such as genre, artist, and types of instrument. Music related emotional terms are frequently used as search keywords, especially for non-vocal music such as film soundtracks. Music emotion recognition is a challenging issue because there are no standard categories, and how music evokes emotion is poorly understood, and related to many factors. Manually labeling music emotion by an expert is infeasible when dealing with huge amounts of music and when opinion on the same musical piece can vary from person to person. A system that is able to reveal the hidden relationships between music-related factors and emotional perception is required. This paper discuses background knowledge on psychology, musicology, and acoustic feature extraction by MATLAB toolboxes. It also includes construction guidelines for a music emotion classification system.