Miracle-dz/UniFAR-FTUs huggingface dataset:
EXPERIENCE OF NURSES FROM THE EMERGENCY DEPARTMENT MANAGEMENT: A QUALITATIVE STUDY

Aims: No hospital can be considered as an ideal treatment center without an active and fully functional emergency room. A significant part of this strong and high performance is related to emergency room management that is affected by contextual factors and conditions. This study was conducted to clarify nurses' experience of emergency room management from nurses' point of view. Methods: This study was carried out through a qualitative approach and content analysis method with conventional approach. Via purposeful sampling, 18 nurses during one year gave unstructured interviews in two teaching hospitals in Tehran. The gathered data were analyzed by using MAXQDA3 software. Results: The results of this study indicated that nurses' experience of emergency room management lay in three main aspects: 1. Neglecting basic needs of human resources, 2. Neglecting development of human resource, 3. Basic and functional management challenges and deficiencies Conclusion: Considering the shortcomings and failures in emergency room management, managers should pay attention to nurses ' basic needs. They should support nurses, consider offers, improve education, and try to overcome challenges and shortcomings of management.
Adaptive Quantization Visibility Caching

Ray tracing has become a viable alternative to rasterization for interactive applications and also forms the basis of most global illumination methods. However, even today's fastest ray‐tracers offer only a tight budget of rays per pixel per frame. Rendering performance can be improved by increasing this budget, or by developing methods that use it more efficiently. In this paper we propose a global visibility caching algorithm that reduces the number of shadow rays required for shading to a fraction of less than 2% in some cases. We quantize the visibility function's domain while ensuring a minimal degradation of the final image quality. To control the introduced error, we adapt the quantization locally, accounting for variations in geometry, sampling densities on both endpoints of the visibility queries, and the light signal itself. Compared to previous approaches for approximating visibility, e.g. shadow mapping, our method has several advantages: (1) it allows caching of arbitrary visibility queries between surface points and is thus applicable to all ray tracing based methods; (2) the approximation error is uniform over the entire image and can be bounded by a user‐specified parameter; (3) the cache is created on‐the‐fly and does not waste any resources on queries that will never be used. We demonstrate the benefits of our method on Whitted‐style ray tracing combined with instant radiosity, as well as an integration with bidirectional path tracing.
Variants of Privacy Preserving Set Intersection and their Practical Applications

Private Set Intersection (PSI) is a cryptographic primitive that allows two network connected parties with hidden inputs to jointly compute the intersection of these inputs while keeping their specific inputs secret. PSI can be used as a building block for a variety of applications, most notably querying a remote relational database without revealing the query or the database. Many constructions of PSI exist, each building off of a subset of an assortment of cryptographic primitives such as: oblivious transfer, hash functions, garbled circuits, public key encryption and signature schemes, and basic number theoretic hardness assumptions. In this dissertation, we study variations of PSI and their practicality to modern day applications. Specifically, we study new security constraints for PSI that arise from applications such as genomics, consumer applications, and inter-agency information sharing. These constraints lead to several novel secure computation protocols. Through actualized prototypes of these schemes we conclude that, specialized PSI protocols are fast enough for use today, even on resource constrained hardware.
Epoxy-based permeable membrane fabrication for 3D microfluidic device

We report for the first time on a simple fabrication via UV photolithography for a free-standing filtration membrane made of epoxy-based photoresist and its integration on a multilevel microfluidic device. The fabrication process involves three-dimensional thick-photoresist microstructuring combined with standard negative photoresist processing. In this paper, a primary feature of membrane permeability dependence on fabrication process parameters was characterized by employing a cross-linking reaction model. The experiments using a multilevel microfluidic device demonstrated the proposed fabrication is capable of fabricating nano-filtration membrane while maintaining a sufficient mechanical strength for applications in polymer-based microfluidic devices.
Industrial Methanol from Syngas: Kinetic Study and Process Simulation

Abstract In this study, a detailed rigorous kinetic model is proposed for the industrial production of methanol taking into account changes in total mole flowrate. The kinetic model proposed is compared with the one proposed in literature (Rezaie et al., Chem Eng Process Process Intensification 2005;44:911–21), showing significant differences in terms of compositions and total mole flow. A complete simulation of the methanol production process is developed with a commercial software. The rigorous reactor model is integrated in the simulation using the CAPE OPEN standard. Flowsheet simulation is carried out, and results show small differences with those found in previous studies (Luyben, Ind Eng Chem Res 2010;49:6150–63).
An ARM-based embedded gesture recognition system using a data glove

Gesture is a natural and intuitive mode of interpersonal communication, which can simulate language and behaviors to express certain meanings and words. In this paper, an embedded gesture recognition system has been designed and developed using a data glove. The design of a data glove is aimed at supplying a auxiliary communication tool for deaf people so that there is more social intercourse between them and the normal. The gesture recognition system which can interpret gesture to voice and text messages is mainly composed of four parts: a data glove, an ARM processor, a display module and an audio module. The data glove comprises five unidirectional bend sensors (FLX-03) and a 3-axis accelerometer. The ARM processor receives the data that is transmitted from the sensors of a data glove through I/O ports. And it also analyzes and calculations the data from distinct gestures, then compares the data with the templates to see if the gestures match. The recognition results are displayed on an LCD screen, and the converted voice is outputted through an external speaker. Combined with the hardware, this paper focuses on the template matching algorithm, including data collection, mining and processing. The experimental results show that the recognition accuracy rate of trained gestures is above 91%.
A synergetic approach to indoor navigation and mapping for aerial reconnaissance and surveillance

Unmanned Air Vehicles (UAVs) lend themselves to provide rescue forces with important information beyond their own field of vision. In this paper, we present a two-part yet synergetic navigation and mapping system for indoor reconnaissance and surveillance through aerial platforms. It faces inherent drawback of common Simultaneous Localization and Mapping (SLAM) approaches: map errors cannot be excluded and will directly afflict the positioning. With a flexible navigation filter and an efficient 2.5D mapping tool as centerpieces, our system facilitates appropriate mutual feedback of supporting information. That is map-based navigation aiding in terms of ego-motion estimation and improved mapping in terms of accuracy, robustness and efficiency. Hereby both modules remain independent in their basic function and are therefore guarded against overlapping errors. Finally, the system is validated by means of real experimental data and a first proof of suitability for application within autonomous exploration is given based on simulated flights.
Antibody prevents the establishment of persistent arenavirus infection in synergy with endogenous T cells

A cardinal feature of the biology of lymphocytic choriomeningitis virus (LCMV) is its ability to establish persistent infections in mice. Persistence is usually established by infection of the mouse during the in utero or neonatal period. Susceptibility can be extended to the adult by treatment with immunosuppressive agents or by infection with immunosuppressive strains of LCMV. In this study we investigated the capacity of passively acquired anti-LCMV antibodies to prevent the establishment of persistence in both neonatal and adult mice. Suckling BALB/c mouse pups nursed by mothers immunized against LCMV before pregnancy had higher survival rates following infection than controls and withstood challenge doses of up to 400 PFU without becoming persistently infected. To establish that maternal antibody alone and not maternally derived T cells provided this protection, nonimmune mothers were infused with monoclonal anti-LCMV neutralizing antibodies within 24 h after delivering their pups. Pups nursing on these passively immunized mothers were resistant to persistent LCMV infection. The establishment of persistence in adult BALB/c mice by the immunosuppressive, macrophage-tropic LCMV variant, clone 13 was also prevented by prophylactic treatment with anti-LCMV monoclonal antibodies. However, the protection afforded by passively acquired antibody was found to be incomplete if the recipients lacked functional CD8+ T cells. While 65% of neonatal athymic (nu/nu) mice nursed by immune nu/+ dams resisted low-dose viral challenge (25 PFU), the majority of nude pups challenged with high doses of virus (100 PFU) became persistently infected. Also, protection was incomplete in beta2-microglobulin knockout mice, which lack functional CD8+ T cells, suggesting that a cooperative effect was exerted by the combination of neutralizing antibody and endogenous T cells. These results indicate that antibodies provide an effective barrier to the establishment of persistent infections in immunocompetent mice and reaffirm that vaccines which induce strong humoral responses may provide efficient protection against arenavirus infections.
Caspase Activation by Adenovirus E4orf4 Protein Is Cell Line Specific and Is Mediated by the Death Receptor Pathway

ABSTRACT Adenovirus E4orf4 protein has been shown to induce transformed cell-specific, protein phosphatase 2A-dependent, and p53-independent apoptosis. It has been further reported that the E4orf4 apoptotic pathway is caspase-independent in CHO cells. Here, we show that E4orf4 induces caspase activation in the human cell lines H1299 and 293T. Caspase activation is required for apoptosis in 293T cells, but not in H1299 cells. Dominant negative mutants of caspase-8 and the death receptor adapter protein FADD/MORT1 inhibit E4orf4-induced apoptosis in 293T cells, suggesting that E4orf4 activates the death receptor pathway. Cytochrome c is released into the cytosol in E4orf4-expressing cells, but caspase-9 is not required for induction of apoptosis. Furthermore, E4orf4 induces accumulation of reactive oxygen species (ROS) in a caspase-8- and FADD/MORT1-dependent manner, and inhibition of ROS generation by 4,5-dihydroxy-1,3-benzene-disulfonic acid (Tiron) inhibits E4orf4-induced apoptosis. Thus, our results demonstrate that E4orf4 engages the death receptor pathway to generate at least part of the molecular events required for E4orf4-induced apoptosis.
FASSM: Enhanced Function Association in Whole Genome Analysis Using Sequence and Structural Motifs

We present an algorithm to detect remote homology, which arises through circular permutation and discontinuous domains. It is also helpful in detecting small domain proteins that are characterized by few conserved residues. The input to the algorithm is a set of multiply aligned protein sequence profiles. This method, coded as FASSM, examines the sequence conservation and positions of protein family signatures or motifs for the annotation of protein sequences and to facilitate the analysis of their domains. The overall coverage of FASSM is 93% in comparison to other validation tools like HMM and IMPALA. The method is especially useful for difficult relationships such as discontinuous domains during whole-genome surveys and is demonstrated to perform accurate family associations at sequence identities as low as 15%.
Comparison of blood folate levels among pregnant Chinese women in areas with high and low prevalence of neural tube defects

Abstract Objective To characterise plasma and red-blood-cell (RBC) folate status among pregnant women in an area with an extremely high prevalence of neural tube defects, and to compare them with those of women from a low prevalence area. Design A cross-sectional survey conducted in 2003. Setting One county and one city from each of the high prevalence area and the low prevalence area in China. Subjects Five hundred and sixty-two women in their first trimester of pregnancy in the high prevalence area and 695 pregnant women in the low prevalence area. Results Women in the high prevalence area had less than half the plasma and RBC folate concentrations (12.2 and 440.0 nmol l− 1, respectively) of women in the low prevalence area (33.5 and 910.4 nmol l− 1, respectively). In the high prevalence area, 40% of rural women were deficient in RBC folate and 50% were deficient in plasma folate; 20% of urban women were deficient in RBC folate and 30% deficient in plasma folate. In contrast, only 4% (RBC folate) and 6% (plasma folate) of rural women, and 2% (RBC folate) and 1% (plasma folate) of urban women, were folate-deficient in the low prevalence area. Less than 10% of rural and about 26% of urban women in the high prevalence area took folic acid periconceptionally, compared with 70% and 60% of women in the low prevalence area. Conclusions Blood folate deficiency is highly prevalent among pregnant women in an area of China with a very high prevalence of neural tube defects.
Hepatic fat fraction: MR imaging for quantitative measurement and display--early experience.

UNLABELLED The institutional review board approved this HIPAA-compliant study. After all five patients with nonalcoholic fatty liver disease signed a consent, they underwent magnetic resonance (MR) imaging for hepatic fat quantification. The purpose of this study was to develop a fast and accurate method to acquire and display quantitative maps of the percentage of hepatic fat. In-phase and out-of-phase gradient-echo MR imaging was performed with dual flip angles (70 degrees, 20 degrees) to resolve ambiguity of the dominant constituent. T2* corrections were also estimated and applied to generate color-coded maps of the estimated percentage of hepatic fat. MR imaging results were compared with biopsy results in two of five patients, and the technique was validated qualitatively and quantitatively with a water-oil phantom. Results of the phantom study confirmed that the dual-flip angle algorithm can be used to correctly identify the dominant constituent, allowing depiction of 0%-100% of fat content. The estimated liver fat fraction was comparable to quantitative fat measurements at biopsy in both patients (MR imaging, 18.3% +/- 2.8 [standard deviation] and 28.6% +/- 2.4, vs quantitative histopathologic analysis, 11.2% and 28.5%, respectively). SUPPLEMENTAL MATERIAL radiology.rsnajnls. org/cgi/content/full/2373041639/DC1
Digital image processing with dynamical neural networks for resource management: theories aspects

In this paper, we present the theories aspects of the problem from the reconstruction and enhancing of radar imaging in the natural resource management with detection of specials characteristics. The problem is oriented to the data massive processing involving with recurrent neural networks. The Maximum Entropy Variational Analysis method is implemented into the recurrent neural networks modified Hopfield-type to the reconstruction and, detection and stopping edges (enhancing) in the radar imaging. Furthermore, here we present two forms of the computational implementation of the recurrent neural network.
Mass balance-based plant-wide wastewater treatment plant models – Part 1: Biodegradability of wastewater organics under anaerobic conditions

From an experimental and theoretical investigation of the continuity of wastewater organic chemical oxygen demand (COD) and nitrogen (N) compounds along the link connecting the primary settling tank (PST) and anaerobic digester (AD), it was found that the primary sludge (PS) characteristics, viz. the biodegradable and unbiodegradable soluble and particulate COD and N component concentrations, need to be calculated from mass balances around the PST so that the organic and N concentrations conform to continuity principles, and the influent unbiodegradable particulate organics determined from response of the activated sludge (AS) system are also unbiodegradable under AD conditions.
Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.
A systematic Approach to Implementing Monogenic Genomic Medicine: Genotype-Driven Diagnosis of Genetic Diseases

Genomic medicine is an emerging paradigm for disease diagnosis and management that incorporates individual genome sequence information based on and identified by next-generation sequencing. Here we report on the initial experience in implementing genomic medicine for inherited diseases in a large children’s hospital. In two families, next-generation sequencing identified molecular diagnoses that had not been disclosed by years of traditional diagnostic tests. Two sisters with progressive ataxia were found to have a mutation in aprataxin gene (APTX c.717G > A, p.Trp239X) and were treated with oral Coenzyme Q10. Two brothers with intellectual disability, dysmorphic features, doughy skin, and truncal obesity were found to have autosomal recessive cutis laxa caused by mutations in pyrroline-5-carboxylate reductase, type 1 (PYCR1 c.120_121delCA). Pediatric genomic medicine appears to enable early diagnosis of inherited diseases that feature clinical or genetic heterogeneity and it may allow for targeted treatment. We discuss several bottlenecks to improving care though genomic medicine, as well as potential solutions.
Overview of Phase I Surgery for Obstructive Sleep Apnea Syndrome

It is well established that obstructive sleep apnea syndrome is associated with increased morbidity and mortality. Surgical therapy has been demonstrated to be a viable treatment option for cure. Thorough presurgical evaluation with the identification of the type of airway abnormality is mandatory to allow for the utilization of a surgical protocol that results in improved clinical outcomes. Phase I surgical protocol is designed to apply specific surgical procedures to alleviate the obstruction(s) present. Following a logical, stepwise surgical approach in airway reconstruction will minimize surgical interventions and avoid unnecessary operations. The incorporation of a risk-management protocol will minimize treatment complications while achieving cure.
Improving the Search Mechanism for Unstructured Peer-to-Peer Networks Using the Statistical Matrix Form

In a traditional file search mechanism, such as flooding, a peer broadcasts a query to its neighbors through an unstructured peer-to-peer (P2P) network until the time-to-live decreases to zero. A major disadvantage of flooding is that, in a large-scale network, this blind-choice strategy usually incurs an enormous traffic overhead. In this paper, we propose a method, called the statistical matrix form (SMF), which improves the flooding mechanism by selecting neighbors according to their capabilities. The SMF measures the following peer characteristics: (1) the number of shared files; (2) the content quality; (3) the query service; and (4) the transmission distance between neighbors. Based on these measurements, appropriate peers can be selected, thereby reducing the traffic overhead significantly. Our experimental results demonstrate that the SMF is effective and efficient. For example, compared with the flooding search mechanism in dynamic unstructured P2P networks, the SMF reduces the traffic overhead by more than 80%. Moreover, it achieves a good success rate and shorter response times.
Online Supplement to Delay-Based Service Differentiation in a Many-Server Queue with Time-Varying Arrival Rates

We study the problem of service-level (SL) differentiation in a multi-class many-server queueing system with time-varying (TV) arrival rates. We address the following question: How many servers are required (staffing) over time and how does the system manager make dynamic scheduling decisions to minimize staffing cost, subject to class-level quality-of-service constraints? With that goal in mind, we propose two types of ratio-control rules, namely (i) the head-ofline-delay-ratio (HLDR) rule, and (ii) the time-varying queue-ratio (TVQR) rule. The former is a blind scheduling rule that extends the accumulating-priority control proposed by Kleinrock (1964) while the latter is a TV version of the FQR rule considered by Gurvich and Whitt (2010). Both rules achieve an important state-space collapse (SSC) in the many-server heavy-traffic (MSHT) limit. We consider a variety of SL types and exploit SSC to construct asymptotically feasible solutions for the joint-staffing-and-scheduling problem. We establish the asymptotic optimality of the proposed solutions under some special choice of the system parameters. A by-product of our study is the sample-path version of the TV MSHT Little’s law that is a consequence of the MSHT limits.