Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel Techniques for Large Data Analysis in a Futures Trading Evaluation Service System

Futures trading evaluation system is used to analyze trading history of individuals, to find out the root cause of profit and loss, so that investors can learn from their past and make better decisions in the future. To analyze trading history of investors, the system processes a large volume of transaction data, to calculate key performance indicators, as well as time series behavior patterns, finally concludes recommendations with the help of an expert knowledge base. The paper firstly presents the working logic of the evaluation system, then it focuses on parallel data processing techniques that the system is based on. Parallel processing architecture, data distribution scheme, key performance indicators calculating algorithms and distributed time series analysis algorithms are elaborated in details. The system is highly scalable, and by exploiting the power of parallel processing, the generation time of an evaluation report is cut down from 1 to 3 minute, to 30 to 45 seconds.
Mithramycin Is a Gene-Selective Sp1 Inhibitor That Identifies a Biological Intersection between Cancer and Neurodegeneration

Oncogenic transformation of postmitotic neurons triggers cell death, but the identity of genes critical for degeneration remain unclear. The antitumor antibiotic mithramycin prolongs survival of mouse models of Huntington's disease in vivo and inhibits oxidative stress-induced death in cortical neurons in vitro. We had correlated protection by mithramycin with its ability to bind to GC-rich DNA and globally displace Sp1 family transcription factors. To understand how antitumor drugs prevent neurodegeneration, here we use structure–activity relationships of mithramycin analogs to discover that selective DNA-binding inhibition of the drug is necessary for its neuroprotective effect. We identify several genes (Myc, c-Src, Hif1α, and p21waf1/cip1) involved in neoplastic transformation, whose altered expression correlates with protective doses of mithramycin or its analogs. Most interestingly, inhibition of one these genes, Myc, is neuroprotective, whereas forced expression of Myc induces Rattus norvegicus neuronal cell death. These results support a model in which cancer cell transformation shares key genetic components with neurodegeneration.
The Jet:Wise Model of National Air Space System Evolution

Jet:Wise is an agent-based model that explores the evolution of the airline industry and its interactions with the National Airspace System (NAS). It models competitive decisions airlines make, such as setting fleet mix, itineraries, schedules, and fares and responding to delays and missed connections. The model addresses questions of the form, “How would a specific, quantifiable change in one aspect of the NAS affect the entire NAS? ” Examples include changes in operational costs, passenger demand, and flight times; removal of certain Federal Aviation Administration restrictions; improvements in technology; new facilities; congestion pricing; mergers; startup airlines; and the expansion of low-cost carriers. Understanding their complex interaction is beyond the ability of traditional modeling tools and has not been attempted until now. Validation evidence is presented: Jet:Wise is shown to produce a close correlation between simulated and observed leisure passenger counts both by origin-destination city pairs and for individual flights.
The effects of regular source of care and health need on medical care use among rural adolescents.

OBJECTIVE To examine those factors associated with the use of different types of ambulatory health services in a rural adolescent population. METHODS The student bodies of 2 middle schools and 2 high schools in rural areas in a mid Atlantic state (N = 1615) were surveyed using a self-administered health status and health services use instrument. Logistic regression was used to assess factors predicting receipt of (1) preventive services, (2) problem-focused services, and (3) emergency services. RESULTS One third of the rural youth reported having received preventive services within the previous 3 months; 41% received problem-focused care, and 18% received emergency services. Having the same provider for both preventive and illness care was the most consistent and significant predictor of receipt for all types of ambulatory services. Of special note is the greater use of emergency services when subjects did not have a consistent provider for both preventive and illness care. Health need variables, measured across a wide range of domains, were additionally predictive, and their significance varied according to the type of services received. CONCLUSIONS This study provides compelling evidence that for rural adolescents, having a regular source of care and medical need are the most important predictors of use across a variety of types of ambulatory care.
Training model for online nurse educators

Background and objective: Online instruction is very different from teaching in a face-to-face setting and educators may lack formal pedagogical training specific to online instruction; in addition, online instructors may feel isolated and have less access to direct support than their counterparts on campus. The objective of this study was to promote best practice in online education through faculty support and professional development; a structured online training process was created.Methods: Design: Instructors that teach in the online venue need teaching and training to feel comfortable with the technology and online pedagogy strategies that support best practice in online education. A structured training process was created to support novice online educators. Setting: Nursing faculty and Masters of Science in Nursing education track students co-taught one online class together. Participants: Faculty and senior level Masters of Science in Nursing education track students were asked to reflect on their one-year teaching and training experience as educators. Methods: Qualitative analysis using Denzin’s interpretive interactionism was used to elicit meaning from participant experiences.Results: Four themes emerged from the data; online pedagogy, knowledge acquisition, mentor-mentee role, and online nurse educator. These themes align with the scholarship of teaching, discovery, application, and integration, respectively. The Training Model for Online Nurse Educators was developed to show this relationship.Conclusions: Using Boyer’s model of scholarship as a framework for online training can prepare instructors for the online nurse educator role. Online instructional delivery is a mainstay in education necessitating nurse educators who are prepared to apply best practice strategies in online education.
Early molecular events during retinoic acid induced differentiation of neuromesodermal progenitors

ABSTRACT Bipotent neuromesodermal progenitors (NMPs) residing in the caudal epiblast drive coordinated body axis extension by generating both posterior neuroectoderm and presomitic mesoderm. Retinoic acid (RA) is required for body axis extension, however the early molecular response to RA signaling is poorly defined, as is its relationship to NMP biology. As endogenous RA is first seen near the time when NMPs appear, we used WNT/FGF agonists to differentiate embryonic stem cells to NMPs which were then treated with a short 2-h pulse of 25 nM RA or 1 µM RA followed by RNA-seq transcriptome analysis. Differential expression analysis of this dataset indicated that treatment with 25 nM RA, but not 1 µM RA, provided physiologically relevant findings. The 25 nM RA dataset yielded a cohort of previously known caudal RA target genes including Fgf8 (repressed) and Sox2 (activated), plus novel early RA signaling targets with nearby conserved RA response elements. Importantly, validation of top-ranked genes in vivo using RA-deficient Raldh2−/− embryos identified novel examples of RA activation (Nkx1-2, Zfp503, Zfp703, Gbx2, Fgf15, Nt5e) or RA repression (Id1) of genes expressed in the NMP niche or progeny. These findings provide evidence for early instructive and permissive roles of RA in controlling differentiation of NMPs to neural and mesodermal lineages. Summary: The findings here demonstrate that the signaling molecule retinoic acid (RA) plays an early role in determining how embryonic progenitor cells decide to differentiate into either mesodermal or neural tissues.
A probabilistic approach to minimize the conjunctive costs of node replacement and performance loss in the management of wireless sensor networks

In this paper, we consider a sensor network with either node replacement or battery replacement as the maintenance operation. We address the problem of how the failed nodes are to be replaced, in order to obtain a desirable tradeoff between maintenance cost and network performance, in the management of the network. Since node replacement and battery replacement are analytically identical, we solve this problem only for the network, where the maintenance operation is node replacement. We do this by converting performance loss into cost terms and minimizing the summation of node replacement costs and performance loss costs. We use Markov decision processes (MDP) to develop a probabilistic approach in order to estimate the longrun cost of the network. For this we use statistical data based on the past behaviour of the network. We also propose an algorithm to determine the optimal node-replacement policy. The longrun node replacement cost and the longrun performance loss cost of the simulated network are found to be theoretically consistent.
Data embedding technique using secret fragment visible mosaic image for covered communication

A novel method is implemented based on information hiding for secure data communication. A new computer art image creates called secret fragment visible mosaic image. The Mosaic image is formed by the design of composing small fragments of a given secret image and selected target image, which appears in an arbitrarily selected target image and use of hiding of the secret image. Secret image and target image is divided into small fragments called tile image and target block respectively. Tile image is embedded in a similar target block based on color variation. Each tile image is transforming their color characteristic to corresponding target blocks using color transform algorithm so that the secret image may be retrieved nearly lossless. Secret image and target image are variable size, then resizing the target image. Customize metafile (CMF) contains the required information for retrieving the secret image. The text message is embedded into the border using the TBPC method. Calculate the hash value of generated the mosaic image. MD 5 hash algorithm is used to compute hash value, which provides integrity of secret data. The proposed method is possible for large volume and variable size of the secret image and target image. This method is feasible for secure and nearly lossless data embedding technique.
A Study on The Psycho-Social Disturbance of Children Who Are Exposed to Domestic Violence : Focusing on Hierarchical Analysis Verification

This study is examined the harmful effects of two groups of children, one group exposed to domestic violence situations and another not exposed. The paper reports how children exposed domestic violence are seriously affected, and presents possible solutions with the help of social work and preventive ways employing practical data. Hierarchical Regression Analysis was used and the outcomes were applied to regression analysis. The significant difference and degree of influence between children in domestic violence situations and those not in such situations are presented as follows: aggressive behavior18%> depression anxiety14.4%> juvenile delinquency9.6%. Based on these results, intervention to protect children exposed to domestic violence, using micro, mezzo, macro approaches can be suggested. These include group social work, family therapy, participation of school and community, and administrative policy to help repair the harmful effects of children involved in domestic violence.
The 'orthogonal algorithm' for optical flow detection using dynamic programming

An algorithm for optical flow detection is introduced. It is based on an iterative search for a displacement field that minimizes the L/sub 1/ or L/sub 2/ distance between two images. Both changes are sliced into parallel and overlapping strips. Corresponding strips are aligned using dynamic programming. Two passes are performed using orthogonal slicing directions. This process is iterated in a pyramidal fashion by reducing the spacing and width of the strips. This algorithm provides very-high-quality matching for calibrated patterns as well as for human visual sensation. The results appear to be at least as good as those obtained with classical optical flow detection methods. <<ETX>>
The hominoid-specific gene TBC1D3 promotes generation of basal neural progenitors and induces cortical folding in mice

Cortical expansion and folding are often linked to the evolution of higher intelligence, but molecular and cellular mechanisms underlying cortical folding remain poorly understood. The hominoid-specific gene TBC1D3 undergoes segmental duplications during hominoid evolution, but its role in brain development has not been explored. Here, we found that expression of TBC1D3 in ventricular cortical progenitors of mice via in utero electroporation caused delamination of ventricular radial glia cells (vRGs) and promoted generation of self-renewing basal progenitors with typical morphology of outer radial glia (oRG), which are most abundant in primates. Furthermore, down-regulation of TBC1D3 in cultured human brain slices decreased generation of oRGs. Interestingly, localized oRG proliferation resulting from either in utero electroporation or transgenic expression of TBC1D3, was often found to underlie cortical regions exhibiting folding. Thus, we have identified a hominoid gene that is required for oRG generation in regulating the cortical expansion and folding. DOI: http://dx.doi. org/10.7554/eLife.18197. 001
Seeing red: the origin of grain pigmentation in US weedy rice

Weedy forms of crop species infest agricultural fields worldwide and are a leading cause of crop losses, yet little is known about how these weeds evolve. Red rice (Oryza sativa), a major weed of cultivated rice fields in the US, is recognized by the dark‐pigmented grain that gives it its common name. Studies using neutral molecular markers have indicated a close relationship between US red rice and domesticated rice, suggesting that the weed may have originated through reversion of domesticated rice to a feral form. We have tested this reversion hypothesis by examining molecular variation at Rc, the regulatory gene responsible for grain pigmentation differences between domesticated and wild rice. Loss‐of‐function mutations at Rc account for the absence of proanthocyanidin pigments in cultivated rice grains, and the major rc domestication allele has been shown to be capable of spontaneous reversion to a functional form through additional mutations at the Rc locus. Using a diverse sample of 156 weedy, domesticated and wild Oryzas, we analysed DNA sequence variation at Rc and its surrounding 4 Mb genomic region. We find that reversion of domestication alleles does not account for the pigmented grains of weed accessions; moreover, we find that haplotypes characterizing the weed are either absent or very rare in cultivated rice. Sequences from genomic regions flanking Rc are consistent with a genomic footprint of the rc selective sweep in cultivated rice, and they are compatible with a close relationship of red rice to Asian Oryzas that have never been cultivated in the US.
Comparison of Discretization Approaches for Granular Association Rule Mining

Granular association rule mining is a new relational data mining approach to reveal patterns hidden in multiple tables. Recently, granular association rules have been proposed for cold-start recommendation, where a customer or a product has just entered the system. The current research considers only nominal data. In this paper, we study the impact of discretization approaches on mining semantically richer and stronger rules from numerical data. Specifically, the equal width, the equal frequency, and the k-means approaches are adopted and compared. The setting of interval numbers is a key issue in discretization approaches. Therefore, different settings are compared through experiments on a well-known real life data set. Experimental results show that: 1) discretization is an effective preprocessing technique in mining stronger rules; 2) the appropriate settings of interval numbers are critical to obtaining more rules; 3) the equal frequency approach outperforms the equal width and the k-means approaches; and 4) the recommendation accuracy and the number of recommendations are improved significantly through the discretization approaches.
On the Same Page: Building Best Practices of Peer Coaching for Medical Educators Using Nominal Group Technique

This article was migrated. The article was marked as recommended. Introduction: Peer coaching is a faculty development approach that improves teaching practice. Elements include peer observation of teaching, feedback, and collegial exchange. Peer coaching supports reflection on teaching, cultivates workplace learning, and fosters learning cultures. Yet, limited resources are available to guide faculty developers in designing and implementing peer coaching initiatives. This gap may lead to initiatives that fail to optimize teaching effectiveness. Methods: The authors convened a focus group of seven participant experts, via video-teleconference, to arrive at consensus on best practices of peer coaching for medical educators. The focus group utilized Nominal Group Technique, a consensus building methodology. Process steps included an introduction, silent idea generation, idea sharing, group discussion, and voting. Consensus was reached with over 50% agreement. Data were qualitatively analyzed using inductive content analysis, and quotes were extracted to support the identification of best practices. Results: Seventeen best practices were identified. All participant experts recommended a framework for the peer observation process including a pre-observation meeting and post-observation debrief. The participant experts stressed the importance of confidentiality and behaviorally-based feedback. To promote collegial exchange, most agreed peer coaching should be a formative process conducted in an environment that is safe and nonthreatening. Finally, peer coaching should be supported at multiple levels within an organization. Conclusion: Expert consensus generated 17 best practices of peer coaching for medical educators that optimize teaching effectiveness. The results provide a practical resource for faculty developers. Future researchers should explore common pitfalls and barriers to the implementation of peer coaching initiatives from the perspectives of academic leadership, peer coaches, and observed educators.
Approximating node-weighted multicast trees in wireless ad-hoc networks

Multicast communication in a wireless ad-hoc network can be established using a tree that spans the multicast sender and receivers as well as other intermediate nodes. If the network is modelled as a graph, the multicast tree is a Steiner tree, the multicast sender and receivers correspond to terminals, and other nodes participating in the tree are Steiner nodes. As Steiner nodes are nodes that participate in the multicast tree by forwarding packets but do not benefit from the multicast, it is a natural objective to compute a tree that minimizes the total cost of the Steiner nodes. We therefore consider the problem of computing, for a given node-weighted graph and a set of terminals, a Steiner tree with Steiner nodes of minimum total weight. For graph classes that admit spanning trees of maximum degree at most d, we obtain a 0.775d-approximation algorithm. We show that this result implies a 3.875-approximation algorithm for unit disk graphs, an O(1/α2)-approximation algorithm for α-unit disk graphs, and an O(λ)-approximation algorithm for (λ + 1)-claw-free graphs.
Longitudinal study of sperm DNA fragmentation as measured by terminal uridine nick end-labelling assay.

BACKGROUND One major limitation in the use of sperm DNA fragmentation as measured by the TdT (terminal deoxynucleotidyl transferase)-mediated dUTP nick-end labelling (TUNEL) assay is the paucity of solid data on the stability of this parameter. METHODS The objective of our study was to evaluate variations in the degree of sperm DNA fragmentation, as measured by the TUNEL assay, over a 6 month period. Five donors provided semen samples (total 107) on the average three times per month, and 10 infertility patients provided semen samples every 4 weeks (total 58). RESULTS The mean percentage of sperm DNA fragmentation for donors was 13.18%, the within-donor standard deviation (SD(W) = 3.79%) was small compared to between-donor (SD(B) = 17.56%). For the group of patients, the mean percentage of sperm DNA fragmentation was 22.44%, with SD(W) of 4.43% within patients and SD(B) of 29.48% between patients. No seasonal rhythm was observed during the study. The intra-class correlation coefficient for all subjects combined was 0.83. Compared to sperm concentration, individual coefficients of variation for sperm DNA fragmentation indicated less variability in four subjects, but were similar in the others. CONCLUSION This longitudinal study shows that sperm DNA fragmentation is a parameter with good stability (repeatability) over time; it can be taken as a baseline both in healthy fertile men and in patients from infertility couples.
Experimental Study of Magnetic Multi-Walled Carbon Nanotube-Doxorubicin Conjugate in a Lymph Node Metastatic Model of Breast Cancer

Background The lymphatic system plays a significant role in the defense of a subject against breast cancer and is one of the major pathways for the metastasis of breast cancer. To improve the prognosis, many means, including surgery, radiotherapy, and chemotherapy, have been used. However, the combination of all these modalities has limited efficacy. Lymph nodes, therefore, have become an exceptionally potential target organ in cancer chemotherapy. Material/Methods A lymph node metastatic model of breast cancer was established in BALB/c mice. Magnetic multi-walled carbon nanotube carrier with good adsorption and lymph node-targeting capacity was prepared and conjugated with doxorubicin to make the magnetic multi-walled carbon nanotube-doxorubicin suspension. Dispersions of doxorubicin, magnetic multi-walled carbon nanotube-doxorubicin, and magnetic multi-walled carbon nanotube were injected into lymph node metastatic mice to compare their inhibitory effects on tumor cells in vivo. Inhibition of these dispersions on EMT-6 breast cancer cells was detected via MTT assay in vitro. Results Although no significant difference was found between the effects of doxorubicin and magnetic multi-walled carbon nanotube-doxorubicin with the same concentration of doxorubicin on EMT-6 breast cancer cells in vitro, in terms of sizes of metastatic lymph nodes and xenograft tumors, apoptosis in metastatic lymph nodes, and adverse reactions, the magnetic multi-walled carbon nanotube-doxorubicin group differed significantly from the other groups. Conclusions The magnetic multi-walled carbon nanotube-doxorubicin clearly played an inhibitory role in lymph node metastases to EMT-6 breast cancer cells.