Miracle-dz/UniFAR-FTUs huggingface dataset:
O banco de dados do "Projeto Genoma Café" na Embrapa Recursos Genéticos e Biotecnologia (CENARGEN)

EST Genome Projects are a relatively inexpensive way to describe genes. The overwhelming amount of data coming from such a project complicates analyzing it. The Brazilian Coffee Genome Project generated 218,150 EST sequences from C. arabica, C. canephora e C. racemosa. The analysis done at Embrapa Genetic Resources and Biotechnology discarded 63,380 sequences and grouped the 154,770 remaining sequences on 45,366 clusters (UniGenes). This work describes the tools currently available to the project users. Going to https://alanine.cenargen. embrapa.br/cafEST/ with the username and password assigned by the project coordinators, one can promptly find the sequence of interesting by imputing data such as the UniGene name, sequenced clone name or even words used in the description of homologous protein. Powerful searched includes finding library specific or preferentially expressed UniGenes.
Improving the Performance of Heterogeneous Hadoop Clusters Using Map Reduce

The key issue that emerges because of the tremendous development of connectivity among devices and frameworks is making such a great amount of data at an exponential rate that an achievable answer for preparing it is getting to be troublesome step by step. Thusly, building up a stage for such propelled dimension of data handling, equipment just as programming improvements should be led to come in level with such generous data. To enhance the proficiency of Hadoop bunches in putting away and dissecting big data, we have proposed an algorithmic methodology that will provide food the necessities of heterogeneous data put away . over Hadoop groups and enhance the execution just as effectiveness. The proposed paper intends to discover the adequacy of new calculation, correlation, proposals, and an aggressive way to deal with discover the best answer for enhancing the big data situation. The Map Reduce method from Hadoop will help in keeping up a nearby watch over the unstructured or heterogeneous Hadoop bunches with bits of knowledge on results obviously from the algorithm.in this paper we proposed new Generating another calculation to tackle these issues for the business just as non-business uses can help the advancement of network. The proposed calculation can help enhance the situation of data ordering calculation MapReduce in heterogeneous Hadoop groups. The exposition work and analyses directed under this work have copied very amazing outcomes, some of them being the selection of schedulers to plan employments, arrangement of data in similitude lattice, bunching before planning inquiries and in addition, iterative, mapping and diminishing and restricting the inner conditions together to stay away from question slowing down and execution times. The test led additionally sets up the way that if a procedure is characterized to deal with the diverse use case situations, one could generally lessen the expense of processing and can profit on depending on disseminated frameworks for quick executions.
AFLP Analysis of Tall Rice Variants by Mediating Maize DNA into Rice

In order to research differences between rice variant plants and the parents at the DNA level and get relevant different DNA bands to provide data for further study on the mechanism of variation,the experiment studied the two tall rice variants C(HN28) and D(HN31) with the AFLP marker technique,which were developed by operating maize DNA into rice with pollen tube pathway.Firstly,11 pairs of selective primers were selected from 64 pairs of AFLP selective primers,which could amplify clear DNA bands more and also could amplify clearer target bands both in the two variant plants.DNA fingerprint analysis of the variant plants and the controls showed that the similarity ratios of the variant plants C,D,and the receptor rice B to the positive control A were 38.30%,38.58% and 32.99%,respectively.In comparison to the receptor rice B,the similarity ratio of the variant plants C and D in DNA fingerprints were 90.04% and 85.84%. The results above indicated that the variant plants differed from the receptor rice B in genomic DNA,and the similarity ratios between the variant plants and the positive control were higher than that of receptor rice.Twelve and eleven target bands identical to the maize control were separately detected from the variant plants C and D,which indicated that maize DNA might exist in the genomes of variant plants and the differences of the variant traits might be induced by maize DNA.
Determination of content of peptides in milk protein hydrolysates

In order to establish a rapid determination method of peptide content of milk protein hydrolysis,In the study macromolecule protein in protein hydrolysate was deposited by using 10% trichloroacetic acid.After centrifugalization and filtration,biuret reagent was added to the clear solution.The OD value was mensurated under 310 nm.Then the content of peptides of the sample was obtained through contrasted on the standard curve of GSH tetrapeptide.
Ultrastructure of the Blepharoplast and the Multilayered Structure in Spermatogenesis in Osmunda cinnamomea var. asiatica

The ultrastructure of the blepharoplast and the multilayered structure (MLS) in the fern Osmunda cinnamomea var. asiatica Fernald have been studied by electron microscopy with respect to spermatogenesis. The blepharoplast appears in the young spermatid. The differentiating blepharoplast is approximately a spherical body, which is composed of densely stained granular material in the center and some cylinders outside of it. The differentiated blepharoplast is also a sphere, but without the densely stained material in the center, consisting of scattered or radially arranged cylinders. The MLS seen in the spermatid lies between the basal bodies and the giant mitochondrion. In the early developmental stage, the MLS only consists of lamellar layers, each of which runs parallel to one another and forms a strip. In the mid stage, the MLS is composed of the microtubular ribbon (MTr), the lamellar layers and a layer of plaque. In the late stage, the MLS forms accessory band, osmiophilic crest and a layer of osmiophilic material. The MTr grows out from the MLS and extends along the surface of the nucleus to unite with the nuclear envelope in a complex. The basal body coming from the cylinder produces the axoneme of the flagella in the distal end and the wedge-shaped structure in the proximal end, respectively. In the present study, the ultrastructural features of blepharoplast and the MLS of the protoleptosporangiopsida fern, O. cinnamomea var. asiatica, have been described and compared with those of other kinds of pteridophytes in detail. The lamellar layers appearing before the formation of the MTr was found and reported for the first time.
Density Peaks Clustering Based on Weighted Local Density Sequence and Nearest Neighbor Assignment

Density peaks clustering (DPC) is a density-based clustering algorithm with excellent clustering performance including accuracy, automatically detecting the number of clusters, and identifying center points. However, the local density of DPC strongly depends on the cutoff distance which must be prespecified; in addition, the strategy assigns each remaining point to the same cluster as its nearest neighbor of higher density in descending order of local density, which is likely to cause cluster label error propagation. To overcome these limitations, we propose an improved DPC by introducing weighted local density sequence and two-stage assignment strategies, called DPCSA. Many previous improved DPC algorithms neglect additional complexity, whereas DPCSA incorporates the nearest neighbor dynamic table to enhance clustering efficiency. The experimental results for 12 artificial and 11 real-world datasets, including Olivetti face, verify that the DPCSA clustering performance is significantly superior to DPC and DPC via heat diffusion (HDDPC), and slightly superior to fuzzy weighted k-nearest neighbors density peak clustering (FKNNDPC). In addition, the DPCSA is more computationally efficient than FKNNDPC and HDDPC, but less than DPC. The source code of DPCSA is available at https://www.github. com/Yu123456/DPCSA.
Transformation of Wheat Thaumatin-Like Protein Gene and Diseases Resistance Analysis of the Transgenic Plants

The thaumatin-like protein in plants, an important member of pathogenesis-related proteins (PRs), involves in plant resistant reaction to many fungi. A series of thaumatin-like protein genes have been isolated and transformed to potato (Solanum tuberosum L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) resulting in resistance improvement to plant diseases. We have cloned a thaumantin-like protein gene, Ta-Tlp, from wheat in our earlier studies. The Ta-Tlp gene expresses in high level in wheat 6VS/6AL translocation line with high resistance to powdery mildew (Erysiphe graminis f. sp. tritici Em. Marchal.), implying its close relation to the resistance of the disease. To further understand the gene’s function, we constructed Ta-Tlp into a expression vector driven by the strong ubi promoter in the present study. The constructed vector pAHC-TlP was transformed into immature embryo-derived calli of a common wheat cultivar Yangmai 158 through particle bombardment. After two rounds of herbicide bialaphos selection and regeneration, herbicide-resistance plants were obtained. The Ta-Tlp was confirmed having been integrated into the wheat genome and expressed in T1 and T2 generations by PCR, Southern blot, and RT-PCR. The transgenic plants of T0, T1, and T2 generations were inoculated by E. graminis f. sp. tritici and F. graminearum for resistance identification. All plants of T0, T1, (183 individuals derived from 6 positive T0 lines), and T2 (241 individuals derived from 6 positive T0 lines) generations appeared some resistance to wheat powdery mildew by delaying disease development, but no distinct resistance to scab (F. graminearum).
Discovering small molecules as Wnt inhibitors that promote heart regeneration and injury repair

Abstract There are intense interests in discovering proregenerative medicine leads that can promote cardiac differentiation and regeneration, as well as repair damaged heart tissues. We have combined zebrafish embryo-based screens with cardiomyogenesis assays to discover selective small molecules that modulate heart development and regeneration with minimal adverse effects. Two related compounds with novel structures, named as Cardiomogen 1 and 2 (CDMG1 and CDMG2), were identified for their capacity to promote myocardial hyperplasia through expansion of the cardiac progenitor cell population. We find that Cardiomogen acts as a Wnt inhibitor by targeting β-catenin and reducing Tcf/Lef-mediated transcription in cultured cells. CDMG treatment of amputated zebrafish hearts reduces nuclear β-catenin in injured heart tissue, increases cardiomyocyte (CM) proliferation, and expedites wound healing, thus accelerating cardiac muscle regeneration. Importantly, Cardiomogen can alleviate the functional deterioration of mammalian hearts after myocardial infarction. Injured hearts exposed to CDMG1 display increased newly formed CMs and reduced fibrotic scar tissue, which are in part attributable to the β-catenin reduction. Our findings indicate Cardiomogen as a Wnt inhibitor in enhancing injury-induced CM proliferation and heart regeneration, highlighting the values of embryo-based small molecule screens in discovery of effective and safe medicine leads.
microCT for Systematic Mouse Phenotyping

Phenotyping of mouse mutants is one of the crucial methods for uncovering genetic network at the level of a whole organism which could help us to understand origin of rare diseases, developmental malformations, but also the process of mammalian evolution. For studying morphological aspects of either embryos or adults, the X-ray computed microtomography (microCT) has become a gold standard within the last years. The threedimensional (3D) context, availability of data to additional analysis (e.g. volumetric, bone density, or body composition), and in-vivo approaches in the case of adults are the main advantages when compared to classic histology and bone morphology. On the other hand, the amount of data is enormous making the data storage and analysis the bottle-neck of the microCT method. To overcome this obstacle, we cooperate with bioinformatics experts to set up automation of the process at maximal possible level. Nevertheless, knowledge and experience of a specialist remain indispensable.
Improved BTG-based Preordering for SMT via Parallel Parameter Averaging: An Empirical Study

Preordering has proven useful in improving the translation quality of statistical machine translation (SMT), especially for language pairs with different syntax. The topdown bracketing transduction grammar (BTG)-based preordering method (Nakagawa 2015) has achieved a state-of-the-art performance since it relies on aligned parallel text only and deos not require any linguistic annotations. Although this online learning algorithm adopted is efficient and effective, it is very susceptible to alignment errors. In a production environment, in particular, such a preorderer is commonly trained on noisy word alignments obtained using an automatic word aligner, resulting in a worse performance compared to those trained on manually annotated datasets. In order to achieve better preordering using automatically aligned datasets, this paper seeks to improve the top-down BTG-based preordering method using various parameter mixing techniques to increase the accuracy of the preorderer and speed up training via parallelisation. The parameters mixing methods and the original online training method (Nakagawa 2015) were empirically compared, and the experimental results show that such parallel parameter averaging methods can dramatically reduce the training time and improve the quality of preordering.
Novel Non-Linear Transient Path Energy Method for the Analytical Analysis of the Non-Periodic and Non-Linear Dynamics of Electrical Machines in the Time Domain

This paper proposes a novel analytical method for the analysis of the dynamics of electrical machines. The method is applied to the analysis of complex permanent magnet (PM)-type magnetic contactors (MCs), which exhibit strong magnetic non-linearities and a high portion of stray and leakage magnetic fluxes. The latter means that the analysis of PM-type MCs using traditional magnetic equivalent circuit (MEC) methods is impossible, thus requiring computationally expensive and time-consuming finite element analysis (FEA). To overcome the limitations of traditional MECs, the magnetic field distribution in PM-type MC is studied in great detail, and a novel non-linear dynamic MEC (ND-MEC) method is proposed. The accuracy of the ND-MEC method is comparable to that of FEA which is achieved by accounting for non-linear effects and dynamic changes in the magnetic flux distribution using a novel stray path elliptical function. Furthermore, the applicability of the ND-MEC is extended to the time domain by combining it with the time difference method (TDM). The complete method, referred to as the non-linear transient path energy method (NT-PEM), combines the ND-MEC, TDM, and a path energy method for the calculation of electromagnetic forces. The validity of the NT-PEM is verified by comparing it with 3D FEA and experimental results obtained from a PM-type MC prototype. The NT-PEM is a fast and inexpensive alternative to FEA, which is particularly advantageous when many designs must be analyzed and optimized while reducing analysis costs. The proposed method can also be applied to the analysis of emerging technologies dealing with multiphysics coupled problems, as in the case of smart materials.
Structure for innovations: A use case taxonomy for smart glasses in service processes

The evolution of smart glasses and AR technology holds potential for support of mobile service processes. Yet, little research has focused on systematic identification of potential use cases. In this article, we present a use case taxonomy derived from multiple case studies employing literature search, ethnographies, interviews and focus groups from the domains of nursing, maintenance and logistics. Building upon the identified use cases we propose a framework of task-technology fit for smart glasses. The taxonomy in combination with the framework will allow researchers and practitioners to identify smart glass use cases that are of inter-domain relevance. Moreover, our artefacts enable a structured approach for identification and assessment of potential smart glass use cases without in-depth knowledge of the technology.
iWatch: A Fall and Activity Recognition System Using Smart Devices

Recent reports show that the average life expectancy is increasing worldwide, posing significant overhead on healthcare systems and increasing demands on long-term care facilities. One of the grand challenges directly related to growing ageing societies is the implications of falling. Many elderly people live alone, especially those in Western countries who cannot afford living in a senior house or retirement facility. In such cases, not only falling is a major concern, but also daily activities must be continuously monitored and analyzed to provide immediate support when needed. Vital signs and environment context are also crucial conditions for preand post-event assessments. Thanks to technology advancements and widespread adoption of the Internet of Things which enables us to provide smart and ubiquitous healthcare services. In this paper, we propose iWatch, a smart and flexible system for fall detection and activity recognition using common smart devices, a smartwatch and a smartphone. Machine learning techniques are used to build efficient and highly accurate activity recognition classifiers. iWatch also provides health risk analysis using threshold-based models and leverages visualization tools to better communicate with the user. iWatch is a promising technology that provides a small step in a giant leap to revolutionize healthcare services, especially for those who needs extra care.
Towards Cyber Resiliency in the Context of Cloud Computing

Cyber resiliency is the capability of an enterprise network to continuously provide (the supported missions and business processes with) essential functions in the midst of an attack campaign. It is defined as “the ability to anticipate, withstand, recover from, and adapt to adverse conditions, stresses, attacks, or compromises on systems that include cyber resources” [1]. Conceptually speaking, the capability can be measured by whether the supported missions and business processes can succeed in spite of the various impact being caused by the attack campaign. Since the success criteria for different missions and business processes are often different, cyber resiliency is in general a relative notion. Enabling business process A to succeed in the midst of an attack campaign does not really mean that the enterprise network’s cyber resiliency capability will also enable business process B to succeed in the midst of the same attack campaign. Although technically it is possible to define non-relative system-wide cyber resiliency criteria at the operating system level or the network service level, such cyber resiliency measurements in many cases do not directly measure the business side cyber resiliency (e.g., to which extent a task is affected by the attack campaign).
Advances in the sterile insect technique for controlling codling moth

The sterile insect technique (SIT) involves the mass release of sterile insects to reduce fertility of wild populations of the same species. The codling moth is a major global pest of apple and pear crops that has invaded 71 countries and 5 continents. In this paper, advances in mass rearing, sterilization and the release of sterile insects for codling moth control are introduced, including artificial diet, population construction, rearing facilities and conditions, adult collection and quality control, long distance transport, sterilization source and equipment, radiation sensitivity, release method, marking and saturation rate. The effectiveness of SIT in countries that have used this technique is reviewed. The codling moth had now been found in Xinjiang, Gansu, Ningxia, Inner Mongolia, Heilongjiang, Jilin and poses a serious threat to China’s fruit industry. The introduction of SIT’s to China is therefore both timely and important.
Self-Management in Long-Term Prostate Cancer Survivors: A Randomized, Controlled Trial.

PURPOSE This randomized clinical trial compared a personally tailored, automated telephone symptom management intervention to improve self-management among long-term survivors of prostate cancer with usual care enhanced with a nontailored newsletter about symptom management. We hypothesized that intervention-group participants would have more confident symptom self-management and reduced symptom burden. METHODS A total of 556 prostate cancer survivors who, more than 1 year after treatment, were experiencing symptom burden were recruited from April 2015 to February 2017 across four Veterans Affairs sites. Participants were randomly assigned to intervention (n = 278) or usual care (n = 278) groups. We compared differences in the primary (symptom burden according to Expanded Prostate Cancer Index Composite-26 [EPIC], confidence in self-management) and secondary outcomes between groups using intent-to-treat analyses. We compared domain-specific changes in symptom burden from baseline to 5 and 12 months among the intervention group according to the primary symptom focus area (urinary, bowel, sexual, general) of participants. RESULTS Most of the prostate cancer survivors in this study were married (54.3%), were white (69.2%), were retired (62.4%), and underwent radiation therapy (56.7% v 46.2% who underwent surgery), and the mean age was 67 years. There were no baseline differences in urinary, bowel, sexual, or hormonal domain EPIC scores across groups. We observed higher EPIC scores in the intervention arm in all domain areas at 5 months, though differences were not statistically significant. No differences were found in secondary outcomes; however, coping appraisal was higher (2.8 v 2.6; P = .02) in intervention-arm patients at 5 months. In subgroup analyses, intervention participants reported improvement from baseline at 5 and 12 months in their symptom focus area domains. CONCLUSION This intervention was well received among veterans who were long-term survivors of prostate cancer. Although overall outcome differences were not observed across groups, the intervention tailored to symptom area of choice may hold promise to improve associated burden.
Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.