Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Variability, Heritability, Genetic Advance and correlation studies for seed yield and yield components in early segregating lines (F3) of Greengram [Vigna radiata (L.) Wilczek]

The present investigation was conducted with the F3 breeding lines derived from three crosses viz., DGGV-7 × V-02-709, DGGV-7 × V-02-802, DGGV-2 × SML-1815 along with their parents used as checks. The progeny lines were evaluated for estimation of genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability and genetic advance. The correlation study was undertaken among the ten selected quantitative characters. The analysis of variance showed, the progeny lines derived from the cross DGGV-7 × V-02-709, recoded very high significant variation for the characters like the number of branches per plant (2.988), pod length (2.363) and seed yield per plant (13.007g). The 100 seed weight (4.7g) was observed in the cross derivative of DGGV-2 × SML-1815 with high heritability 73.26 per cent and moderate genetic advance under mean (19.65). The breeding lines of DGGV-7 × V-02-709 have recorded mean seed yield 3.7 g with the range of 3.22 to 4.65 g and the PCV (17.35%), GCV (14.23%) was moderate with high heritability (72.12%) coupled with moderate genetic advance over mean (17.45%). There is a positive significant correlation was observed between plant height, number of clusters per plant, number of pods per plant, number of seeds per pod and seed yield per plant. Therefore, these characters should give higher priority at the time of selection for improvement of yield in greengram.
Study of micronuclei in cervical pap smear

Carcinoma of the cervix is a common cause of mortality in women regardless of effective screening methods. Screening for (MN) in cells has been one among the tests used in cancer screening. Several containing cells rises in carcinogen- exposed tissues much earlier than the symptoms. Here in this study usefulness of (MN) in screening cervical lesions was evaluated. We studied comparison of MN score among different cervical lesions and the significance of the difference in the score. We evaluated 406 cervical smears, categorized them using the “Bethesda 2014 system". Mean MN scores among the different cervical lesion categories were compared, and the differences were studied statistically for its significance. Results showed a gradual increase in mean MN score with increasing severity of the cervical lesion and the differences in these scores were statistically significant (P < 0.05) among all the categories, with significantly higher mean MN scores in high grade squamous wounds and invasive carcinomas (IC)than others. We concluded that the MN test could serve as an additional and practical screening test in conjunction with the conventional cervical Pap smear for cervical cancer screening.
A Highly Reliable Strong Physical Unclonable Function Design Based on FPGA

Physical unclonable function (PUF) generates unique secret keys from unavoidable IC manufacturing variations, which can eliminate high computation expense and additional key storage. The inherent flexibility and lower time-to-market have made field programmable gate array (FPGA) the platform of choice for faster implementation. However, logic elements on FPGA are predefined while some types of PUFs need strictly mirrored symmetric routing. This paper presents a robust and FPGA friendly PUF based on oscillator collapse (OC-PUF) with million number of challenge-response pairs (CRPs). Mirrored routes are obtained with a novel delay cell design and a signal path configuration technique. In the meanwhile, the response bias issues on FPGA is effectively resolved. Measured on Altera DE2-115, the average interchip hamming distance (inter-chip HD) of the proposed OC-PUF is 46.7%. After applying dynamic threshold with a value 255, intra-chip hamming distance (intra-chip HD) dropped to 5.46E-06 at nominal conditions.
Solving Shortest Path Problems Using Mathematical Literacy Skill Figured Out By Pre-Service Teachers

Mathematical literacy is an important ability to be taught to the mathematics pre-service teacher. The students who have good mathematical literacy skills will be sensitive to the mathematical concepts which are relevant to the phenomenon or problem. One of the problems that is given to mathematics pre-service teacher is the shortest path problem in Graph Theory courses. The purpose of this study is to explore the mathematical literacy abilities of the pre-service teacher in solving the shortest path problems. The research subjects were 56 mathematics pre-service teacher of Universitas PGRI Madiun, Indonesia. The data were collected through problem-solving tests which were then analyzed based on indicators of mathematical literacy ability namely formulate, employ, and interpret. The results shows that the mathematical literacy abilities of pre-service teacher in solving the shortest path problem consist of three categories, namely complete, incomplete, and incomplete mathematical literacy abilities. There are 9 students with complete mathematical literacy skills can formulate, employ, and interpret. There are 18 students with incomplete mathematical literacy skills can formulate and employ. There are 29 students with incomplete mathematical literacy can only formulate.
AFLP Fingerprinting Analysis of Citrus Cultivars and Wild Accessions from Oman Suggests the Presence of Six Distinct Cultivars

Abstract A study was conducted to evaluate genetic relatedness of 27 citrus cultivars and 6 wild citrus accessions using AFLP fingerprinting. The 27 citrus cultivars belonged to Citrus sinensis, C. aurantifolia, C. aurantium, C. paradise, C. reticulata, C. limon, C. latifolia, C. maxima, C. limettoides, C. limetta, C. medica and C. Jambhiri. The wild cultivars were obtained from Oman while the other cultivars originated from Oman and other countries. AFLP analysis using 4 primer pair combinations resolved 910 polymorphic alleles. All citrus cultivars and accessions had low genetic diversity (H = 0.0281 to 0.1300), with the percent polymorphic loci ranging from 8 to 35%. Populations of the six wild citrus accessions showed a very low level of genetic diversity (< 0.0700). Cluster analysis of the 33 cultivars and accessions showed that they share a high level of genetic similarity (81‒99%; mean = 92%). The six wild accessions clustered into two main clusters, with the analysis indicating that the six wild accessions may make up six distinct cultivars. The study provides information on the phylogeny of citrus cultivars and citrus diversity in Oman, a country through which citrus moved in the past from Asia to different African and European countries. In addition, it shows that some distinct citrus cultivars are present in this part of the world.
Water Structures and Packing Efficiency in Methylene Blue Cyanometallate Salts

Crystal structure prediction is the holy grail of crystal engineering and is key to its ambition of driving the formation of solids based on the selection of their molecular constituents. However, this noble quest is hampered by the limited predictability of the incorporation of solvent molecules, first and foremost the ubiquitous water. In this context, we herein report the structure of four methylene blue cyanometallate phases, where anions with various shapes and charges influence the packing motif and lead to the formation of differently hydrated structures. Importantly, water molecules are observed to play various roles as isolated fillings, dimers, or an infinite network with up to 13 water molecules per repeating unit. Each crystal structure has been determined by single-crystal X-ray diffraction and evaluated with the aid of Hirshfeld surface analysis, focussing on the role of water molecules and the hierarchy of different classes of interactions in the overall supramolecular landscape of the crystals. Finally, the collected pieces of evidence are matched together to highlight the leading role of MB stacking and to derive an explanation for the observed hydration diversity based on the structural role of water molecules in the crystal architecture.
NetGO: improving large-scale protein function prediction with massive network information

Automated function prediction (AFP) of proteins is of great significance in biology. In essence, AFP is a large-scale multi-label classification over pairs of proteins and GO terms. Existing AFP approaches, however, have their limitations on both sides of proteins and GO terms. Using various sequence information and the robust learning to rank (LTR) framework, we have developed GOLabeler, a state-of-the-art approach of CAFA3, which overcomes the limitation of the GO term side, such as imbalanced GO terms. Unfortunately, for the protein side issue, available abundant protein information, except for sequences, have not been effectively used for large-scale AFP in CAFA. We propose NetGO that is able to improve large-scale AFP with massive network information. The novelties of NetGO have threefold in using network information: 1) the powerful LTR framework of NetGO efficiently and effectively integrates both sequence and network information, which can easily make large-scale AFP; 2) NetGO can use whole and massive network information of all species (>2000) in STRING (other than only high confidence links and/or some specific species); and 3) NetGO can still use network information to annotate a protein by homology transfer even if it is not covered in STRING. Under numerous experimental settings, we examined the performance of NetGO, such as general performance comparison, species-specific prediction, and prediction on difficult proteins, by using training and test data separated by time-delayed settings of CAFA. Experimental results have clearly demonstrated that NetGO outperforms GOLabeler, DeepGO, and other compared baseline methods significantly. In addition, several interesting findings from our experiments on NetGO would be useful for future AFP research.
Climatology and Dynamical Evolution of Extreme Rainfall Events in the Sinai Peninsula—Egypt

The whole Mediterranean is suffering today because of climate changes, with projections of more severe impacts predicted for the coming decades. Egypt, on the southeastern flank of the Mediterranean Sea, is facing many challenges for water and food security, further exacerbated by the arid climate conditions. The Nile River represents the largest freshwater resource for the country, with a minor contribution coming from rainfall and from non-renewable groundwater aquifers. In more recent years, another important source is represented by non-conventional sources, such as treated wastewater reuse and desalination; these water resources are increasingly becoming valuable additional contributors to water availability. Moreover, although rainfall is scarce in Egypt, studies have shown that rainfall and flash floods can become an additional available source of water in the future. While presently rare, heavy rainfalls and flash floods are responsible for huge losses of lives and infrastructure especially in parts of the country, such as in the Sinai Peninsula. Despite the harsh climate, water from these events, when opportunely conveyed and treated, can represent a precious source of freshwater for small communities of Bedouins. In this work, rainfall climatology and flash flood events are presented, together with a discussion about the dynamics of some selected episodes and indications about future climate scenarios. Results can be used to evaluate the water harvesting potential in a region where water is scarce, also providing indications for improving the weather forecast. Basic information needed for identifying possible risks for population and infrastructures, when fed into hydrological models, could help to evaluate the flash flood water volumes at the outlets of the effective watershed(s). This valuable information will help policymakers and local governments to define strategies and measures for water harvesting and/or protection works.
The Effect of Bloom-based ILP Instruction on Iranian EFL learners’ Use of External and Internal Modification Strategies in the Speech Act of Request

The way people perform a speech act differs across cultures. People from different cultures may have different perceptions of similar social factors and interpret them differentially. These differences can lead to cross-cultural miscommunications when language users perform a given speech act such as request. Based on the request analysis categories introduced by Blum-Kulka et al. (1989b) and Schauer (2009), the present study examined Iranian EFL learners' deviations in utilizing internal and external modifications from native speakers' norms and explored how Bloom-based instruction can contribute to the acquisition of internal and external modifications. To this end, a researcher-developed Written Discourse Completion Task (WDCT) was utilized to collect data from 61 participants: a. treatment group (20), b. control group (23), and c. native speakers (18). The data were categorized based on a framework adapted from Blum-Kulka et al. (1989b) and Schauer's (2009) coding schemes for internal and external modifications. The results suggested that, in the pretest, Iranian EFL learners’ use of request modification strategies differed significantly from native speakers’ norms. It was found that that after the Bloom-based ILP instruction, the treatment group progressed towards native speakers' norms in the application of several modification strategies. These findings imply that the employment of Bloom’s Taxonomy, with specific focus on high order thinking skills in the development of pragmatics tasks and activities can help EFL learners approach native speakers’ norms.
Response to basal resources by stream macroinvertebrates is shaped by watershed urbanization, riparian canopy cover, and season

Riparian reforestation is a common restoration action in urban streams, but relatively little is known about the influence of local riparian vegetation in the face of watershed-scale urban land cover. Allochthonous organic matter and benthic algae are important basal energy resources in streams, but the roles of watershed urbanization vs near-stream vegetation in the availability of these resources are not well understood. Our goal was to understand how the interaction of land cover at 2 spatial scales (watershed vs reach) and seasonal dynamics shape basal resources and their effects on macroinvertebrate communities. We assessed relationships between seasonal patterns in standing stocks of particulate organic matter (POM) and benthic periphyton and macroinvertebrate community composition in open- and closed-canopy reaches of 4 urban and 4 reference streams in northern Kentucky, USA. POM standing stocks were not strongly influenced by watershed or riparian condition. Benthic algal biomass was greater in urban than in reference streams in all seasons and in open than in closed riparian canopies in summer when light levels are most affected by a deciduous canopy. Relationships between macroinvertebrate functional feeding group (FFG) biomass and their primary food resources were influenced by watershed land use and season, but riparian canopy effects were minor. The proportion of collectors varied by season, whereas the proportion of shredders was higher in reference than urban streams. Scraper biomass was influenced by benthic algal biomass and varied seasonally, whereas predator biomass was driven by prey-insect biomass. Periphyton density was affected by the interaction of watershed- and reach-scale land cover and was the only basal resource strongly related to consumer taxa. Watershed land use influences the stream ecosystem, but local riparian canopy may be important in limiting benthic algal accumulation.
Photon Detection in heavy-ion experiments

We present the measurements of multiplicity and pseudorapidity distributions of inclusive photons in proton-proton (pp) and heavy-ion (AA) collisions using the Photon Multiplicity Detector (PMD) employed at STAR and ALICE experiments. The working principle, design and features of PMD are discussed. The results are compared to different Monte Carlo (MC) predictions. The dependence of average photon multiplicity on centre-of-mass energy in pp collisions is discussed. The limiting fragmentation scenario for inclusive photon production in both pp and AA collisions are also reported.
The Impact of Physical Activity to Physical Fitness and Nutrional Status of Grade X Surabaya Vocational High School

The purpose of this research is to improve physical fitness which is one of the goals of physical education in Indonesia while also improving the nutritional status of Surabaya vocational high school students. This research uses the treatment of physical activity 3 times a week in 2 months as a task in physical education to improve physical fitness and nutrional status on the sample of this research. Research design uses quasi experimental design with metode non-randomized control group pretest-posttest design. Research data was obtained as follows: data processing result on experiment group show that physical activity to VO2max got significant score based calculating using SPSS of 0,00 and physical activity to nutrional status got sig. of 0,60. Whereas in the control group, physical actifity got sig. of 0.20 to VO2max and sig. to 0.11 on nutrional status. Based on the above analysis it can be concluded that physical activity has a significant effect on physical fitness but physical activity has no significant effect on nutrional status to Surabaya vocational high school students.
Spatial and temporal variation of forest net primary productivity components on contrasting soils in northwestern Amazon

Climate is a strong determinant of tropical forest productivity; therefore, it is often assumed that Amazonian forest growing on the same local rainfall regime responds similarly to fluctuations in rainfall, independently of soil differences among them. We evaluated intraand inter-annual variation of net primary productivity (NPP) components, and forest dynamics during 2004–2012 yr in five forests on clay, clay-loam, sandy-clay-loam, sandy-loam and loamy-sand soils, and the same local rainfall regime in northwestern Amazonia (Colombia). The questions were as follows: (1) Do NPP components and forest dynamics respond synchronously to temporal rainfall fluctuations? (2) Are the responses between above and belowground components and forest dynamics similar for different forest stands? A slight and complex synchronicity among different NPP components in their response to temporal rainfall fluctuations were found; few plots showed that aboveground biomass (AGB) and stem growth were susceptible to rainfall fluctuations, while belowground components (fine roots) showed correlation with one-month lagged rainfall. Furthermore, despite that northwestern Amazonia is considered relatively aseasonal, litterfall showed high seasonality in the loam-soil forest group, as well as the fine-root mass, particularly during the 2005 drought. Litterfall correlation with rainfall of sandy-loam terra-firme forest was time lagged as well as fine-root mass of the loamy-sand forest. The correlation between mortality and rainfall was weak, except for the loamy-sand forest (white-sand forest, 77%). High mortality rates occurred in the non-flooded forests for the censuses that included the dry years (2004–2005, 2005–2006). Interestingly, litterfall, AGB increment, and recruitment showed high correlation among forests, particularly within the loam-soil forest group. Nonetheless, leaf area index (LAI) measured in the most contrasting forests (clay and loamy-sand soil) was poorly correlated with rainfall, but highly correlated among them, which could be indicating a phenotypic response to the incident radiation in these sites; also, LAI did not reflect the differences in NPP components and their response to rainfall. Overall, the different temporal behavior of NPP components among forests in relation to rainfall fluctuations suggests the important role that soil exerts on the responses of plant species in each site, besides their effect on forest dynamics and community composition.
Modelling conduction delays in the corpus callosum using MRI-measured g-ratio

Conduction of action potentials along myelinated axons is affected by its structural features, such as the axonal g-ratio. The g-ratio is the ratio between the inner and outer diameters of the myelin sheath surrounding the axon. The effect of g-ratio variance on conduction properties has been quantitatively evaluated using single- axon models. It has recently become possible to estimate a g-ratio weighted measurement using quantitative MRI. Nevertheless, it is still unclear whether the variance in the g-ratio in the healthy human brain leads to significant differences in conduction velocity. In this work we tested whether the g-ratio MRI measurement can be used to predict conduction delays in the corpus callosum. We present a novel framework in which the structural properties of fibers (i.e. length and g-ratio, measured with MRI), are incorporated in a biophysical model of axon conduction, to predict conduction delays of long-range white matter fibers. We applied this framework to the corpus callosum, and found conduction delay estimates that are compatible with values generated more directly (∼15 ms). Furthermore, since studies that use response time and electrophysiology suggest an increase in conduction delays with age, we compared younger and older subjects. We investigated whether there are differences in the g-ratio and the fiber length between the age groups, and whether they lead to a difference in conduction delays. We found no significant differences between the predicted delays of the two groups. Our study provides a framework for predicting conduction latencies in vivo. The framework could have major implications for future studies of white matter diseases and large range network computations. Our results highlight the need for improving additional in vivo measurements of white matter microstructure.
Rainfall Prediction using Machine Learning & Deep Learning Techniques

In India, Agriculture is the key point for survival. For agriculture, rainfall is most important. These days rainfall prediction has become a major problem. Prediction of rainfall gives awareness to people and know in advance about rainfall to take certain precautions to protect their crop from rainfall. Many techniques came into existence to predict rainfall. Machine Learning algorithms are mostly useful in predicting rainfall. Some of the major Machine Learning algorithms are ARIMA Model(Auto-Regressive Integrated Moving Average), Artificial Neural Network, Logistic Regression, Support Vector Machine and Self Organizing Map. Two commonly used models predict seasonal rainfall such as Linear and Non-Linear models. The first models are ARIMA Model. While using Artificial Neural Network(ANN) predicting rainfall can be done using Back Propagation NN, Cascade NN or Layer Recurrent Network. Artificial NN is same as Biological Neural Networks.
Delinquency, Arrest and Early School Leaving*

Boys typically initiate delinquent behaviour during their teenage years, and many go on to be arrested. We show that engaging in delinquency and being arrested in youth are each associated with early school leaving. The effect of delinquency on school leaving is largely driven by crimes that produce a monetary return, and the increase in school leaving is greater when onset of these types of crime, and arrest, occur at younger ages. The sizeable impact of delinquency on school leaving highlights the need for crime prevention efforts to extend beyond youth who come into contact with the justice system.