Miracle-dz/UniFAR-FTUs huggingface dataset:
The Double-Time Protein Kinase Regulates the Subcellular Localization of the Drosophila Clock Protein Period

The Period (PER), Timeless (TIM), and Double-Time (DBT) proteins are essential components of one feedback loop in the Drosophila circadian molecular clock. PER and TIM physically interact. Coexpression of PER and TIM promotes their nuclear accumulation and influences the activity of DBT: although DBT phosphorylates and destabilizes PER, this is suppressed by TIM. Experiments using Drosophila cells in culture have indicated that PER can translocate to the nucleus without TIM and will repress transcription in a DBT-potentiated manner. In this study, we examined the control of PER subcellular localization in Drosophila clock cells in vivo.We found that PER can translocate to the nucleus in tim01 null mutants but only if DBT kinase activity is inhibited. We also found that nuclear PER is a potent transcriptional repressor in dbt mutants in vivo without TIM. Thus, in vivo, DBT regulates PER subcellular localization, in addition to its previously documented role as a mediator of PER stability. However, DBT does not seem essential for transcriptional repression by PER. It was reported previously that overexpression of a second kinase, Shaggy (SGG)/Glycogen Synthase Kinase 3, accelerates PER nuclear accumulation. Here, we show that these effects of SGG on PER nuclear accumulation require TIM. We propose a revised clock model that incorporates this tight kinase regulation of PER and TIM nuclear entry.
Response of Potato to Nitrogen and Potassium Fertilization

A study was undertaken to assess the technological gap, farmer's knowledge on crop husbandry and production and marketing constraints on banana enterprise in Nawalparasi district during June to July 2004. This study has involved a combination of methodologies such as in-situ observation, key informant survey, focus group discussion, Participatory Rural Appraisal and Rapid Market Appraisal conducted by multidisciplinary team and secondary data were used. The motive force behind farmers to shift from a predominantly maize based cropping system into cash generating banana enterprise was due to lack of irrigation facility. However, an overwhelming constraint to the development and expansion of commercial production for this enterprise is extreme marketing problem. The awareness of growers about constraints on marketing has been realized. The technological gap between the research and farmer's knowledge were also felt directly. The orchard size ranges from one Kattha to 2.5 Bighas (339 sq meters to 1.7 ha) of land and orchard age ranges from recently established to 10 years old with ratoon cropping system. Plant population ranges from 1800 to 2400 per ha. It was found that most of the farmers have adequately applied nitrogen and phosphorus but potash was far below the recommended dose. Small farmers having less than two Katthas (660 sq meters) of orchard size faced acute marketing problem than commercial farmers. It was realized that there has a paradox situation of plenty with scarcity in production and supply system. The peak period of production has heavily concentrated from December to March, when there has been very low market price at all the market centers. Analysis on low fruit quality and production, and objective tree to solve marketing problems has been discussed.
Extending the infrared radio correlation

Co-addition of deep (rms ∼ 30 μJy) 20-cm data obtained with the Australia Telescope Compact Array at the location of Spitzer Wide Field Survey (SWIRE) sources has yielded statistics of radio source counterparts to faint 24-μm sources in stacked images with rms < 1 μJy. We confirm that the infrared–radio correlation extends to f_(24 μm) = 100 μJy but with a significantly lower coefficient, f_(20 cm) = 0. 039f_(24 μm) [q_(24) = log (f_(24 μm)/f20 cm) = 1.39 ± 0.02] than hitherto reported. We postulate that this may be due to a change in the mean q_(24) value ratio for objects with f_(24 μm) < 1 mJy.
ICON : The Icosahedral Nonhydrostatic Modelling Framework of DWD and MPI -

This article gives an overview of the Icosahedral Nonhydrostatic (ICON) Modelling Framework, which is being developed in a collaboration between the German Weather Service (DWD) and Max-Planck Institute for Meteorology (MPI-M) in order to establish a unified modelling system for numerical weather prediction and climate modelling. After a brief description of the dynamical core, the grid-nesting approach and the physics parametrization package, a selection of idealized validation tests as well as NWP scores comparing ICON with the currently operational hydrostatic global model GME are presented. The results reveal that ICON achieves better skill scores at reduced computational cost. Moreover, it is shown that the dynamical core of ICON is well prepared for future use at truly nonhydrostatic scales, being able to cope with much steeper mountains than is typical for models with terrain-following coordinates.
Global oral health course: Perception among dental students in central India

A questionnaire study was conducted among dental students in Central India. The study population included 264 dental students, who voluntarily completed a questionnaire, comprising of 16 close ended questions. There were 9 questions to judge knowledge and 5 questions for attitude assessment towards global oral health course. Two additional questions were included to assess the willingness to volunteer in international setting; and also, to assess dental student’s perspection on global oral health course. Chi Square test was used to compare between categorical variables. Analysis of Variance (ANOVA) was used to compare mean of knowledge and attitude scores. P value of ⩽. 05 was considered significant for all statistical analysis. Eighty seven percent of the surveyed students (222) stated that they would consider volunteering their dental skills as a future dentist in international setting. Majority of the students in the present study were not aware about the global oral health status (99.2%) and theoral health care systems of industrialized and emerging economies (99.2%), had not been trained to serve underserved population (68%), had not been trained in global health ethics (70.1%) and none of the students had been trained for cultural competence in addressing international oral health issues (100%). Most of the dental students were not aware, that, WHO created basic package of oral care (63%) about the primary health care strategy (59.5%) and about the role and functions of FDI (66.7%). The majority of students expressed a desire to volunteer their professional services in international settings. However few students knew about WHO’s BPOC or FDI’S role in global oral health. The findings indicate a need for global oral health course among dental students in Central India.
China's Outward Direct Investment in Africa

The empirical determinants of China's outward direct investment (ODI) in Africa are examined using an officially approved ODI dataset and a relatively new OECD–IMF format ODI dataset. China's ODI is found responding to the canonical economic determinants that include the market seeking motive, the risk factor, and the resources seeking motive. It is also affected by the intensity of trade ties and the presence of China's contracted projects. A host country's natural resources have an impact on China's decision on how much to invest in the country rather than on whether to invest in the country or not. China's drive for Africa's natural resources is mainly a recent phenomenon and, probably, became prominent after the “Going Global” policy adopted in 2002.
USING INSTANCE-SPECIFIC AND CLASS-CONSISTENT CUES

We aim to resolve the difficulties of action recognition arising from the large intra-class variations. These unfavorable variations make it infeasible to represent one action instance by other ones of the same action. We hence propose to extract both instance-specific and class-consistent features to facilitate action recognition. Specifically, the instance-specific features explore the self-similarities among frames of each video instance, while class-consistent features summarize withinclass similarities. We introduce a generative formulation to combine the two diverse types of features. The experimental results demonstrate the effectiveness of our approach.
Use of concept maps to analyze students' understanding of the I/O subsystem

The Input/Output topic is mandatory in the Computer Architecture branch of the computing curricula. However, in our experience it is a rather complex topic for the students to understand. This paper presents the process followed to analyze the concept maps built by the students at the end of the "Computer Structure" subject, in the second semester of the degree course. The analysis process is explained because we had to adapt the software used in other disciplines to our needs. Merging all the concept maps showed that some relationships were missing, some were very messy and others were very strong. Based on the results achieved, some points need to be reinforced during the learning process.
A pilot study of robotic-assisted exercise for hand weakness after stroke

Upper limb paresis is a major source of disability in stroke survivors, and robotic aided exercise therapy is a promising approach to enhance motor abilities. Few devices have been available to provide robotic therapy to the fingers and hand. We report an open-label pilot study of 12 individuals with chronic moderate hemiparesis after stroke who underwent a six-week training program using a hand robotic device. Participants received a total of 18 hours of robotic therapy. Improvements were found in multiple measures of motor performance, including the Upper Extremity Fugl-Meyer, the Motor Activity Log, the Manual Ability Measure-36, and the Jebsen Hand Function Test. All subjects tolerated the treatment well and no complications were observed. We conclude that robotic therapy for hand paresis after stroke is safe and feasible, and that further studies of efficacy are justified by these preliminary results.
Low-Overhead Self-Healing Methodology for Current Matching in Current-Steering DAC

In this brief, a low-overhead self-healing method for current matching in current-steering digital-to-analog converters (CS-DACs) is demonstrated. In contrast to traditional calibration methods that adjust current values, a statistical element selection (SES) algorithm optimizes the selection of unary current cells via combinatorial redundancy. This SES-based self-healing method relaxes the matching requirements for the current source array and achieves high static linearity at a minimum overhead cost of one current comparator and one digital controller. Moreover, this proposed low-overhead method is fully compatible with other segmented CS-DAC designs. A 14-bit CS-DAC design with on-chip self-healing control loop was implemented in 130-nm CMOS technology to demonstrate the proposed approach. The core area of the prototype chip was measured as 0.9 mm2, with less than 0.1 mm2 occupied by the current source array. After self-healing, the INLmax was measured as 0.64 least significant bit and spurious-free dynamic range was 85 dB for a 2-MHz input signal at 200-MS/s sampling rate.
Computationally and Statistically Efficient Truncated Regression

We provide a computationally and statistically efficient estimator for the classical problem of truncated linear regression, where the dependent variable $y = w^T x + \epsilon$ and its corresponding vector of covariates $x \in R^k$ are only revealed if the dependent variable falls in some subset $S \subseteq R$; otherwise the existence of the pair $(x, y)$ is hidden. This problem has remained a challenge since the early works of [Tobin 1958, Amemiya 1973, Hausman and Wise 1977], its applications are abundant, and its history dates back even further to the work of Galton, Pearson, Lee, and Fisher. While consistent estimators of the regression coefficients have been identified, the error rates are not well-understood, especially in high dimensions. Under a thickness assumption about the covariance matrix of the covariates in the revealed sample, we provide a computationally efficient estimator for the coefficient vector $w$ from $n$ revealed samples that attains $l_2$ error $\tilde{O}(\sqrt{k/n})$. Our estimator uses Projected Stochastic Gradient Descent (PSGD) without replacement on the negative log-likelihood of the truncated sample. For the statistically efficient estimation we only need oracle access to the set $S$. In order to achieve computational efficiency we need to assume that $S$ is a union of a finite number of intervals but still can be complicated. PSGD without replacement must be restricted to an appropriately defined convex cone to guarantee that the negative log-likelihood is strongly convex, which in turn is established using concentration of matrices on variables with sub-exponential tails. We perform experiments on simulated data to illustrate the accuracy of our estimator. As a corollary, we show that SGD learns the parameters of single-layer neural networks with noisy activation functions.
Machine learning-based prediction of drug-drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties.

OBJECTIVE Drug-drug interactions (DDIs) are an important consideration in both drug development and clinical application, especially for co-administered medications. While it is necessary to identify all possible DDIs during clinical trials, DDIs are frequently reported after the drugs are approved for clinical use, and they are a common cause of adverse drug reactions (ADR) and increasing healthcare costs. Computational prediction may assist in identifying potential DDIs during clinical trials. METHODS Here we propose a heterogeneous network-assisted inference (HNAI) framework to assist with the prediction of DDIs. First, we constructed a comprehensive DDI network that contained 6946 unique DDI pairs connecting 721 approved drugs based on DrugBank data. Next, we calculated drug-drug pair similarities using four features: phenotypic similarity based on a comprehensive drug-ADR network, therapeutic similarity based on the drug Anatomical Therapeutic Chemical classification system, chemical structural similarity from SMILES data, and genomic similarity based on a large drug-target interaction network built using the DrugBank and Therapeutic Target Database. Finally, we applied five predictive models in the HNAI framework: naive Bayes, decision tree, k-nearest neighbor, logistic regression, and support vector machine, respectively. RESULTS The area under the receiver operating characteristic curve of the HNAI models is 0.67 as evaluated using fivefold cross-validation. Using antipsychotic drugs as an example, several HNAI-predicted DDIs that involve weight gain and cytochrome P450 inhibition were supported by literature resources. CONCLUSIONS Through machine learning-based integration of drug phenotypic, therapeutic, structural, and genomic similarities, we demonstrated that HNAI is promising for uncovering DDIs in drug development and postmarketing surveillance.
Enhancement of DNA ligase I level by gemcitabine in human cancer cells.

PURPOSE DNA ligase I is an essential enzyme for completing DNA replication and DNA repair by ligating Okazaki fragments and by joining single-strand breaks formed either directly by DNA-damaging agents or indirectly by DNA repair enzymes, respectively. In this study, we examined whether the DNA ligase I level could be modulated in human tumor cell lines by treatment with gemcitabine (2', 2'-difluoro-2'-deoxycytidine), which is a nucleoside analogue of cytidine with proven antitumor activity against a broad spectrum of human cancers in clinical studies. EXPERIMENTAL DESIGN To determine the effect of gemcitabine on DNA ligase I expression, Western blot analysis was used to measure the DNA ligase I levels in MiaPaCa, NGP, and SK-N-BE cells treated with different concentrations of gemcitabine and harvested at different time intervals. Cell cycle analysis was also performed to determine the underlying mechanism of DNA ligase I level enhancement in response to gemcitabine. In addition, other agents that share the same mechanism of action with gemcitabine were used to elucidate further details. RESULTS When different types of tumor cell lines, including MiaPaCa, NGP, and SK-N-BE, were treated with gemcitabine, the level of DNA ligase I increased severalfold despite significant cell growth inhibition. In contrast, other DNA ligases (III and IV) either remained unchanged or decreased with treatment. Cell cycle analysis showed that arrest in S-phase corresponded to an increase of DNA ligase I levels in gemcitabine treated cells. Other agents, such as 1-beta-D-arabinofuranosylcytosine and hydroxyurea, which partly share mechanisms of action with gemcitabine by targeting DNA polymerases and ribonucleotide reductase, respectively, also caused an increase of DNA ligase I levels. However, 5-fluorouracil, which predominantly targets thymidylate synthase, did not cause an increase of DNA ligase I level. CONCLUSIONS Our results suggest that an arrest of DNA replication caused by gemcitabine treatment through incorporation of gemcitabine triphosphate into replicating DNA and inhibition of ribonucleotide reductase would trigger an increase in DNA ligase I levels in cancer cells. The elevated presence of DNA ligase I in S-phase-arrested cells leads us to speculate that DNA ligase I might have an important role in repairing DNA damage caused by stalled replication forks.
On the Role of Triadic Substructures in Complex Networks

In the course of the growth of the Internet and due to increasing availability of data, over the last two decades, the field of network science has established itself as an own area of research. With quantitative scientists from computer science, mathematics, and physics working on datasets from biology, economics, sociology, political sciences, and many others, network science serves as a paradigm for interdisciplinary research. One of the major goals in network science is to unravel the relationship between topological graph structure and a network's function. As evidence suggests, systems from the same fields, i.e. with similar function, tend to exhibit similar structure. However, it is still vague whether a similar graph structure automatically implies likewise function. This dissertation aims at helping to bridge this gap, while particularly focusing on the role of triadic structures. After a general introduction to the main concepts of network science, existing work devoted to the relevance of triadic substructures is reviewed. A major challenge in modeling such structure is the fact that not all three-node subgraphs can be specified independently of each other, as pairs of nodes may participate in multiple triadic subgraphs. In order to overcome this obstacle, a novel class of generative network models based on pair-disjoint triadic building blocks is suggested. It is further investigated whether triad motifs - subgraph patterns which appear significantly more frequently than expected at random - occur homogeneously or heterogeneously distributed over graphs. Finally, the influence of triadic substructure on the evolution of dynamical processes acting on their nodes is studied. It is observed that certain motifs impose clear signatures on the systems' dynamics, even when embedded in a larger network structure.
Establishment , growth and development of plantain and chicory under grazing

Pasture herbs can increase pasture production and feed quality over summer when ryegrass based pasture often constrains livestock production. The growth and development of plantain (‘Ceres Tonic’), chicory (‘Choice’) and red clover (‘Redmore’) were related to thermal time during establishment. The time to first grazing, with sheep, was 8, 12, or 19 weeks from an autumn sowing. After 8 weeks there was > 30 % plant loss for all species compared with a loss of 3% and 13% at 19 weeks for plantain and chicory, respectively. Plantain and chicory required a minimum of six and seven true leaves, respectively, for sufficient root growth for plant survival after grazing. Modelling showed that plantain and chicory need to be sown before mid-March in Manawatu to be ready for their first grazing before winter. In their first year, plantain produced 17 t DM/ha and chicory 14 t DM/ha.
Chronic Hypokalemia and Intraoperative Dysrhythmias

To investigate whether chronic hypokalemia increases the occurrence of dysrhythmias during anesthesia, the authors recorded the intraoperative electrocardiograms of normokalemic (K+ = 5.0 - 3.5 mEq/1; N = 88) and chronically hypokalemic patients (K+ = 3.4 - 2.6 mEq/1; N = 62). In each patient, serum potassium was measured and a 12-lead ECG was analyzed prior to surgery. No patient received potassium perioperatively. Lead II was monitored continuously during anesthesia, either by a Holter monitor (N = 81) or by a trained observer (N = 69). A variety of general anesthetic techniques were utilized, without consideration for the potassium level. The hypokalemic population had a higher incidence of hypertensive and ASA Class III patients (P = 0.03). Analysis of variance revealed no significant difference in the incidence of other characteristics between the hypokalemic and normokalemic groups: age, hypoxemia, cardiac disease, preoperative dysrhythmias, digitalis therapy, surgical site, anesthetic agent, and intubation. The method of ECG monitoring did not affect the incidence of dysrhythmias recorded. Multivariate analysis revealed that the occurrence of intraoperative dysrhythmias correlated with the presence of preoperative dysrhythmias only. The authors conclude that chronic hypokalemia per se is not associated with a higher incidence of intraoperative dysrhythmias.
Strategies used to manage climatic risk: Lessons from farmers with expertise in dryland farming

The management practices used by two brothers on their high performing summer-dry semi-finishing sheep and cattle farm were investigated over 2 1/2 years (2006– 2008). The study highlighted that in a dryland environment, the farmers designed their system to cope with both climatic variability and market risk. To reduce production risk, the farmers have strategies that increase feed supply over the summer autumn, and transfer feed from the spring to the summer, autumn and winter periods. Their strategies are designed to significantly reduce feed demand over the summer autumn, protect capital stock live weights and ensure adequate pasture cover levels at lambing. To reduce market risk, the farmers have strategies that allow the bulk of stock to be sold prime and in periods when most other farmers are not selling stock. An important element of their market risk strategy is the generation of adequate stocks of feed reserves that can be used to delay stock sales in a drought until markets improve.