Miracle-dz/UniFAR-FTUs huggingface dataset:
INFLUENCIA DEL ACEITE DE EUCALIPTO EN LOS COMPONENTES QUÍMICOS, PRODUCCIÓN DE GAS Y DEGRADABILIDAD DEL RASTROJO DE MAÍZ Y PAJA DE AVENA

The effects of eucalyptus oils on ruminal fermentation of two agro-industry byproducts (corn stalk and oat straw), were studied using the in vitro gas production (GP) technique. Eucalyptus oil was added at 0, 30, 90, and 180 mg/l of incubation medium (equal to 0, 1.2, 3.6, and 7.2 mg/g DM substrate). Gas volumes were recorded at 2, 4, 6, 8, 10, 12, 24, 36, 48 and 72 h of incubation, and substrate DM, neutral detergent fiber (NDF) and acid detergent fiber (ADF) degradability were determined at 72 h of incubation. Eucalyptus oil increased (P<0.05) the asymptotic GP and GP of corn stalks and oat straw. Eucalyptu oil decreased fermentation pH (P<0.05) of corn stalks and oat straw. The inclusion of eucalyptu oil increased (P<0.05) DM degradability of corn stalks, oat straw. Eucalyptus oil decreased NDF degradability of corn stalks, with weak effects on NDF degradabilitie of oat straw. It can conclude that the application of eucalyptu oil positively affected rumen fermentation of the two agro-industry byproducts as roughage feeds. Increasing the dose of oils inclusion, enhanced the fermentation parameters; where the dose 180 mg oil/l increased GP, while the doses 30 and 90 mg oil/l increased nutrients digestibility.
Design Methodology for Human Symbiotic Machines Based on the Description of User's Mental Model

∗1Department of Mechanical Engineering, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan E-mail: fukui@hnl.t. u-tokyo.ac. jp ∗2Komatsu, Ltd. 2-3-6 Akasaka, Minato-ku, Tokyo 107-8414, Japan E-mail: kousaka@ics.t. u-tokyo.ac. jp ∗3The University of Tokyo Future Center Initiative 227-6 Wakashiba, Kashiwa-shi, Chiba 277-0871, Japan E-mail: tomomasasato@jcom.home. ne.jp ∗4Department of Mechano-Informatics, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan E-mail: simosaka@ics.t. u-tokyo.ac. jp
SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications

The Internet of Things (IoT) has gained popularity in recent years. Today’s IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. In cloud data center networks (DCN), TCP incast usually happens when multiple senders simultaneously communicate with a single receiver. However, when TCP incast happens, DCN may suffer from both throughput collapse for TCP burst flows and temporary starvation for TCP background flows. In this paper, we propose a software defined network (SDN)-based TCP congestion control mechanism, referred to as SDTCP, to leverage the features, e.g., centralized control methods and the global view of the network, in order to solve the TCP incast problems. When we detect network congestion on an OpenFlow switch, our controller can select the background flows and reduce their bandwidth by adjusting the advertised window of TCP ACK packets of the corresponding background flows so as to reserve more bandwidth for burst flows. SDTCP is transparent to the end systems and can accurately decelerate the rate of background flows by leveraging the global view of the network gained via SDN. The experiments demonstrate that our SDTCP can provide high tolerance for burst flows and achieve better flow completion time for short flows. Therefore, SDTCP is an effective and scalable solution for the TCP incast problem.
POLAR 2.0: An effective routability-driven placer

A wirelength-driven placer without considering routability would lead to unroutable results. To mitigate routing congestion, there are two basic approaches: (1) minimizing the routing demand; (2) distributing the routing demand properly. In this paper, we propose a new placer POLAR 2.0 emphasizing both approaches. To minimize the routing demand, POLAR 2.0 attaches very high importance to maintaining a good wirelength-driven placement in the global placement stage. To distribute the routing demand, cells in congested regions are spread out by a novel routability-driven rough legalization in a global manner and by a history based cell inflation technique in a local manner. The experimental results based on ICCAD 2012 contest benchmark suite show that POLAR 2.0 outperforms all published academic routability-driven placers both in runtime and quality.
On the application of a psychoacoustically motivated speech-quality measure in CELP speech-coding

The crucial task in a CELP speech codec consists of finding the optimal excitation vector for the synthesis filter. This is usually done in an `analysis-by-synthesis' structure by minimizing the mean-square error of the original and the coded/decoded speech frame. It is a common assumption that distance measures other than MSE and adapted to the human auditory perception should result in better speech quality. Such measures could be based on scientific results provided by psychoacoustics. However, due to the computational load there is no possibility to implement complex psychoacoustical models in real-time speech codecs and, for the time being, we are restricted to the MSE. Nevertheless, it is interesting to study the potential of psychoacoustic distance measures to improve speech codecs if complexity restrictions are neglected. This paper shows how a psychoacoustics-based distance measure can be integrated into a CELP codec, and the unexpected results are presented.
Coupling Power Losses in Inductive Power Transfer Systems With Litz-Wire Coils

Inductive power transmission (IPT) systems are composed of at least one transmitter coil and one receiver coil. The efficiency of these systems is determined by the power losses in both coils due to two phenomena: conduction losses and proximity losses. Proximity losses depend on the current densities induced in the winding by the magnetic fields of the system. Some analytical models of efficiency in IPT systems have been proposed in the past, but these methods only consider the proximity losses for isolated coils. However, the mutual coupling between the magnetic fields of both coils must be taken into account to achieve accurate power losses estimation. In this paper, the effect of the coupling power losses in multiple coil systems is fully described based in part on the results of previous works. Finally, model based simulation results are compared to experimental measurements to verify the proposed analysis.
Effects of School Closure on Incidence of Pandemic Influenza in Alberta, Canada

BACKGROUND Control of pandemic influenza by social-distancing measures, such as school closures, is a controversial aspect of pandemic planning. However, investigations of the extent to which these measures actually affect the progression of a pandemic have been limited. OBJECTIVE To examine correlations between the incidence of pandemic H1N1 (pH1N1) influenza in Alberta, Canada, in 2009 and school closures or weather changes, and to estimate the effects of school closures and weather changes on pH1N1 transmission. DESIGN Mathematical transmission models were fit to data that compared the pattern of confirmed pH1N1 cases with the school calendar and weather patterns. SETTING Alberta, Canada, from 19 April 2009 to 2 January 2010. DATA SOURCES 2009 virologic test results, 2006 census data, 2009 daily temperature and humidity data, and 2009 school calendars. MEASUREMENTS Age-specific daily counts of positive results for pH1N1 from the complete database of 35 510 specimens submitted to the Alberta Provincial Laboratory for Public Health for virologic testing from 19 April 2009 to 2 January 2010. RESULTS The ending and restarting of school terms had a major effect in attenuating the first wave and starting the second wave of pandemic influenza cases. Mathematical models suggested that school closure reduced transmission among school-age children by more than 50% and that this was a key factor in interrupting transmission. The models also indicated that seasonal changes in weather had a significant effect on the temporal pattern of the epidemic. LIMITATIONS Data probably represent a small sample of all viral infections. The mathematical models make simplifying assumptions in order to make simulations and analysis feasible. CONCLUSION Analysis of data from unrestricted virologic testing during an influenza pandemic provides compelling evidence that closing schools can have dramatic effects on transmission of pandemic influenza. School closure seems to be an effective strategy for slowing the spread of pandemic influenza in countries with social contact networks similar to those in Canada. PRIMARY FUNDING SOURCE Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Public Health Agency of Canada.
Responses of Maximal Aerobic Power and Capacity to Aerobic Training

The purpose of this experiment was to investigate the individual differences and the specificity in the response of maximal aerobic power (MAP) and capacity (MAC) to a 20-week aerobic training program. Twenty-four subjects (25 +/- 4 years), ascertained as sedentary, including 13 women and 11 men, participated in this study. MAP was determined with a progressive maximal ergocycle test, while MAC was computed as the total work output accomplished during a 90-min maximal ergocycle test. A modified bicycle ergometer allowed the exact measurement of the distance and the load for the computation of the work performed during MAC. The aerobic training program enhanced mean MAP/kg and MAC/kg by 33% and 51%, respectively. Although MAP/kg response to training was similar in both sexes, there was a sex difference in the response of MAC/kg, men improving 50% more than women. Individual differences in the response to the standardized training program were considerable with training gains ranging from 5% to 88% for MAP/kg and from 16% to 97% for MAC/kg. Correlations between training increments in MAP/kg with those in MAC/kg were rather low ranging from 0.28 to 0.44. These results indicate that there is a sex difference in the trainability of aerobic capacity, but not of maximal aerobic power, under the same 20-week aerobic training program. Moreover, large individual differences in the response to similar aerobic training are observed in sedentary persons, suggesting that certain genotypes are more sensitive to training than others. Finally, there is a high level of specificity in the response to training of the power and of the capacity of the aerobic energy metabolism.
Comprehensive detection and characterization of human druggable pockets through novel binding site descriptors

Druggable pockets are protein regions that have the ability to bind organic small molecules, and their characterization is essential in target-based drug discovery. However, strategies to derive pocket descriptors are scarce and usually exhibit limited applicability. Here, we present PocketVec, a novel approach to generate pocket descriptors for any protein binding site of interest through the inverse virtual screening of lead-like molecules. We assess the performance of our descriptors in a variety of scenarios, showing that it is on par with the best available methodologies, while overcoming some important limitations. In parallel, we systematically search for druggable pockets in the folded human proteome, using experimentally determined protein structures and AlphaFold2 models, identifying over 32,000 binding sites in more than 20,000 protein domains. Finally, we derive PocketVec descriptors for each small molecule binding site and run an all-against-all similarity search, exploring over 1.2 billion pairwise comparisons. We show how PocketVec descriptors facilitate the identification of druggable pocket similarities not revealed by structure- or sequence-based comparisons. Indeed, our analyses unveil dense clusters of similar pockets in distinct proteins for which no inhibitor has yet been crystalized, opening the door to strategies to prioritize the development of chemical probes to cover the druggable space.
A comprehensive comparative study on term weighting schemes for text categorization with support vector machines

Term weighting scheme, which has been used to convert the documents as vectors in the term space, is a vital step in automatic text categorization. In this paper, we conducted comprehensive experiments to compare various term weighting schemes with SVM on two widely-used benchmark data sets. We also presented a new term weighting scheme tf-rf to improve the term's discriminating power. The controlled experimental results showed that this newly proposed tf-rf scheme is significantly better than other widely-used term weighting schemes. Compared with schemes related with tf factor alone, the idf factor does not improve or even decrease the term's discriminating power for text categorization.
Neural correlates in the time course of inferences: costs and benefits for less-skilled readers at the university level

Inferences are an indicator of a greater reading comprehension, as they imply a combination of implicit and explicit information that usually combines a textual representation with background knowledge of the reader. The aim of this study is to explore the costs and benefits of the time course of inferences in university students with reading comprehension difficulties at 3 stages during a narration. The method used was the event-related potential (ERP) technique in order to register the brain activity of 63 teaching program students while they read familiar, less-familiar and neutral stories. Results show a slow negativity potential component with greater negativity in words coming from familiar contexts when compared to less familiar and neutral ones in the first locus; an N400 component and a Post-N400 component in the second locus, reflecting greater negativity in familiar contexts when compared to less-familiar ones; and, lastly, through the use of a lexical decision task, FN400 and N400 components were found in the third locus, especially for pseudowords. These results are interpreted as a preferably bottom-up processing, which is characterized by lexical access difficulties in less-skilled readers.
Impact of large‐scale EV integration and fast chargers in a Norwegian LV grid

Norway has implemented economic incentives over several years to encourage a transition from conventional vehicles to electric vehicles (EVs), and now has the largest share of EVs per capita in the world. In this study, the authors explore the impacts of increasing EV penetration levels in a Norwegian distribution grid, by using real power measurements obtained from household smart meters in load flow analyses. The implications of installing a fast charger in the grid have been assessed, and an optimal location for it is proposed, aiming at minimising both grid losses and voltage deviations. Moreover, the potential for reactive power injection to reduce the voltage deviations caused by fast chargers has been investigated. Results show that the EV hosting capacity of the grid is good for a majority of the end-users, but the weakest power cable in the system will be overloaded at a 20% EV penetration level. The network tolerated an EV penetration of 50% with regard to the voltage levels at all end-users. Injecting reactive power at the location of an installed fast charger proved to significantly reduce the largest voltage deviations otherwise imposed by the charger.
Hairpin-RNA Spray Confers Resistance to Mungbean Yellow Mosaic India Virus in Mungbean

The prevalence of Begomovirus diseases poses a significant threat to legume crops, necessitating the exploration of innovative control measures. This investigation explores the utilization of dsRNA molecules to initiate RNA interference (RNAi) targeting begomovirus, particularly focusing on Mungbean yellow mosaic India virus (MYMIV) and its potential threat to mungbean crops. Given the lack of genetic resistance in commercially available mungbean varieties, the study endeavors to employ RNAi as a strategic method for the effective control of MYMIV. The approach involves the preparation of vectors for the transient expression of three dsRNA targeting multiple overlapping ORFs of MYMIV DNA A through agroinoculation, and the selection of a highly efficient construct for dsRNA expression in bacteria, enabling topical application to mungbean plants in growth chamber experiments. Agroinoculation assays demonstrate effective resistance against MYMIV, as confirmed by reduced symptom severity, limited virus accumulation, and the presence of viral mRNAs. The stability of the prepared dsRNA against nucleases is confirmed, showcasing its ability to enter plant cells, move to non treated trifoliate leaves, and form siRNA when sprayed onto mungbean leaves, as validated by qRT-PCR and northern blotting. Varied combinations of the timing of dsRNA spray and virus infection reveal differential resistance against the virus. Notably, spraying two days before or on the same day as virus exposure emerges as the most suitable time to achieve optimal resistance against virus infection. In light of these findings, the topical application of dsRNAs stands out as a promising and effective strategy for MYMIV control in mungbean crops.
Sports injuries and illnesses during the second Asian Beach Games

Background Prevention of sport injuries and illnesses is a focus for epidemiological surveillance. Objectives To record and analyse all sports injuries and illnesses registered during the second Asian Beach Games. Design A descriptive epidemiological study using the International Olympic Committee Surveillance system to register injuries and illnesses during the second Asian Beach Games. Methods The second Asian Beach Games hosted 1132 athletes from 43 countries competing in 14 beach sports. All National Olympic Committees' physicians of the participating teams were invited to report all injuries and illnesses. In addition, medical officers at the different Olympic venues and the main Olympic village reported injuries and illnesses treated at the clinics on a daily basis. Results A total of 177 injuries were reported equating to an incidence rate of 156.4 per 1000 registered athletes. Tent pegging recorded the highest incidence of injuries with 357 per 1000 registered athletes. The most prevalent injuries were in the foot/toe with 14.1% of all reported injuries. The majority of injuries were incurred during competition (75.4%). In addition, the most common mechanism of injury was contact with another athlete (n=42, 23.7%) and combined sudden and gradual overuse contributed to 30% of the total injury burden. Furthermore, 118 illnesses were reported resulting in an incidence rate of 104.2 illnesses per 1000 registered athletes. The most affected system was the respiratory tract (39.1%) with infection being the most common cause (n=33, 38.0%). The incidence of injury and illness differed significantly among the 14 sports. Conclusion The data indicate that the risk of injury from beach games is sport dependant. This means that any preventive measures have to be tailored for each discipline. Furthermore, the study showed that respiratory infections are the commonest illness in beach sports and therefore, event organisers should focus improving public health measures and hygiene awareness.
Biophysics-based protein language models for protein engineering

Protein language models trained on evolutionary data have emerged as powerful tools for predictive problems involving protein sequence, structure, and function. However, these models overlook decades of research into biophysical factors governing protein function. We propose Mutational Effect Transfer Learning (METL), a protein language model framework that unites advanced machine learning and biophysical modeling. Using the METL framework, we pretrain transformer-based neural networks on biophysical simulation data to capture fundamental relationships between protein sequence, structure, and energetics. We finetune METL on experimental sequence-function data to harness these biophysical signals and apply them when predicting protein properties like thermostability, catalytic activity, and fluorescence. METL excels in challenging protein engineering tasks like generalizing from small training sets and position extrapolation, although existing methods that train on evolutionary signals remain powerful for many types of experimental assays. We demonstrate METL’s ability to design functional green fluorescent protein variants when trained on only 64 examples, showcasing the potential of biophysics-based protein language models for protein engineering.
Wind turbine wakes: exploring the underexplored

In this thesis, we aim to contribute to the research on two wind energy topics, namely, vertical-axis wind turbines (VAWTs) and wind turbines on topography. Although these two topics may seem too distant to be reconciled in one thesis, as the title of the thesis suggests, the common feature that they share with each other is that both of them are among the topics that have benefited from relatively little research and development in the wind energy community. In the VAWT part, first, we adapt and implement two actuator-type VAWT parameterization models (i.e. the actuator swept-surface model and the actuator line model) for use in numerical flow simulations with the purpose of studying the wakes of VAWTs and their performance in the atmospheric boundary layer (ABL) and eventually predicting the flow in sizable wind farms. These models are implemented in a large-eddy simulation (LES) framework, and the results are validated with experimental data. After validating the model, we investigate the energetic performance and wake structure of a megawatt-VAWT which is placed in the ABL. We characterize, in particular, the energetic performance of such a turbine by calculating the power coefficient of the turbine for more than 100 different combinations of tip-speed ratios and blade chord lengths (i.e. different solidities). The optimum combination of solidity (defined as Nc/R, where N is the number of blades, c is the chord length and R is the rotor radius) and tip-speed ratio is found to be 0.18 and 4.5, respectively. This combination results in a power coefficient of 0.47. In the topography part, we implement the actuator disk model (to parameterize the effect of wind turbines) together with the coordinate transformation method (to resolve the topography) in our LES framework to simulate a wind farm sited on topography and also to validate our LES framework for turbine-topography systems with wind-tunnel measurements. Next, we consider the effect of pressure gradient (which is an important effect created by topography) on turbulent planar and axisymmetric wakes. For both cases, we develop analytical models to predict the wake evolution in pressure gradient conditions. The models are based on the cross-stream integration of the streamwise momentum equation and use the self-similarity of the mean flow. We also make an experimentally-supported assumption that the ratio of the maximum velocity deficit to the wake width is independent of the imposed pressure gradient. The models are validated with both experimental and LES data. Furthermore, in the last study of the topography part, we build on all of the previous accomplishments to give a better picture of what happens to a turbine wake when it