Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Brain Networks of Complex Problem Solving

Complex problem solving is a high level cognitive process which has been thoroughly studied over the last decade. The Tower of London (TOL) is a task that has been widely used to study problem-solving. In this study, we aim to explore the underlying cognitive network dynamics among anatomical regions of complex problem solving and its sub-phases, namely planning and execution. A new brain network construction model establishing dynamic functional brain networks using fMRI is proposed. The first step of the model is a preprocessing pipeline that manages to decrease the spatial redundancy while increasing the temporal resolution of the fMRI recordings. Then, dynamic brain networks are estimated using artificial neural networks. The network properties of the estimated brain networks are studied in order to identify regions of interest, such as hubs and subgroups of densely connected brain regions. The major similarities and dissimilarities of the network structure of planning and execution phases are highlighted. Our findings show the hubs and clusters of densely interconnected regions during both subtasks. It is observed that there are more hubs during the planning phase compared to the execution phase, and the clusters are more strongly connected during planning compared to execution.
Marker-trait associations in two-rowed spring barley accessions from Kazakhstan and the USA

In this study, phenotyping and single nucleotide polymorphism (SNP) genotyping data of 272 accessions of two-rowed spring barley from the USA along with 94 accessions from Kazakhstan were assessed in field trials at six breeding organizations in Kazakhstan to evaluate the performance of the USA samples over three years (2009–2011). The average grain yield over the six locations was not significantly higher in Kazakh accessions in comparison to the USA samples. Twenty four samples from Montana, Washington, the USDA station in Aberdeen Idaho, and the Anheuser-Busch breeding programs showed heavier average yield than the local standard cultivar “Ubagan”. Principal Coordinate analysis based on two sets of SNP data suggested that Kazakh accessions were closest to the USA accessions among eight groups of samples from different parts of the World, and within five US barley origin groups the samples from Montana and Washington perfectly matched six groups of Kazakh breeding origins. A genome-wide association study (GWAS) using data from eighteen field trials allowed the identification of ninety one marker-trait associations (MTA) in two or more environments for nine traits, including key characters such as heading time (HT), number of kernels per spike (NKS), and thousand grain weight (TGW). Our GWAS allowed the identification of eight MTA for HT and NKS, and sixteen MTA for TGW, when those MTA were linked to mapped SNPs. Based on comparisons of chromosomal positions of MTA identified in this study, and positions of known genes and quantitative trait loci for HT, NKS and TGW, it was suggested that MTA for HT on chromosome 2H (at 158.2 cM, 11_21414), MTA for NKS on 5H (at 118.6 cM, 11_20298), and two MTA for TGW on chromosome 4H (at 94.7 cM, 12_30718, and at 129.3 cM, 11_20013) were potentially new associations in barley. GWAS suggested that six MTA for HT, including two on chromosome 1H, two on chromosome 3H, and one each on chromosomes 4H and 6H, had useful pleiotropic effects for improving barley spike traits.
Histological Features of the Olive Seed and Presence of 7S-Type Seed Storage Proteins as Hallmarks of the Olive Fruit Development

The production of olive oil is an important economic engine in the Mediterranean area. Nowadays, olive oil is obtained mainly by mechanical processes, by using the whole fruit as the primary raw material. Although the mesocarp is the main source of lipids contributing to olive oil formation, the seed also contributes to the olive oil composition and attributes. The olive seed is also becoming an interesting emerging material itself when obtained after alternative processing of the olive fruit. Such seed is used for the production of differential oil and a unique flour among other bioactive products, with increasing uses and applications in cosmetics, nutrition, and health. However, olive seed histology has been poorly studied to date. A complete description of its anatomy is described for the first time in the present study by using the ‘Picual’ cultivar as a model to study the development of the different tissues of the olive seed from 60 to 210 days after anthesis. A deep analysis of the seed coats, endosperm storage tissue and the embryo during their development has been performed. Moreover, a panel of other olive cultivars has been used to compare the weight contribution of the different tissues to the seed, seed weight variability and the number of seeds per fruit. In addition to the histological features, accumulation of seed storage proteins of the 7S-type (β-conglutins) in the seed tissues has been assessed by both biochemical and immunocytochemical methods. These hallmarks will help to settle the basis for future studies related to the location of different metabolites along the olive seed and mesocarp development, and therefore helping to assess the appropriate ripening stage for different commercial and industrial purposes.
Path Loss Model for UAV-Assisted RFET

In this letter, we develop channel models for unmanned aerial vehicle-aided air-to-ground (AtG) radio frequency energy transfer (RFET). AtG path loss plays a key role in RFET-based recharging of field nodes. Representative field environments consist of different types of built-up areas, namely, suburban, urban, dense urban, urban high-rise, and rural agriculture deployment scenarios. For emulating the built-up areas, ITU-R recommendations are considered, whereas for rural agricultural field deployment scenario, dynamics of vegetation growth with time is considered. Accuracy of the proposed path loss models are validated by conducting real AtG radio frequency transmission experiments in emulated suburban and agricultural fields.
Verification of the Injection Enhancement Effect in IGBTs by Measuring the Electron and Hole Currents Separately

The injection enhancement effect in IGBTs was experimentally verified by separately measuring emitter electron-and hole-currents for the first time. Finger contacts were employed as ladder-like periodic n+ and p+ emitters to allow the independent measurement of these currents. Both reducing the mesa width and increasing the cell pitch were found to increase electron injection from the emitter, demonstrating the injection enhancement effect. These experimental results agreed well with the simulation results.
Gene‐specific criteria for PTEN variant curation: Recommendations from the ClinGen PTEN Expert Panel

The ClinGen PTEN Expert Panel was organized by the ClinGen Hereditary Cancer Clinical Domain Working Group to assemble clinicians, researchers, and molecular diagnosticians with PTEN expertise to develop specifications to the 2015 ACMG/AMP Sequence Variant Interpretation Guidelines for PTEN variant interpretation. We describe finalized PTEN‐specific variant classification criteria and outcomes from pilot testing of 42 variants with benign/likely benign (BEN/LBEN), pathogenic/likely pathogenic (PATH/LPATH), uncertain significance (VUS), and conflicting (CONF) ClinVar assertions. Utilizing these rules, classifications concordant with ClinVar assertions were achieved for 14/15 (93.3%) BEN/LBEN and 16/16 (100%) PATH/LPATH ClinVar consensus variants for an overall concordance of 96.8% (30/31). The variant where agreement was not reached was a synonymous variant near a splice donor with noncanonical sequence for which in silico models cannot predict the native site. Applying these rules to six VUS and five CONF variants, adding shared internal laboratory data enabled one VUS to be classified as LBEN and two CONF variants to be as classified as PATH and LPATH. This study highlights the benefit of gene‐specific criteria and the value of sharing internal laboratory data for variant interpretation. Our PTEN‐specific criteria and expertly reviewed assertions should prove helpful for laboratories and others curating PTEN variants.
The Hidden Cost of Window Management

Most window management systems support multitasking by allowing users to open, resize, position, and switch between application windows. Although multitasking has become a way of life for most knowledge workers, our current understanding of how users use window management features to switch between multiple tasks---which may comprise multiple application windows---is limited. In this paper, we present a study providing an in-depth analysis of how task switching is supported in Windows 7. As part of analysis, we developed an interface-agnostic classification of common task switching operations supported by window managers which can be used to quantify the time spent on each constituting action. Our study shows that task switching is a time intensive activity and highlights the dominant actions that contribute to task switch time. Furthermore, our classification highlights the specific operations that are optimized by more recent and experimental window managers and allows identifying opportunities for design that could further reduce the overhead of switching between tasks.
Changes in Neuronal Representations of Consonants in the Ascending Auditory System and Their Role in Speech Recognition

A fundamental task of the ascending auditory system is to produce representations that facilitate the recognition of complex sounds. This is particularly challenging in the context of acoustic variability, such as that between different talkers producing the same phoneme. These representations are transformed as information is propagated throughout the ascending auditory system from the inner ear to the auditory cortex (AI). Investigating these transformations and their role in speech recognition is key to understanding hearing impairment and the development of future clinical interventions. Here, we obtained neural responses to an extensive set of natural vowel-consonant-vowel phoneme sequences, each produced by multiple talkers, in three stages of the auditory processing pathway. Auditory nerve (AN) representations were simulated using a model of the peripheral auditory system and extracellular neuronal activity was recorded in the inferior colliculus (IC) and primary auditory cortex (AI) of anaesthetized guinea pigs. A classifier was developed to examine the efficacy of these representations for recognizing the speech sounds. Individual neurons convey progressively less information from AN to AI. Nonetheless, at the population level, representations are sufficiently rich to facilitate recognition of consonants with a high degree of accuracy at all stages indicating a progression from a dense, redundant representation to a sparse, distributed one. We examined the timescale of the neural code for consonant recognition and found that optimal timescales increase throughout the ascending auditory system from a few milliseconds in the periphery to several tens of milliseconds in the cortex. Despite these longer timescales, we found little evidence to suggest that representations up to the level of AI become increasingly invariant to across-talker differences. Instead, our results support the idea that the role of the subcortical auditory system is one of dimensionality expansion, which could provide a basis for flexible classification of arbitrary speech sounds.
Epidemiological Evaluation of Meniscal Ramp Lesions in 3214 Anterior Cruciate Ligament–Injured Knees From the SANTI Study Group Database: A Risk Factor Analysis and Study of Secondary Meniscectomy Rates Following 769 Ramp Repairs

Background: Ramp lesions are characterized by disruption of the peripheral meniscocapsular attachments of the posterior horn of the medial meniscus. Ramp repair performed at the time of anterior cruciate ligament reconstruction (ACLR) has been shown to improve knee biomechanics. Purpose: The primary objectives of this study were to evaluate the incidence of and risk factors for ramp lesions among a large series of patients undergoing ACLR. Secondary objectives were to determine the reoperation rate for failure of ramp repair, defined by subsequent reoperations for partial medial meniscectomy. Study Design: Case-control study; Level of evidence, 3. Case series; Level of evidence, 4. Methods: All patients underwent transnotch posteromedial compartment evaluation of the knee during ACLR. Ramp repair was performed if a lesion was detected. Potentially important risk factors were analyzed for their association with ramp lesions. A secondary analysis of all patients who underwent ramp repair and had a minimum follow-up of 2 years was undertaken to determine the secondary partial meniscectomy rate for failed ramp repair. Results: The overall incidence of ramp lesions in the study population was 23.9% (769 ramp lesions among 3214 patients). Multivariate analysis demonstrated that the presence of ramp lesions was significantly associated with the following risk factors: male sex, patients aged <30 years, revision ACLR, chronic injuries, preoperative side-to-side laxity >6 mm, and concomitant lateral meniscal tears. The secondary meniscectomy rate was 10.8% at a mean follow-up of 45.6 months (range, 24.2-66.2 months). Patients who underwent ACLR + anterolateral ligament reconstruction had a >2-fold reduction in the risk of reoperation for failure of ramp repair as compared with patients who underwent isolated ACLR (hazard ratio, 0.457; 95% CI, 0.226-0.864; P = .021). Conclusion: There is a high incidence of ramp lesions among patients undergoing ACLR. The identification of important risk factors for ramp lesions should help raise an appropriate index of suspicion and prompt posteromedial compartment evaluation. The overall secondary partial meniscectomy rate after ramp repair is 10.8%. Anterolateral ligament reconstruction appears to confer a protective effect on the ramp repair performed at the time of ACLR and results in a significant reduction in secondary meniscectomy rates.
Deep Power Forecasting Model for Building Attached Photovoltaic System

Geographical dispersion and output power fluctuations are the major barriers to efficient utilization and grid connection of building attached photovoltaic (BAPV). To eliminate these negative factors, a reliable energy management system and an accurate power forecasting model are necessary. In this paper, we first design an energy management micro-grid based on the energy Internet, which aims to tackle the problems faced by the grid-connected BAPV through the effective dual-flow management of energy and information. In the context of the proposed micro-grid, we propose a deep power forecasting model that employs a convolutional neural network to find the nonlinear relationship between meteorological information and BAPV power, while the data fed to the model are obtained through the 2-D Fourier transform of meteorological data. We evaluate the proposed model based on real-world meteorological and power data sets. Numerical results highlight the superiority of our forecasting model in terms of accuracy and reliability.
Design of Transmit Beamwidth and Dwell Time Under K-Distributed Clutter and Gaussian Noise

This paper handles the problem of optimizing the scanning policy of a surveillance system in the presence of Rayleigh targets in a mixture of K-distributed clutter and Gaussian noise. Adopting the detection rate (DR) and false alarm rate (FAR) as performance measures, we show that the said optimization amounts to solving a constrained DR maximization, wherein the free parameters are the transmit beamwidth, the dwell time, and the detection threshold, whereas the constraints concern the maximum FAR and time on target. A thorough performance assessment is offered, aimed at eliciting the influence of the signal-to-noise and clutter-to-noise ratios, the clutter shape parameter, and the rate of change of the target response. The results indicate that, although a uniformly optimum transmit policy does not exist, some trends can be devised, which appears of particular relevance especially for systems that can avail themselves of some degree of cognition.
Genetic diversity and population structure analysis of eight local chicken breeds of Southern Xinjiang

ABSTRACT 1. The genetic diversity and population structure were studied for eight local chicken breeds, including Anjiyan (AN), Hetian Black (HH), Hetian Ma (HM), Aheqi (AH), Baicheng You (BC), Hejing (HJ), Tashkurghan (TS) and Ruoqiang (RQ), in the Southern Xinjiang region of China, using 20 microsatellite markers. 2. Total 336 alleles were obtained from all chicken breeds, with a mean of 16.8 alleles per locus. The polymorphism information content ranged from 0.444 to 0.911, with a mean of 0.729 and almost all of the loci showed significant deviation from Hardy-Weinberg standards. The observed and expected heterozygosity of the eight breeds ranged from 0.5 to 0.677 and from 0.656 to 0.774, with the lowest observed in the AN and the highest in BC breed. The average breed genetic diversity was 0.655 for AN and 0.766 for BC chickens. 3. According to the neighbour-joining (NJ) method, three main clusters were identified in the NJ phylogenetic tree with AN and RQ breeds in one clade, HH and HM breeds in the second clade and TS, HJ, AH and BC breeds in the third clade. 4. Based on STRUCTURE analysis, the most likely cluster number of all breeds was K = 4, whereby HH and HM breeds formed one cluster and AH, BC, HJ and TS formed another, and RQ, AN chicken formed their own distinct cluster. These results indicated that HH and HM breeds had similar genetic background, as did the breeds of AH, BC, HJ and TS. RQ, AN breed had unique genetic backgrounds, distinct from the other breeds. Genetic introgression was detected from AN to HH and HM. 5. The results of the current study can be used as baseline genetic information to implement effective conservation programs and to make better use of these local chicken breeds, especially for the AN, RQ and TS breeds.
Integrating SLAM and gas distribution mapping (SLAM-GDM) for real-time gas source localization

ABSTRACT Gas distribution mapping (GDM) learns models of the spatial distribution of gas concentrations across 2D/3D environments, among others, for the purpose of localizing gas sources. GDM requires run-time robot positioning in order to associate measurements with locations in a global coordinate frame. Most approaches assume that the robot has perfect knowledge about its position, which does not necessarily hold in realistic scenarios. We argue that the simultaneous localization and mapping (SLAM) algorithm should be used together with GDM to allow operation in an unknown environment. This paper proposes an SLAM-GDM approach that combines Hector SLAM and Kernel DM + V through a map merging technique. We argue that Hector SLAM is suitable for the SLAM-GDM approach since it does not perform loop closure or global corrections, which in turn would require to re-compute the gas distribution map. Real-time experiments were conducted in an environment with single and multiple gas sources. The results showed that the predictions of gas source location in all trials were often correct to around 0.5–1.5 m for the large indoor area being tested. The results also verified that the proposed SLAM-GDM approach and the designed system were able to achieve real-time operation. GRAPHICAL ABSTRACT
Bibliometric Analysis of Publications of ICAR Top Ranked Agricultural Universities of India : An Indian Citation Index (ICI) Based Study

The present study intends to analyze the research output of ICARs top ranked five Agricultural Universities (AUs) represented in Indian publications in Indian Citation Index (ICI) during 2006 to 2015. The study has been conducted to assess the share of research output of five AUs in Indian publications, subject categories of these publications, type of documents published, top journals preferred for publication and citation received by these publications. It was found that Indian Agricultural Research Institute (IARI), New Delhi had the largest share in terms of number of publications of articles in Indian publication and also in citations and cited articles.
3D TCAD modeling of NO2CNT FET sensors

A new approach for TCAD modeling of CNT FET gas sensors is presented, whose key feature is the use of an effective Gaussian DOS to mimic the 1D CNT DOS. The TCAD procedure has been applied to the simulation of a suspended CNT FET for NO2sensing. Our results indicate that the model is able to provide I- V characteristics in excellent agreement with the experimental data, both before and after gas exposure.
Expressive Content-Based Routing in Software-Defined Networks

With the vision of Internet of Things gaining popularity at a global level, efficient publish/subscribe middleware for communication within and across data centers is extremely desirable. In this respect, the very popular Software-Defined Networking, which enables publish/subscribe middleware to perform line-rate filtering of events directly on hardware, can prove to be very useful. While deploying content filters directly on switches of a software-defined network allows optimized paths, high throughput rates, and low end-to-end latency, it suffers from certain inherent limitations with respect to number of bits available on hardware switches to represent these filters. Such a limitation affects expressiveness of filters, resulting in unnecessary traffic in the network. In this paper, we explore various complementary techniques to represent content filters expressively while being limited by hardware. We implement and evaluate techniques that i) use workload, in terms of events and subscriptions, to represent content, and ii) efficiently select attributes to reduce redundancy in content. Our detailed performance evaluations show the potential of these techniques in reducing unnecessary traffic when subjected to different workloads. Furthermore, the techniques proposed in this paper require significant updates to the network, i.e., the data plane, which must be performed in a consistent manner to ensure desired system behavior. As a result, in this paper, we, also, design and evaluate a light-weight approach that ensures data plane consistency in the presence of dynamic network updates.