Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemical Elicitor-Induced Modulation of Antioxidant Metabolism and Enhancement of Secondary Metabolite Accumulation in Cell Suspension Cultures of Scrophularia kakudensis Franch

Scrophularia kakudensis is an important medicinal plant with pharmaceutically valuable secondary metabolites. To develop a sustainable source of naturaceuticals with vital therapeutic importance, a cell suspension culture was established in S. kakudensis for the first time. Friable calli were induced from the leaf explants cultured on a Murashige and Skoog (MS) medium containing 3.0 mg·L−1 6-benzyladenine (BA) in a combination with 2 mg·L−1 2,4-dichlorophenoxy acetic acid (2,4-D). From the callus cultures, a cell suspension culture was initiated and the cellular differentiation was investigated. In addition, the effect of biotic elicitors such as methyl jasmonate (MeJa), salicylic acid (SA), and sodium nitroprusside (SNP) on the accumulation of secondary metabolites and antioxidant properties was demonstrated. Among the elicitors, the MeJa elicited the accumulation of total phenols, flavonoids, and acacetin, a flavonoid compound with multiple pharmaceutical values. Similarly, the higher concentrations of the MeJa significantly modulated the activities of antioxidant enzymes and enhanced the scavenging potentials of free radicals of cell suspension extracts. Overall, the outcomes of this study can be utilized for the large scale production of pharmaceutically important secondary metabolites from S. kakudensis through cell suspension cultures.
Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation

Blind source separation problems are difficult because they are inherently unidentifiable, yet the entire goal is to identify meaningful sources. We introduce a way of incorporating domain knowledge into this problem, called signal aggregate constraints (SACs). SACs encourage the total signal for each of the unknown sources to be close to a specified value. This is based on the observation that the total signal often varies widely across the unknown sources, and we often have a good idea of what total values to expect. We incorporate SACs into an additive factorial hidden Markov model (AFHMM) to formulate the energy disaggregation problems where only one mixture signal is assumed to be observed. A convex quadratic program for approximate inference is employed for recovering those source signals. On a real-world energy disaggregation data set, we show that the use of SACs dramatically improves the original AFHMM, and significantly improves over a recent state-of-the-art approach.
The Putative Protein Methyltransferase LAE1 of Trichoderma atroviride Is a Key Regulator of Asexual Development and Mycoparasitism

In Ascomycota the protein methyltransferase LaeA is a global regulator that affects the expression of secondary metabolite gene clusters, and controls sexual and asexual development. The common mycoparasitic fungus Trichoderma atroviride is one of the most widely studied agents of biological control of plant-pathogenic fungi that also serves as a model for the research on regulation of asexual sporulation (conidiation) by environmental stimuli such as light and/or mechanical injury. In order to learn the possible involvement of LAE1 in these two traits, we assessed the effect of deletion and overexpression of lae1 gene on conidiation and mycoparasitic interaction. In the presence of light, conidiation was 50% decreased in a Δ lae1 and 30–50% increased in lae1-overexpressing (OElae1) strains. In darkness, Δ lae1 strains did not sporulate, and the OElae1 strains produced as much spores as the parent strain. Loss-of-function of lae1 also abolished sporulation triggered by mechanical injury of the mycelia. Deletion of lae1 also increased the sensitivity of T. atroviride to oxidative stress, abolished its ability to defend against other fungi and led to a loss of mycoparasitic behaviour, whereas the OElae1 strains displayed enhanced mycoparasitic vigor. The loss of mycoparasitic activity in the Δ lae1 strain correlated with a significant underexpressionn of several genes normally upregulated during mycoparasitic interaction (proteases, GH16 ß-glucanases, polyketide synthases and small cystein-rich secreted proteins), which in turn was reflected in the partial reduction of formation of fungicidal water soluble metabolites and volatile compounds. Our study shows T. atroviride LAE1 is essential for asexual reproduction in the dark and for defense and parasitism on other fungi.
Māori women educators’ pedagogy and Kaupapa Māori methodology

This thesis wove three Māori women educators’ pedagogy into the Whatu metaphor, from the findings, continuance and sustenance, every place a learning place and knowing each other. Kaupapa Māori philosophies informed the research methodology, which in turn became an instrument of analysis and subject of my research experience.
Tumor-Infiltrating CD4+ T Lymphocytes Express APO2 Ligand (APO2L)/TRAIL upon Specific Stimulation with Autologous Lung Carcinoma Cells: Role of IFN-α on APO2L/TRAIL Expression and -Mediated Cytotoxicity1

In the present report, we have investigated TRAIL/APO2 ligand (APO2L) expression, regulation, and function in human lung carcinoma tumor-infiltrating lymphocytes. Using a panel of non-small cell lung carcinoma cell lines, we first showed that most of them expressed TRAIL-R1/DR4, TRAIL-R2/DR5, but not TRAIL-R3/DcR1 and TRAIL-R4/DcR2, and were susceptible to APO2L/TRAIL-induced cell death. Two APO2L/TRAIL-sensitive tumor cell lines (MHC class I+/II+ or I+/II−) were selected and specific CD4+ HLA-DR- or CD8+ HLA-A2-restricted CTL clones were respectively isolated from autologous tumor-infiltrating lymphocytes. Interestingly, although the established T cell clones did not constitutively express detectable levels of APO2L/TRAIL, engagement of their TCR via activation with specific tumor cells selectively induced profound APO2L/TRAIL expression on the CD4+, but not on the CD8+, CTL clones. Furthermore, as opposed to the CD8+ CTL clone which mainly used granule exocytosis pathway, the CD4+ CTL clone lysed the specific target via both perforin/granzymes and APO2L/TRAIL-mediated mechanisms. The latter cytotoxicity correlated with APO2L/TRAIL expression and was significantly enhanced in the presence of IFN-α. More interestingly, in vivo studies performed in SCID/nonobese diabetic mice transplanted with autologous tumor and transferred with the specific CD4+ CTL clone in combination with IFN-α resulted in an important APO2L/TRAIL-mediated tumor growth inhibition, which was prohibited by soluble TRAIL-R2. Our findings suggest that APO2L/TRAIL, specifically induced by autologous tumor and up-regulated by IFN-α, may be a key mediator of tumor-specific CD4+ CTL-mediated cell death and point to a potent role of this T cell subset in tumor growth control.
Autogenous control is not sufficient to ensure steady-state growth rate-dependent regulation of the S10 ribosomal protein operon of Escherichia coli

The regulation of the S10 ribosomal protein operon of Escherichia coli was studied by using a lambda prophage containing the beginning of the S10 operon (including the promoter, leader, and first one and one-half structural genes) fused to lacZ. The synthesis of the lacZ fusion protein encoded by the phage showed the expected inhibition during oversynthesis of ribosomal protein L4, the autogenous regulatory protein of the S10 operon. Moreover, the fusion gene responded to a nutritional shift-up in the same way that genuine ribosomal protein genes did. However, the gene did not exhibit the expected growth rate-dependent regulation during steady-state growth. Thus, the genetic information carried on the prophage is sufficient for L4-mediated autogenous control and a normal nutritional shift-up response but is not sufficient for steady-state growth rate-dependent control. These results suggest that, at least for the 11-gene S10 ribosomal protein operon, additional regulatory processes are required to coordinate the synthesis of ribosomal proteins with cell growth rate and, furthermore, that sequences downstream of the proximal one and one-half genes of the operon are involved in this control.
Development of a Schedule of Current Physiotherapy Treatment Used to Improve Movement Control and Functional Use of the Lower Limb after Stroke: A Precursor to a Clinical Trial

Objective. To develop a treatment schedule of physical therapy techniques used to improve movement control and functional use of the paretic lower limb after stroke in U.K. clinical centers to be involved in a subsequent clinical trial of experimental interventions given in addition to routine clinical practice. Methods. Ten physiotherapists experienced in stroke rehabilitation who worked in or near the clinical centers to be involved in a subsequent clinical trial completed an individual semi-structured interview. The verbatim transcripts were condensed independently by 2 researchers into a draft list of interventions. The researchers then resolved disagreement through discussion and produced a preliminary list of interventions. At a focus group meeting, the participating physiotherapists discussed the preliminary list, refined it to produce a final list, and then transformed it into a draft treatment schedule. The draft treatment schedule was piloted in clinical practice. Refinements were made, and the final treatment schedule was produced. Results. The treatment schedule consists of an A4 recording form with instructions and glossary of terms printed on the back. Each treatment record provides information including duration of treatment, treatment aims, and the 45 specific physical therapy interventions provided in the 11 sections (e.g., “splinting techniques” and “function - in sitting towards standing”). Conclusion. A treatment schedule was produced, which can now be used in a subsequent phase II evaluative trial.
DOCKING BASED PHARMACOPHORE MODEL FOR MYCOBACTERIUM TUBERCULOSIS PEPTIDE DEFORMYLASE INHIBITORS AND ITS APPLICATION IN DRUG DESIGNING

Objective: Peptide deformylase (PDF) is a metalloprotease enzyme playing important role in protein synthesis. This enzyme is encoded by def gene and its essentiality makes it as attractive drug-target in drug discovery process. The objective of this study was to explore the computational approaches to investigate PDF inhibitors. Methods: In this study, we have explored the binding mode of Mycobacterium tuberculosis (M.tb ) PDF inhibitors using AutoDock and identified the key residues involved in bonding. We have also screened the Zinc database and identified potential hits with more potent binding energy as compared to previously known inhibitors. Results: Our study suggested that Val50 and Leu107 are the key residues involve in H-bonding. We have also identified two hydrophobic pockets and two electron acceptor regions using docking based pharmacophore features. Among the various docking based descriptors, binding free energy and unbound system energy showed a correlation value 0.14 and 0.65 with inhibitory activity. However, removal of two outliers identified by clustering technique showed the improvement in correlation value 0.44, and 0.89 with inhibitory activity. Conclusion: This study will be useful in future for better inhibitor designing and understanding the ligand protein interactions against mtb PDF protein.
Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals

Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.
HetNetwork Coding: Scaling Throughput in Heterogeneous Networks using Multiple Radio Interfaces

The explosive demand for data has called for solution approaches that range from spectrally agile cognitive radios with novel spectrum sharing, to use of higher frequency spectrum as well as smaller and denser cell deployments with diverse access technologies, referred to as heterogeneous networks (HetNets). Simultaneously, advances in electronics and storage, has led to the advent of wireless devices equipped with multiple radio interfaces (e.g. WiFi, WiMAX, LTE, etc.) and the ability to store and efficiently process large amounts of data. Motivated by the convergence of HetNets and multi-platform radios, we propose HetNetwork Coding as a means to utilize the available radio interfaces in parallel along with network coding to increase wireless data throughput. Specifically we explore the use of random linear network coding at the network layer where packets can travel through multiple interfaces and be received via multihoming. Using both simulations and experimentation with real hardware on WiFi and WiMAX platforms, we study the scaling of throughput enabled by such HetNetwork coding. We find from our simulations and experiments that the use of this method increases the throughput, with greater gains achieved for cases when the system is heavily loaded or the channel quality is poor. Our results also reveal that the throughput gains achieved scale linearly with the number of radio interfaces at the nodes.
Towards the Secrecy Capacity of the Gaussian MIMO Wire-Tap Channel: The 2-2-1 Channel

We find the secrecy capacity of the 2-2-1 Gaussian MIMO wiretap channel, which consists of a transmitter and a receiver with two antennas each, and an eavesdropper with a single antenna. We determine the secrecy capacity of this channel by proposing an achievable scheme and then developing a tight upper bound that meets the proposed achievable secrecy rate. We show that, for this channel, Gaussian signalling in the form of beam-forming is optimal, and no pre-processing of information is necessary.
CS 224 N Final Project : Detecting Key Needs in Crisis

When a crisis occurs, the world springs into action to try and understand what is happening and what help is required. During these times, twitter has become a key avenue through which to disseminate information. In this paper, we classify tweets into 18 key categories (such as [volunteering] or [injury]) in order to organize the stream of knowledge coming in. We also attempt to predict when a particular category will be tweeted about by leveraging past tweets and categories to predict future tweet categories. Our most successful result, intermixing a Word2Vec model with a standard feed-forward classifier is able to classify the tweets with 59% accuracy. We find that more sophisticated models (including added depth to a feedforward model and an LSTM that uses a sequence of words to predict a tweet) prove to be less effective than a more generic classification methodology, likely because of overfitting on labels that are more common and 2) noise created by combining various types of crises, such as earthquakes and floods, together. We show that our classification model is more successful when restrained to specific types of events, with 70% accuracy on earthquake data, for example. Additionally, we determine that leveraging past history to predict future tweet patterns is moderately successful. We showcase our LSTM methodology which has achieved a 33% accuracy. Lastly, we test out our model on the more recent twitter compilations for two natural disasters: the earthquake in Italy and Louisiana Floods. We show, via qualitative examples and analysis, that our model can likely scale to natural disasters of various forms.
Weak ε-nets have basis of size o(1/ε log (1/ε)) in any dimension

Given a set P of n points in R<sup>d</sup> and ε > 0, we consider the problemof constructing weak ε-nets for P.We show the following: pick a random sample Q of size O(1/ε log (1/ε)) from P. Then, with constant probability, a weak ε-net of P can be constructed from only the points of Q. This shows that weak ε-nets in R<sup>d</sup> can be computed from a subset of P of size O(1/ε log(1/ε)) with only the constant of proportionality depending on the dimension, unlike all previous work where the size of the subset had the dimension in the exponent of 1/ε. However, our final weak ε-nets still have a large size (with the dimension appearing in the exponent of 1/ε).
Associations of the UCP 2 Gene Locus With Asymptomatic Carotid Atherosclerosis in Middle-Aged Women

Objective—Reactive oxygen species (ROS) contribute to atherogenesis. Uncoupling protein 2 (UCP2) reduces mitochondrial ROS generation and protects against the disease in animal models. A common 866G/A promoter polymorphism that has been associated with obesity and -cell function may also affect UCP2 gene expression in cells of the arterial wall. Methods and Results—Genotype distributions of the 866G/A and of a 45nt-del/ins polymorphism in the 3 -untranslated region of the UCP2 gene were determined in 1334 participants of the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk (SAPHIR). We observed a modest association of the 866G/A promoter polymorphism and 2-loci haplotypes with asymptomatic carotid atherosclerosis in female study participants. Functional studies revealed increased expression of the 866G wild-type allele in human umbilical vein endothelial cells and differentiated THP-1 cells. Electrophoretic mobility shift assay studies and antibody-interference assays performed with nuclear extracts of various cell lines showed binding of cell-type specific protein complexes to the region encompassing the 866 site and suggested involvement of hypoxia inducible factor 1 in the regulation of UCP2 gene expression in endothelial cells and macrophages. Conclusions—Our results suggest a role of UCP2 in atherogenesis as originally proposed from studies in animal and cell culture models. (Arterioscler Thromb Vasc Biol. 2005;25:604-610.)
Functional linkages between leaf traits and net photosynthetic rate: reconciling empirical and mechanistic models

Summary 1. We had two objectives: (i) to determine the generality of, and extend the applicability of, a previously reported empirical relationship between leaf-level net photosynthetic rate ( A M , nmol g − 1 s − 1 ), specific leaf area (SLA, m 2 kg − 1 ) and leaf nitrogen mass fraction ( N M , mmol g − 1 ); and (ii) to compare these empirical results with a mechanistic model of photosynthesis in order to provide a mechanistic justification for the empirical pattern. 2. Our results were based on both literature and original data. There were a total of 160 and 87 data points for the leaf-level and whole-plant data, respectively. 3. Our multiple regression for single leaves was ln( A M ) = 0·66 + 0·71 ln(SLA) + 0·79 ln( N M ), r 2 = − 0·80; only the intercept (0·11) differed for the whole-plant data. These results are not significantly different from previously published relationships. 4. We then converted the mechanistic model of Evans and Poorter, and a modified version which includes leaf lamina thickness ( T ) and leaf dry matter (tissue) concentration ( C M ), into directed acyclic graphs. We then derived reduced graphs that involved only T , C M , SLA, N M and A M . These were tested using structural equation modelling, with measured lamina thickness ( T ′ ) and leaf dry matter ratio (LDMR, g dry mass g − 1 fresh mass) as indicators of T and C M . The original Evans‐Poorter model was rejected, but the modified version fitted the structural relationships well. The same qualitative models also applied to the whole-plant data, although the path coefficients sometimes differed. 5. Using simulations, we show that the original Evans‐Poorter model predicts a positive correlation between SLA and N M that maximizes A M . The data closely follow this predicted relationship. The correlation between the actual values of A M (standardized units) and the predicted values obtained from the modified Evans‐Poorter model was 0·74 and increased to 0·82 once three outlier points were removed. 6. These results provide a mechanistic explanation for the empirical trends relating leaf form and carbon fixation, and predict that SLA and leaf N must be quantitatively co-ordinated to maximize C fixation.
Robust automatic speech recognition using a perceptually-based optimal spectral amplitude estimator speech enhancement algorithm in various low-SNR environments

This paper addresses the problem of noise robustness of automatic speech recognition (ASR) systems in various noisy environments using a Minimum Mean-Square Error Short-Time Spectral Amplitude Estimator (MMSE-STSA). This was accomplished by the integration of a Perceptual Weighting Filter (PWF) with the MMSE-STSA algorithm in order to improve the preprocessing speech enhancement performance. The proposed PWF-based STSA algo-rithm is integrated in the front-end of an ASR system in order to evaluate its robustness in severe interfering noisy environments. Experiments were conducted using a noisy version of speech signals extracted from the TIMIT database. The Hidden Markov model Toolkit (HTK) was used throughout our experiments. Re-sults show that the proposed approach when included in the front-end of an HTK-based ASR system, outperforms that of the conventional recognition process in interfering noisy environments for a wide range of SNRs down to -4 dB.
Functional somatotopy in sensorimotor cortex

In an effort to understand the highly distributed somatotopy of primary motor cortex, this review draws on principles derived from studies of auditory, visual and somatosensory cortical areas. In each case, a behaviorally important feature or function is overlaid in multiple locations on an underlying topographic map of the peripheral sensory surface. Recent studies of hand muscle synergies suggest the types of two-dimensional functional axes that might reasonably be mapped to the two-dimensional surface of the primary motor cortex. However, other research emphasizes that even a functional somatotopy must be extremely flexible.