Miracle-dz/UniFAR-FTUs huggingface dataset:
Spontaneous brain network activity: Analysis of its temporal complexity

The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node) and participation coefficients (the between-module connectivity of a node) were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1) Entropy is higher for the participation coefficient than for the clustering coefficient. (2) The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3) The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. Author Summary In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient) and integration (the participation coefficient) are temporally complex, situated between complete order and disorder. Our results also indicated that “segregated network nodes” may attempt to minimize the network’s entropy, whereas “integrated network nodes” require a higher information load, and therefore need to increase entropy. We believe that combining temporal information from functional brain networks and entropy can be used to test the decomplexification theory of disease, especially in neurological and psychiatric conditions characterized by paroxysmal brain abnormalities (e.g., schizophrenia and epilepsy).
Seizure Prediction Through Clustering and Temporal Analysis of Micro Electrocorticographic Data

We have developed flexible, active, multiplexed recording devices for high resolution recording over large, clinically relevant areas in the brain. While this technology has enabled a much higher-resolution view of the electrical activity of the brain, the analytical methods to process, categorize and respond to the huge volumes of data produced by these devices have not yet been developed. In our previous work, we applied advanced video analysis techniques to segment electrographic spikes, extracted features from the identified segments, and then used clustering methods (particularly Dirichlet Process Mixture models) to group similar spatiotemporal spike patterns. From this analysis, we were able to identify common spike motion patterns. In this paper, we explored the possibility of predicting seizures in this dataset using the Hidden Markov Model (HMM) to characterize the temporal dynamics of spike cluster labels. HMM and other supervised learning methods are united under the same framework to perform seizure prediction. These methods have been applied to in-vivo feline seizure recordings and yielded promising results.
What’s in Your Embedding, And How It Predicts Task Performance

Attempts to find a single technique for general-purpose intrinsic evaluation of word embeddings have so far not been successful. We present a new approach based on scaled-up qualitative analysis of word vector neighborhoods that quantifies interpretable characteristics of a given model (e.g. its preference for synonyms or shared morphological forms as nearest neighbors). We analyze 21 such factors and show how they correlate with performance on 14 extrinsic and intrinsic task datasets (and also explain the lack of correlation between some of them). Our approach enables multi-faceted evaluation, parameter search, and generally – a more principled, hypothesis-driven approach to development of distributional semantic representations.
Isolation and Identification of Bacterial Flora from Internal Organs of Broiler and Their Antibiogram Studies

The present research work was carried out for the isolation and identification of bacterial flora from internal organs of broiler during the period from January 2012 to June 2012. Ten Hubbard classic broiler bird were purchased from retail market in Mymensingh, Bangladesh. The birds were sacrificed and their liver, lung, esophagus, duodenum and tracheal swab samples were collected (n=50). Using standard bacteriological techniques, Escherichia coli was isolated from 26 (52%) samples. Similarly, Salmonella spp. , Staphylococcus spp. , Bacillus spp. , and Pasteurella spp. were isolated from 15 (30%), 10 (20%), 9 (18%) and 4 (8%) samples, respectively. On the basis of individual sample type, E. coli could be isolated from 8 (80%) duodenum samples being the most prevalent organism. On the other hand , Salmonella spp. , Staphylococci spp. , Bacillus spp. and Pasteurella spp. were identified in 5 (50%) lungs, 5 (50%) liver, 4 (40%) duodenum and 2 (20%) lungs samples, respectively. Among these isolated bacteria, E. coli was found to be pathogenic for mice. Antibiogram studies revealed that Ciprofloxacin was highly sensitive against all the isolated bacteria. Diversified bacterial species are prevalent in broiler. However, E. coli and Salmonella spp. infection might make the bird vulnerable for easy access of infection. Proper vaccination and use of selective antibiotics are crucial in protecting broilers from these pathogens. DOI: http://dx.doi. org/10.3329/mh.v1i2. 14094 Microbes and Health, 2012 1(2): 72-75
Geomorphology reveals active décollement geometry in the central Himalayan seismic gap

The similar to 700-km-long ``central seismic gap'' is the most prominent segment of the Himalayan front not to have ruptured in a major earthquake during the last 200-500 yr. This prolonged seismic quiescence has led to the proposition that this region, with a population >10 million, is overdue for a great earthquake. Despite the region's recognized seismic risk, the geometry of faults likely to host large earthquakes remains poorly understood. Here, we place new constraints on the spatial distribution of rock uplift within the western similar to 400 km of the central seismic gap using topographic and river profile analyses together with basinwide erosion rate estimates from cosmogenic Be-10. The data sets show a distinctive physiographic transition at the base of the high Himalaya in the state of Uttarakhand, India, characterized by abrupt strike-normal increases in channel steepness and a tenfold increase in erosion rates. When combined with previously published geophysical imaging and seismicity data sets, we interpret the observed spatial distribution of erosion rates and channel steepness to reflect the landscape response to spatially variable rock uplift due to a structurally coherent ramp-flat system of the Main Himalayan Thrust. Although it remains unresolved whether the kinematics of the Main Himalayan Thrust ramp involve an emergent fault or duplex, the landscape and erosion rate patterns suggest that the decollement beneath the state of Uttarakhand provides a sufficiently large and coherent fault segment capable of hosting a great earthquake.
Species-Specific Responses of Tree Saplings to Herbivory in Contrasting Light Environments: An Experimental Approach

Abstract: Light availability and herbivory are 2 major factors affecting the regeneration of woody species, and thus a better perception of how light and herbivory interact to shape the sapling performance of cohabitant tree species emerges as a key issue. The purpose of this work is to experimentally analyze the influence of light conditions on tree responses to browsing. We evaluated the responses to browsing (simulated by mechanical clipping of 50% of current-year shoots) of saplings from 2 deciduous (Acer opalus ssp. granatense and Quercus pyrenaica) and 2 evergreen (Quercus ilex and Pinus nigra ssp. salzmannii) late-successional tree species, measuring an array of morphological, physiological, and biochemical traits. The experiment was performed with saplings grown for 2 y under 3 experimental light environments emulating natural microhabitats: full (open microhabitats), 80% (below pioneer shrub canopy), and 13% (below tree canopy) sunlight. Clipping affected biomass distribution, growth, and sapling size, while only slight physiological and biochemical effects were detected. Species characteristics and the light environment in which saplings grow determine their capacity to recover biomass lost after herbivore damage. Black pine was found to be the least tolerant species to clipping, whereas the broadleaf species displayed greater recovery after clipping. Light scarcity increased the nutritional quality of plants and negatively affected herbivory tolerance of 3 of the 4 species.
A Framework for Robust Steady-State Voltage Stability of Distribution Systems

Power injection uncertainties in distribution power grids, which are mostly induced by aggressive introduction of intermittent renewable sources, may drive the system away from normal operating regimes and potentially lead to the loss of long-term voltage stability (LTVS). Naturally, there is an ever increasing need for a tool for assessing the LTVS of a distribution system. This paper presents a fast and reliable tool for constructing \emph{inner approximations} of LTVS regions in multidimensional injection space such that every point in our constructed region is guaranteed to be solvable. Numerical simulations demonstrate that our approach outperforms all existing inner approximation methods in most cases. Furthermore, the constructed regions are shown to cover substantial fractions of the true voltage stability region. The paper will later discuss a number of important applications of the proposed technique, including fast screening for viable injection changes, constructing an effective solvability index and rigorously certified loadability limits.
Effect of Zinc Sulfate in Protection against Cisplatin-Induced Nephrotoxicity in Cancer Patients

Cisplatin is a potent antitumor agent that is useful in chemotherapy of various types of cancers. Currently, nephrotoxicity limits its usefulness. The main mechanism responsible for nephrotoxicity is oxidative stress with associated inflammation. This study was to evaluate the protective effect of zinc sulphate on cisplatin-induced nephrotoxicity in cancer patients. Twenty eight patients were participated in the study and were randomized into two groups. Patients in group I (N=14) received six cycles of cisplatin based regimen every 21 days. Patients in group II (N=14) received zinc sulphate in addition to cisplatin based regimen. Serum cystatin C and cystatin C-based GFR were measured at base line and 21 days after 1, 2, 4 and 6 cycles while urinary malondialdehyde and IL-18 were measured at base line and 1 day after 1, 2, 4 and 6 cycles of cisplatin based regimen. Zinc sulfate addition to cisplatin in group II significantly (P<0.05) ameliorated the cisplatin-induced increment in serum cystatin C, urinary malondialdehyde and IL-18 and the cisplatin-induced decline in cystatin C-based GFR that were demonstrated in group I. The significant protective effect of zinc sulfate on cisplatin-induced nephrotoxicity may be through its antioxidant and anti-inflammatory action.
The Role of Polycyclic Aromatic Hydrocarbons in Ultraviolet Extinction. I. Probing Small Molecular Polycyclic Aromatic Hydrocarbons

We have obtained new Hubble Space Telescope/Space Telescope Imaging Spectrograph spectra to search for structure in the ultraviolet interstellar extinction curve, with particular emphasis on a search for absorption features produced by polycyclic aromatic hydrocarbons (PAHs). The presence of these molecules in the interstellar medium has been postulated to explain the infrared emission features seen in the 3-13 μm spectra of numerous sources. Ultraviolet (UV) spectra are uniquely capable of identifying specific PAH molecules. We obtained high signal-to-noise ratio UV spectra of stars that are significantly more reddened than those observed in previous studies. These data put limits on the role of small (30-50 carbon atoms) PAHs in UV extinction and call for further observations to probe the role of larger PAHs. PAHs are of importance because of their ubiquity and high abundance inferred from the infrared data, and also because they may link the molecular and dust phases of the interstellar medium. A presence or absence of UV absorption bands due to PAHs could be a definitive test of this hypothesis. We should be able to detect a 20 Å wide feature down to a 3 σ limit of ~0.02 AV. No such absorption features are seen other than the well-known 2175 Å bump.
Pattern of Adverse Drug Reactions in Cancer Patients at a Tertiary Care Hospital In Telangana Region of South India

Pattern of adverse drug reaction studies in cancer patients is rare in India. Adverse drug reactions associated with the use of anticancer drugs are a worldwide problem which cannot be ignored. Adverse drug reactions can range from mild reaction like nausea, vomiting or any other to severe myelosuppression. This study was planned to observe adverse drug reactions in cancer patients receiving radiation therapy or chemotherapy aged above 18 years and visiting MGM Hospital for treatment and regular check-ups. During the study period, 201 cancer patients who came to the hospital were screened for occurrence of adverse drug reactions during their treatment with chemotherapy and radiotherapy. Almost each and every patient was suffering with at least 2-3 ADRs. Female sufferers are more than male patients. Breast cancer prevalence is more when compared to any other types of cancer. A total of 3370 ADRs were observed in our study population. In the study population mostly affected organ systems were gastrointestinal system -31%, CNS & PNS systems30% followed by musculoskeletal system-16%, respiratory system-8%, sensory system-7% and skin and appendages-7% respectively.
DMD genotype correlations from the Duchenne Registry: Endogenous exon skipping is a factor in prolonged ambulation for individuals with a defined mutation subtype

Antisense oligonucleotide (AON)‐mediated exon skipping is an emerging therapeutic for individuals with Duchenne muscular dystrophy (DMD). Skipping of exons adjacent to common exon deletions in DMD using AONs can produce in‐frame transcripts and functional protein. Targeted skipping of DMD exons 8, 44, 45, 50, 51, 52, 53, and 55 is predicted to benefit 47% of affected individuals. We observed a correlation between mutation subgroups and age at loss of ambulation in the Duchenne Registry, a large database of phenotypic and genetic data for DMD (N = 765). Males amenable to exon 44 (N = 74) and exon 8 skipping (N = 18) showed prolonged ambulation compared to other exon skip groups and nonsense mutations (P = 0.035 and P < 0.01, respectively). In particular, exon 45 deletions were associated with prolonged age at loss of ambulation relative to the rest of the exon 44 skip amenable cohort and other DMD mutations. Exon 3–7 deletions also showed prolonged ambulation relative to all other exon 8 skippable mutations. Cultured myotubes from DMD patients with deletions of exons 3–7 or exon 45 showed higher endogenous skipping than other mutations, providing a potential biological rationale for our observations. These results highlight the utility of aggregating phenotypic and genotypic data for rare pediatric diseases to reveal progression differences, identify potentially confounding factors, and probe molecular mechanisms that may affect disease severity.
Uptake of Heavy Metals , and Antioxidative Enzymes in Brassica juncea L . Seedlings as Affected by Zn in Binary Combinations with Other Heavy Metals

The present study attempts to understand the uptake of heavy metals and stress tolerance in Brassica juncea L. seedlings under the effect of Zn in binary combinations with Cr, Ni, Co and Cu through the production of antioxidative enzymes superoxide dismutase (SOD), guaiacol peroxidase (GPX), catalase (CAT), ascorbate peroxidase (APX) and glutathione reductase (GR). It was observed that the order of uptake of heavy metals by the seedling in single metal solutions was Zn > Cu > Co > Cr > Ni. Zn in binary combination with other heavy metals, mutually decreased the uptake of each other, the maximum decrease being 66.1% in the uptake of Cr in (Cr100+Zn100) binary solution. All the metals, whether applied singly or in combinations, significantly increased the activities of antioxidative enzymes, except for CAT. Zn was the most effective metal in increasing the activities of antioxidative enzymes. At 100 mg l, it increased the activities of GR, GPX and APX by 101%, 64%, and 42% respectively, whereas maximum SOD activity (16 mM UA mg protein) was induced by 100 mg l Cr. Of all the binary combinations, Zn+Co and Zn+Ni were most effective in increasing the activities of GPX and GR, respectively, whereas Zn+Cu and Zn+Cr increased the activities of APX and SOD, respectively. Binary interaction models revealed that Cr, Ni, Co and Cu act antagonistic to Zn to increase the activity of GR, whereas for GPX, APX and SOD, these metals in binary combinations with Zn, were mutually antagonistic, thereby causing a negative interactive effect. Cr, Co and Cu were mutually antagonistic to Zn for catalase activity, whereas interaction between Ni and Zn was synergistic for this enzyme. _____________________________________________________________________________________________________________
A Fast Model‐Predictive Speed Controller for Minimised Charge Consumption of Electric Vehicles

This paper presents the design of a real‐time implementable energy‐efficient model‐predictive cruise controller for electric vehicles including the driving speed reference generation. The controller is designed to meet the properties of a series‐production electric vehicle whose characteristics are identified and validated by measurements. The predictive eco‐cruise controller aims at finding the best compromise between speed‐reference tracking and energy consumption of the vehicle using an underlying dynamic model of the vehicle motion and charge consumption. The originally non‐linear motion model is transformed into a linear model mainly by using a coordinate transform. To obtain a piecewise linear approximation of the charge consumption map, the measured characteristics are approximated by a convex piecewise linear function represented as the maximum of a set of linear constraint functions. The reformulations finally lead to a model‐predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real‐time implementation with guaranteed convergence. Simulation results of the closed‐loop operation finally illustrate the effectiveness of the approach.
Developing business plan for software companies using constructive discussion and industrial experiences

There are several different plans which are needed for managing software business. One of the most important ones is a software business plan. The importance of it bases on the underlying idea that it forms up the foundation of the software business as well as it discusses how important challenges should be solved. In addition it gives needed information for third parties like financing institutions about the future targets of the company. Firstly, this paper discusses of the nature of the software business. Secondly, it discusses of the important issues and topics needed in preparing any business plan and thirdly, using the discussion as a basis it formulates a business plan model for the software companies. As all business plans are practical tools for managing businesses the developed business plan is discussed also in industrial context. The industrial discussion shows that developed business plan is useful for the software companies. It also reveals rather well the practical order how industrial managers are running their businesses. Finally, discussion comments show that the proposed business plan serves software companies and financing institutions as action plan, road map and sales tool as well as informs customers about the software company's ways of working. The theoretical discussion in this paper is constructive in nature. Therefore the theoretical part of this paper constructs a new reality by using results which in part have been presented before and have proven to be usable. The industrial experience part of this paper is a case study in nature. The case study method has been chosen because it offers a natural and practical tool for presenting chronologically the results of the industrial experiences discussion.
Advances in Pancreatic Cancer Treatment

pancreatic cancer (PC) in the US. The incidence has been increasing since the 1930s. Prognosis of PC is extremely poor. Approximately 31,000 patients in the US die from PC each year, making it the fourth leading cause of cancer-related death in the US. Five-year overall survival (OS) rate for advanced pancreatic cancer (APC) is less than 1%. Poor prognosis had been attributed to the inability to diagnose while the tumor is resectable and its propensity toward early vascular dissemination and spread to regional lymph nodes. In inoperable PC, gemcitabine is the only cytotoxic agent approved by the US Food and Drug Administration (FDA), based on the results of the multicentered randomized phase III clinical trial that compared 5-fluorouracil (5-FU) with gemcitabine. In this study, treatment with gemcitabine resulted in a relative improvement of 36% in median survival (MS) (5.7 versus 4.2 months for gemcitabine and 5-FU, respectively). For the past 10 years, many cytotoxic and targeted agents have been pitted against or combined with gemcitabine in randomized phase III trials and no drug has been shown to be superior to single-agent gemcitabine. Luckily, in the past year, for the first time, two large, randomized phase III studies in APC—capecitabine plus gemcitabine versus gemcitabine, and erlotinib plus gemcitabine versus gemcitabine—have demonstrated the superiority of a gemcitabine-containing combination over single-agent gemcitabine. In this paper we will review the current advancement in PC treatment. Resectable Pancreatic Cancer Ten percent of patients have resectable disease at the time of PC diagnosis. Prognosis of patients after complete resection of node-negative cancer is poor, with three-year disease-specific survival rate at 27% (95% confidence interval (CI): 23–32%) and MS of 15–19 months. The treatment plan in the adjuvant setting is currently dependent on which side of the Atlantic you are located: chemotherapy alone is mostly used in Europe—European Study Group for Pancreatic Cancer-1 (ESPAC-1), Charité Onkologie Clinical-001 (CONKO-001)—while chemoradiation therapy (CRT) is the current standard in the US—Gastrointestinal Study Group (GITSG), Radiation Therapy Oncology Group 9704 (RTOG 9704).