Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmacological and biopharmaceutical studies of paracetamol and N-acetyl-D-glucosamine combination as an analgetic drug

The aim. Experimental selection of paracetamol and N-acetyl-D-glucosamine (NAG) ratio and combined dose and bioavailability study of the pharmaceutical composition and active pharmaceutical ingredient (API) in the model of cell biomembranes. Materials and methods. The following substances were used: paracetamol, Actimask Acetaminophen (gelatin-coated paracetamol), and NAG. For pharmacological studies were used laboratory rats, which received test objects intragastrically. The study was performed on the model of inflammatory hyperalgesia according to the Randall-Selitto method. The values of pain threshold before and after pathology induction were established. For biopharmaceutical studies, dry L-α-dimyristoylphosphatidylcholine purchased from Avanti Polar Lipids (purity 99.9 %) was used, hydrated with an appropriate amount of double-distilled water to obtain 70 % wt. /wt. water dispersion. Differential scanning calorimetry (DSC) studies were performed employing DSC 1 microcalorimeter (Mettler Toledo). Pharmaceuticals investigated were placed on the bottom of a crucible, then a proper amount of the lipid membrane was added and this moment was taken as the time reference point (t=0). Then a crucible was sealed with a lid and a sample was undergone consecutive temperature scans, heating from 0 to 35 ºC at a scanning rate of 2 ºC/min. The procedure was repeated until no more changes in DSC profiles were observed, i.e. system equilibrium was reached. Results. It has been experimentally proven that the combination of paracetamol and NAG in the ratio of 4:1 showed better analgesic efficacy. The dose of active ingredients was determined to be 50 mg/kg by the sum of API. The active interaction of paracetamol with the bilayer of biomembranes was established and it was determined that Actimask has a worse rate of penetration into the membrane due to the coating of paracetamol with a gelatin shell. NAG didn't significantly affect the rate of penetration of Actimask through the bilayer of membranes, but the auxiliary components of the tablet mixture significantly improved the rate and completeness of penetration of paracetamol through the bilayer of biomembranes. Conclusions. The study found the most effective ratio between paracetamol and NAG in the composition, which is 4:1. The next step was to determine the dose of API, which is 50 mg/kg of the sum of active substances. It has been determined that paracetamol has good permeability through the bilayer of biomembranes, and the tablet mass significantly improves the permeability of paracetamol
A Statistical Model to Assess Indirect CO2 Emissions of the UAE Residential Sector

This study presents a regional bottom-up model for assessing space cooling energy and related greenhouse gas emissions. The model was developed with the aim of improving the quality and quantity of cooling energy and emission data, especially for the benefit of local decision making. Based on a benchmarking study, a representative archetype was developed, simulation software used and linear statistical model constructed. This model explores the way in which CO2 emission levels are affected by different energy efficiency measures to reduce cooling energy consumption in buildings. The analysis showed that improving building energy efficiency could generate considerable carbon emissions reduction credits with competitive benefit. The developed model was found to be capable in selecting cost-effective, environmentally-preferred building efficiency measures and evaluating the future trend of CO2 emissions in the residential building of Alain city
Effect of feeding regimen on circadian activity rhythms of food anticipatory by ghrelin hormone in a pig model

ABSTRACT Increasingly diverse meal patterns affect the internal body clock. Ghrelin secretion is closely associated with the anticipation of a regularly scheduled mealtime, leading ghrelin to be a putative candidate for food-related entraining signals that drive activity rhythms. Here, growing pigs with different meal frequencies were used to construct an irregular eating pattern model. We found that irregular eating patterns changed central ghrelin levels of pigs, affected the circadian entrainment and circadian rhythm pathways in hypothalamus tissue, and altered the daily behavior and food anticipatory activity (FAA). To determine whether ghrelin exerts an effect, growing pigs were intravenously injected with ghrelin antagonist [D-Lys3]-GHRP-6 for 7 days. We showed here that [D-Lys3]-GHRP-6 administration decreased locomotor activity of growing pigs in the 4-h window preceding onset of food availability. In addition, we also confirmed that the direct role of ghrelin in molecular mechanism of regulating clock genes expression via calcium mobilization through intracellular PKC/PLC and AC/PKA pathways in vitro. Collectively, irregular eating patterns affect the central circadian system by ghrelin, supporting ghrelin as a temporal messenger of food-entrainment in hypothalamic circadian functions.
Comparative and Classifactory Topic Analysis Using Latent Dirichlet Allocation

The aim of this bachelor thesis is to compare and empirically test the use of classification to improve the topic models Latent Dirichlet Allocation (LDA) and Author Topic Modeling (ATM) in the context of the social media platform Twitter. For this purpose, a corpus was classified with the Dewey Decimal Classification (DDC) and then used to train the topic models. A second dataset, the unclassified corpus, was used for comparison. The assumption that the use of classification could improve the topic models did not prove true for the LDA topic model. Here, a sufficiently good improvement of the models could not be achieved. The ATM model, on the other hand, could be improved by using the classification. In general, the ATM model performed significantly better than the LDA model. In the context of the social media platform Twitter, it can thus be seen that the ATMmodel is superior to the LDA model and can additionally be improved by classifying the data.
Lecture Note 6: Extensive-Form Games

2 Perfect-Information EFGs We start by considering perfect-information EFGs. The term perfect information refers to the fact that in these games, every player always knows the exact state of the game. A perfect-information EFG is a game played on a tree, where each internal node belongs to some player. The actions for the player at a given node is the set of branches, and by selecting a branch the game proceeds to the following node. An example is shown in Figure 1 on the left. That game has four nodes where players take actions, two belong to player 1 (labelled P1) and two belonging to player 2 (labelled P2). Additionally, the game tree has 6 leaf nodes. At each leaf node, each player receives some payoff. In this particular game, it is a zero-sum game, and the value at a leaf denotes the value that player 1 receives. P1
Continued Use of Retracted Publications: Implications for Information Systems and Scientific Publishing

Reports on the preliminary results of an empirical study of postretraction citations of biomedical research literature. Retractions of biomedical publications have a serious impact on research enterprise and public health. Retractions to correct literature and alert readers are actions by the journals based on evidence of serious flaws or errors or upon the request of the authors. The process of retraction could take a few weeks or years after publication. The purpose of this study is to investigate how retracted peer-reviewed journal articles were cited post-retraction. Post-retraction citing articles are those published two years after the retraction year. The dataset includes 961 post-retraction citing articles that cited one or more of 77 retracted articles. The 77 retracted articles were also recommended by experts in a literature recommendation database (Faculty Opinions). The findings show that a higher percentage of the continued use of the retracted articles made no mention of the retraction or invalid results in these articles. Retracted articles and their retraction notices need to be open access; entities involved in publishing and providing literature resources must practice diligence in ensuring the validity of scientific literature.
Polynomial Event Semantics Negation

Polynomial event semantics is an interpretation of Neo-Davidsonian semantics in which the thorny event quantification problem does not even arise. Denotations are constructed strictly compositionally, from lexical entries up, and quantifiers are analyzed in situ. All advantages of event semantics, in particular, regarding entailment, are preserved. The previous work has dealt only with positive polarity phrases involving universal, existential and counting quantification. We now extend the polynomial event semantics to sentences with negation and negative quantification, including adverbial quantification, with attendant ambiguities. The analysis remains compositional, and does not require positing of non-existing entities or events.
Double-blind, Randomized, Placebo-Controlled study to evaluate the Efficacy of an early treatment with Herbal Supplement based in the Prevention of Post-Traumatic Stress Disorder in emergency department (PHYTeS Study)

Introduction: The prevention from Post-traumatic stress disorder (PTSD) is therefore of major public health interest and one of the concerns of any emergency physician. The purpose of our study was to evaluate the efficacy and safety of an herbal supplement to prevent the occurrence of PTSD in high-risk patients. Methods: It is a randomized, double-blind, prospective, interventional study including patients exposed to a potentially traumatic event that meets DSM-V Criterion A and has a Peri-traumatic Distress Inventory score or the Questionnary for traumatic dissociation experiments (PDEQ) and/or L.Crocq score higher than the thresholds between day 1 and day 3. Two hundred patients were included randomly assigned into two groups: Aleozen group and placebo group. Patients included in aleozen group received Aleozen(R) for 10 days while patients in placebo group received Placebo. A CAPS-5 assessment was performed for all patients at different moments. The main objective was to assess the efficacy of Aleozen after 90 days of an exposition to traumatic events according to PTSD. Secondary objectives were to evaluate the safety of Aleozen(R) at 10 and 30 days after its administration and PTSD in the study population after one year of inclusion. Results: No statistical differences were noted between the two groups in term of baseline characteristics including age, sex and the ISS score. After 90 days of follow-up, and according to the CAPS-5 scale, 85 patients (42.5%) of the population study showed PTSD. Concerning primary endpoint, less PTSD were seen in intervention group compared to placebo group (38.8% versus 61.2% respectively; p<0.001). During the study, no adverse events were noted. Conclusion: Results of this work suggest the potential preventive effects of an herbal supplement on PTSD for traumatic patient in emergency. Further confirmatory studies are needed.
Analysis, design, and prototyping of a narrowband radio for application in wireless sensor networks

In the past few years, system-level exploration of wireless data-harvesting techniques have driven circuit designers to consider power-aware radio nodes as a key component of wireless sensor networks. In this work, a discrete implementation of a narrow-band radio in the ISM band will be described. The constructed narrow-band radio achieves a bit-rate of 1Mbit/sec, and features a 0dBm to 20dBm adjustable power amplifier. A discussion of circuits, systems, and implementation will be presented. High frequency analog design will also be discussed in detail. Finally, an analysis of the power-states and power hooks in the narrow-band radio will be explored to demonstrate a flexible, power-aware radio system design. Thesis Supervisor: Anantha P. Chandrakasan Title: Associate Professor
CIKM AnalytiCup 2017 – Lazada Product Title Quality Challenge Multi-Deep-Ensemble For Product Title Quality Scoring

Although NLP techniques have been employed for many applications,product title quality scoring remains a tough problem for the lack of semantic words.In this paper,we present a multiple deep ensemble method for the challenge. In our experiment, feature engineering and selection is essential for all of models,while the effect of some features are intuitive or relative to exact task.After proper feature preparing,we projected tree-based models like xgboost,lightgbm,random forest and adaboost as our start,then we used up to 7 different models to perform ensembling,we concatenated category embedding features and numeric features with the outputs of recurrent neural network that derived from word embedding to cover the sentiment meanning in addition,we weighted 4 models that was based on previous ensemble models together as our output at last.We won first place on conciseness task of CIKM AnalytiCup 2017: Lazada Product Title Quality Challenge,which indicates that our method is effective.
Optimization of the control system for an electric power system operating on a constant-power hyperbole

For an electric power system (EPS) of the combined propulsion complex (CPC), working on a constant-power hyperbola (CPH), the strategy of managing power distribution between propulsion electric motors and own needs consumers has been improved. The study reported here aimed to reduce fluctuations in current consumption and load by optimizing voltage controllers and the rotation frequency of generator assemblies (GA). The system of EPS GA voltage and frequency stabilization was synthesized by determining, in the system of equations, the dynamics of the values of EPS links' time constants and the coefficients that correspond to control parameters. To define the characteristics of the control signals from the regulators of EPS GA rotation frequency and excitation voltage, the laws that control the speed and excitation current were calculated. After sampling the coefficients of the GA speed control regulator, the tasks for the excitation voltage controller were determined. The methodology of data acquisition was applied on the basis of a correlation between the EPS characteristics and the experimental characteristics of GA. The system of EPS dynamics equations was optimized in accordance with the structure and settings of the optimal controller and the probability of a situational error by using Spearman's rank correlation coefficient. The optimization has made it possible to reduce the likelihood of a situational error during the synchronization of GA and enable the stable operation of GA close to the mode of operation on CPH. The power controller was tested under the mode of changing the load of own needs with the power levels of EPS on CPH in the range of 50‒100 % of the rated power. The range of deviations of the current consumed with an enabled GA rotation controller was 10 % of the average value. The range of EPS power deviations with the power controller turned on was 5 %.
Principles of Cognitive Maps

This thesis analyses the concept of a cognitive map in the research fields of geography. Cognitive mapping research is essential as it investigates the relations between cognitive maps and external representations of space that people regularly use by acquiring spatial knowledge, such as maps in geographic information systems. Moreover, cognitive maps, when expanded on semantic maps, explain the relations between people and things in a non-physically environment, where the considered space is not spanned by distance but with other non-spatially variables. Nevertheless, cognitive maps are often distorted. Although a good formation of a cognitive map is vital in navigation processes, cognitive distortions are barely investigated in the field of geography. By analyzing the relevant work, especially Tobler’s first law of geography, a new lexical variant of Tobler’s first law could be stated that could presumably describe a specific distortion in the processing of landmarks in cognitive maps.
Regelungsprobleme in paketvermittelten Kommunikationsnetzen/ Control problems in packet-switched communication networks

Dieser Aufsatz gibt einen Überblick über den Aufbau und die Funktionsweise paketvermittelter Kommunikationsnetze (Weiterverkehrsund lokale Netze) sowie über die mit der Informationsübertragung verbundenen Verkehrsprobleme. Insbesondere wird die Anwendung von graphentheoretischen, regelungstechnischen und Optimierungsverfahren beider Vermeidung und Auflösung von Überlastsituationen in Weitverkehrsnetzen betrachtet. Abschließend wird auf die verkehrstechnischen Besonderheiten der zur Zeit entstehenden Breitbandkommunikationsnetze eingegangen.
Effects of Cofiring Coal and Biomass Fuel on the Pulverized Coal Injection Combustion Zone in Blast Furnaces

CO2 emissions are a major contributor to global warming. Biomass combustion is one approach to tackling this issue. Biomass is used with coal combustion in thermal power plants or with blast furnaces (BFs) because it is a carbon-neutral fuel; therefore, biomass provides the advantage of reduced CO2 emissions. To examine the effect of co-firing on pulverized coal injection (PCI) in BFs, two coals of different ranks were blended with the biomass in different proportions, and then their combustion behaviors were examined using a laminar flow reactor (LFR). The PCI combustion primarily functions as a source of heat and CO to supply the upper part of the BF. To create a similar PCI combustion environment, the LFR burner forms a diffusion flat flame with an oxygen concentration of 26% with a flame temperature of ~2000–2250 K at a heating rate of 105 K/s. The combustion characteristics, such as the flame structure, burning coal particle temperature, unburned carbon (UBC), and CO and CO2 emissions were measured to evaluate their effect on PCI combustion. With the increase in the biomass blending ratio, the brightness of the volatile cloud significantly increased, and the particle temperature tended to decrease. The fragmentation phenomenon, which was observed for certain coal samples, decreased with the increase in the biomass blending ratio. In particular, with an increase in the biomass blending ratio, the optimum combustion point occurred, caused by the fragmentation of coal and volatile gas combustion of biomass.
A Review on Theurapeutic Properties of Centella asiatica and Furture Perspectives

Plant-based drug discovery has drawn the attention of researchers, especially the one used as traditional medicines. Centella asiatica, a medicinal herb widely distributed throughout the world is popular as a traditional medicine. In Ayurveda, it is used either alone or as an important ingredient of several formulations for the management of CNS, skin and gastrointestinal diseases. The aerial parts and roots are used for medicinal purpose, and its chemical constituents have wide therapeutic applications in areas of antimicrobial, anti-inflammatory, anticancer, neuroprotective, antioxidant, and wound healing activities. Many of its uses have been proven scientifically, and bioactive ingredients have been validated. Hence, in this narrative review of literature study we aimed to describe and delineate the therapeutic properties of Centella asiatica and overview on future perspectives are also highlighted.
Extraction of Competing Models using Distant Supervision and Graph Ranking

We introduce the task of detection of competing model entities from scientific documents. We define competing models as those models that solve a particular task that is investigated in the target research document. The task is challenging due to the fact that contextual information is required from the entire target document to predict the model entities. Hence, traditional sequence labelling approaches fail in such settings. Furthermore, model entities themselves are long-tailed in nature, i.e, their prevalence in scientific literature is limited, along with a scarcity of labelled data for training supervised learning techniques. To address the above bottlenecks, we combine an Unsupervised Graph Ranking algorithm with a SciBERT-CRF based sequence labeller to predict the entities. We introduce a strong baseline using the above mentioned pipeline. Also, to address the label scarcity of long-tailed model entities, we use distant supervision leveraging an external Knowledge Base (KB) to generate synthetic training data. We address the problem of overfitting in small sized datasets for supervised NER baselines using a simple entity replacement technique. We introduce this model as part of a starting point for an end-to-end automated framework to extract relevant model names and link them with their respective cited papers from research documents. We believe this task will serve as an important starting point to map the research landscape of computer science in a scalable manner, needing minimal human intervention. The code and dataset is available in the given link : https://github.com/Swayatta/Competing-Models.
Design and Implementation of an Embedded Pedestrian Detector

Pedestrian detection in complex scenes is a key challenge in traffic detection by video. A newly designed, embedded pedestrian detector based on the kernel TI's DSP chip (TMS320DM642) is proposed. The detector adopts the Hausdorff distance template-matching algorithm for pedestrian detection and tracking. The framework of the algorithm and its DSP optimization procedure is described in detail. The results of a real crossing experiment indicate that the detector is able to rapidly detect pedestrians in a complex traffic scene with 95% precision. Video-based pedestrian detection is a valuable practice among fields of intelligent traffic control, intelligent community monitoring, and supermarket passenger flow estimation. With advances in image processing technology and cost-effective improvement of hardware, pedestrian detection has been widely used in many areas. In recent years, with the development of embedded technology, especially the maturation of the digital signal processors (DSP), embedded pedestrian detection has been improved in both hardware and software. The unique stability of DSP, repeatability of function, superior data processing capability, and especially its programmable and easily implemented adaptive processing, have tremendously developed the real-time image processing field. In comparison with PC machine that is vulnerable to environmental interference, the ability of DSP chip for a particular processing task has considerable advantages for intelligent transportation systems. The pedestrian as an object is a complex pattern influenced by many factors, and finding an effective way to extract the common features of the pedestrian in order to describe the pedestrian model is a key for pedestrian detection. Through combining the characteristics of pedestrian detection and DSP, a DSP-based embedded pedestrian detector which includes the Hausdorff distance template matching algorithm for real-time detection and pedestrian tracking system is constructed through the development platform of TI's DSP chip TMS320DM642 for multimedia applications.