Miracle-dz/UniFAR-FTUs huggingface dataset:
Pulsatile signaling in intercellular communication

The efficiency of various patterns of pulsatile stimulation is determined in a model in which a receptor becomes desensitized in the presence of its stimulatory ligand. The effect of stochastic or chaotic changes in the duration and/or interval between successive pulses in a series of square-wave stimuli is investigated. Before addressing the effect of random variations in the pulsatile signal, we first extend the results of a previous analysis (Li, Y. X., and A. Goldbeter. 1989. Biophys. J. 55:125-145) by demonstrating the existence of an optimal periodic signal that maximizes target cell responsiveness whatever the magnitude of stimulation. As to the effect of stochastic or chaotic variations in the pulsatile stimulus, three kinds of random distributions are used, namely, a Gaussian and a white-noise distribution, and a chaotic time series generated by the logistic map. All these random distributions are symmetrically centered around the reference value of the duration or interval that characterizes the optimal periodic stimulus yielding maximal responsiveness in target cells. Stochastically or chaotically varying pulses are less effective than the periodic signal that corresponds to the optimal pattern of pulsatile stimulation. The response of the receptor system is most sensitive to changes in the time interval that separates successive stimuli. Similar conclusions hold when stochastic or chaotic signals are compared to a reference periodic stimulus differing from the optimal one, although the effect of random variations is then reduced. The decreased efficiency of stochastic pulses accounts for the observed superiority of periodic versus stochastic pulses of cyclic AMP (cAMP) in Dictyostelium amoebae. The results are also discussed with respect to the efficiency of periodic versus stochastic or chaotic patterns of hormone secretion.
Electrical Machines Thermal Model: Advanced Calibration Techniques

Thermal analysis is a key aspect in electrical machine design and for those operating with severe duty where a high-reliability thermal analysis is required. This paper presents a comprehensive analysis of techniques for calibrating generic thermal model of electrical machines. The proposed approach combines two existing experimental methods commonly used in thermal testing of electrical devices. The first method uses a short-duty transient excitation to derive the winding thermal parameters, whereas the second method uses a steady-state excitation to estimate the thermal parameters related to the heat transfer from the winding. Both experimental methods are based on a well-defined heat source provided by a constant current (dc) excitation. For reference, alternative existing methods for calibrating thermal models, are usually combining the winding thermal data predictions and a set of experimentally derived temperatures from dc tests. Such approach, however, might be inadequate if not supported by extensive experimental data. This frequently leads to a significant rate of inaccuracy, thus having a significant impact on the reliability of temperature predictions. The main advantage of newly proposed approach is the reducing of the number of variable parameters and a more systematic calibration process. Additionally, a detailed test procedure for generic thermal model calibration is presented and discussed.
Galaxy correlations, matter correlations and biasing

From the simple assumption that the many-body matter correlation functions behave as a product of two-body correlation functions, that is expected to hold at the scales (0.1 to 10 h −1 Mpc) where the universe in non-linear, we derive the expression of the two- and three-body correlation functions of condensed objects. We demonstrate that the galaxy and the matter correlations are proportional. Their ratio is shown to be a product of two bias factors that depend only on the intrinsic properties of the two objects that are correlated.
Combination of Auction Theory and Multi-Armed Bandits: Model, Algorithm, and Application

The multi-armed bandit (MAB) models have always received lots of attention from multiple research communities due to their broad application domains. The optimal selection problem with unknown rewards in advance, such as ad recommendation in social networks, spectrum access in the cognitive radio field, etc., can be efficiently solved by using MAB models. In an MAB model, given <inline-formula><tex-math notation="LaTeX">$N$</tex-math><alternatives><mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="gao-ieq1-3197459.gif"/></alternatives></inline-formula> arms whose rewards are unknown in advance, the player selects exactly one arm in each round, and his goal is to maximize the cumulative rewards over a fixed horizon. Further, a more general model called combinatorial MAB (i.e., CMAB), where <inline-formula><tex-math notation="LaTeX">$K$</tex-math><alternatives><mml:math><mml:mi>K</mml:mi></mml:math><inline-graphic xlink:href="gao-ieq2-3197459.gif"/></alternatives></inline-formula> arms can be played simultaneously in each round, is put forward. However, the existing CMAB models neglect the strategic behaviors of the <inline-formula><tex-math notation="LaTeX">$N$</tex-math><alternatives><mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="gao-ieq3-3197459.gif"/></alternatives></inline-formula> arms, which indicates that one arm might report false information to increase its own profits. In fact, in many applications such as user selection in crowdsensing, the arms are not the feelingless machines but the rational individuals. To this end, we combine the upper confidence bound (UCB) with auction theory to develop a new algorithm called auction-based UCB (AUCB). We divide the auction-based CMAB problem into two sub-problems: winning arm selection and payment computation problems. For AUCB, we derive an upper bound on regret and prove the truthfulness in one round, individual rationality, and computational efficiency. In addition, we consider an extended situation that some arms may be unavailable in some rounds and the arms will bid inconsistently in different rounds. We devise another algorithm called eAUCB to solve this problem. Extensive simulations are conducted to show the significant performance of the proposed algorithms.
Identification of challenges and their ranking in the implementation of cloud ERP: A comparative study for SMEs and large organizations

Purpose The purpose of this paper is to identify the critical challenges in the implementation of cloud enterprise resource planning (ERP). The challenges identified were customization, organizational change, long-term costs, business complexity, loss of information technology competencies, legal issues, integration, data extraction, monitoring, migration, security, network dependency, limited functionality, awareness, performance, integrity of provider, perception, and subscription costs. Here the small and medium enterprises (SMEs) and large organizations were differentiated with respect to the challenges identified. This paper also suggested ranked lists of challenges both for SMEs and large organizations. Design/methodology/approach An online survey was conducted and data of 93 respondents were analyzed. Exploratory factor analysis and one-way analysis of variance (ANOVA) was used to statistically test the data. Here the SMEs and large organizations were differentiated with respect to the challenges identified. Findings This study shows that SMEs and large organizations differ from each other for most of the challenges except business complexity, integration, monitoring, security, limited functionality, performance, and integrity of provider. Also from the ranked list of challenges in cloud ERP, security was the top concern for both SMEs and large organizations. Originality/value The findings may help organizations to get a broad idea about the challenges which are critical for the implementation of cloud ERP.
Multiagent-based agile manufacturing: requirement-driven low cost production

Author supplied: The production system described in this paper in an im- plementation of an agile agent-based production system. This system is designed to meet the requirements of modern production, where short time to market, requirement-driven production and low cost small quan- tity production are important issues. The production is done on special devices called equiplets. A grid of these equiplets connected by a fast network is capable of producing a variety of diverent products in parallel. The multi-agent-based software infrastructure is responsible for the agile manufacturing. A product agent is responsible for the production of a single product and equiplet agents will perform the production steps to assemble the product. This paper describes this multiagent-based production system with the focus on the product agent.
NEW ROBUST ADAPTIVE BEAMFORMING METHOD FOR MULTIPATH COHERENT SIGNAL RECEPTION

In this paper a novel robust beamforming method is devised to receive multipath signals effectively. The new algorithm constructs a transformation matrix derived through high-order angle constraint to suppress the interferences with the directions of arrival (DOA) of interference signals. Using the transformed data, the composite steering vector of the multipath signals is estimated as the principal eigenvector of the signal subspace, and then is utilized in minimum variance distortionless response (MVDR) beamforming to compute the optimal weight vector. The new algorithm is improved in robustness to DOA error by forming wide nulls in incident directions of the interferences, and keeps effective in the presence of coherent interferences. Simulations analyses are provided to illustrate the robustness and effectiveness of the new beamformer.
Chemical Sensor Nanotechnology in Pharmaceutical Drug Research

The increase in demand for pharmaceutical treatments due to pandemic-related illnesses has created a need for improved quality control in drug manufacturing. Understanding the physical, biological, and chemical properties of APIs is an important area of health-related research. As such, research into enhanced chemical sensing and analysis of pharmaceutical ingredients (APIs) for drug development, delivery and monitoring has become immensely popular in the nanotechnology space. Nanomaterial-based chemical sensors have been used to detect and analyze APIs related to the treatment of various illnesses pre and post administration. Furthermore, electrical and optical techniques are often coupled with nano-chemical sensors to produce data for various applications which relate to the efficiencies of the APIs. In this review, we focus on the latest nanotechnology applied to probing the chemical and biochemical properties of pharmaceutical drugs, placing specific interest on several types of nanomaterial-based chemical sensors, their characteristics, detection methods, and applications. This study offers insight into the progress in drug development and monitoring research for designing improved quality control methods for pharmaceutical and health-related research.
Experimental, Molecular Docking and Molecular Dynamics Investigation on Newly Synthesized Diethyl 4-(Anthracen-9-yl)-2,6-Dimethyl-1,4-Dihydropyridine-3,5-Dicarboxylate

Abstract The novel compound diethyl 4-(anthracen-9-yl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate (DHPA) was synthesized via the Hantzsch method. The synthesized compound was studied through FT-IR, FT-Raman, UV-Vis and NMR studies were compared with Density Functional Theory (DFT) calculations using the B3LYP exchange-correlation functional to evaluate the synthesized compound. Analyzing the molecular structure of the compound provides more biological information that aids in drug design. Quantum chemical calculations using the DFT method, such as molecular geometry optimization, vibrational assignments, frontier molecular orbitals (FMO), molecular electrostatic potential (MEP) map, natural bond orbitals (NBO), global reactive descriptors, and local reactive descriptors, were performed to analyze the structural characteristics and biological properties of the compound. Finally, molecular docking and molecular dynamics were used to determine the binding interaction and stability of the compound in the docked site. The results from simulation studies suggest that DHPA might be an alternative calcium channel blocker drug. Graphical Abstract
Association of Meibomian Gland Dysfunction with Oral Statin Use

This retrospective cross-sectional study aimed to determine the association of oral statin use, dry eye disease (DED), and meibomian gland dysfunction (MGD). A total of 93 subjects were included and divided into two groups: statin users (n = 45) and nonstatin users (n = 47). Significant differences were observed in the total cholesterol (p = 0.013), low-density lipoprotein (LDL) (p = 0.005), and meiboscore (p = 0.000) levels between the two groups. For stratified analysis, the statin group was divided into subgroups according to the type or dose of statin and total duration of statin use. However, there were no differences in clinical features between the subgroups. In multiple regression analysis, meiboscore was significantly associated with age (slope = 0.05, p = 0.00) and statin use (slope = −1.19, p = 0.00), with an R2 of 0.44. Thus, older adults and participants who do not use statin appeared to have higher scores. In conclusion, although the mechanism is unclear, statins may exert a protective effect on the meibomian gland. Further lipidomic studies are required to determine the pharmacological effects of statins on the meibomian gland and other meibum components.
Anabolic Effects of a Novel Simvastatin Derivative on Treating Rat Bone Defects

Large bone defects may develop fracture nonunion, leading to disability and psychosocial burdens. Bone grafting with anabolic agents is a good autografting alternative. Simvastatin, as a cholesterol-lowering agent worldwide, is proven to enhance osteogenesis. Considering its dose-dependent adverse effects, we developed a simvastatin derivative, named KMUHC-01, which has bone anabolic capacity and lower cytotoxicity than simvastatin. We hypothesize that KMUHC-01 could help bone formation in bone-defect animal models. We used rat models of critical calvarial and long-bone defects to evaluate the effects of KMUHC-01 and simvastatin on biological changes at the bone defect through histology, immunohistology, and mechanical testing using three-point bending and evaluated the new bone formation microstructure through microcomputed tomography analysis. The newly formed bone microstructure at the calvarial defect site showed a significantly improved trabecular bone volume in the KMUHC-01 1-μM group compared with that in the control and simvastatin groups. The biomechanical study revealed a significantly increased maximal strength in the KMUHC-01 1-μM group compared with that in the control group. KUMHC-01, as a simvastatin derivative, showed a great anabolic effect in promoting bone defect healing. However, further studies will be conducted to prove the bioavailability and bone-forming efficacy of KMUHC-01 via systemic administration.
SIMPLE GROUPS OF FINITE MORLEY RANK OF ODD AND DEGENERATE TYPE

OF THE DISSERTATION Simple Groups of Finite Morley Rank of Odd and Degenerate Type by Jeffrey Burdges Dissertation Director: Professor Gregory Cherlin The present thesis aims to drive Borovik’s program towards its final endgame, and to lay out a plan for bringing it to a conclusion. Borovik’s program is an approach to the longstanding Algebraicity Conjecture of Cherlin and Zilber, which proposes that all simple groups of finite Morley rank are algebraic. We develop a new characteristic zero notion of unipotence and use it to make progress on various aspects of this algebraicity conjecture. Specifically, we remove the assumption of the noninvolvement of “bad fields,” known as tameness, from several points in the existing odd type theory. Tameness is removed from two critical applications within the signalizer functor theory used in the proof of Borovik’s trichotomy theorem, a result which provides the basic case division in odd type. Tameness is also removed from several points in the analysis of minimal connected simple groups. We also advance the study of groups of degenerate type which are not bad groups, by providing them with an analog of the trichotomy theorem, and we answer a question of Poizat regarding the effects of the Borovik-Poizat axioms from groups of finite Morley rank, outside of the context of groups. A strategy for the conclusion of Borovik’s project, in a suitable form, is outlined in the final chapter.
Leveraging Augmented Intelligence of Things to Enhance Lifetime of UAV-Enabled Aerial Networks

Augmented intelligence is an innovative amplification of artificial intelligence that allows human experts to take over the autonomous decision of machines. It also facilitates human-intelligence-based decisions on the network edge using low-cost and small-sized devices. Augmented intelligence and the Internet of Things collectively create augmented intelligence of things. It logically and effortlessly interrelates human intelligence to articulate smart decisions. Unmanned aerial vehicles find various applications ranging from search operations during disasters to intruders identification; thus, they are suitable for aerial networks, where connections between base stations and servers are extinct. This article presents an approach to enhance the lifetime of unmanned-aerial-vehicles-enabled aerial networks via augmented intelligence. It first considers the available battery power to transform a large-size deep neural network into a lightweight. We next present a knowledge-distillation-based approach, which reduces training time and enhances accuracy. Finally, we evaluate the approach on the existing dataset.
UAV-Based Hyperspectral Imagery for Detection of Root, Butt, and Stem Rot in Norway Spruce

Numerous species of pathogenic wood decay fungi, including members of the genera Heterobasidion and Armillaria, exist in forests in the northern hemisphere. Detection of these fungi through field surveys is often difficult due to a lack of visual symptoms and is cost-prohibitive for most applications. Remotely sensed data can offer a lower-cost alternative for collecting information about vegetation health. This study used hyperspectral imagery collected from unmanned aerial vehicles (UAVs) to detect the presence of wood decay in Norway spruce (Picea abies L. Karst) at two sites in Norway. UAV-based sensors were tested as they offer flexibility and potential cost advantages for small landowners. Ground reference data regarding pathogenic wood decay were collected by harvest machine operators and field crews after harvest. Support vector machines were used to classify the presence of root, butt, and stem rot infection. Classification accuracies as high as 76% with a kappa value of 0.24 were obtained with 490-band hyperspectral imagery, while 29-band imagery provided a lower classification accuracy (~60%, kappa = 0.13).
Transcriptome Analysis of the Anti-Proliferative Effects of Ginsenoside Rh3 on HCT116 Colorectal Cancer Cells

The mechanism of ginsenoside Rh3 activity against cancer remains unclear. This study aimed to investigate the underlying mechanism. The effects of Rh3 on the cell proliferation, migration and invasion, and cycle and apoptosis were analyzed using CCK-8 assay, transwell migration assay and flow cytometry, respectively. The RNA transcriptome was sequenced and data were analyzed by R software. Protein expression and protein-protein interactions were determined by Western blotting and co-immunoprecipitation, respectively. The results showed Rh3 inhibited HCT116 cell proliferation, invasion, and migration, arrested cells at G1 phase; and increased apoptosis. Rh3 downregulated 314 genes and upregulated 371 genes. Gene Set Enrichment Analysis (GSEA) using The Kyoto Encyclopedia of Genes Genomics ranked DNA replication first, while GSEA using Gene Ontology ranked the initiation of DNA replication first. Compared with tumor data from The Cancer Genome Atlas (TCGA), most of genes related to DNA replication were oppositely regulated by Rh3. Furthermore, Rh3 down-regulated key protein expression related to DNA replication (Orc6, Cdt1, and Mcm2), but did not affect the loading of Mcm complexes onto ORC complexes nor the phosphorylation at ser139 of Mcm2. Therefore, Rh3 may inhibit colorectal cancer HCT116 cells by downregulation of genes related to DNA replication.
Mitigating Apoptotic and Inflammatory Signaling via Global Caspase Inhibition in Hibernating Ground Squirrels, Spermophilus lateralis

In most systems, the caspase cascade is activated during cellular stress and results in inflammation and apoptosis. Hibernators experience stressors such as extremely low body temperatures, bradycardia, possible ischemia and reperfusion, and acidosis. However, widespread inflammation and apoptosis would represent an energetic expense that is incompatible with hibernation. To better understand global caspase regulation during hibernation, we employed a systems-level approach and analyzed 11 caspases in ground squirrel liver that are involved in inflammatory (caspases 1, 4, 5, 11, and 12) and apoptotic (caspases 2, 6, 7, 8, 9, and 10) pathways. Western blots revealed liberation of active forms for two inflammatory (caspases 11 and 12) and two apoptotic (caspases 6 and 9) caspases during hibernation (e.g., p15, the most active fragment of caspase 6, increased 8.26±0.70-fold in interbout-aroused animals). We used specific peptide substrates to interrogate the four seemingly activated caspases and demonstrated no expected increases in proteolytic activity. Specific targets of these four caspases were similarly not cleaved, demonstrating that initiation of caspase activation may occur without concomitant downstream effects. Similarly, we found no evidence for upstream activation for caspase 9 signaling based on permeabilization of the outer mitochondrial membrane. We contend that these caspases are suppressed after seeming activation during hibernation. Incomplete caspase signaling is effectively mitigating the induction of widespread inflammation and apoptosis during hibernation.
Larval Anopheles Species Composition and Diversity at Different Habitats and Seasons of Gondar Zuria District, Ethiopia

Anopheles species' larval habitats are diversified and season dependent. Anopheles larvae can be found at different habitats and their preference may vary seasonally. Knowledge of species diversity and distribution helps plan malaria control interventions. Anopheles larvae were sampled using the WHO standard 350 ml dipper from breeding habitats of irrigation, pond, sewage, stream, and swamp. The collected sample larvae were identified microscopically to species using morphological keys. Among Anopheles species recorded, Anopheles gambiae complex was the most abundant followed by Anopheles christyi, Anopheles cinereus, Anopheles demeilloni, and Anopheles pharoensis in descending order. Anopheles species occurred more in January than in other months of the study period and less in March and April. For any particular mosquito species, larval abundance did not significantly vary between the habitats; in other words, all habitats contributed equally. In this study, we confirmed that Anopheles mosquito larval population varied more with respect to species than to habitats and months. Interventions could be launched targeting each habitat; during the month, numbers were high.