Miracle-dz/UniFAR-FTUs huggingface dataset:
Decay Processes and Life Predictions for Lithium Ion Satellite Cells

We have pursued the following steps in the life qualification of lithium ion cells for GEO satellites: • Establish a parametric test data base for flight cells as a function of use and storage. • Use careful DPA of the cells to determine the fundamental changes occurring within the cell. • Determine performance projections for the cell based on the observed internal changes and the measured rates of performance change. This process has been most seriously pursued for the qualification of lithium ion technology for the 15-year GEO mission and with electrochemical cells manufactured by SAFT. Empirically, we find (employing parallel real cycling and storage testing followed by additive decay summation) that the cells demonstrate approximately a 10% loss in energy storage capacity taken through the full mission life. The validity of the approach is based on the decay process elucidation which results for the DPA. Cell DPA conclusively shows that all wear out process in the SAFT cell when operated in the controlled GEO environment arise in the positive electrode. Positive electrode coulombic storage capacity loss appears to be a consequence of structural changes which occur as a result of cycling and possibly destructive reactions between the active material and electrolyte environment during both cycling and storage. Impedance growth is also isolated to the positive electrode. The growth appears to be entirely diffusional in nature. Statistical analysis of test data show that there is a “film-like” t 1/2 component during periods of storage and a component linear with time (or cycles) during cyclic use. DPA evidence appears to support that finding as an amorphous surface film develops on storage. The thickness of this film may actually be reduced by cyclic operation and we presume that the continued impedance growth is due to changes in the mobility of lithium within the crystal structure. The DPA and life test correlation have allowed us to validate the empirical extrapolation of cell performance to end of life. Combined with the fact that we see relatively small changes (~10%) over mission life this provides the confidence required for flight use.
PERFORMANCE ANALYSIS OF MTPR ROUTING PROTOCOL IN POWER DEFICIENT NODE

Power conservation in MobileAd hoc Network (MANET) is a major challenge even today for researchers. To conserve it various power aware routing protocols have been proposed. These protocols do not take into consideration the residual power left in nodes. To find the impact of the same a simulator was designed in MATLAB-7.01. The routing protocol used in our simulation is Minimum Total Power Routing (MTPR) and different performance metrics such as path optimality, throughput and hop count were recorded in presence and absence of power s carce node. The result shows significant impact of power scarce node on MANET performance.
Novel Centralized Pseudonym Changing Scheme for Location Privacy in V2X Communication

Vehicular ad hoc networks allow vehicles to share their information for the safety and efficiency of traffic purposes. However, information sharing can threaten the driver’s privacy as it includes spatiotemporal information, and the messages are unencrypted and broadcasted periodically. Therefore, they cannot estimate their privacy level because it also depends on their surroundings. This article proposes a centralized adaptive pseudonym change scheme that permits the certificate’s authority to adjust the pseudonyms assignment for each requesting vehicle. This scheme adapts dynamically depending on the density of the traffic environment and the user’s privacy level, and it aims to solve the trade-off problem between wasting pseudonyms and Sybil attack. We employ a Knapsack problem-based algorithm for target tracking and an entropy-based method to measure each vehicle’s privacy. In order to demonstrate the applicability of our framework, we use real-life data captured during the interoperability tests of the European project InterCor. According to the experimental results, the proposed scheme could easily estimate the level of confidentiality and, therefore, may best respond to the adaptation of the pseudonyms.
Evaluation and Management of Cerebral Vasospasm after Subarachnoid Hemorrhage

Constriction of the large and medium-sized cerebral arteries following an aneurysmal subarachnoid haemorrhage (aSAH) is a well-known condition that primarily affects the anterior circulation supplied by the internal carotid arteries. SAH is a rare but potentially fatal type of stroke. Across the literature, authors have defined vasospasm using terms such as "symptomatic vasospasm," "delayed cerebral ischemia" (DCI), "transcranial Doppler vasospasm," and "angiographic vasospasm. " Because posthemorrhagic vasospasm causes significant neurologic morbidity and death, there has been a great deal of interest and research into its physiologic basis and developing effective preventative and treatment strategies. The triple-H therapy hemodynamic augmentation technique, which includes hypertension, hemodilution, and hypervolemia, has been an important part of the treatment. In this article, we'll look at cerebral vasospasm following subarachnoid haemorrhage, including its causes, epidemiology, evaluation, and, most importantly, management.
Exploring The Innovativeness Of The South Caucasus Economies: Main Trends And Factors

The main purpose of the present research is to establish an exploratory picture of innovativeness in Armenia, Azerbaijan, and Georgia. The main trends and key determinants of innovativeness in the South Caucasus have rarely been investigated in mainstream economic research. However, the South Caucasus is a rapidly developing post-Soviet region, and it is geographically strategic for several key players in the global economy, including China and the European Union (EU). In fact, the role of the South Caucasus in international economic agreements is growing due to increased partnerships between Eastern and Western countries. Thus, the region’s current and future innovativeness will determine its integration into global value chains (GVCs). This study employs figure analysis to examine and compare the innovativeness of individual countries and the region as a whole against relevant economic and institutional indicators discussed in the literature. Using scatter plots, a polynomial trendline approach allowed the data to be divided into more meaningful periods of analysis to better understand peaks and dips in national innovativeness in association with selected economic and institutional indicators in the South Caucasus. Overall, the results show that economic growth and economic freedom play an important role in innovativeness in the South Caucasus, while institutional factors present more of a mixed picture. More specifically, the region’s overall innovativeness was positively correlated with rule of law and property rights to a certain extent, but this association was not consistent. In addition, Armenia and Georgia experienced higher growth in national innovativeness between 2011 and 2020, while this growth was weaker in Azerbaijan. This paper’s results may help the South Caucasus countries conceptualize their innovativeness in terms of the region’s overall innovativeness and key economic and institutional variables. Moreover, more sophisticated quantitative techniques and econometric models may be applied in future research.
Investigação em educação histórica: a “autópsia” de um estudo baseado na teoria fundamentada – Grounded Theory

A Educação Histórica enquanto campo de saber pautou-se desde a sua origem pela procura de compreender como se faz sentido do passado e se pensa a História. Assim, a investigação em Educação Histórica tem sido alicerçada em várias abordagens,essencialmente, de foro qualitativo para procurar compreender em profundidade as ideias dos vários agentes educativos e históricos. A Teoria Fundamentada – Grounded Theory tem sido uma das abordagens investigativas partilhadas por vários estudos neste campo de saber, especialmente em Portugal e no Reino Unido. Propõe-se a partilha do percurso investigativo de um estudo em Educação Histórica que pretendia compreender as conceções de professores de História acerca da narrativa enquanto uma das faces da consciência histórica. Assim, esta “autópsia” a este estudo de investigação pode permitir que seja mais percetível como a Teoria Fundamentada pode ser operacionalizada em estudos de investigação em Educação Histórica, desde os momentos iniciais de definição de problema de investigação, participantes, instrumentos de recolha de dados, análise contínua de dados e a construção de teias concetuais, passando pelas decisões que foram sendo tomadas, até à concretização do estudo final e construção de perfis de ideias.A investigação em Educação Histórica tem caminhos a percorrer, considerando-se que estudos de investigação colaborativos e longitudinais poderão ser interessantes para uma compreensão multiperspetivada mais dialógica interculturalmente.
Replicação Máquina de Estados Paralelas com Escalonamento Híbrido

Replicação Máquina de Estados (RME) é uma abordagem muito utilizada na implementação de sistemas tolerantes a falhas e consiste em replicar os servidores e fazer com que os mesmos executem deterministicamente, e na mesma ordem, o mesmo conjunto de requisições. Para melhorar o desempenho, RMEs paralelas utilizam escalonadores que tiram proveito da semântica das requisições e permitem a execução paralela de algumas delas. No escalonamento tardio as requisições são escalonadas para execução após serem ordenadas, enquanto que no escalonamento antecipado parte das decisões de escalonamento são realizadas antes da ordenação e respeitadas durante a execução. Este trabalho propõe um protocolo de escalonamento híbrido que tira proveito das vantagens de cada uma das abordagens anteriores. Experimentos mostram que o escalonador híbrido supera as outras abordagens em diversos cenários.
Where We Stand With Precision Therapeutics in Myeloma: Prosperity, Promises, and Pipedreams

Multiple myeloma remains an incurable disease despite numerous novel agents being approved in the last decade. Furthermore, disease behavior and susceptibility to current treatments often vary drastically from patient to patient. To date there are no approved therapies in myeloma that are targeted to specific patient populations based on genomic or immunologic findings. Precision medicine, using biomarkers descriptive of a specific tumor’s biology and predictive of response to appropriate agents, may continue to push the field forward by expanding our treatment arsenal while refining our ability to expose patients to only those treatments likely to be efficacious. Extensive research efforts have been carried out in this endeavor including the use of agents targeting Bcl2 and the RAS/MAPK and PI3K/AKT/mTOR pathways. Thus far, clinical trials have yielded occasional successes intermixed with disappointments, reflecting significant hurdles which still remain including the complex crosstalk between oncogenic pathways and the nonlinear genetic development of myeloma, prone to cultivating sub-clones with distinctive mutations. In this review, we explore the landscape of precision therapeutics in multiple myeloma and underscore the degree to which research efforts have produced tangible clinical results.
Differentiation of Cells Isolated from Human Femoral Heads into Functional Osteoclasts

Proper formation of the skeleton during development is crucial for the mobility of humans and the maintenance of essential organs. The production of bone is regulated by osteoblasts and osteoclasts. An imbalance of these cells can lead to a decrease in bone mineral density, which leads to fractures. While many studies are emerging to understand the role of osteoblasts, less studies are present about the role of osteoclasts. This present study utilized bone marrow cells isolated directly from the bone marrow of femoral heads obtained from osteoarthritic (OA) patients after undergoing hip replacement surgery. Here, we used tartrate resistant acid phosphatase (TRAP) staining, Cathepsin K, and nuclei to identity osteoclasts and their functionality after stimulation with macrophage-colony stimulation factor (M-CSF) and receptor activator of nuclear factor kappa-β ligand (RANKL). Our data demonstrated that isolated cells can be differentiated into functional osteoclasts, as indicated by the 92% and 83% of cells that stained positive for TRAP and Cathepsin K, respectively. Furthermore, isolated cells remain viable and terminally differentiate into osteoclasts when stimulated with RANKL. These data demonstrate that cells isolated from human femoral heads can be differentiated into osteoclasts to study bone disorders during development and adulthood.
Joseph Turow. The voice catchers: How marketers listen in to exploit your feelings, your privacy, and your wallet

“Voice profiling is a gateway drug to a new era of hyper-personalized targeting,” (p. 227) Joseph Turow concludes in his book The Voice Catchers: How Marketers Listen in to Exploit Your Feelings, Your Privacy, and Your Wallet. This crucial function of what Turow calls the “voice intelligence industry” explains the urgency of Turow’s most recent endeavor: a thorough examination of this industry which consists of different players, most centrally call center firms and the developers of voice assistants such as Amazon’s Alexa, the Google Assistant, Apple’s Siri, and Samsung’s Bixby. The industry is united by its interest in using voice as another source for collecting biometrical data. Such voiceprints, as Turow figuratively puts it, are the “gold in people’s speech” (p. 192). In contrast to the face as another source for biometrical data, voice has received comparatively little public attention.
Wavelets

The subject of ‘wavelets’ is expanding at such a tremendous rate that it is impossible to give, within these few pages, a complete introduction to all aspects of its theory. We hope, however, to allow the reader to become sufficiently acquainted with the subject to understand, in part, the enthusiasm of its proponents toward its potential application to various numerical problems. Furthermore, we hope that our exposition can guide the reader who wishes to make more serious excursions into the subject. Our viewpoint is biased by our experience in approximation theory and data compression; we warn the reader that there are other viewpoints that are either not represented here or discussed only briefly. For example, orthogonal wavelets were developed primarily in the context of signal processing, an application upon which we touch only indirectly. However, there are several good expositions (e.g. Daubechies (1990) and Rioul and Vetterli (1991)) of this application. A discussion of wavelet decompositions in the context of Littlewood-Paley theory can be found in the monograph of Frazier et al. (1991). We shall also not attempt to give a complete discussion of the history of wavelets. Historical accounts can be found in the book of Meyer (1990) and the introduction of the article of Daubechies (1990). We shall try to give sufficient historical commentary in the course of our presentation to provide some feeling for the subject's development.
New Secondary Metabolites from the Marine-Derived Fungus Talaromyces mangshanicus BTBU20211089

Seven new compounds, namely talaromanloid A (1), talaromydene (2), 10-hydroxy-8-demethyltalaromydine and 11-hydroxy-8-demethyltalaromydine (3 and 4), talaromylectone (5), and ditalaromylectones A and B (6 and 7), together with seven known compounds were identified from a marine-derived fungus, Talaromyces mangshanicus BTBU20211089, which was isolated from a sediment sample collected from the South China Sea. Their chemical structures were determined using spectroscopic data, including HRESIMS, 1D, and 2D NMR techniques. The absolute configurations of 1 and 2 were elucidated by comparing experimental and calculated ECD spectra. Compounds 1, 2, 6, and 7 are new compounds possessing a novel carbon skeleton. Compound 6 is a dimeric molecule of 3 and 9. Compound 7 shared a unique structure of the cyclized dimer of 3 and 4. All the compounds were tested for their bioactivities against Staphylococcus aureus, Escherichia coli, and Candida albicans.
Targeting of Smad7 in Mesenchymal Cells Does Not Exacerbate Fibrosis During Experimental Chronic Pancreatitis

Objectives Transforming growth factor-β (TGF-β)–mediated accumulation of extracellular matrix proteins such as collagen I is a common feature of fibrosis. Pancreatic stellate cells play an integral role in the pathogenesis of pancreatitis, and their profibrotic ability is mainly mediated by TGF-β signaling. To specifically address the role of fibrogenic cells in experimental pancreatic fibrosis, we deleted Smad7, the main feedback inhibitor of TGF-β signaling in this cell type in mice. Methods A mouse strain harboring a conditional knockout allele of Smad7 (Smad7fl/fl) with the tamoxifen-inducible inducible Col1a2-CreERT allele was generated and compared with wild-type mice challenged with the cerulein-based model of chronic pancreatitis. Results Pancreatic stellate cells lacking Smad7 had significantly increased collagen I and fibronectin production and showed a higher activation level in vitro. Surprisingly, the fibrotic index in the pancreata of treated conditional knockout mice was only slightly increased, without statistical significance. Except for fibronectin, the expression of different extracellular matrix proteins and the numbers of fibroblasts and inflammatory cells were similar between Smad7-mutant and control mice. Conclusions There was no clear evidence that the lack of Smad7 in pancreatic stellate cells plays a major role in experimental pancreatitis, at least in the mouse model investigated here.
Review on Effective Treatments of Burning Mouth Syndrome

Ghasemi S1*, Zokaee H2, Mirzaei F3 and Daroudi G4 1DDS, MSc of Oral Surgery, Clinical Assistant Professor of OMFS Department of Augusta University ,GA,USA, 2Assisstant Professor of Oral and Maxillofacial Medicine, Dental Research Center, Golestan University of Medical Sciences, Gorgan, Iran 3Dentistry Student, Student Research Committee, Golestan University of Medical Sciences, Gorgan, Iran 4Dentistry Student, Student Research Committee, Golestan University of Medical Sciences, Gorgan, Iran
Subsequent Subarachnoid Hemorrhage from Clinically Unrelated Vertebral Artery Dissection after Thrombolytic Therapy

Thrombolysis administration poses certain safety issues in ischemic stroke patients with cerebrovascular changes that are vulnerable to hemorrhage. Furthermore, the lack of related studies has resulted in an unclear understanding of thrombolysis safety in ischemic stroke patients with intracranial dissection, including those involving the vertebral artery. This study describes a case of a 59-year-old female who developed subarachnoid hemorrhage from clinically unrelated vertebral artery dissection after thrombolysis. Histories of severe headache with posterior fossa involvement in patients receiving thrombolytic therapy may indicate careful assessment for intracranial vertebral artery dissection, even if the clinical picture of the patient suggests another arterial syndrome.
Network Traffic Prediction Model Considering Road Traffic Parameters Using Artificial Intelligence Methods in VANET

Vehicular Ad hoc Networks (VANETs) are established on vehicles that are intelligent and can have Vehicle-to-Vehicle (V2V) and Vehicle-to-Road Side Units (V2R) communications. In this paper, we propose a model for predicting network traffic by considering the parameters that can lead to road traffic happening. The proposed model integrates a Random Forest- Gated Recurrent Unit- Network Traffic Prediction algorithm (RF-GRU-NTP) to predict the network traffic flow based on the traffic in the road and network simultaneously. This model has three phases including network traffic prediction based on V2R communication, road traffic prediction based on V2V communication, and network traffic prediction considering road traffic happening based on V2V and V2R communication. The hybrid proposed model which implements in the third phase, selects the important features from the combined dataset (including V2V and V2R communications), by using the Random Forest (RF) machine learning algorithm, then the deep learning algorithms to predict the network traffic flow apply, where the Gated Recurrent Unit (GRU) algorithm gives the best results. The simulation results show that the proposed RF-GRU-NTP model has better performance in execution time and prediction errors than other algorithms which used for network traffic prediction.
Efficient Computer Aided Diagnosis System for Hepatic Tumors Using Computed Tomography Scans

One of the leading causes of mortality worldwide is liver cancer. The earlier the detection of hepatic tumors, the lower the mortality rate. This paper introduces a computer-aided diagnosis system to extract hepatic tumors from computed tomography scans and classify them into malignant or benign tumors. Segmenting hepatic tumors from computed tomography scans is considered a challenging task due to the fuzziness in the liver pixel range, intensity values overlap between the liver and neighboring organs, high noise from computed tomography scanner, and large variance in tumors shapes. The proposed method consists of three main stages; liver segmentation using Fast Generalized Fuzzy C-Means, tumor segmentation using dynamic thresholding, and the tumor’s classification into malignant/benign using support vector machines classifier. The performance of the proposed system was evaluated using three liver benchmark datasets, which are MICCAI-Sliver07, LiTS17, and 3Dircadb. The proposed computer adided diagnosis system achieved an average accuracy of 96.75%, sensetivity of 96.38%, specificity of 95.20% and Dice similarity coefficient of 95.13%.
Confronting or avoiding confrontation? The role of sexism in evaluating women who avoid confronting discrimination (¿Confrontar o evitar hacerlo? El rol del sexismo en la evaluación de mujeres que evitan confrontar la discriminación)

ABSTRACT Confrontation is a good strategy for lowering discrimination. Given that victims who confront are evaluated negatively, the role of witnesses of discrimination is crucial. Therefore, the aim of this study was to analyse how women who confront discrimination not directed towards them are evaluated (versus those who don’t confront), by examining the role of two factors: sexist attitudes and the characteristics of the woman. In one experimental study with a general population (N = 657), we found that women who confront a racist comment are perceived more positively than women who do not confront. However, women who do not confront are more positively evaluated by sexist participants (vs less sexist individuals). The characteristics of the women do not affect the participants’ evaluation of them. These results show that even though women who confront may be positively evaluated in general, prejudice towards women is a key factor in the perception of women who choose not to confront.
AUTOMATED TIMETABLE GENERATOR USING PARTICLE SWARM OPTIMIZATION

The timetabling problem at universities is an NP-hard problem under multiple constraints and limited resources. Thus a technique that can handle constraints is needed to optimize the problem. This paper focuses on Particle Swarm Optimization (PSO) for finding optimal solutions to the problem of course Timetabling at a Punjabi University Patiala. PSO is a promising scheme for solving NP - hard problems due to its fast convergence and fewer parameter settings . There are two objectives in this. First provide a detailed introduction to the topic of timetabling, Particle Swarm Optimization their method and their variations. The second objective is to apply them to the problem of Course Timetabling. The proposed algorithm is tested using the timetabling data from Department of Computer Science, Punjabi University, Patiala.