Search

Your search keyword '"Marjani"' showing total 4,755 results
Start Over Author "Marjani"
4,755 results on '"Marjani"'

1. The Influence Of Strategic Orientation Dimensions On Market Performance During Covid-19 Pandemic: A Study Of Culinary Business In Kendari City, Indonesia

Author

Indri Hapsari, Yunitawati Lampasa, Marjani Marjani, Juwita Juwita, and Hairudin Bugis

Subjects
dimension, strategy orientation, market performance, covid-19, Management. Industrial management, HD28-70, Business, HF5001-6182
Abstract

This study aimed to analyze the effect of the strategic orientation dimension on the culinary business market performance in Kendari City during the Corona Virus Disease Pandemic. The method used was descriptive quantitative with a non-probability sampling approach with purposive sampling technique. The population was culinary business actors who still survive and have been running for the business more than 2 years during the COVID-19 pandemic. The sample in this study only obtained 38 respondents. The data analysis technique in this research was path analysis using SmartPLS VS 3.0. The results showed an analysis of the strategic dimensions that have an aggressive attitude and had significant effect on market performance so that culinary business actors can improve their market performance during the COVID-19 pandemic.

Published
2023
Full Text
View/download PDF

2. Effect of Rubus anatolicus Leaf Extract on Glucose Metabolism in HepG2, CRI-D2 and C2C12 Cell Lines

Author

Safarzad M, Marjani A, Saghaeian Jazi M, Qujeq D, Mir SM, Marjani M, and Nezhadebrahimi Kaldehi A

Subjects
rubus anatolicus, glucose metabolism, hepg2, cri-d2, c2c12, cell lines, Specialties of internal medicine, RC581-951
Abstract

Mahdieh Safarzad,1 Abdoljalal Marjani,1 Marie Saghaeian Jazi,1 Durdi Qujeq,2 Seyed Mostafa Mir,2 Majid Marjani,3 Abbas Nezhadebrahimi Kaldehi1 1Metabolic Disorders Research Center, Department of Biochemistry and Biophysics, Gorgan Faculty of Medicine, Golestan University Medical Sciences, Gorgan, Iran; 2Cellular and Molecular Biology Research Center, Health Research Institute, Department of Clinical Biochemistry, Student Research Committee, Babol University of Medical Science, Babol, Iran; 3Faculty of Pharmacy, Eastern Mediterranean University, Famagusta 99628, TurkeyCorrespondence: Abdoljalal MarjaniMetabolic Disorders Research Center, Department of Biochemistry and Biophysics, Faculty of Medicine, Golestan University of Medical Sciences, Gorgan, Golestan Province 4934174515, IranTel +98 171 4421651Fax +98 171 4440225Email abdoljalal@yahoo.comIntroduction: The aim of this study was to assess the effects of Rubus anatolicus on glucose metabolism in HepG2, CRI-D2 and C2C12 cell lines.Materials and Methods: R. anatolicus was collected in Golestan province, Iran. Three different cell lines HepG2 (human liver cell), CRI-D2 (mice pancreatic cell) and C2C12 (rat myoblast) were used for cell culture experiments. Cell viability was measured using MTT assay. Cells were treated with various concentrations of the extract (6.25– 400 μg/mL) and then the extracellular glucose level and intracellular glycogen content were measured using colorimetric methods. The insulin level of the culture medium was measured using the ELISA method.Results: Our findings showed that R. anatolicus extract enhances glucose uptake and consumption by all three cell lines. The R. anatolicus extract exposure also elevated cellular glycogen content in HepG2 and C2C12 cells (for 200 and 100 μg/mL) significantly. We found a significant increase in glucose uptake and consequently higher stimulation of insulin secretion in CRI-D2 cell pancreatic cells treated with R. anatolicus extract.Conclusion: The R. anatolicus appears to activate glucose uptake and cellular glycogen synthesis probably by activating the glycogenesis or inhibition of glycogenolysis pathways. The extract enhances insulin secretion in the pancreatic cells by increased glucose uptake.Keywords: Rubus anatolicus, glucose metabolism, HepG2, CRI-D2, C2C12, cell lines

Published
2020

3. Differentially Private Best-Arm Identification

Author

Azize, Achraf, Jourdan, Marc, Marjani, Aymen Al, and Basu, Debabrota

Subjects
Statistics - Machine Learning, Computer Science - Cryptography and Security, Computer Science - Machine Learning, Mathematics - Statistics Theory
Abstract

Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical trials, tuning hyper-parameters, and conducting user studies. Motivated by the data privacy concerns invoked by these applications, we study the problem of BAI with fixed confidence in both the local and central models, i.e. $\epsilon$-local and $\epsilon$-global Differential Privacy (DP). First, to quantify the cost of privacy, we derive lower bounds on the sample complexity of any $\delta$-correct BAI algorithm satisfying $\epsilon$-global DP or $\epsilon$-local DP. Our lower bounds suggest the existence of two privacy regimes. In the high-privacy regime, the hardness depends on a coupled effect of privacy and novel information-theoretic quantities involving the Total Variation. In the low-privacy regime, the lower bounds reduce to the non-private lower bounds. We propose $\epsilon$-local DP and $\epsilon$-global DP variants of a Top Two algorithm, namely CTB-TT and AdaP-TT*, respectively. For $\epsilon$-local DP, CTB-TT is asymptotically optimal by plugging in a private estimator of the means based on Randomised Response. For $\epsilon$-global DP, our private estimator of the mean runs in arm-dependent adaptive episodes and adds Laplace noise to ensure a good privacy-utility trade-off. By adapting the transportation costs, the expected sample complexity of AdaP-TT* reaches the asymptotic lower bound up to multiplicative constants., Comment: arXiv admin note: substantial text overlap with arXiv:2309.02202

Published
2024

4. MicroRNA-146a as a Prognostic Biomarker for Esophageal Squamous Cell Carcinoma

Author

Sadegh Shesh Poli M, Khajeniazi S, Behnampour N, Kalani MR, Moradi A, and Marjani A

Subjects
mir-146a, cyclooxygenase-2, esophageal cancer, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Maryam Sadegh Shesh Poli,1 Safoura Khajeniazi,2 Nasser Behnampour,3 Mohammad Reza Kalani,4 Abdolvahab Moradi,5 Abdoljalal Marjani6 1School of New Technologies, Golestan University of Medical Sciences, Gorgan, Iran; 2Medical Cellular and Molecular Research Center, Golestan University of Medical Sciences, Gorgan, Iran; 3Health Management and Social Development Research Center, Gorgan, Iran; 4Molecular Medicine Research Center, Golestan University of Medical Sciences, Gorgan, Iran; 5Gastroenterology and Hepatology Research Center, Golestan University of Medical Sciences, Gorgan, Iran; 6Abdoljalal Marjani Metabolic Disorders Research Center, Department of Biochemistry and Biophysics, Faculty of Medicine, Golestan University of Medical Sciences, Gorgan, IranCorrespondence: Abdolvahab MoradiGastroenterology and Hepatology Research Center, Golestan University of Medical Sciences, Gorgan 4934174515, IranTel +98 9111772107Email abmoradi@yahoo.comAbdoljalal MarjaniMetabolic Disorders Research Center, Department of Biochemistry and Biophysics, Faculty of Medicine, Golestan University of Medical Sciences, Gorgan, Golestan Province 4934174515, IranTel +98 171 4421651Fax +98 171 4440225Email abdoljalal@yahoo.comBackground and Aims: MicroRNAs including miR146a have a regulatory role on the expression of genes and act with binding to 3ʹ-UTR region of the genes. Cyclooxygenase-2 (COX-2) is involved in carcinogenesis as an inflammatory marker, and microRNA-146a (miR-146a) as a negative regulatory factor. We aimed to evaluate miR146a expression as a prognostic or diagnostic biomarker for esophageal squamous cell carcinoma (ESCC) and also an association between miR146a and COX2 expression.Materials and Methods: We quantified the level of miR-146a and COX-2 expression in cancerous and adjacent normal tissue samples obtained from 34 patients with ESCC, using real-time–PCR. Statistical analyses were conducted using one-sample t-test. Receiver-operating characteristic (ROC) curve and Kaplan–Meier analysis were applied to assay miR146a as a diagnostic and prognostic marker, respectively, during 4 years of the study. Furthermore, the Cox regression model was performed to assay the hazard ratio (HR). The association between miR-146a and COX2 expression level in ESCC patients was evaluated by nonparametric Spearman’s rho analysis.Results: The results revealed a reduction of miR-146a expression in 50% of cancerous tissue when compared with adjacent normal regions (P-value=0.127). COX-2 expression in 80% of ESCC patients was higher than in the controls (P-value=0.001). Overall, in 60% of cases, direct association was seen between microRNA-146a and COX-2 expression level (correlation coefficient= 0.438, P-value=0.011). COX2 can be considered as a diagnostic biomarker (AUC=0.834, sensitivity=72%, specificity =83%, P-value< 0.0001) but miR146a cannot be considered as a diagnostic biomarker (AUC=0.553, sensitivity=88%, specificity =28%, P-value=0.453). Survival analysis by Kaplan–Meier method showed miR146a and COX2 expression can be probably considered as prognostic biomarkers for ESCC because patients with high expression of miR146a had 7 months shorter life span and patients with low expression of COX2 had 8 months shorter life span.Conclusion: COX2 expression is a diagnostic biomarker. MiR-146a and COX2 expression can probably be considered as prognostic biomarkers for survival in ESCC.Keywords: miR-146a, cyclooxygenase-2, esophageal cancer

Published
2020

5. Resistance of Several Hibiscus cannabinus genotypes Against Meloidogyne incognita

Author

Parnidi Parnidi, Lita Soetopo, Damanhuri Damanhuri, and Marjani Marjani

Subjects
asam salisilat, fenol, lignin, nematoda puru akar, tanah berpasir, Botany, QK1-989
Abstract

Kenaf merupakan salah satu tanaman yang menghasilkan serat alam. Infeksi Meloidogyne incognita (nematoda puru akar) pada tanaman kenaf menyebabkan tanaman kerdil sehingga menurunkan produksi tanaman. Penelitian ini bertujuan menentukan ketahanan tujuh genotipe kenaf terhadap M. incognita. Percobaan dilakukan dengan menginfestasi tanaman kenaf yang berumur 15 hari setelah tanam (HST) dengan M. incognita pada populasi 40 nematoda juvenil 2 per 100 g tanah. Medium tanam yang digunakan ialah tanah berpasir dengan komposisi pasir 55%, debu 36%, dan liat 17%. Variabel ketahanan terdiri atas indeks puru akar dan faktor reproduksi nematoda. Analisis asam salisilat, fenol, lignin serta beberapa variabel pertumbuhan tanaman dilakukan pada umur tanaman 75 HST. Diantara tujuh genotipe tanaman kenaf yang dievaluasi terdapat 3 genotipe yang toleran (KR4, KR15 dan KR5) dan 4 genotipe sangat rentan (KR1, KR6, Kin2, dan DS028). Genotipe yang memiliki respons toleran terhadap M. incognita menunjukkan peningkatan senyawa fenol, asam salisilat, dan lignin pada akar dibandingkan dengan kontrol. Penurunan tinggi tanaman, bobot segar tajuk, dan bobot segar akar bervariasi akibat infeksi M. incognita.

Published
2021
Full Text
View/download PDF

6. Agricultural waste biomass-assisted nanostructures: Synthesis and application

Author

Zamani Asghar, Marjani Ahmad Poursattar, and Mousavi Zahra

Subjects
agricultural waste, metal oxide, nanoparticles, nanoporous materials, catalysis, textural properties, Chemistry, QD1-999
Abstract

Metal oxide nanoporous materials and nanoparticles have main potential uses in several different fields such as nanoelectronics, biomedical science, renewable solar energy, drug-gene delivery, thermal insulation, and so on. On the other hand, it is vital for scientists to understand that agricultural waste biomass-assisted synthesis is less costly, environmentally friendly and renewable strategy, and therefore, agricultural wastes are ideal renewable resources for production of nanostructures as a substitute for toxic chemicals. This present review includes significant recent improvements concerning the synthesis of agricultural waste biomass-assisted metal oxide nanostructures and their application. The goal is to provide a vision for the use of non-extracted agricultural waste, especially lignocellulosic biomass an inexpensive, green, differentiated resource and policy for the synthesis of valuable nanoporous materials and nanoparticles.

Published
2019
Full Text
View/download PDF

7. Synthesis of pyrazolopyridine and pyrazoloquinoline derivatives by one-pot, three-component reactions of arylglyoxals, 3-methyl-1-aryl-1H-pyrazol-5-amines and cyclic 1,3-dicarbonyl compounds in the presence of tetrapropylammonium bromide

Author

Marjani Ahmad Poursattar, Khalafy Jabbar, and Akbarzadeh Somayeh

Subjects
arylglyoxals, cyclic 1,3-dicarbonyl compounds, 3-methyl-1-aryl-1h-pyrazol-5-amines, pyrazolopyridines, pyrazoloquinolines, tetrapropylammonium bromide, Chemistry, QD1-999
Abstract

Pyrazolopyridine and pyrazoloquinoline derivatives were obtained by a one-pot, three-component reaction of arylglyoxals, 3-methyl-1-aryl-1H-pyrazol-5-amines and cyclic 1,3-dicarbonyl compounds in the presence of tetrapropylammonium bromide at 80°C in water through Knoevenagel and Micheal reactions, followed by intramolecular condensation, unexpected dearoylation and oxidation. Mild reaction conditions, high yields, simplicity of work up procedure, starting materials availability and clean product formation are some of the main advantages of this synthetic strategy.

Published
2019
Full Text
View/download PDF

9. Serum levels of nitrite/nitrate, lipid profile, and Fasting Plasma Glucose and their associations in subclinical hypothyroid women before and after a two month treatment by levothyroxine

Author

Hashemi Mohammad Mostakhdem, Kosari Elahe, Mansourian Azad Reza, and Marjani Abdoljalal

Subjects
subclinical hypothyroid, levothyroxine, nitrite/nitrate, lipid profile, fasting plasma glucose, Internal medicine, RC31-1245
Abstract

Background. Subclinical hypothyroidism (sHT) is a condition defined by elevated TSH values with normal levels of free thyroid hormones. Altered metabolic status is one of the consequences of sHT which can affect serum levels of FPG, lipid profile, and nitric oxide which propounds cardiovascular consequences per se. The aim of this study was to determine the possible effects of sHT on nitrite/nitrate levels, as a marker of endothelial performance.

Published
2017
Full Text
View/download PDF

10. Serum Progranulin Levels in Type 2 Diabetic Patients with Metabolic Syndrome

Author

Shafaei Azam, Marjani Abdoljalal, and Khoshnia Masoud

Subjects
diabetes mellitus, type 2, syndrome x, metabolic, diseases, Internal medicine, RC31-1245
Abstract

Introduction. The role of progranulin in individuals with metabolic syndrome is not exactly clear.We aimed to assess the serum level of progranulin in type 2 diabetic patients with and without metabolic syndrome and compare them with healthy controls.

Published
2016
Full Text
View/download PDF

12. Towards Instance-Optimality in Online PAC Reinforcement Learning

Author

Al-Marjani, Aymen, Tirinzoni, Andrea, and Kaufmann, Emilie

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

Several recent works have proposed instance-dependent upper bounds on the number of episodes needed to identify, with probability $1-\delta$, an $\varepsilon$-optimal policy in finite-horizon tabular Markov Decision Processes (MDPs). These upper bounds feature various complexity measures for the MDP, which are defined based on different notions of sub-optimality gaps. However, as of now, no lower bound has been established to assess the optimality of any of these complexity measures, except for the special case of MDPs with deterministic transitions. In this paper, we propose the first instance-dependent lower bound on the sample complexity required for the PAC identification of a near-optimal policy in any tabular episodic MDP. Additionally, we demonstrate that the sample complexity of the PEDEL algorithm of \cite{Wagenmaker22linearMDP} closely approaches this lower bound. Considering the intractability of PEDEL, we formulate an open question regarding the possibility of achieving our lower bound using a computationally-efficient algorithm.

Published
2023

13. On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence

Author

Azize, Achraf, Jourdan, Marc, Marjani, Aymen Al, and Basu, Debabrota

Subjects
Statistics - Machine Learning, Computer Science - Cryptography and Security, Computer Science - Machine Learning, Mathematics - Statistics Theory
Abstract

Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical trials, tuning hyper-parameters, and conducting user studies to name a few. Motivated by the data privacy concerns invoked by these applications, we study the problem of BAI with fixed confidence under $\epsilon$-global Differential Privacy (DP). First, to quantify the cost of privacy, we derive a lower bound on the sample complexity of any $\delta$-correct BAI algorithm satisfying $\epsilon$-global DP. Our lower bound suggests the existence of two privacy regimes depending on the privacy budget $\epsilon$. In the high-privacy regime (small $\epsilon$), the hardness depends on a coupled effect of privacy and a novel information-theoretic quantity, called the Total Variation Characteristic Time. In the low-privacy regime (large $\epsilon$), the sample complexity lower bound reduces to the classical non-private lower bound. Second, we propose AdaP-TT, an $\epsilon$-global DP variant of the Top Two algorithm. AdaP-TT runs in arm-dependent adaptive episodes and adds Laplace noise to ensure a good privacy-utility trade-off. We derive an asymptotic upper bound on the sample complexity of AdaP-TT that matches with the lower bound up to multiplicative constants in the high-privacy regime. Finally, we provide an experimental analysis of AdaP-TT that validates our theoretical results.

Published
2023

14. Control Home Appliances Through Internet of Things To Assist Elderly In Their Daily Routine

Author

Phua Karsten Cheng Kai, Goh Wei Wei, and Marjani Mohsen

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

Aging population rate in Malaysia is getting higher every year. When people becoming older, they start losing their abilities to do some of the activities properly and easily that they were able to do when they were younger. Basic tasks like cooking and cleaning, which were once part of manageable daily routine, become too difficult to perform as they enter to the elderly age. Despite this, many elderlies choose to live independently in their own home. This paper presents a new approach to utilize advanced Internet of Things (IoT) based pulse sensors for elderly. This proposed solution is an embedded scheme that support elderly with controlled automation solution that control and operates various home electrical appliances such as lights, fans, and televisions based on the measurement of pulse rate and instructions. The solution consists of pulse sensors, microcontrollers which integrated with Blynk server as a communication protocol. The proposed solution aims to minimize elderly movement by providing substantial assistance to the physically challenged elderly without assistance from any third person. The scope of the article focuses on enhancing and improving quality life of elderly. The main advantage of the proposed solution is that it is sensible and required zero technology knowledge that provides users with an automation solution with minimum movement needed. The proposed solution reduces human labours, effort, and energy conservation in the meantime. This study is limited to the scale of elderly in Malaysia rather than the whole world.

Published
2021
Full Text
View/download PDF

15. Active Coverage for PAC Reinforcement Learning

Author

Al-Marjani, Aymen, Tirinzoni, Andrea, and Kaufmann, Emilie

Subjects
Computer Science - Machine Learning
Abstract

Collecting and leveraging data with good coverage properties plays a crucial role in different aspects of reinforcement learning (RL), including reward-free exploration and offline learning. However, the notion of "good coverage" really depends on the application at hand, as data suitable for one context may not be so for another. In this paper, we formalize the problem of active coverage in episodic Markov decision processes (MDPs), where the goal is to interact with the environment so as to fulfill given sampling requirements. This framework is sufficiently flexible to specify any desired coverage property, making it applicable to any problem that involves online exploration. Our main contribution is an instance-dependent lower bound on the sample complexity of active coverage and a simple game-theoretic algorithm, CovGame, that nearly matches it. We then show that CovGame can be used as a building block to solve different PAC RL tasks. In particular, we obtain a simple algorithm for PAC reward-free exploration with an instance-dependent sample complexity that, in certain MDPs which are "easy to explore", is lower than the minimax one. By further coupling this exploration algorithm with a new technique to do implicit eliminations in policy space, we obtain a computationally-efficient algorithm for best-policy identification whose instance-dependent sample complexity scales with gaps between policy values., Comment: Accepted at COLT 2023

Published
2023

27. Factors associated with death or intensive care unit admission due to pandemic 2009 influenza A (H1N1) infection

Author

Tabarsi Payam, Moradi Ahmadreza, Marjani Majid, Baghaei Parvaneh, Hashemian Seyed, Nadji Seyed, Fakharian Atefeh, Mansouri Davood, Masjedi Mohammadreza, and Velayati Aliakbar

Subjects
Hospital mortality, influenza a virus H1N1 subtype, intensive care units, risk factors, Diseases of the circulatory (Cardiovascular) system, RC666-701, Diseases of the respiratory system, RC705-779
Abstract

Background : In preparation for pandemic HINI or H1N1 influenza (H1N1) it is necessary to identify factors associated with mortality of patients with HINI and hospital admissions to intensive care unit (ICU) of patients diagnosed in 2009 with HINI. Objectives : To describe the clinical and epidemiological features associated with 2009 HIN1 mortality and ICU patient admissions to Masih Daneshvari Teaching Hospital, Iran. Methods : A retrospective cross-sectional study was conducted among patients with mortality and admissions to ICU with confirmed HINI. Demographic, clinical, laboratory, radiological findings, and epidemiologic data were abstracted from medical records, using a standardized datasheet. Results : From June through December 2009, 20 out of the 46 confirmed hospitalized patients with confirmed H1NI were admitted to the ICU and 7 (15%) died. Among various variables, opium inhalation (P = 0.01), having productive cough, hemoptysis, chest pain, confusion, and loss of consciousness were significantly related to ICU admission (P < 0.05). Pleural effusion (P = 0.006), elevated liver enzymes, as well as CPK and LDH level were significantly relevant to ICU admission (P < 0.05). Delayed antiviral treatment was more common among patients who died and the elderly. Discussion : Patients who were admitted to ICU with confirmed H1N1 included the following risk factors: delayed initiation of antiviral therapy, history of opium inhalation and symptoms including; productive cough, hemoptysis, chest pain, confusion, and loss of consciousness. The mortality rate in the study population was high but compares favorably with other recent published studies.

Published
2011

31. Synthesis of new N-Benzoxazole and N-Benzothiazole derivatives of 3-(4-Substituted- phenyl)aminoisoxazol-5(2H)-ones and comparison of their base induced rearrangement

Author

Khalafy Jabbar, Marjani Ahmad Poursattar, and Ebrahimlo Ali Reza Molla

Subjects
isoxazolones, 2-chlorobenzoxazole, 2-chlorobenzothiazole, indoles, imidazobenzothiazoles, triethylamine, base induced rearrangements, Chemistry, QD1-999
Abstract

3-Arylaminoisoxazol-5(2H)-ones, substituted on nitrogen with benzoxazole and benzothiazole groups react with triethylamine in ethanol under reflux to afford the corresponding indole and imidazobenzothiazole derivatives, respectively.

Published
2006

32. Event-based RGB-D sensing with structured light

Author

Bajestani, Seyed Ehsan Marjani and Beltrame, Giovanni

Subjects
Computer Science - Robotics
Abstract

Event-based cameras (ECs) are bio-inspired sensors that asynchronously report brightness changes for each pixel. Due to their high dynamic range, pixel bandwidth, temporal resolution, low power consumption, and computational simplicity, they are beneficial for vision-based projects in challenging lighting conditions and they can detect fast movements with their microsecond response time. The first generation of ECs are monochrome, but color data is very useful and sometimes essential for certain vision-based applications. The latest technology enables manufacturers to build color ECs, trading off the size of the sensor and substantially reducing the resolution compared to monochrome models, despite having the same bandwidth. In addition, ECs only detect changes in light and do not show static or slowly moving objects. We introduce a method to detect full RGB events using a monochrome EC aided by a structured light projector. The projector emits rapidly changing RGB patterns of light beams on the scene, the reflection of which is captured by the EC. We combine the benefits of ECs and projection-based techniques and allow depth and color detection of static or moving objects with a commercial TI LightCrafter 4500 projector and a monocular monochrome EC, paving the way for frameless RGB-D sensing applications.

Published
2022

33. Optimistic PAC Reinforcement Learning: the Instance-Dependent View

Author

Tirinzoni, Andrea, Al-Marjani, Aymen, and Kaufmann, Emilie

Subjects
Computer Science - Machine Learning
Abstract

Optimistic algorithms have been extensively studied for regret minimization in episodic tabular MDPs, both from a minimax and an instance-dependent view. However, for the PAC RL problem, where the goal is to identify a near-optimal policy with high probability, little is known about their instance-dependent sample complexity. A negative result of Wagenmaker et al. (2021) suggests that optimistic sampling rules cannot be used to attain the (still elusive) optimal instance-dependent sample complexity. On the positive side, we provide the first instance-dependent bound for an optimistic algorithm for PAC RL, BPI-UCRL, for which only minimax guarantees were available (Kaufmann et al., 2021). While our bound features some minimal visitation probabilities, it also features a refined notion of sub-optimality gap compared to the value gaps that appear in prior work. Moreover, in MDPs with deterministic transitions, we show that BPI-UCRL is actually near-optimal. On the technical side, our analysis is very simple thanks to a new "target trick" of independent interest. We complement these findings with a novel hardness result explaining why the instance-dependent complexity of PAC RL cannot be easily related to that of regret minimization, unlike in the minimax regime., Comment: arXiv admin note: text overlap with arXiv:2203.09251

Published
2022

39. Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

Author

Tirinzoni, Andrea, Al-Marjani, Aymen, and Kaufmann, Emilie

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

In probably approximately correct (PAC) reinforcement learning (RL), an agent is required to identify an $\epsilon$-optimal policy with probability $1-\delta$. While minimax optimal algorithms exist for this problem, its instance-dependent complexity remains elusive in episodic Markov decision processes (MDPs). In this paper, we propose the first nearly matching (up to a horizon squared factor and logarithmic terms) upper and lower bounds on the sample complexity of PAC RL in deterministic episodic MDPs with finite state and action spaces. In particular, our bounds feature a new notion of sub-optimality gap for state-action pairs that we call the deterministic return gap. While our instance-dependent lower bound is written as a linear program, our algorithms are very simple and do not require solving such an optimization problem during learning. Their design and analyses employ novel ideas, including graph-theoretical concepts (minimum flows) and a new maximum-coverage exploration strategy.

Published
2022

40. On the complexity of All $\varepsilon$-Best Arms Identification

Author

Marjani, Aymen Al, Kocák, Tomáš, and Garivier, Aurélien

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

We consider the question introduced by \cite{Mason2020} of identifying all the $\varepsilon$-optimal arms in a finite stochastic multi-armed bandit with Gaussian rewards. We give two lower bounds on the sample complexity of any algorithm solving the problem with a confidence at least $1-\delta$. The first, unimprovable in the asymptotic regime, motivates the design of a Track-and-Stop strategy whose average sample complexity is asymptotically optimal when the risk $\delta$ goes to zero. Notably, we provide an efficient numerical method to solve the convex max-min program that appears in the lower bound. Our method is based on a complete characterization of the alternative bandit instances that the optimal sampling strategy needs to rule out, thus making our bound tighter than the one provided by \cite{Mason2020}. The second lower bound deals with the regime of high and moderate values of the risk $\delta$, and characterizes the behavior of any algorithm in the initial phase. It emphasizes the linear dependency of the sample complexity in the number of arms. Finally, we report on numerical simulations demonstrating our algorithm's advantage over state-of-the-art methods, even for moderate risks.

Published
2022

41. The incidence of bacteriuria among the school girls in Bander-Turkman

Author

Farajollahi M (MD), Marjani AJ (PhD), Ahangari T (PhD), Vakili MA (MSc), and Saghali NM (MD)

Subjects
Bacteriuria, School girls, Pyuria, Medicine, Medicine (General), R5-920
Abstract

Urinary tract infection is one of the most common bacteria infections. The incidence of urinary tract infections in school age is more common in girls than in boys. Children have to be screened for asymptomatic bacteriuria before they reach to the state of renal damage. In our district no such study has been made to determine the prevalence of bacteriuria. Urine samples were collected from 642 school girls aged between 6-11 years, and were investigated by doing urine analysis and urine culture. 15 girls had significant bacteriuria, (>10^5 bacteria/ml). 11 children had pyuria (WBC>5), and 6 samples had both significant bacteriuria and pyuria. At the same time there were 5 cases with sterile pyuria. 6 girls had nitrite in their urine samples. All of the urine samples with positive nitrite test had significant bacteriuria. The study shows that there is a positive correlation between pyuria of nitrite and significant bacteriuria. Escherichia-coli is the most common microorganism in schoolgirls with significant bacteriuria. The incidence of screening bacteriuria was 2.3% which most of them were asymptomatic.

Published
1999

50. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection

Author

Abel, Laurent, Aiuti, Alessandro, Al-Muhsen, Saleh, Al-Mulla, Fahd, Amara, Ali, Anderson, Mark S., Andreakos, Evangelos, Arias, Andrés A., Arkin, Lisa M., Feldman, Hagit Baris, Bastard, Paul, Belot, Alexandre, Biggs, Catherine M., Bogunovic, Dusan, Bolze, Alexandre, Bondarenko, Anastasiia, Borghesi, Alessandro, Bousfiha, Ahmed A., Brodin, Petter, Bryceson, Yenan, Butte, Manish J., Casanova, Jean-Laurent, Casari, Giorgio, Christodoulou, John, Cobat, Aurélie, Colobran, Roger, Condino-Neto, Antonio, Constantinescu, Stefan N., Cooper, Megan A., Dalgard, Clifton L., Desai, Murkesh, Drolet, Beth A., Duval, Xavier, El Baghdadi, Jamila, Eloy, Philippine, Espinosa-Padilla, Sara, Fellay, Jacques, Flores, Carlos, Franco, José Luis, Froidure, Antoine, Gorochov, Guy, Gregersen, Peter K., Grimbacher, Bodo, Haerynck, Filomeen, Hagin, David, Halwani, Rabih, Hammarström, Lennart, Heath, James R., Hsieh, Elena W.Y., Husebye, Eystein, Imai, Kohsuke, Itan, Yuval, Jouanguy, Emmanuelle, Kaja, Elżbieta, Karamitros, Timokratis, Kisand, Kai, Ku, Cheng-Lung, Lau, Yu-Lung, Ling, Yun, Lucas, Carrie L., Maniatis, Tom, Mansouri, Davood, Maródi, László, Mentré, France, Meyts, Isabelle, Milner, Joshua D., Mironska, Kristina, Mogensen, Trine H., Morio, Tomohiro, Ng, Lisa F.P., Notarangelo, Luigi D., Novelli, Antonio, Novelli, Giuseppe, O'Farrelly, Cliona, Okada, Satoshi, Okamoto, Keisuke, Ozcelik, Tayfun, Pan-Hammarström, Qiang, Pape, Jean W., Perez de Diego, Rebeca, Perez-Tur, Jordi, Perlin, David S., Pesole, Graziano, Planas, Anna M., Prando, Carolina, Pujol, Aurora, Puel, Anne, Quintana-Murci, Lluis, Ramaswamy, Sathishkumar, Renia, Laurent, Resnick, Igor, Rodríguez-Gallego, Carlos, Sancho-Shimizu, Vanessa, Sediva, Anna, Seppänen, Mikko R.J., Shahrooei, Mohammad, Shcherbina, Anna, Slaby, Ondrej, Snow, Andrew L., Soler-Palacín, Pere, Soumelis, Vassili, Spaan, András N., Tancevski, Ivan, Tangye, Stuart G., Tayoun, Ahmad Abou, Temel, Şehime Gülsün, Thorball, Christian, Tiberghien, Pierre, Trouillet-Assant, Sophie, Turvey, Stuart E., Uddin, K. M. Furkan, Uddin, Mohammed J., van de Beek, Diederik, Vinh, Donald C., von Bernuth, Horst, Wauters, Joost, Zatz, Mayana, Zawadzki, Pawel, Zhang, Qian, Zhang, Shen-Ying, Bureau, Serge, Vacher, Yannick, Gysembergh-Houal, Anne, Demerville, Lauren, Benleulmi-Chaachoua, Abla, Abad, Sebastien, Abassi, Radhiya, Abdellaoui, Abdelrafie, Abdelmalek, Abdelkrim, Abdoul, Hendy, Abergel, Helene, Abeud, Fariza, Abgrall, Sophie, Abisror, Noemie, Adechian, Marylise, Aderdour, Nordine, Admane, Hakeem Farid, Adnet, Frederic, Afritt, Sara, Agostini, Helene, Aguilar, Claire, Agut, Sophie, Aiello, Tommaso Francesco, Kaci, Marc Ait, Oufella, Hafid Ait, Ajeenthiravasan, Gokula, Alauzy, Virginie, Alby-Laurent, Fanny, Allard, Lucie, Alyanakian, Marie-Alexandra, Borrero, Blanca Amador, Amam, Sabrina, Amrouche, Lucile, Andronikof, Marc, Anglicheau, Dany, Anguel, Nadia, Annane, Djillali, Aounzou, Mohammed, Aparicio, Caroline, Aratus, Gladys, Arlet, Jean-Benoit, Arzoine, Jeremy, Aslangul, Elisabeth, Assefi, Mona, Aubry, Adeline, Audiffred, Laetitia, Audureau, Etienne, Auger, Christelle Nathalie, Auregan, Jean-Charles, Awotar, Celine, Milla, Sonia Ayllon, Azan, Delphine, Azemar, Laurene, Azzouguen, Billal, Elrufaai, Marwa Bachir, Badsi, Aïda, Bakouboula, Prissile, Balcerowiak, Coline, Balde, Fanta, Baldivia, Elodie, Bangamingo, Eliane-Flore, Baptiste, Amandine, Baran-Marszak, Fanny, Barau, Caroline, Barget, Nathalie, Baronnet, Flore, Barthelemy, Romain, Baudel, Jean-Luc, Baudry, Camille, Baudry, Elodie, Beaugerie, Laurent, Belamri, Adel, Belaube, Nicolas, Belilita, Rhida, Bellassen, Pierre, Belmokhtar, Rawan, Beltran, Isabel, Benainous, Ruben, Benallaoua, Mourad, Benamouzig, Robert, Benbara, Amélie, Benhida, Jaouad, Benkhelouf, Anis, Benlagha, Jihene, Benmostafa, Chahinez, Benothmane, Skander, Bentifraouine, Miassa, Berard, Laurence, Bernier, Quentin, Berti, Enora, Bertier, Astrid, Berton, Laure, Bessis, Simon, Beurton, Alexandra, Bianco, Celine, Bianquis, Clara, Bidar, Frank, Blanche, Philippe, Blayau, Clarisse, Bleibtreu, Alexandre, Blin, Emmanuelle, Bloch-Queyrat, Coralie, Boissier, Marie-Christophe, Bollens, Diane, Bolzoni, Marion, Bompard, Rudy pierre, Bonnet, Nicolas, Bonnouvrier, Justine, Botha, Shirmonecrystal, Boucenna, Wissam, Bouchama, Fatiha, Bouchaud, Olivier, Bouchghoul, Hanane, Boudjebla, Taoueslylia, Boudjema, Noel, Bouffard, Catherine, Bougle, Adrien, Bouguerra, Meriem, Bouras, Leila, Bourcier, Agnes, Durand, Anne Bourgarit, Bourrier, Anne, Bouscarat, Fabrice, Bouvry, Diane, Bouziri, Nesrine, Bouzrara, Ons, Bribier, Sarah, Brugier, Delphine, Brunel, Melanie, Bui, Eida, Buisson, Anne, Bukreyeva, Iryna, Bureau, Côme, Cadranel, Jacques, Cailhol, Johann, Calin, Ruxandra, Vega, Clara Campos, Canavaggio, Pauline, Cancella, Marta, Cantin, Delphine, Cao, Albert, Carbillon, Lionel, Carlier, Nicolas, Cassard, Clementine, Castor, Guylaine, Cauchy, Marion, Cha, Olivier, Chaigne, Benjamin, Challal, Salima, Champion, Karine, Chariot, Patrick, Chas, Julie, Chauveau, Simon, Chauvin, Anthony, Chauvin, Clement, Chavarot, Nathalie, Chebbout, Kamélia, Cherai, Mustapha, Cherubini, Ilaria, Chevalier, Amelie, Chiarabini, Thibault, Chinet, Thierry, Chocron, Richard, Choinier, Pascaline, Chommeloux, Juliette, Choquet, Christophe, Choupeaux, Laure, Chousterman, Benjamin, Ciocan, Dragosmarius, Clarke, Ada, Clavere, Gaëlle, Clavier, Florian, Clement, Karine, Clerc, Sebastien, Cohen, Yves, Cohen, Fleur, Cohen, Adrien, Coilly, Audrey, Colboc, Hester, Colin, Pauline, Collet, Magalie, Comarmond, Chloé, Combacon, Emeline, Combes, Alain, Comparon, Celine, Constantin, Jean-Michel, Cordel, Hugues, Cordier, Anne-Gael, Costantini, Adrien, Chalumeau, Nathalie Costedoat, Couffignal, Camille, Coupeau, Doriane, Creange, Alain, Lamarre, Yannie Cuvillier, Da Silveira, Charlène, Guibal El Kayani, Sandrine Dautheville, De Castro, Nathalie, De Rycke, Yann, Del Pozo, Lucie, Delannoy, Quentin, Delay, Mathieu, Deleris, Robin, Delforge, Juliette, Delphine, Laëtitia, Demare, Noemie, Demeret, Sophie, Demoule, Alexandre, Deniau, Aurore, Depret, François, Derolez, Sophie, Derradji, Ouda, Derridj, Nawal, Descamps, Vincent, Deschamps, Lydia, Desconclois, Celine, Desnos, Cyrielle, Desongins, Karine, Dhote, Robin, Diallo, Benjamin, Didier, Morgane, Diemer, Myriam, Diez, Stephane, Djadi-Prat, Juliette, Djamouri Monnory, Fatima-Zohra, Djebara, Siham, Djebra, Naoual, Djietcheu, Minette, Djillali, Hadjer, Djouadi, Nouara, Donneger, Severine, Santos, Catarina Dos, Dournon, Nathalie, Dres, Martin, Droctove, Laura, Drogrey, Marie, Dropy, Margot, Drouet, Elodie, Dubosq, Valérie, Dubreucq, Evelyne, Dubus, Estelle, Duchemann, Boris, Duchenoy, Thibault, Dudoignon, Emmanuel, Dufau, Romain, Dumas, Florence, Duran, Clara, Duron, Emmanuelle, Durrbach, Antoine, Duvivier, Claudine, Ebstein, Nathan, El Khalifa, Jihane, Elabbadi, Alexandre, Elie, Caroline, Ernotte, Gabriel, Esling, Anne, Etienne, Martin, Eyer, Xavier, Fartoukh, Muriel Sarah, Fayali, Takoua, Fermaut, Marion, Fiorentino, Arianna, Fliss, Souha, Fournier, Marie-Céline, Fournier, Benjamin, Francois, Hélène, Freynet, Olivia, Frigout, Yvann, Fromont, Isaure, Fuentes, Axelle, Furet, Thomas, Galand, Joris, Garnier, Marc, Gaubert, Agnes, Gaudry, Stéphane, Gaugain, Samuel, Gauthier, Damien, Gautier, Maxime, Georgin-Lavialle, Sophie, Geromin, Daniela, Ghalayini, Mohamed, Ghaleh, Bijan, Ghezal, Myriam, Gibelin, Aude, Gimeno, Linda, Girard, Benoit, Leprieur, Bénédicte Giroux, Gomes, Doryan, Gomes-Pires, Elisabete, Gouge, Anne, Gouja, Amel, Goulet, Helene, Goupil, Sylvain, De Bouille, Jeanne Goupil, Gras, Julien, Greffe, Segolene, Grimaldi, Lamiae, Guedeney, Paul, Guidet, Bertrand, Guillo, Matthias, Gulczynski, Mariechristelle, Hadjam, Tassadit, Haguenauer, Didier, Hammal, Soumeya, Hammoudi, Nadjib, Hanon, Olivier, Harrois, Anarole, Hausfater, Pierre, Hautem, Coraline, Hekimian, Guillaume, Heming, Nicholas, Hermine, Olivier, Ho, Sylvie, Houllier, Marie, Huot, Benjamin, Huscenot, Tessa, Saied, Wafa Ibn, Ikherbane, Ghilas, Imarazene, Meriem, Ingiliz, Patrick, Iratni, Lina, Jaureguiberry, Stephane, Jean-Marc, Jean-Francois, Jeyarajasingham, Deleena, Jouany, Pauline, Jouis, Veronique, Jourdaine, Clement, Kafif, Ouifiya, Kallala, Rim, Katsahian, Sandrine, Kelesyan, Lilit, Keo, Vixra, Ketz, Flora, Khamis, Warda, Khelili, Enfel, Khellaf, Mehdi, Kotokpo Youkou, Christy Gaëlla, Kounis, Ilias, Kpalma, Gaelle, Krause, Jessica, Labbe, Vincent, Lacombe, Karine, Lacorte, Jean-Marc, Lafont, Anne Gaelle, Lafont, Emmanuel, Lagha, Lynda, Lamhaut, Lionel, Lancelot, Aymeric, Landman, Cecilia, Lanternier, Fanny, Larcheveque, Cecile, Combe, Caroline Lascoux, Lassel, Ludovic, Laverdant, Benjamin, Lavergne, Christophe, Lavillegrand, Jean-Rémi, Lazureanu, Pompilia, Le Guennec, Loïc, Leberre, Lamia, Leblanc, Claire, Leboyer, Marion, Lecomte, Francois, Lecorre, Marine, Leenhardt, Romain, Lefebvre, Marylou, Lefebvre, Bénédicte, Legendre, Paul, Leger, Anne, Legros, Laurence, Legrosse, Justyna, Lehuunghia, Sébastien, Lemarec, Julien, Leporrier-Ext, Jeremie, Lesein, Manon, Lesur, Hubert, Levy, Vincent, Levy, Albert, Lopes, Edwige, Lopes, Amanda, Lopez, Vanessa, Lopinto, Julien, Lortholary, Olivier, Louadah, Badr, Loze, Bénédicte, Lucas, Marie-Laure, Lucasamichi, Axelle, Luong, Liem Binh, Magazimama-Ext, Arouna, Maingret, David, Mameri, Lakhdar, Manivet, Philippe, Mansouri, Cylia, Marcault, Estelle, Marey, Jonathan, Marin, Nathalie, Marois, Clémence, Martin, Olivier, Martineau, Lou, Martinez-Lopez, Cannelle, Martyniuck, Pierre, De Farcy, Pauline Mary, Marzouk, Nessrine, Masmoudi, Rafik, Mebazaa, Alexandre, Mechai, Frédéric, Mecozzi, Fabio, Mediouni, Chamseddine, Megarbane, Bruno, Meghadecha, Mohamed, Mejean, Élodie, Mekinian, Arsene, Abdelhadi, Nour Mekki, Mekni, Rania, Meliti, Thinhinan Sabrina, Lima, Breno Melo, Meng, Paris, Merbah, Soraya, Messani, Fadhila, Messaoudi, Yasmine, Mewasing, Baboo-Irwinsingh, Meziane, Lydia, Michelot-Burger, Carole, Mignot, Françoise, Minka, Fadi Hillary, Miyara, Makoto, Moine, Pierre, Molina, Jean-Michel, Montegnies-Boulet, Anaïs, Monti, Alexandra, Montlahuc, Claire, Montout, Anne-Lise, Moores, Alexandre, Morbieu, Caroline, Mortelette, Helene, Mouly, Stéphane, Muzaffar, Rosita, Nacerddine, Cherifa Iness, Nadal, Marine, Nadif, Hajer, Nassarmadji, Kladoum, Natella, Pierre, Ndingamondze, Sandrine, Neraal, Stefan, Nguyen, Caroline, N'Guyen, Bao, Larmurier, Isabelle Nion, Nlomenyengue, Luc, Noel, Nicolas, Nunes, Hilario, Omar, Edris, Ouazene, Zineb, Ouedraogo, Elise, Ouelaa, Wassila, Oukhedouma, Anissa, Amara, Yasmina Ould, Oya, Herve, Oziel, Johanna, Padilla, Thomas, Paillaud, Elena, Paiva, Solenne, Parfait, Beatrice, Parize, Perrine, Parizot, Christophe, Parrot, Antoine, Pavot, Arthur, Peaudecerf, Laetitia, Pene, Frédéric, Pepin, Marion, Pernet, Julie, Pernin, Claire, Petit, Mylène, Peyrony, Olivier, Pietri, Marie-Pierre, Pietri, Olivia, De Chambrun, Marc Pineton, Pinson, Michelle, Pintado, Claire, Piquard, Valentine, Pires, Christine, Planquette, Benjamin, Poirier, Sandrine, Pomel, Anne-Laure, Pons, Stéphanie, Ponscarme, Diane, Pourcelot, Annegaelle, Pourcher, Valérie, Pouvaret, Anne, Prever, Florian, Previlon, Miresta, Prevost, Margot, Provoost, Marie-Julie, Quemeneur, Cyril, Rafat, Cédric, Rami, Agathe, Ranque, Brigitte, Raphael, Maurice, Raphalen, Jean Herle, Rastoin, Anna, Raux, Mathieu, Rebai, Amani, Reby, Michael, Regent, Alexis, Regrag, Asma, Resche-Rigon, Matthieu, Ressaire, Quentin, Richard, Christian, Richard, Mariecaroline, Robert, Maxence, Rohaut, Benjamin, Rolland-Debord, Camille, Ropers, Jacques, Roque-Afonso, Anne-Marie, Rosso, Charlotte, Rousseaux, Mélanie, Rousseaux, Nabila, Roux, Swasti, Roux, Lorène, Rouzaud, Claire, Rozes, Antoine, Rubenstein, Emma, Sabate, Jean-Marc, Sabet, Sheila, Sacleux, Sophie-Caroline, Kermanach, Nathalie Saidenberg, Saliba, Faouzi, Salmon, Dominique, Savale, Laurent, Savary, Guillaume, Sberro, Rebecca, Scemla, Anne, Schlemmer, Frederic, Schwartz, Mathieu, Sedfi, Saïd, Sefir-Kribel, Samia, Seksik, Philippe, Sellier, Pierre, Selves, Agathe, Sembach, Nicole, Semerano, Luca, Senat, Marie-Victoire, Sene, Damien, Serris, Alexandra, Sese, Lucile, Sghiouar, Naima, Sigaux, Johanna, Siguier, Martin, Silvain, Johanne, Simon, Noémie, Simon, Tabassome, Skandri, Lina Innes, Slimani, Miassa, Snauwaert, Aurélie, Sokol, Harry, Soliman, Heithem, Soltani, Nisrine, Soyer, Benjamin, Steg, Gabriel, Suarez, Lydia, Szwebel, Tali-Anne, Taffame, Kossi, Tandjaoui-Lambiotte, Yacine, Tantet, Claire, Tateo, Mariagrazia, Theodose, Igor, Thiebaud, Pierre clement, Thomas, Caroline, Tiercelet, Kelly, Tisserand, Julie, Tomczak, Carole, Torelino, Krystel, Touam-Ext, Fatima, Toumi, Lilia, Toury, Gustave, Toy-Miou, Mireille, Dinh Thanh Lien, Olivia Tran, Trandinh, Alexy, Treluyer, Jean-Marc, Trinque, Baptiste, Truchot, Jennifer, Tubach, Florence, Tubiana, Sarah, Tunesi, Simone, Turpin, Matthieu, Turpin, Agathe, Urbina, Tomas, Narvaez, Rafael Usubillaga, Uzunhan, Yurdagul, Vaittinadaayar, Prabakar, Valent, Arnaud, Valentian, Maelle, Valin, Nadia, Vallet, Hélène, Vaz, Marina, Vazquezibarra, Miguel-Alejandro, Vedie, Benoit, Velly, Laetitia, Verstuyft, Celine, Viallette, Cedric, Vicaut, Eric, Vignes, Dorothee, Vimpere, Damien, Virlouvet, Myriam, Voiriot, Guillaume, Voisot, Lena, Weiss, Emmanuel, Weiss, Nicolas, Winchenne, Anaïs, Yordanov, Youri, Zafrani, Lara, Zaidan, Mohamad, Zaidi, Wissem, Zak, Cathia, Zarhrate-Ghoul, Aida, Zatout, Ouassila, Zeino, Suzanne, Zeitouni, Michel, Zemirli, Naïma, Zerah, Lorene, Zia, Ounsa, Ziol, Marianne, Zolario, Oceane, Zuber, Julien, Andrejak, Claire, Angoulvant, François, Bachelet, Delphine, Bartoli, Marie, Basmaci, Romain, Behillil, Sylvie, Beluze, Marine, Benkerrou, Dehbia, Bhavsar, Krishna, Bouadma, Lila, Bouchez, Sabelline, Bouscambert, Maude, Cervantes-Gonzalez, Minerva, Chair, Anissa, Chirouze, Catherine, Coelho, Alexandra, Couffin-Cadiergues, Sandrine, d’Ortenzio, Eric, Debray, Marie-Pierre, Deconinck, Laurene, Deplanque, Dominique, Descamps, Diane, Desvallée, Mathilde, Diallo, Alpha, Diouf, Alphonsine, Dorival, Céline, Dubos, François, Elharrar, Brigitte, Enouf, Vincent, Esperou, Hélène, Esposito-Farese, Marina, Etienne, Manuel, Devouge, Eglantine Ferrand, Gault, Nathalie, Gaymard, Alexandre, Ghosn, Jade, Gigante, Tristan, Gilg, Morgane, Guedj, Jérémie, Hoctin, Alexandre, Hoffmann, Isabelle, Houas, Ikram, Hulot, Jean-Sébastien, Jaafoura, Salma, Kaguelidou, Florentia, Kali, Sabrina, Khalil, Antoine, Khan, Coralie, Laouénan, Cédric, Laribi, Samira, Le, Minh, Le Hingrat, Quentin, Le Mestre, Soizic, Le Nagard, Hervé, Lescure, François-Xavier, Letrou, Sophie, Levy, Yves, Lina, Bruno, Lingas, Guillaume, Lucet, Jean-Christophe, Malvy, Denis, Mambert, Marina, Meziane, Amina, Mouquet, Hugo, Mullaert, Jimmy, Neant, Nadège, Nguyen, Duc, Noret, Marion, Nseir, Saad, Papadopoulos, Aurélie, Paul, Christelle, Peiffer-Smadja, Nathan, Perpoint, Thomas, Petrov-Sanchez, Ventzislava, Peytavin, Gilles, Pham, Huong, Picone, Olivier, Puéchal, Oriane, Rabaud, Christian, Rosa-Calatrava, Manuel, Rossignol, Bénédicte, Rossignol, Patrick, Roy, Carine, Schneider, Marion, Su, Richa, Tardivon, Coralie, Tellier, Marie-Capucine, Téoulé, François, Terrier, Olivier, Timsit, Jean-François, Tual, Christelle, Van Der Werf, Sylvie, Vanel, Noémie, Veislinger, Aurélie, Visseaux, Benoit, Wiedemann, Aurélie, Yazdanpanah, Yazdan, Alavoine, Loubna, Burdet, Charles, Charpentier, Charlotte, Dechanet, Aline, Ecobichon, Jean-Luc, Frezouls, Wahiba, Houhou, Nadhira, Lehacaut, Jonathan, Manchon, Pauline, Nouroudine, Mariama, Quintin, Caroline, Thy, Michael, van der Werf, Sylvie, Vignali, Valérie, Chahine, Abir, Waucquier, Nawal, Migaud, Maria-Claire, Djossou, Félix, Mergeay-Fabre, Mayka, Lucarelli, Aude, Demar, Magalie, Bruneau, Léa, Gérardin, Patrick, Maillot, Adrien, Payet, Christine, Laviolle, Bruno, Laine, Fabrice, Paris, Christophe, Desille-Dugast, Mireille, Fouchard, Julie, Pistone, Thierry, Perreau, Pauline, Gissot, Valérie, Goas, Carole L.E., Montagne, Samatha, Richard, Lucie, Bouiller, Kévin, Desmarets, Maxime, Meunier, Alexandre, Bourgeon, Marilou, Lefévre, Benjamin, Jeulin, Hélène, Legrand, Karine, Lomazzi, Sandra, Tardy, Bernard, Gagneux-Brunon, Amandine, Bertholon, Frédérique, Botelho-Nevers, Elisabeth, Kouakam, Christelle, Nicolas, Leturque, Roufai, Layidé, Amat, Karine, Espérou, Hélène, Hendou, Samia, Foti, Giuseppe, Citerio, Giuseppe, Contro, Ernesto, Pesci, Alberto, Valsecchi, Maria Grazia, Cazzaniga, Marina, Bellani, Giacomo, Abad, Jorge, Accordino, Giulia, Angelini, Micol, Aguilera-Albesa, Sergio, Aguiló-Cucurull, Aina, Özkan, Esra Akyüz, Darazam, Ilad Alavi, Roblero Albisures, Jonathan Antonio, Aldave, Juan C., Ramos, Miquel Alfonso, Khan, Taj Ali, Aliberti, Anna, Nadji, Seyed Alireza, Alkan, Gulsum, AlKhater, Suzan A., Allardet-Servent, Jerome, Allende, Luis M., Alonso-Arias, Rebeca, Alshahrani, Mohammed S., Alsina, Laia, Amoura, Zahir, Antolí, Arnau, Arrestier, Romain, Aubart, Mélodie, Auguet, Teresa, Avramenko, Iryna, Aytekin, Gökhan, Azot, Axelle, Bahram, Seiamak, Bajolle, Fanny, Baldanti, Fausto, Baldolli, Aurélie, Ballester, Maite, Barrou, Benoit, Barzaghi, Federica, Basso, Sabrina, Bayhan, Gulsum Iclal, Bezrodnik, Liliana, Bilbao, Agurtzane, Blanchard-Rohner, Geraldine, Blanco, Ignacio, Blandinières, Adeline, Blázquez-Gamero, Daniel, Bloomfield, Marketa, Bolivar-Prados, Mireia, Borie, Raphael, Botdhlo-Nevers, Elisabeth, Bousquet, Aurore, Boutolleau, David, Bouvattier, Claire, Boyarchuk, Oksana, Bravais, Juliette, Briones, M. Luisa, Brunner, Marie-Eve, Bruno, Raffaele, Bueno, Maria Rita P., Bukhari, Huda, Bustamante, Jacinta, Cáceres Agra, Juan José, Capra, Ruggero, Carapito, Raphael, Carrabba, Maria, Casasnovas, Carlos, Caseris, Marion, Cassaniti, Irene, Castelle, Martin, Castelli, Francesco, Castillo de Vera, Martín, Castro, Mateus V., Catherinot, Emilie, Celik, Jale Bengi, Ceschi, Alessandro, Chalumeau, Martin, Charbit, Bruno, Boulanger, Cécile, Clavé, Père, Clotet, Bonaventura, Codina, Anna, Comarmond, Cloé, Comoli, Patrizia, Corsico, Angelo G., Coşkuner, Taner, Cvetkovski, Aleksandar, Cyrus, Cyril, Dalmau, David, Danion, François, Darley, David Ross, Das, Vincent, Dauby, Nicolas, Dauger, Stéphane, De Munte, Paul, de Pontual, Loic, Dehban, Amin, Delplancq, Geoffroy, Desguerre, Isabelle, Di Sabatino, Antonio, Diehl, Jean-Luc, Dobbelaere, Stephanie, Domínguez-Garrido, Elena, Dubost, Clément, Ekwall, Olov, Bozdemir, Şefika Elmas, Elnagdy, Marwa H., Emiroglu, Melike, Endo, Akifumi, Erdeniz, Emine Hafize, Aytekin, Selma Erol, Etxart Lasa, Maria Pilar, Euvrard, Romain, Fabio, Giovanna, Faivre, Laurence, Falck, Antonin, Fartoukh, Muriel, Faure, Morgane, Arquero, Miguel Fernandez, Ferrer, Ricard, Ferreres, Jose, Francois, Bruno, Fumadó, Victoria, Fung, Kitty S.C., Fusco, Francesca, Gagro, Alenka, Solis, Blanca Garcia, Garçon, Pierre, Gaussem, Pascale, Gayretli, Zeynep, Gil-Herrera, Juana, Gilardin, Laurent, Gatineau, Audrey Giraud, Girona-Alarcón, Mònica, Cifuentes Godínez, Karen Alejandra, Goffard, Jean-Christophe, Gonzales, Nacho, Gonzalez-Granado, Luis I., González-Montelongo, Rafaela, Guerder, Antoine, Gülhan, Belgin, Gumucio, Victor Daniel, Hanitsch, Leif Gunnar, Gunst, Jan, Gut, Marta, Hadjadj, Jérôme, Hancerli, Selda, Hariyan, Tetyana, Hatipoglu, Nevin, Heppekcan, Deniz, Hernandez-Brito, Elisa, Ho, Po-ki, Holanda-Peña, María Soledad, Horcajada, Juan P., Hraiech, Sami, Humbert, Linda, Hung, Ivan F.N., Iglesias, Alejandro D., Íñigo-Campos, Antonio, Jamme, Matthieu, Arranz, María Jesús, Jimeno, Marie-Thérèse, Jordan, Iolanda, Kanık-Yüksek, Saliha, Kara, Yalcin, Karahan, Aydın, Karbuz, Adem, Yasar, Kadriye Kart, Kasapcopur, Ozgur, Kashimada, Kenichi, Keles, Sevgi, Demirkol, Yasemin Kendir, Kido, Yasutoshi, Kizil, Can, Kılıç, Ahmet Osman, Klocperk, Adam, Koutsoukou, Antonia, Król, Zbigniew J., Ksouri, Hatem, Kuentz, Paul, Kwan, Arthur M.C., Kwan, Yat Wah M., Kwok, Janette S.Y., Lagier, Jean-Christophe, Lam, David S.Y., Lampropoulou, Vicky, Le Bourgeois, Fleur, Leo, Yee-Sin, Lopez, Rafael Leon, Leung, Daniel, Levin, Michael, Levy, Michael, Lévy, Romain, Li, Zhi, Lilleri, Daniele, Adrian Bolanos Lima, Edson Jose, Linglart, Agnes, López-Collazo, Eduardo, Lorenzo-Salazar, José M., Louapre, Céline, Lubetzki, Catherine, Lung, Kwok-Cheung, Luyt, Charles-Edouard, Lye, David C., Magnone, Cinthia, Marchioni, Enrico, Marioli, Carola, Marjani, Majid, Marques, Laura, Pereira, Jesus Marquez, Martín-Nalda, Andrea, Pueyo, David Martínez, Martinez-Picado, Javier, Marzana, Iciar, Mata-Martínez, Carmen, Mathian, Alexis, Matos, Larissa R.B., Matthews, Gail V., Mayaux, Julien, McLaughlin-Garcia, Raquel, Meersseman, Philippe, Mège, Jean-Louis, Mekontso-Dessap, Armand, Melki, Isabelle, Meloni, Federica, Meritet, Jean-François, Merlani, Paolo, Akcan, Özge Metin, Mezidi, Mehdi, Migeotte, Isabelle, Millereux, Maude, Million, Matthieu, Mirault, Tristan, Mircher, Clotilde, Mirsaeidi, Mehdi, Mizoguchi, Yoko, Modi, Bhavi P., Mojoli, Francesco, Moncomble, Elsa, Melián, Abián Montesdeoca, Martinez, Antonio Morales, Morandeira, Francisco, Morange, Pierre-Emmanuel, Mordacq, Clémence, Morelle, Guillaume, Mouly, Stéphane J., Muñoz-Barrera, Adrián, Nafati, Cyril, Nagashima, Shintaro, Nakagama, Yu, Neven, Bénédicte, Neves, João Farela, Ng, Yuk-Yung, Hubert Nielly, Medina, Yeray Novoa, Cuadros, Esmeralda Nuñez, Karabela, Semsi Nur, Ocejo-Vinyals, J. Gonzalo, Oualha, Mehdi, Ouedrani, Amani, Özçelik, Tayfun, Ozkaya-Parlakay, Aslinur, Pagani, Michele, Papadaki, Maria, Parola, Philippe, Pascreau, Tiffany, Paul, Stéphane, Paz-Artal, Estela, Pedraza, Sigifredo, González Pellecer, Nancy Carolina, Pellegrini, Silvia, Pérez de Diego, Rebeca, Pérez-Fernández, Xosé Luis, Philippe, Aurélien, Philippot, Quentin, Picod, Adrien, Pineton de Chambrun, Marc, Piralla, Antonio, Planas-Serra, Laura, Ploin, Dominique, Poissy, Julien, Poncelet, Géraldine, Poulakou, Garyphallia, Pouletty, Marie S., Pourshahnazari, Persia, Qiu-Chen, Jia Li, Quentric, Paul, Rambaud, Thomas, Raoult, Didier, Raoult, Violette, Rebillat, Anne-Sophie, Redin, Claire, Resmini, Léa, Ricart, Pilar, Richard, Jean-Christophe, Rigo-Bonnin, Raúl, Rivet, Nadia, Rivière, Jacques G., Rocamora-Blanch, Gemma, Rodero, Mathieu P., Rodrigo, Carlos, Rodriguez, Luis Antonio, Rodriguez-Gallego, Carlos, Rodriguez-Palmero, Agustí, Romero, Carolina Soledad, Rothenbuhler, Anya, Roux, Damien, Rovina, Nikoletta, Rozenberg, Flore, Ruch, Yvon, Ruiz, Montse, Ruiz del Prado, Maria Yolanda, Ruiz-Rodriguez, Juan Carlos, Sabater-Riera, Joan, Saks, Kai, Salagianni, Maria, Sanchez, Oliver, Sánchez-Montalvá, Adrián, Sánchez-Ramón, Silvia, Schidlowski, Laire, Schluter, Agatha, Schmidt, Julien, Schmidt, Matthieu, Schuetz, Catharina, Schweitzer, Cyril E., Scolari, Francesco, Seijo, Luis, Seminario, Analia Gisela, Seng, Piseth, Senoglu, Sevtap, Seppänen, Mikko, Llovich, Alex Serra, Siguret, Virginie, Siouti, Eleni, Smadja, David M., Smith, Nikaia, Sobh, Ali, Solanich, Xavier, Solé-Violán, Jordi, Soler, Catherine, Sözeri, Betül, Stella, Giulia Maria, Stepanovskiy, Yuriy, Stoclin, Annabelle, Taccone, Fabio, Taupin, Jean-Luc, Tavernier, Simon J., Tello, Loreto Vidaur, Terrier, Benjamin, Thiery, Guillaume, Thorn, Karolina, Thumerelle, Caroline, Tipu, Imran, Tolstrup, Martin, Tomasoni, Gabriele, Toubiana, Julie, Alvarez, Josep Trenado, Triantafyllia, Vasiliki, Troya, Jesús, Tsang, Owen T.Y., Tserel, Liina, Tso, Eugene Y.K., Tucci, Alessandra, Tüter Öz, Şadiye Kübra, Ursini, Matilde Valeria, Utsumi, Takanori, Vabres, Pierre, Valencia-Ramos, Juan, Van Den Rym, Ana Maria, Vandernoot, Isabelle, Velez-Santamaria, Valentina, Zuniga Veliz, Silvia Patricia, Vidigal, Mateus C., Viel, Sébastien, Villain, Cédric, Vilaire-Meunier, Marie E., Villar-García, Judit, Vincent, Audrey, Van der Linden, Dimitri, Volokha, Alla, Vuotto, Fanny, Wauters, Els, Wu, Alan K.L., Wu, Tak-Chiu, Yahşi, Aysun, Yesilbas, Osman, Yildiz, Mehmet, Young, Barnaby E., Yükselmiş, Ufuk, Zecca, Marco, Zuccaro, Valentina, Van Praet, Jens, Lambrecht, Bart N., Van Braeckel, Eva, Bosteels, Cédric, Hoste, Levi, Hoste, Eric, Bauters, Fré, De Clercq, Jozefien, Heijmans, Catherine, Slabbynck, Hans, Naesens, Leslie, Florkin, Benoit, Young, Mary-Anne, Willis, Amanda, Lapuente-Suanzes, Paloma, de Andrés-Martín, Ana, Berkell, Matilda, Carelli, Valerio, Fiorentino, Alessia, Malhotra, Surbhi, Mattiaccio, Alessandro, Pippucci, Tommaso, Seri, Marco, Tacconelli, Evelina, van Agtmael, Michiel, Algera, Anne Geke, Appelman, Brent, van Baarle, Frank, Bax, Diane, Beudel, Martijn, Bogaard, Harm Jan, Bomers, Marije, Bonta, Peter, Bos, Lieuwe, Botta, Michela, de Brabander, Justin, de Bree, Godelieve, de Bruin, Sanne, Buis, David T.P., Bugiani, Marianna, Bulle, Esther, Chouchane, Osoul, Cloherty, Alex, Dijkstra, Mirjam, Dongelmans, Dave A., Dujardin, Romein W.G., Elbers, Paul, Fleuren, Lucas, Geerlings, Suzanne, Geijtenbeek, Theo, Girbes, Armand, Goorhuis, Bram, Grobusch, Martin P., Hafkamp, Florianne, Hagens, Laura, Hamann, Jorg, Harris, Vanessa, Hemke, Robert, Hermans, Sabine M., Heunks, Leo, Hollmann, Markus, Horn, Janneke, Hovius, Joppe W., de Jong, Menno D., Koning, Rutger, Lim, Endry H.T., van Mourik, Niels, Nellen, Jeaninne, Nossent, Esther J., Paulus, Frederique, Peters, Edgar, Pina-Fuentes, Dan A.I., van der Poll, Tom, Preckel, Bennedikt, Prins, Jan M., Raasveld, Jorinde, Reijnders, Tom, de Rotte, Maurits C.F. J., Schinkel, Michiel, Schultz, Marcus J., Schrauwen, Femke A.P., Schuurmans, Alex, Schuurmans, Jaap, Sigaloff, Kim, Slim, Marleen A., Smeele, Patrick, Smit, Marry, Stijnis, Cornelis S., Stilma, Willemke, Teunissen, Charlotte, Thoral, Patrick, Tsonas, Anissa M., Tuinman, Pieter R., van der Valk, Marc, Veelo, Denise P., Volleman, Carolien, de Vries, Heder, Vught, Lonneke A., van Vugt, Michèle, Wouters, Dorien, Zwinderman, A.H., Brouwer, Matthijs C., Wiersinga, W. Joost, Vlaar, Alexander P.J., Tompkins, Miranda F., Alba, Camille, Hupalo, Daniel N., Rosenberger, John, Sukumar, Gauthaman, Wilkerson, Matthew D., Zhang, Xijun, Lack, Justin, Oler, Andrew J., Dobbs, Kerry, Delmonte, Ottavia M., Danielson, Jeffrey J., Biondi, Andrea, Bettini, Laura Rachele, D’Angiò, Mariella, Beretta, Ilaria, Imberti, Luisa, Sottini, Alessandra, Quaresima, Virginia, Quiros-Roldan, Eugenia, Rossi, Camillo, Castagnoli, Riccardo, Montagna, Daniela, Licari, Amelia, Marseglia, Gian Luigi, Marchal, Astrid, Cirulli, Elizabeth T., Neveux, Iva, Bellos, Evangelos, Thwaites, Ryan S., Schiabor Barrett, Kelly M., Zhang, Yu, Nemes-Bokun, Ivana, Kalinova, Mariya, Catchpole, Andrew, Lack, Justin B., Chiu, Christopher, and Grzymski, Joseph J.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results