Giresun University

In response to the 2013 Update of the European Strategy for Particle Physics, the Future Circular Collider (FCC) study was launched, as an international collaboration hosted by CERN. This study covers a highest-luminosity high-energy lepton collider (FCC-ee) and an energy-frontier hadron collider (FCC-hh), which could, successively, be installed in the same 100 km tunnel. The scientific capabilities of the integrated FCC programme would serve the worldwide community throughout the 21st century. The FCC study also investigates an LHC energy upgrade, using FCC-hh technology. This document constitutes the second volume of the FCC Conceptual Design Report, devoted to the electron-positron collider FCC-ee. After summarizing the physics discovery opportunities, it presents the accelerator design, performance reach, a staged operation scenario, the underlying technologies, civil engineering, technical infrastructure, and an implementation plan. FCC-ee can be built with today's technology. Most of the FCC-ee infrastructure could be reused for FCC-hh. Combining concepts from past and present lepton colliders and adding a few novel elements, the FCC-ee design promises outstandingly high luminosity. This will make the FCC-ee a unique precision instrument to study the heaviest known particles (Z, W and H bosons and the top quark), offering great direct and indirect sensitivity to new physics.

Abstract: We review the physics opportunities of the Future Circular Collider, covering its e+e-, pp, ep and heavy ion programmes. We describe the measurement capabilities of each FCC component, addressing the study of electroweak, Higgs and strong interactions, the top quark and flavour, as well as phenomena beyond the Standard Model. We highlight the synergy and complementarity of the different colliders, which will contribute to a uniquely coherent and ambitious research programme, providing an unmatchable combination of precision and sensitivity to new physics.

Abstract: In response to the 2013 Update of the European Strategy for Particle Physics (EPPSU), the Future Circular Collider (FCC) study was launched as a world-wide international collaboration hosted by CERN. The FCC study covered an energy-frontier hadron collider (FCC-hh), a highest-luminosity high-energy lepton collider (FCC-ee), the corresponding 100 km tunnel infrastructure, as well as the physics opportunities of these two colliders, and a high-energy LHC, based on FCC-hh technology. This document constitutes the third volume of the FCC Conceptual Design Report, devoted to the hadron collider FCC-hh. It summarizes the FCC-hh physics discovery opportunities, presents the FCC-hh accelerator design, performance reach, and staged operation plan, discusses the underlying technologies, the civil engineering and technical infrastructure, and also sketches a possible implementation. Combining ingredients from the Large Hadron Collider (LHC), the high-luminosity LHC upgrade and adding novel technologies and approaches, the FCC-hh design aims at significantly extending the energy frontier to 100 TeV. Its unprecedented centre of-mass collision energy will make the FCC-hh a unique instrument to explore physics beyond the Standard Model, offering great direct sensitivity to new physics and discoveries.

Light-by-light scattering (γγ → γγ) is a quantum-mechanical process that is forbidden in the classical theory of electrodynamics. This reaction is accessible at the Large Hadron Collider thanks to the large electromagnetic field strengths generated by ultra-relativistic colliding lead ions. Using 480 μb−1 of lead–lead collision data recorded at a centre-of-mass energy per nucleon pair of 5.02 TeV by the ATLAS detector, here we report evidence for light-by-light scattering. A total of 13 candidate events were observed with an expected background of 2.6 ± 0.7 events. After background subtraction and analysis corrections, the fiducial cross-section of the process Pb + Pb (γγ) → Pb(∗) + Pb(∗)γγ, for photon transverse energy ET > 3 GeV, photon absolute pseudorapidity |η| < 2.4, diphoton invariant mass greater than 6 GeV, diphoton transverse momentum lower than 2 GeV and diphoton acoplanarity below 0.01, is measured to be 70 ± 24 (stat.) ± 17 (syst.) nb, which is in agreement with the standard model predictions. Quantum electrodynamics predicts a rare process in which light is scattered by light. The ATLAS Collaboration reports signs of this elusive effect in the collisions of ultra-relativistic lead ions.

The concentration of globally alarming potential toxic elements (PTEs) like Aluminum (Al), chrome (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), lead (Pb), and uranium (U) were measured in surface sediment of seven major rivers residing in Giresun (one of the most important Hazelnut production areas of Turkey). The mean concentrations of PTEs in all river sediments showed the descending order of Al > Fe > Mn > Zn > Cu > Pb > Cr > Ni > Co > As > U > Cd. The level of studied metals in most of the rivers exceeded the threshold effect level (TEL), indicating a potential risk to the environment. Certain indices, including the sediment quality guidelines (SQGs), contamination factor (CF), pollution load index (PLI), enrichment factor (EF), potential ecological risk index (Eri), geoaccumulation index (Igeo), toxic risk index (TRI), modified hazard quotient (mHQ) and ecological contamination index (ECI) were used to assess the ecological risk posed by PTEs in sediment. Contamination factor (CF) and geoaccumulation index (Igeo) demonstrated that most of the sediment samples were moderately to considerably contaminated by Cu, As, Cd and Pb. In view of the potential ecological risk index, sediments from Pazarsuyu Stream (PS), Batlama Stream (BS) and Gelevera Stream (GLS) showed considerable potential ecological risk. The sources of PTEs and the relations between them were determined by using principal component analysis/factor analysis (PCA/FA), Hierarchical clustering analysis (HCA) and Pearson correlation index (PCI). Three factors explaining 83.94% of the total variance was found by PCA/FA. 43.34% of the total variance explained by the first factor (F1) was correlated with Ni, Cr, Pb and Co elements. 28.35% of the total variance explained by the second factor (F2) was correlated with U, Al, the third factor (F3) explains 12.24% of the total variance and correlated with Zn, Cd, Cu and As elements. These factors revealed that the quality of the sediment was mainly influenced by anthropogenic effects. The extent of pollution by heavy metals in the studied streams implies that the condition is much frightening to the biota and inhabitants in the vicinity of these rivers as well.

Background:The purpose of this study is to determine the effect of an activity set developed according to the inquiry-based learning approach in the unit “Particulate Structure of Matter” on students’ critical thinking skills in science and technology courses. The study was conducted with 90 sixth grade students attending four sixth grade classes of a secondary school.Material and methods:Within the framework of the study, in order to evaluate the effects of inquiry-based learning approach on the students’ critical thinking skills in science and technology courses, the guided activity set was developed by the researchers in line with the inquiry-based learning approach. In this study, pre-test and posttest control group experimental designs were used.Results:The findings of the study revealed that science and technology learning supported with the guided activities developed in line with the inquiry-based learning approach have significant effects on students’ critical thinking skills in science and technology courses.Conclusions:The critical thinking level of the experimental group students taught with the inquiry-based learning approach was found to be higher than that of the control group students taught with the traditional lecturing method.the critical thinking level of the experimental group students showed a positive increase in all the dimensions.

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses proton-proton collision data corresponding to an integrated luminosity of 36.1 fb -1 at a centre-of-mass energy of 13 TeV collected in 2015 and 2016 with the ATLAS detector at the Large Hadron Collider. Events are required to have at least one jet with a transverse momentum above 250 GeV and no leptons (e or ). Several signal regions are considered with increasing requirements on the missing transverse momentum above 250 GeV. Good agreement is observed between the number of events in data and Standard Model predictions. The results are translated into exclusion limits in models with pair-produced weakly interacting dark-matter candidates, large extra spatial dimensions, and supersymmetric particles in several compressed scenarios.

A search is conducted for new resonant and non-resonant high-mass phenomena in dielectron and dimuon final states. The search uses 36.1 fb$^{-1}$ of proton-proton collision data, collected at $\sqrt{s}$ = 13 TeV by the ATLAS experiment at the LHC in 2015 and 2016. No significant deviation from the Standard Model prediction is observed. Upper limits at 95% credibility level are set on the cross-section times branching ratio for resonances decaying into dileptons, which are converted to lower limits on the resonance mass, up to 4.1 for the E$_{6}$-motivated Z'$_{\chi}$. Lower limits on the $qq \ell\ell$ contact interaction scale are set between 24 TeV and 40 TeV, depending on the model.

The spatio-temporal variations of surface water quality and the level of metal contamination in the sediment of Pazarsuyu Stream were determined by using multivariate statistical techniques and pollution indicators, respectively. The water and sediment samples were collected monthly from four different stations along the Pazarsuyu Stream between June 2014 and May 2015 and analyzed using standard methods. Results were assessed according to national and international water quality criteria and the water quality parameters in some stations were found to be over these criteria levels. The present study showed that statistical techniques such as Pearson Correlation Index (PCI), Principal Component Analysis (PCA), Cluster Analysis (CA), One Way ANOVA need to be used to get better information for the studies on the water quality of surface waters. PCA identified six factors accounting for 82.88% of the total variation in the data. The abundance of sediment heavy metals was in the order of Fe > Mn > Zn > Pb > Cu > Cr > Co > Cd. The heavy metal contamination in the sediments was evaluated by applying the enrichment factor (EF), contamination factor (CF), geoaccumulation index (Igeo) and potential ecological risk index (PERI). Pb was heavily contaminated and has a significant enrichment of contamination according to calculated EF values. Therefore, the stream water can be used for irrigation with precaution but extensive treatment required before using for domestic purposes to prevent adverse public health effects.

Betimsel içerik analizi yöntemi, belirli bir konuda ya da alanda birbirinden bağımsız olarak yapılan nitel ve nicel çalışmaların derinlemesine incelenip düzenlenmesi anlamına gelir. Böylece o konu ya da alandaki genel eğilimler belirlenmektedir. Bu yöntemde elde edilen sonuçların, hedeflenen konulara yönelik olarak gelecekte planlanan çalışmalara yön göstermesi beklenmektedir. Bu çalışmanın temel amacı, eğitim bilimleri alanında sıkça kullanılmakta olan betimsel içerik analizi yönteminin, diğer sosyal bilimler alanlarında da kullanılabilmesi için, analizin nasıl yapılacağına dair soruların giderilmesini sağlamaktır. Çalışmanın, sosyal bilimler alanında betimsel içerik analizini kullanmak isteyen akademisyenlere yön göstermesi, temel bir kaynak olması hedeflenmektedir. Betimsel içerik analizinde, özellikle incelenen çalışmaların amaçlarına, gerekçelerine, sonuçlarına ve önerilerine ait analizlerde nitel analiz yaklaşımlarına uygun olarak, kod havuzu oluşturup, bu kodlara uygun temalandırma/kategorilendirme yönteminin kullanılması, betimsel içerik analizi çalışmalarının nitelik açısından da zenginleşmesini sağlayacaktır. Ayrıca, yapılacak olan betimsel içerik analizi çalışmalarında, incelenen çalışmalar, standartlaşmış analiz aşamaları dışında, benzer konulardaki diğer betimsel içerik analizi çalışmalarından ayrılması adına, farklı yönlerden de analize tabi tutulması gerekmektedir.

Abstract This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 $$\hbox {fb}^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mtext>fb</mml:mtext><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math> of pp collision data at $$\sqrt{s}=13$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msqrt><mml:mi>s</mml:mi></mml:msqrt><mml:mo>=</mml:mo><mml:mn>13</mml:mn></mml:mrow></mml:math> TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of $$Z\rightarrow \mu \mu $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>Z</mml:mi><mml:mo>→</mml:mo><mml:mi>μ</mml:mi><mml:mi>μ</mml:mi></mml:mrow></mml:math> and $$J/\psi \rightarrow \mu \mu $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>J</mml:mi><mml:mo>/</mml:mo><mml:mi>ψ</mml:mi><mml:mo>→</mml:mo><mml:mi>μ</mml:mi><mml:mi>μ</mml:mi></mml:mrow></mml:math> decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of $$|\eta |&lt;2.7$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>|</mml:mo><mml:mi>η</mml:mi><mml:mo>|</mml:mo><mml:mo>&lt;</mml:mo><mml:mn>2.7</mml:mn></mml:mrow></mml:math> .

Abstract Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb $$^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow/><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math> of proton–proton collision data with a centre-of-mass energy of $$\sqrt{s}=13$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msqrt><mml:mi>s</mml:mi></mml:msqrt><mml:mo>=</mml:mo><mml:mn>13</mml:mn></mml:mrow></mml:math> $${\text {Te}}{\text {V}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>TeV</mml:mtext></mml:math> collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti- $$k_t$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>k</mml:mi><mml:mi>t</mml:mi></mml:msub></mml:math> jet algorithm with radius parameter $$R=0.4$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>R</mml:mi><mml:mo>=</mml:mo><mml:mn>0.4</mml:mn></mml:mrow></mml:math> is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets ( $$|\eta |&lt;1.2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>|</mml:mo><mml:mi>η</mml:mi><mml:mo>|</mml:mo><mml:mo>&lt;</mml:mo><mml:mn>1.2</mml:mn></mml:mrow></mml:math> ) vary from 1% for a wide range of high- $$p_{{\text {T}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>p</mml:mi><mml:mtext>T</mml:mtext></mml:msub></mml:math> jets ( $$250&lt;p_{{\text {T}}} &lt;2000~{\text {Ge}}{\text {V}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>250</mml:mn><mml:mo>&lt;</mml:mo><mml:msub><mml:mi>p</mml:mi><mml:mtext>T</mml:mtext></mml:msub><mml:mo>&lt;</mml:mo><mml:mn>2000</mml:mn><mml:mspace/><mml:mtext>GeV</mml:mtext></mml:mrow></mml:math> ), to 5% at very low $$p_{{\text {T}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>p</mml:mi><mml:mtext>T</mml:mtext></mml:msub></mml:math> ( $$20~{\text {Ge}}{\text {V}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>20</mml:mn><mml:mspace/><mml:mtext>GeV</mml:mtext></mml:mrow></mml:math> ) and 3.5% at very high $$p_{{\text {T}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>p</mml:mi><mml:mtext>T</mml:mtext></mml:msub></mml:math> ( $$&gt;2.5~{\text {Te}}{\text {V}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn>2.5</mml:mn><mml:mspace/><mml:mtext>TeV</mml:mtext></mml:mrow></mml:math> ). The relative jet energy resolution is measured and ranges from ( $$24 \pm 1.5$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>24</mml:mn><mml:mo>±</mml:mo><mml:mn>1.5</mml:mn></mml:mrow></mml:math> )% at 20 $${\text {Ge}}{\text {V}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>GeV</mml:mtext></mml:math> to ( $$6 \pm 0.5$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>6</mml:mn><mml:mo>±</mml:mo><mml:mn>0.5</mml:mn></mml:mrow></mml:math> )% at 300 $${\text {Ge}}{\text {V}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>GeV</mml:mtext></mml:math> .

In the present work, we determined the gamma-ray attenuation characteristics of eight different polymers(Polyamide (Nylon 6) (PA-6), polyacrylonitrile (PAN), polyvinylidenechloride (PVDC), polyaniline (PANI), polyethyleneterephthalate (PET), polyphenylenesulfide (PPS), polypyrrole (PPy) and polytetrafluoroethylene (PTFE)) using transmission geometry utilizing the high resolution HPGe detector and different radioactive sources in the energy range 81–1333 keV. The experimental linear attenuation coefficient values are compared with theoretical data (WinXCOM data). The linear attenuation coefficient of all polymers reduced quickly with the increase in energy, at the beginning, while decrease more slowly in the region from 267 keV to 835 keV. The effective atomic number of PVDC and PTFE are comparatively higher than the Zeff of the remaining polymers, while PA-6 possesses the lowest effective atomic number. The half value layer results showed that PTFE (C2F4, highest density) is more effective to attenuate the gamma photons. Also, the theoretical results of macroscopic effective removal cross section for fast neutrons (∑R) were computed to investigate the neutron attenuation characteristics. It is found that the ∑R values of the eight investigated polymers are close and ranged from 0.07058 cm−1 for PVDC to 0.11510 cm−1 for PA-6. Keywords: Polymer, Neutron, Gamma photon, Attenuation, Shielding

A search for heavy neutral Higgs bosons and $Z^{\prime}$ bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb$^{-1}$ from proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to $\tau^+\tau^-$ with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for $Z^{\prime}$ bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude $\tan\beta &gt; 1.0$ for $m_A$ = 0.25 TeV and $\tan\beta &gt; 42$ for $m_A$ = 1.5 TeV at the 95% confidence level. For the Sequential Standard Model, $Z^{\prime}_\mathrm{SSM}$ with $m_{Z^{\prime}} &lt; 2.42$ TeV is excluded at 95% confidence level, while $Z^{\prime}_\mathrm{NU}$ with $m_{Z^{\prime}} &lt; 2.25$ TeV is excluded for the non-universal $G(221)$ model that exhibits enhanced couplings to third-generation fermions.

A comprehensive study of photon interaction features has been made for some alloys containing Pd and Ag content to evaluate its possible use as alternative gamma radiations shielding material. The mass attenuation coefficient (μ/ρ) of the present alloys was measured at various photon energies between 81 keV–1333 keV utilizing HPGe detector. The measured μ/ρ values were compared to those of theoretical and computational (MCNPX code) results. The results exhibited that the μ/ρ values of the studied alloys are in the same line with results of WinXCOM software and MCNPX code results at all energies. Moreover, Pd75/Ag25 alloy sample has the maximum radiation protection efficiency (about 53% at 81 keV) and lowest half value layer, which shows that Pd75/Ag25 has superior gamma radiation shielding performance among the other compared alloys.

Abstract The Large Hadron–Electron Collider (LHeC) is designed to move the field of deep inelastic scattering (DIS) to the energy and intensity frontier of particle physics. Exploiting energy-recovery technology, it collides a novel, intense electron beam with a proton or ion beam from the High-Luminosity Large Hadron Collider (HL-LHC). The accelerator and interaction region are designed for concurrent electron–proton and proton–proton operations. This report represents an update to the LHeC’s conceptual design report (CDR), published in 2012. It comprises new results on the parton structure of the proton and heavier nuclei, QCD dynamics, and electroweak and top-quark physics. It is shown how the LHeC will open a new chapter of nuclear particle physics by extending the accessible kinematic range of lepton–nucleus scattering by several orders of magnitude. Due to its enhanced luminosity and large energy and the cleanliness of the final hadronic states, the LHeC has a strong Higgs physics programme and its own discovery potential for new physics. Building on the 2012 CDR, this report contains a detailed updated design for the energy-recovery electron linac (ERL), including a new lattice, magnet and superconducting radio-frequency technology, and further components. Challenges of energy recovery are described, and the lower-energy, high-current, three-turn ERL facility, PERLE at Orsay, is presented, which uses the LHeC characteristics serving as a development facility for the design and operation of the LHeC. An updated detector design is presented corresponding to the acceptance, resolution, and calibration goals that arise from the Higgs and parton-density-function physics programmes. This paper also presents novel results for the Future Circular Collider in electron–hadron (FCC-eh) mode, which utilises the same ERL technology to further extend the reach of DIS to even higher centre-of-mass energies.

In this paper, we prove the correct q-Hermite-Hadamard inequality, some new q-Hermite-Hadamard inequalities, and generalized q-Hermite-Hadamard inequality. By using the left hand part of the correct q-Hermite-Hadamard inequality, we have a new equality. Finally using the new equality, we give some q-midpoint type integral inequalities through q-differentiable convex and q-differentiable quasi-convex functions. Many results given in this paper provide extensions of others given in previous works. (C) 2016 The Authors. Production and hosting by Elsevier B.V.

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

A bstract A study of the decays B s 0 → μ + μ − and B 0 → μ + μ − has been performed using 26.3 fb −1 of 13 TeV LHC proton-proton collision data collected with the ATLAS detector in 2015 and 2016. Since the detector resolution in μ + μ − invariant mass is comparable to the B s 0 - B 0 mass difference, a single fit determines the signal yields for both decay modes. This results in a measurement of the branching fraction $$ \mathrm{\mathcal{B}}\left({B}_s^0\to {\mu}^{+}{\mu}^{-}\right)=\left({3.2}_{-1.0}^{+1.1}\right)\times {10}^{-9} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℬ</mml:mi> <mml:mfenced> <mml:mrow> <mml:msubsup> <mml:mi>B</mml:mi> <mml:mi>s</mml:mi> <mml:mn>0</mml:mn> </mml:msubsup> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mrow> </mml:mfenced> <mml:mo>=</mml:mo> <mml:mfenced> <mml:msubsup> <mml:mn>3.2</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1.0</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>1.1</mml:mn> </mml:mrow> </mml:msubsup> </mml:mfenced> <mml:mo>×</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>9</mml:mn> </mml:mrow> </mml:msup> </mml:math> and an upper limit $$ \mathrm{\mathcal{B}}\left({B}^0\to {\mu}^{+}{\mu}^{-}\right)&lt;4.3\times {10}^{-10} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℬ</mml:mi> <mml:mfenced> <mml:mrow> <mml:msup> <mml:mi>B</mml:mi> <mml:mn>0</mml:mn> </mml:msup> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mrow> </mml:mfenced> <mml:mo>&lt;</mml:mo> <mml:mn>4.3</mml:mn> <mml:mo>×</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>10</mml:mn> </mml:mrow> </mml:msup> </mml:math> at 95% confidence level. The result is combined with the Run 1 ATLAS result, yielding $$ \mathrm{\mathcal{B}}\left({B}_s^0\to {\mu}^{+}{\mu}^{-}\right)=\left({2.8}_{-0.7}^{+0.8}\right)\times {10}^{-9} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℬ</mml:mi> <mml:mfenced> <mml:mrow> <mml:msubsup> <mml:mi>B</mml:mi> <mml:mi>s</mml:mi> <mml:mn>0</mml:mn> </mml:msubsup> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mrow> </mml:mfenced> <mml:mo>=</mml:mo> <mml:mfenced> <mml:msubsup> <mml:mn>2.8</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>0.7</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>0.8</mml:mn> </mml:mrow> </mml:msubsup> </mml:mfenced> <mml:mo>×</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>9</mml:mn> </mml:mrow> </mml:msup> </mml:math> and $$ \mathrm{\mathcal{B}}\left({B}^0\to {\mu}^{+}{\mu}^{-}\right)&lt;2.1\times {10}^{-10} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℬ</mml:mi> <mml:mfenced> <mml:mrow> <mml:msup> <mml:mi>B</mml:mi> <mml:mn>0</mml:mn> </mml:msup> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mrow> </mml:mfenced> <mml:mo>&lt;</mml:mo> <mml:mn>2.1</mml:mn> <mml:mo>×</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>10</mml:mn> </mml:mrow> </mml:msup> </mml:math> at 95% confidence level. The combined result is consistent with the Standard Model prediction within 2.4 standard deviations in the $$ \mathrm{\mathcal{B}}\left({B}^0\to {\mu}^{+}{\mu}^{-}\right)-\mathrm{\mathcal{B}}\left({B}_s^0\to {\mu}^{+}{\mu}^{-}\right) $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℬ</mml:mi> <mml:mfenced> <mml:mrow> <mml:msup> <mml:mi>B</mml:mi> <mml:mn>0</mml:mn> </mml:msup> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mrow> </mml:mfenced> <mml:mo>−</mml:mo> <mml:mi>ℬ</mml:mi> <mml:mfenced> <mml:mrow> <mml:msubsup> <mml:mi>B</mml:mi> <mml:mi>s</mml:mi> <mml:mn>0</mml:mn> </mml:msubsup> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>μ</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mrow> </mml:mfenced> </mml:math>

Hazelnut is a type of plant that grows in wet and humid climatic conditions. Adverse climatic conditions result in the formation of aflatoxin in hazelnuts during the harvesting, drying, and storing processes. Aflatoxin is considered an important food contaminant, which makes aflatoxin analysis important in the international produce trade. For this reason, validation is important for the analysis of aflatoxin in hazelnuts. The limit of detection (LOD) and limit of quantification (LOQ) are two important parameters in validation. In this study, the LOD and LOQ values have been determined using the Association of Official Agricultural Chemists (AOAC) Method 991.31, which is one of the most viable high-performance liquid chromatography analysis methods in the analysis of aflatoxin in hazelnuts. Several approaches can be used to calculate LOD and LOQ values. In this study, to calculate the LOD and LOQ values, the visual evaluation (empirical) method, the signal-to-noise method, and calibration curve approaches were applied. The most appropriate approaches were compared. Our conclusion is that the visual evaluation method provided much more realistic LOD and LOQ values.