bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening of Lactic Acid Bacteria from Oysters for Antibacterial Activity Against Selected Pathogens
Authors: Yuvizar Cut , Dewiyanti I
Published: February 2024

Lactic acid bacteria (LAB) are among the important groups of bacteria and considered as probiotics development. LAB is mostly isolated from the gastrointestinal tract (GIT) from organism such as oyster. Oyster belongs in to class Bivalvia which live in estuaries area. The purpose of research was to isolate and screened for antibacterial activity against selected pathogens. The LAB was isolated by pour plate method using MRSA (De Man, Rogosa, Sharpe Agar) as selection media for LAB. Then, LAB was screened by an agar diffusion assay for antibacterial activity. The result showed that four isolates (TR-01; TR-02; TR-03 and TR-04) have inhibitory activity against pathogens including E. coli, Salmonella enterica, Staphylococcus aureus, Bacillus cereus. Therefore, it is needed further assay to selected 4 isolates as potential probiotics.
Bioprospecting and Detection of NRPS Gene of Sea Cucumber Stichopus monotuberculatus Symbiont-bacteria Against Microbial Fish Pathogens Aeromonas hydrophila and Vibrio harveyi
Authors: Budiharjo Anto , Girsang Cindy Maria Putri , Lunggani Arina Tri , Mardiah Fanny Amalina , Wulandari Dyah , Sulardiono Bambang , Chilmawati Diana
Published: February 2024

Vibriosis and septicemia are infections caused by bacteria that rise many problems on aquaculture industry. Bioprospection of marine organisms such as sea cucumber are very promising as they are widely known to contain symbiotic microorganisms having antibacterial potential. This study aimed to analyze the antibacterial potential of sea cucumber Stichopus monotuberculatus symbiont bacteria against Aeromonas hydrophila and Vibrio harveyi, as well as to detect its NRPS gene. The research methods used were the isolation of symbiotic bacteria in the gut of the sea cucumber S. monotuberculatus, screening for its antibacterial activity, identification of 16S rRNA, and detection of NRPS gene clusters. A total of 16 bacteria were isolated, where 12 isolates had the potential to inhibit the pathogen A. hydrophila and 7 isolates had the potential to inhibit the growth of the pathogenic V. harveyi. Based on the identification of 16S rRNA, the symbiotic bacteria that was able to inhibit the growth of A. hydrophila was Bacillus subtilis, whereas bacteria that inhibited the pathogen of V. harveyi was Bacillus flexus. B. subtilis and B. flexus were detected to have NRPS gene clusters with an amplicon size of about 250 bp.
Continental depositional record of climate and tectonic evolution around the Eocene-Oligocene transition in southeast France: perpectives from the Vistrenque Basin (Camargue)
Authors: Semmani Nazim , Fournier François , Suc Jean-Pierre , Fauquette Séverine , Séranne Michel , Léonide Philippe , Marié Lionel , Borgomano Jean
Published: February 2024

Based on detailed sedimentological analyses of cores, interpretation of well logs and a set of geochemical measurements performed on lacustrine sedimentary rocks, the palaeoenvironmental evolution and the sedimentary architecture of the Paleogene continental Vistrenque Basin (SE France) have been reconstructed. The analysis of sedimentary archives revealed three main stages of basin infill evolution: (1) a deep-lake basin (Priabonian-earliest Rupelian) whose sedimentation was dominated by terrigenous gravity-driven deposits during a period of high subsidence rate and strike-slip fault activity and under a prevailing humid climate; (2) an evaporative deep lake (early Rupelian) characterized by a drastic reduction in lake volume (forced-regression), terrigenous supplies and deposition of evaporites in disconnected sub-basins; (3) an overall long-term normal regressive stage (middle Rupelian to earliest Chattian) of lake infill characterized by an increase in terrigenous supplies and a vertical upward transition from deep-lake gravity-driven deposits to marginal lake and floodplain sedimentation. The onset of lake volume reduction and forced regression during the early Rupelian is associated with (1) the reworking of marginal lake carbonates into the deep lake areas, (2) the deposition of organic-rich sediments (TOC > 10%) coupled with sulphate-reduction processes in the deepest areas of the lake, (3) an important decrease in terrigenous supplies and (4) a long-term increase in δ18O of matrix-supported carbonates. This early Rupelian forced regression of the Vistrenque lacustrine system is interpreted to result from a regional decrease in precipitation in response to global cooling during the Eocene-Oligocene Transition (EOT). The final infill of the Vistrenque lake system (late Rupelian-early Chattian) and the onset of a floodplain occurred in more humid conditions during a stage of decreased activity of the Nîmes Fault, prior to or during an early stage of the Liguro-Provençal rifting.
Bioorganic Mineral Fertilizer on the Basis of Black Manage, Phosphorite Raw Materials and Biopreparts of Microorganisms
Authors: Kanoatov Khayrullo , Namazov Shafoat , Temirov Uktam , Usanboyev Najimuddin , Pirimov Tuychi
Published: February 2024

This article presents the results of studies on the production of bioorganic mineral fertilizers by treating a mixture based on black manure and phosphorite raw materials with a solution that accelerates the humification of organic matter, binds molecular nitrogen and enriches it with physiologically active substances, as well as microorganisms that play an important role in soil fertility. Based on the results of the study, it was found that treatment of a mixture based on black manure and phosphorite raw materials with a solution containing beneficial microorganisms accelerates the humification of organic matter, increases the conversion of phosphorus and reduces the release of nitrogen and organic matter into the gas phase.
Entropy Method of Multi-Attribute Decision-Making Problems
Authors: Shanmugapriya P. , Selvakumari K. , Kavitha S.
Published: February 2024

Food choice aims to identify the solution totheexiguity of the food. It is possible to do this through diversification. Finding the best selection of food alternatives is the goal of food diversification.. Multi-attribute decision-making (MADM) methods attempt to choose the best alternative from a group of possibilities based on several parameters. This paper provides the description of the entropy process use in the analysis and application of multi attribute decision-making (MADM) for choosing foods.
Analysis of the efficiency of a 300kw solar photovoltaic system in the climate of uzbekistan
Authors: Raxmatov Ilhom Ismatovich , Samiev Kamoliddin A’zamovich , Juraev Khusniddin Oltinboyevich , Mirzaev Mirfayz Salimovich
Published: February 2024

In this research work, the efficiency of a 300 kW grid-connected solar photovoltaic system was analyzed over a year under the climatic conditions of different regions of Uzbekistan. It has been established that the maximum power value that a 300 kW solar photovoltaic installation can produce per year is 0.477 MW, and the minimum is 0.452 MW. Taking into account regional climatic conditions, it was determined that the shortest payback period for photovoltaic systems from generated electricity is 8.6 years, and the shortest is 9 years. It is estimated that between 90.4 and 95.5 tons of CO2 gases could be prevented in the region by 300 kW solar photovoltaic systems.
Fake Currency Detection
Authors: Shamini S. Sweetline , Nandhini G. , Varshini R.S. , Dharini T.
Published: February 2024

Due to the great technological developments in the field of color printing in the past few years, it is becoming increasingly recognized that counterfeiting is a serious problem. It used to be possible and very simple for anyone to quickly prepare and print counterfeit currency notes using a computer and a laser printer at homes or places of employment. In the past, only printing houses had these facilities. The most crucial issue is now how to accurately distinguish fake currency from real currency using automatic machines. Almost all nations struggle greatly with the issue of counterfeit currency notes. But since counterfeiting has become such a pressing issue in India, it is thought to be the most serious issue there. Therefore, it is necessary to create a module that will aid in the quick and efficient recognition and detection of paper currency notes. An approach for the identification and verification of Indian currency is described in this proposed system. The authenticity of the currency will be verified using image processing methods, regardless of whether it is genuine.
Study of the Production and Efficiency of Variable and Loading Equipment in the Mining of Minerals
Authors: Nasirov Utkir , Umirzokov Azamat , Nosirov Nurzod , Fatkhiddinov Asliddinjon , Eshonkulov Uchkun , Kushnazorov Ibrakhim
Published: February 2024

This article reviewed and analyzed the study of performance and efficiency of exchange-loading equipment. Despite a number of previous studies in this area, many issues require further in-depth study. In particular, the influence of operational factors on the nature of the total resistances overcome by the drive for the use of excavation and loading equipment has not been sufficiently studied, the dependence of the change in the power component of the diesel load mode during the technological cycle and its influence on the energy intensity of the process have not been determined.
Vehicle number recognition by using existing general surveillance cameras
Authors: Sharmila V. Ceronmani , Jerin Paul J. , Kumar Jeevan , Pramoth Kumar R.B.
Published: February 2024

India has a lot of cars because it is the densest-populated country in the world. Therefore, it's important to use a traffic management system to detect vehicles accurately. It detects a vehicle plate image from a camera and extracts the number. It's an embedded system that recognizes license plates in real-time. A real-time embedded system called Vehicle Plate Number Recognition (VNPR) recognizes license plate numbers automatically in this work using VGG16 algorithm. When a vehicle enters the entrance by the gate of the institution or highly restricted areas, the system records and captures video and recognizes the number plate. It will automatically recognize the license plate and search the data of the owner's vehicle and their challan details.
Survey on Embedding Economical Autonomous Navigation System for Mobile Robots and UAV
Authors: S.U. Suganthi , C.S. Hemanth Kumar , S. Aditya Gurjale , A. Mithunesh Rajan
Published: February 2024

Navigation has traditionally served the purpose of determining one's position, locating destinations, and charting a course towards them. It furnishes accurate details about the whereabouts of specific places or objects. Despite numerous advancements and enhancements in navigation technology, there have been ongoing discussions about its potential for autonomy. This suggests a scenario where navigation operates independently, without human intervention. Devices equipped with this capability comprehend their destination and chart the most efficient route to reach it. A crucial concept in this context is Visual Odometry (VO), which calculates the relative position between successive image frames. Likewise, the positioning of mobile robots relies on similar principles. However, a significant challenge arises over time as VO is susceptible to accumulating errors, known as drift. The Inertial Measurement Unit (IMU), which consists of accelerometers, gyroscopes, and magnetometers, is added to counteract this. These elements provide data that is more accurate and helps reduce noise. The integration of IMU with VO results in the creation of Visual Inertial Odometry (VIO). Furthermore, combining VIO with Global Positioning System (GPS) data through an Extended Kalman Filter (EKF) enhances localization accuracy both locally and globally. Additionally, stereo disparity estimation is employed to generate a depth perception map for obstacle detection, converted into a 2D grid map of occupancy after. While a waypoint follower directs the robot or devices toward its intended objective, local route planning algorithms create interim waypoints to prevent obstructions.
Comparative Study on the effects of Urban Heat Islands using Remote Sensing and Geographical Information System for the Salem district, India
Authors: Sivakumar V.L. , Raju Anand , A.V. Sundaram
Published: February 2024

The ecology and all of its components are suffering greatly as a result of the unchecked speed of development. At this rate, environmental degradation will have an impact on humanity and associated fields. In order to prevent the consequences of expansion from pushing the environment into a situation from which it is incapable of recovering, there should be ongoing, earnest efforts made towards sustainable development. The three pillars of ecodevelopment are the environment, humanity, and economy. A stable growth rate is necessary to attain a just balance between these pillars. Since agriculture employs the majority of the population, it also has an impact on the balance of the ecosystem. Because every unplanned step towards progress puts us back in the environmental front, we must thus be mindful of the boundaries of environmental challenges in order to achieve equitable economic growth. The hope for sustainable development lies in decreased deforestation, greater food security, conservative agricultural practices, the use of biopesticides, and prudent use of natural resources. To be effective, environmental policy probably needs to employ a variety of tools, each addressing a distinct aspect of the issue and attempting to minimise redundancies and pointless regulations. Appropriately pricing environmental inputs facilitates sustainable resource provision and use management. Long-term corporate investment in new technology and innovation is encouraged by a consistent and clear environmental policy, which also increases investment certainty. Environmental and economic success are interdependent. Economic activity and advancement depend on the natural environment because it provides the resources needed to produce goods and services and because it processes and absorbs waste and pollution, which are unwanted byproducts. This paper focuses on how environmental assets assist control risks associated with social and economic activities, flood risks, local climate regulation (temperature and air quality), and the availability of clean water and other resources.
Theoretical analysis on the transmission dynamics of HBV Disease with the effect of intervention of vaccination and treatment
Authors: Sivasamy Pavithra , Kumar Vanthana Ramesh
Published: February 2024

In this paper, we formulate a SVEIQR model for the Hepatitis B virus (HBV) using ordinary differential equations. The model is then tested for well posedness by finding the positivity, boundedness and existence of the solution. Then, an approximate analytical solution to the model is obtained by executing the Homotopy Perturbation Method (HPM) which is a coupling of homotopy and perturbation techniques. This solutionhelps us to study the model dynamically. The validity of the method is checked by using numerical simulation. These results show that HPM is highly reliable in solving such non-linear models. The results are applicable to the entire solution domain.
Deep-Learning based Melanoma Detection using Cloud Approach
Authors: Sudhakaran Pradeep , Koushik V.S.K. , Charan N. , M. Preetha
Published: February 2024

The aim of computer vision techniquesand deep learning in the era of digitalization is to derive valuable insights from them and generate novel understanding. This makes it possible to employ imaging to quickly diagnose and treat a variety of diseases. In the field of dermatology, deep neural networks are utilized to differentiate between images of melanoma and non-melanoma skin lesions. In this paper, we have emphasised two important aspects of melanoma detection research. The accuracy of classifiers is the first thing to take into account, even with very little modifications to the dataset's characteristics there will be a lot of difference in accuracy. We investigated transfer learning issues in this case. We propose that continual training-test iterations are necessary to create reliable prediction models based on the results of the initial study.The second argument is the need for a system with a flexible design that can accommodate changes to training datasets.Our proposal for creating and implementing a melanoma detection service that utilizes clinical and thermoscopic images involves the development and implementing a hybrid architecture that fuses fog, edge and cloud computing. In addition, this design should aim to decrease the duration of the ongoing retraining process, which is necessary to accommodate the large volume of data that requires evaluation. This notion has been reinforced by experiments using a single computer and a variety of distribution techniques, which show how a dispersed strategy ensures output attainment in a noticeably more sufficient amount of time.
A Investigation of Kidney Function in the Hypo-Thyroidism Individuals at the Tertiary Healthcare Centre
Authors: Kakraniya Pawan , Ambad Ranjit , Jha Rakesh Kumar , Jadhav Deepali , Dhawade Manish Ramdas , Wankhade Yashwant
Published: February 2024

The most prevalent endocrine illnesses worldwide are thyroid disorders. India is also no different. There are thought to be 42 million thyroid ailment sufferers in India, based on projections from numerous research on the condition. to investigate Kidney function in hypo-thyroid individuals at a tertiary medical facility. This cross-sectional investigation was conducted over a one-year period in 100 hypo-thyroid individuals at a Medical College and Hospital in Central India after receiving approval from the institutional ethical committee. The investigation includes similar euthyroid participants in addition to the diagnosed hypo-thyroidism individuals who provided consent. Both groups underwent the kidney function test, which included indicators such as creatinine clearance, creatinine urea, and uric acid, among others. Unpaired t-test statistics were computed using SPSS version 22 software. 49 -16%, 50-59 12%, and >60 10%. Women individuals made up 66% of the total population, with male individuals making up 24%. The Creatinine Clearance was considerably poorer in the hypo-thyroidism individuals compared to controls, measuring 102.08±9.98, 80.74±10.56 (P 0.001), Creatinine -0.82±0.102, 0.726±0.0456 (P 0.001), Urea -28.18±3.18, 21.82±3.01 (P 0.001), and Uric acid - 5.082±0.7614, 3.124±0.158 (P 0.001). According to the results of our investigation, the majority of hypo-thyroid individuals were women and in the age range of 30-39. They also demonstrated significantly abnormal kidney function tests, such as lower creatinine clearance and higher creatinine, urea, and uric acid levels in comparison to euthyroid individuals.
Artificial Intelligence in the Detection of Breast Cancer
Authors: Bisen Ashwini , Makade Jagadish , Lamture Yashwant , Jha Rakesh Kumar
Published: February 2024

Breast carcinoma, the prevalently existing malignancy and the primary cause of disease mortality among females worldwide. Breast cancer is determined by a multitude of elements, including ageing, genetic history, specific alterations and genetic variations, a record of fecundity and menopause, a sedentary lifestyle, alcohol use, adiposity, nutrition, race and pectoral radiation treatment. Since the previous two decades, various researches on breast cancer has enabled significant advancements in our understanding of the condition, leading to more effective and non-toxic treatments. Increased scanning and public awareness have enabled early detection at stages amenable to full surgical intervention and curative therapy. Breast cancer screening mammography tries to detect the illness at an early stage when therapy would be more effective. Because mammography are such high-resolution images, researchers have thought of putting AI technology to use. They've trained the AI to examine minute patches and create a map of the most dangerous areas. The research shows that AI can recognize differences that are unnoticeable and recognizes breast tumors exactly like a skilled radiologist, providing the most accurate data. As a result, the incidence of this disease has dramatically increased,especially among juveniles. In this article, there are discussions about several causes, medical signs, non-drug treatments (such as radiation and surgery), and drugs (such as chemotherapy, and gene therapy) and thus, its detection by AI.In clinical medicine, AI can aid in establishing diagnoses and predicting the progression of disease in the future. AI jobs go beyond the computer-aided detection that is already used. AI's automated capabilities have the potential to advance medical professionals' diagnostic abilities in fields including exact tumor volume delineation, cancer phenotype extraction, translation of tumoral phenotypic characteristics to clinical genotype ramifications, and risk prediction. In breast cancer, the value of integrating image-specific data with underlying biological,pathologic, and clinical traits is growing.
Intrusion Detection System Using Machine Learning by RNN Method
Authors: Azarudeen K. , Ghulam Dasthageer , Rakesh G. , Sathaiah Balaji , Vishal Raj
Published: February 2024

As computer networks continue to grow, network intrusions become more frequent, advanced, and volatile, making it challenging to detect them. This has led to an increase in illegal intrusions that current security tools cannot handle. NIDS is currently available and most reliable ways to monitor network traffic, identify unauthorized usage, and detect malicious attacks. NIDS can provide better visibility of network activity and detect any evidence of attacks and malicious traffic. Recent research has shown that machine learning-based NIDS, particularly with deep learning, is more effective in detecting variants of network attacks compared to traditional rule-based solutions. This proposed model that introduces novel deep learning methodologies for network intrusion detection. The model consists of three approaches: LSTM-RNN, various classifying methodology, and a hybrid Sparse autoencoder with DNN. The LSTM-RNN evaluated NSL-KDD dataset and classified as multi-attack classification. The model outperformed with Adamax optimizer in terms of accuracy, detection rate, and low false alarm rate.
Enhance the AI Virtual System Accuracy with Novel Hand Gesture Recognition Algorithm Comparing to Convolutional Neural Network
Authors: Sadiq Shaik , Saraswathi S.
Published: February 2024

The objective of this study is to enhance the precision of AI virtual systems by implementing Novel Hand Gesture Recognition techniques in comparison to Convolutional Neural Network. Materials and Methods: To recognise hand motions, a Convolutional Neural Network with distinct training and testing stages is utilized. The average Gpower for the test is between 0.05 and 0.85, or around 85%. Sample size is determined as 27,455 for each group using G Power 3.1 software (G Power setting parameters: α=0.05 and power=0.85). Results and Discussion: Novel Hand gesture recognition 92.60% identifies between objects and boosts the observed accuracy with a statistically non-significant value of p=0.123 (p>0.05) in comparison to the convolutional neural network's 88.59%. Conclusion: Comparison of the Novel Hand gesture Recognition algorithm and Convolutional Neural Network in terms of performance that shows Hand gesture recognition has 91.62% with better accuracy.
Fingerprint Password Method Provides Improved Accuracy over Token-based Authentication for Efficient and Secure File Transfers
Authors: Rithvik R.K. , Mohan A.
Published: February 2024

The goal of this study is to improve the accuracy of secure file transfer by proposing and evaluating a novel fingerprint password method in comparison to the existing token-based authentication method.In this study, a dataset of 20 samples was obtained from Kaggle, with 10 samples in each group (Group 1 and Group 2) to determine the accuracy of secure file transfer. The data was analyzed using G-power at 0.8, and with alpha and beta values set at 0.05 and 0.2, respectively. A 95% confidence interval was used. Both the novel Fingerprint password method and the Two factor authentication method were applied to the same number of data samples (N = 10) for secure file transaction, and it was found that the Fingerprint password method had a higher accuracy rate. The study found that the fingerprint password method had a higher accuracy rate than the token-based authentication method when securing file transactions. Specifically, the fingerprint password method had an accuracy rate of 95.66%, while the token-based method had an accuracy rate of 93.45%. Since, hence the p=0.001 (p<0.05), the study's results found that there is a statistically significant difference between two algorithms.: This study has shown that the fingerprint biometric password method is a viable and effective alternative to token-based authentication methods for secure file transactions. It provides a more secure and user-friendly solution, without the need for additional hardware.
Attosecond science: a new era for many-body physics
Authors: Biegert Jens
Published: February 2024

The properties and the functionality of materials and devices, or chemical reactions, are determined by the microscopic interaction of their building blocks, i.e., between electrons, holes, and nuclei. Thus, understanding the many-body interaction between these fundamental building blocks holds the key to advancing fundamental science and, at the same time, directly leads to applications. Attosecond science now provides an entirely new view into the quantum many-body interaction of these microscopic building blocks.
Narbengewebe
Authors: Corts Magga
Published: February 2024

In dieser DHZ-Ausgabe beschäftigt sich die Rubrik „Funktionelle Anatomie“ mit Narbengewebe.
Prüfungsthema: Gehirn und Nervensystem
Authors: Schmid Eva C.
Published: February 2024

Liebe Heilpraktikeranwärter – mit diesen Karteikarten wollen wir Sie bei der Vorbereitung auf die mündliche Heilpraktikerüberprüfung unterstützen. Viel Erfolg beim Lernen wünscht Ihnen HP Eva C. Schmid!
Narben und Zähne im Blick
Authors: Neumann Sabine , Sirocko Sigrid
Published: February 2024

Um Therapieblockaden zu ermitteln, kann sich die Reflexzonentherapie am Fuß – hier: Hanne-Marquardt-Fussreflex® – unterschiedlicher Ansätze bedienen, wie die beiden Fallbeispiele veranschaulichen. Störfelder durch Narben sowie Wechselbeziehungen der Zahn-Kiefer-Gebiete, die sich bei einer Belastung im Organismus im Fuß widerspiegeln, können Hinweise für die Therapie geben. Die Reflexzonentherapie am Fuß setzt Reize, die für Entlastung in den Zielorganen und eine energetische Regulation sorgen, und kann so bei zahnärztlichen Behandlungen eine sinnvolle Ergänzung sein.
Grundlagen und Instrumente des klinischen
Risikomanagements
Authors: Krukenkamp Sabine , Schwarz Yulia
Published: February 2024

Risiken im OP gibt es viele – manche davon können Patienten
schwer schädigen. Um das zu verhindern, müssen Fehlerquellen
identifiziert und Maßnahmen ergriffen werden. Unterstützen
können hierbei das Critical Incident Reporting System, die
Fehlermöglichkeits- und Einflussanalyse, Checklisten, das
Beschwerdemanagement und klinische Behandlungspfade. Wir stellen Ihnen die
wichtigsten Instrumente des klinischen Risikomanagements vor.
Prognostische Faktoren bei einem schrittweisen Ansatz zur nicht-pharmakologischen Therapie von Sauerstoff und mechanischer Beatmung bis hin zur extrakorporalen Membranoxygenierung bei COVID-19
Authors: Matthes Sandhya , Holl Johannes , Randerath Johannes , Treml Marcel , Sofianos Georgios , Bockover Michael , Oesterlee Ulrike , Herkenrath Simon , Knoch Johannes , Hagmeyer Lars , Randerath Winfried
Published: February 2024

Hintergrund Unser Zentrum verfolgte bei der nicht-pharmakologischen Behandlung des Atemversagens bei COVID-19 in Übereinstimmung mit den deutschen nationalen Leitlinien einen schrittweisen Ansatz, bei dem die nicht-invasiven Maßnahmen vor der invasiven mechanischen Beatmung (IMV) oder der extrakorporalen Membranoxygenierung (ECMO) eskaliert wurden. Das Ziel dieser Studie war, diesen individualisierten Ansatz der nicht-pharmakologischen Therapie im Hinblick auf die Patientencharakteristika und klinische Merkmale zu analysieren, die bei der Vorhersage einer schwereren Erkrankung – insbesondere einer erforderlichen intensivmedizinischen Behandlung – helfen können.

Methodik Diese retrospektive, monozentrische Studie an stationären COVID-19-Patienten zwischen März 2020 und Dezember 2021 analysierte anthropometrische Daten, nicht-pharmakologische Maximaltherapie und Überlebensstatus auf Basis der in den Patientenakten dokumentierten Daten.

Ergebnisse Von 1052 COVID-19-bedingten Einweisungen wurden 835 Patienten in die Analysekohorte aufgenommen (54% männlich, Median 58 Jahre). 34% (n=284) erhielten keine Therapie, 40% (n=337) konventionelle Sauerstofftherapie (COT), 3% (n=22) High-Flow-Nasenkanüle (HFNC), 9% (n=73) kontinuierlichen Atemwegspositivdruck (CPAP), 7% (n=56) nicht-invasive Beatmung (NIV), 4% (n=34) invasive mechanische Ventilation (IMV) und 3% (n=29) extrakorporale Membranoxygenierung (ECMO) als maximale Therapie. Von 551 Patienten, die mindestens mit COT behandelt wurden, mussten 12,3% intubiert werden. Insgesamt mussten 183 Patienten auf der Intensivstation behandelt werden und 106 (13%) starben. 25 (74%) IMV-Patienten und 23 (79%) ECMO-Patienten verstarben. Verstorbene litten häufiger an arterieller Hypertonie, Demenz, Diabetes und Dyslipidämie. Die logistische Regression zeigte folgende Risikofaktoren für die Sterblichkeit: eine Sauerstoffbedarf von ≥2 L/min bei Studienbeginn (OR 6,96 [4,01–12,08]), Alter (OR 1,09 [1,05–1,14]) und männliches Geschlecht (OR 2,23 [0,79–6,31]).

Schlussfolgerung Die unmittelbare klinische Entscheidung des Arztes für eine Sauerstofftherapie spielt neben anderen anerkannten Risikofaktoren eine wichtige Rolle bei der Vorhersage des Schweregrads des Krankheitsverlaufs und damit bei der Behandlung von COVID-19.
Wissenschaftliche Aktivität in der deutschen Thoraxchirurgie gemessen an der Publikationsleistung
Authors: Ried Michael , Pfannschmidt Luisa Marie , Hofmann Hans-Stefan
Published: February 2024

Die thoraxchirurgische Versorgung erfolgt in Deutschland vornehmlich in nicht universitären Zentren mit klinischem Fokus und weniger an den Universitätsklinika. Inwieweit sich innerhalb dieser unterschiedlichen Strukturen eine wissenschaftliche Tätigkeit realisieren lässt, wird anhand der Publikationsleistungen untersucht.

Es erfolgte eine PubMed-Abfrage nach ausgewählten Autoren (thoraxchirurgische Leiter*in in Deutschland) im Zeitraum von 01/2012 bis 12/2021. Eingeschlossen wurden Universitätsklinika, DKG-zertifizierte Lungenkrebszentren (DKG: Deutsche Krebsgesellschaft) und DGT-zertifizierte Thoraxzentren (DGT: Deutsche Gesellschaft für Thoraxchirurgie).

Es wurden n = 54 nicht universitäre Zentren (DKG-Zertifikat n = 50 und/oder DGT-Zertifikat n = 22) und n = 36 Universitätsklinika (n = 9 eigenständige Klinik/Abteilung) analysiert. Insgesamt wurden n = 2414 Publikationen ermittelt, wobei am häufigsten Originalarbeiten (n = 1776; 74%) und Publikationen mit thoraxchirurgischem Schwerpunkt (n = 1501; 62%) gefunden wurden. Bei diesen Arbeiten lagen die Publikationsleistungen der nicht universitären Zentren bei n = 599 Publikationen (11/Zentrum) und damit signifikant unter denen der Universitätsklinika (n = 902; 25/Klinik; p ≤ 0,001). Signifikant höhere Publikationsleistungen bestätigten sich bei eigenständiger (n = 560; 62/Klinik) im Vergleich zu nicht eigenständiger universitärer Thoraxchirurgie (n = 342; 13/Klinik; p = 0,003). Es wurde ein 10-Jahres-Trend mit einer nahezu Verdoppelung der Publikationsleistung von n = 105 (universitär: n = 63) auf n = 203 (universitär: n = 124) Publikationen/Jahr nachgewiesen. Die kumulativen
Impact-Faktoren (IF) ergaben 2845 IF (52,7 IF/Klinik) für nicht universitäre Zentren, 6361 IF (235,6 IF/Klinik) für die nicht eigenständige und 2931 IF (325,7 IF/Klinik) für die eigenständige universitäre Thoraxchirurgie.

Die wissenschaftlichen Aktivitäten haben in nicht universitären Zentren, aber vor allem in der universitären Thoraxchirurgie, zugenommen. Diese positiven Entwicklungen sind unter den anstehenden politischen Veränderungen (Krankenhausstrukturgesetz, Mindestmengen) in akuter Gefahr. Strukturelle Veränderungen wie z. B. die eigenständige universitäre Thoraxchirurgie oder Kooperationsmodelle mit außeruniversitären Zentren können Lösungsansätze bieten.
Double-edged sword: China’s free trade agreements reinforces embodied greenhouse gas transfers in agricultural products
Authors: Hu Yanyong , Zou Zhixiao , Wu Jiaxi , Meng Zheng
Published: February 2024

China, as the world’s largest importer, heavily relies on agricultural products. However, the impact of China’s free trade agreements (FTAs) on greenhouse gas (GHG) emissions embodied in agricultural product imports has been overlooked. It’s crucial to analyze changes in embodied GHG emissions resulting from FTAs. We categorize 367 agricultural products into 15 categories and construct a dataset on the embodied GHG emissions of these products imported by China from 119 countries between 2000 and 2015. Using the Propensity Score Matching (PSM)-progressive difference-in-differences (DID) method, our findings indicate that China’s FTAs have double-edged impact on agricultural product imports. It has positively influenced imports, with a 12.22% annual growth rate, promoting economic integration. However, it has negatively affected GHG emissions, leading to a 53.00% increase in emissions from agricultural imports. These findings highlight the importance of addressing production and consumption in reducing GHG strategies with agricultural products.
Conformational dynamics of adenylate kinase in crystals
Authors: Kim Junhyung , Moon Sojin , Romo Tod D. , Yang Yifei , Bae Euiyoung , Phillips George N.
Published: February 2024

Adenylate kinase is a ubiquitous enzyme in living systems and undergoes dramatic conformational changes during its catalytic cycle. For these reasons, it is widely studied by genetic, biochemical, and biophysical methods, both experimental and theoretical. We have determined the basic crystal structures of three differently liganded states of adenylate kinase from Methanotorrus igneus, a hyperthermophilic organism whose adenylate kinase is a homotrimeric oligomer. The multiple copies of each protomer in the asymmetric unit of the crystal provide a unique opportunity to study the variation in the structure and were further analyzed using advanced crystallographic refinement methods and analysis tools to reveal conformational heterogeneity and, thus, implied dynamic behaviors in the catalytic cycle.
Advanced manufacturing provides tailor-made solutions for crystallography with x-ray free-electron lasers
Authors: Paulson Lars , Narayanasamy Sankar Raju , Shelby Megan L. , Frank Matthias , Trebbin Martin
Published: February 2024

Serial crystallography at large facilities, such as x-ray free-electron lasers and synchrotrons, evolved as a powerful method for the high-resolution structural investigation of proteins that are critical for human health, thus advancing drug discovery and novel therapies. However, a critical barrier to successful serial crystallography experiments lies in the efficient handling of the protein microcrystals and solutions at microscales. Microfluidics are the obvious approach for any high-throughput, nano-to-microliter sample handling, that also requires design flexibility and rapid prototyping to deal with the variable shapes, sizes, and density of crystals. Here, we discuss recent advances in polymer 3D printing for microfluidics-based serial crystallography research and present a demonstration of emerging, large-scale, nano-3D printing approaches leading into the future of 3D sample environment and delivery device fabrication from liquid jet gas-dynamic virtual nozzles devices to fixed-target sample environment technology.
Dark and Dronc activation inDrosophila melanogaster
Authors: Tian Lu , Li Yini , Shi Yigong
Published: February 2024

The onset of apoptosis is characterized by a cascade of caspase activation, where initiator caspases are activated by a multimeric adaptor complex known as the apoptosome. InDrosophila melanogaster, the initiator caspase Dronc undergoes autocatalytic activation in the presence of the Dark apoptosome. Despite rigorous investigations, the activation mechanism for Dronc remains elusive. Here, we report the cryo-EM structures of an auto-inhibited Dark monomer and a single-layered, multimeric Dark/Dronc complex. Our biochemical analysis suggests that the auto-inhibited Dark oligomerizes upon binding to Dronc, which is sufficient for the activation of both Dark and Dronc. In contrast, the previously observed double-ring Dark apoptosome may represent a non-functional or “off-pathway” conformation. These findings expand our understanding on the molecular mechanism of apoptosis inDrosophila.
The social transmission of empathy relies on observational reinforcement learning
Authors: Zhou Yuqing , Han Shihui , Kang Pyungwon , Tobler Philippe N. , Hein Grit
Published: February 2024

Theories of moral development propose that empathy is transmitted across individuals. However, the mechanisms through which empathy is socially transmitted remain unclear. Here, we combine computational learning models and functional MRI to investigate whether, and if so, how empathic and non-empathic responses observed in others affect the empathy of female observers. The results of three independent studies showed that watching empathic or non-empathic responses generates a learning signal that respectively increases or decreases empathy ratings of the observer. A fourth study revealed that the learning-related transmission of empathy is stronger when observing human rather than computer demonstrators. Finally, we show that the social transmission of empathy alters empathy-related responses in the anterior insula, i.e., the same region that correlated with empathy baseline ratings, as well as its functional connectivity with the temporoparietal junction. Together, our findings provide a computational and neural mechanism for the social transmission of empathy that accounts for changes in individual empathic responses in empathic and non-empathic social environments.
Ligand-induced incompatible curvatures control ultrathin nanoplatelet polymorphism and chirality
Authors: Monego Debora , Dutta Sarit , Grossman Doron , Krapez Marion , Bauer Pierre , Hubley Austin , Margueritat Jérémie , Mahler Benoit , Widmer-Cooper Asaph , Abécassis Benjamin
Published: February 2024

The ability of thin materials to shape-shift is a common occurrence that leads to dynamic pattern formation and function in natural and man-made structures. However, harnessing this concept to rationally design inorganic structures at the nanoscale has remained far from reach due to a lack of fundamental understanding of the essential physical components. Here, we show that the interaction between organic ligands and the nanocrystal surface is responsible for the full range of chiral shapes seen in colloidal nanoplatelets. The adsorption of ligands results in incompatible curvatures on the top and bottom surfaces of the NPL, causing them to deform into helicoïds, helical ribbons, or tubes depending on the lateral dimensions and crystallographic orientation of the NPL. We demonstrate that nanoplatelets belong to the broad class of geometrically frustrated assemblies and exhibit one of their hallmark features: a transition between helicoïds and helical ribbons at a critical width. The effective curvature

κ

¯

is the single aggregate parameter that encodes the details of the ligand/surface interaction, determining the nanoplatelets’ geometry for a given width and crystallographic orientation. The conceptual framework described here will aid the rational design of dynamic, chiral nanostructures with high fundamental and practical relevance.
Molecular basis for curvature formation in SepF polymerization
Authors: Liu Wenjing , Zhang Chang , Zhang Huawei , Ma Shaojie , Deng Jing , Wang Daping , Chang Ziwei , Yang Jun
Published: February 2024

The self-assembly of proteins into curved structures plays an important role in many cellular processes. One good example of this phenomenon is observed in the septum-forming protein (SepF), which forms polymerized structures with uniform curvatures. SepF is essential for regulating the thickness of the septum during bacteria cell division. In
Bacillus subtilis
, SepF polymerization involves two distinct interfaces, the β–β and α–α interfaces, which define the assembly unit and contact interfaces, respectively. However, the mechanism of curvature formation in this step is not yet fully understood. In this study, we employed solid-state NMR (SSNMR) to compare the structures of cyclic wild-type SepF assemblies with linear assemblies resulting from a mutation of G137 on the β–β interface. Our results demonstrate that while the sequence differences arise from the internal assembly unit, the dramatic changes in the shape of the assemblies depend on the α–α interface between the units. We further provide atomic-level insights into how the angular variation of the α2 helix on the α–α interface affects the curvature of the assemblies, using a combination of SSNMR, cryo-electron microscopy, and simulation methods. Our findings shed light on the shape control of protein assemblies and emphasize the importance of interhelical contacts in retaining curvature.
Same yet different
Authors: Ivaska Ilmari , Tamm Anne
Published: February 2024

The article compares the distributional differences in the use of the partitive object cases in Estonian and
Finnish via multifactorial modeling in contrastive research using the European Parliament parallel text corpus. Based on previous
contrastive research on Finnic, we expected the principles of object case marking to be similar for Estonian and Finnish
(confirmed), and the partitive objects to be more numerous in Estonian than in Finnish (not confirmed, as countable objects with
scalar verbs proved less likely to be partitive in Estonian). We hypothesized that multifactorial modeling in contrastive research
design could help identify the causes for variation and unfold subtle differences between related language systems. Since
preferences related to grammatical voice and constituent order revealed subtle differences between the systems, this hypothesis
was confirmed.
Multivariable calculus textbook representation of non-cartesian coordinates: a misalignment between multivariable calculus textbook content and upper-division physics application
Authors: Dalton Chaelee , Farlow Brian , Christensen Warren M
Published: February 2024

Upper-division undergraduate physics coursework necessitates a firm grasp on and fluid use of mathematical knowledge, including an understanding of non-cartesian (specifically polar, spherical and cylindrical) coordinates and how to use them. A limited body of research into physics students’ thinking about coordinate systems suggests that even for upper-division students, understanding of coordinate system concepts is emergent. To more fully grasp upper-division physics students’ incoming understanding of non-cartesian coordinates, the prevalence of non-cartesian content in seven popular Calculus textbooks was studied. Using content analysis techniques, a coding scheme was developed to gain insight into the presentation of coordinate system content both quantitatively and qualitatively. An initial finding was that non-cartesian basis unit vectors were absent in all but one book. A deeper analysis of three of the calculus textbooks showed that cartesian coordinates comprise an overwhelming proportion of the textbooks’ content and that qualitatively the cartesian coordinate system is presented as the default coordinate system. Quantitative and qualitative results are presented with implications for how these results might impact physics teaching and research at the middle and upper-division.
Quantitative passive imaging by iterative holography: the example of helioseismic holography
Authors: Müller Björn , Hohage Thorsten , Fournier Damien , Gizon Laurent
Published: February 2024

In passive imaging, one attempts to reconstruct some coefficients in a wave equation from correlations of observed randomly excited solutions to this wave equation. Many methods proposed for this class of inverse problem so far are only qualitative, e.g. trying to identify the support of a perturbation. Major challenges are the increase in dimensionality when computing correlations from primary data in a preprocessing step, and often very poor pointwise signal-to-noise ratios. In this paper, we propose an approach that addresses both of these challenges: it works only on the primary data while implicitly using the full information contained in the correlation data, and it provides quantitative estimates and convergence by iteration. Our work is motivated by helioseismic holography, a well-established imaging method to map heterogenities and flows in the solar interior. We show that the back-propagation used in classical helioseismic holography can be interpreted as the adjoint of the Fréchet derivative of the operator which maps the properties of the solar interior to the correlation data on the solar surface. The theoretical and numerical framework for passive imaging problems developed in this paper extends helioseismic holography to nonlinear problems and allows for quantitative reconstructions. We present a proof of concept in uniform media.
Measurement of steep dispersion associated with magnetically assisted gain in Zeeman degenerate two-level system of cold atoms
Authors: de Aquino Carvalho J C , Moreira R S N , Tabosa J W R
Published: February 2024

We report on the measurements of magnetically assisted dispersion and gain in a Zeeman degenerate two-level system associated with the closed D
2 hyperfine transition

F

g

=
3
→

F

e

=
2

cold cesium atoms. We use a Mach–Zehnder interferometer to measure the dispersive properties of this system in the presence of a magnetic field, transversal to the quantization direction, when the atomic system is excited by a coupling and probe beams with orthogonal polarizations. We have measured the spectrum of the refraction index for different magnitudes of the external magnetic field and different coupling beam intensities. A previously published theoretical model, using a simpler atomic transition

F

g

=
1
→

F

e

=
0

, accounts reasonably for the experimentally observed gain and dispersive lineshapes.
Targeted optimization in small-scale atomic structure calculations: application to Au I
Authors: Caliskan Sema , Grumer Jon , Amarsi Anish M
Published: February 2024

The lack of reliable atomic data can be a severe limitation in astrophysical modelling, in particular of events such as kilonovae that require information on all neutron-capture elements across a wide range of ionization stages. Notably, the presence of non-orthonormalities between electron orbitals representing configurations that are close in energy can introduce significant inaccuracies in computed energies and transition probabilities. Here, we propose an explicit targeted optimization (TO) method that can effectively circumvent this concern while retaining an orthonormal orbital basis set. We illustrate this method within the framework of small-scale atomic structure models of Au I, using the Grasp2018 multiconfigurational Dirac–Hartree–Fock atomic structure code. By comparing to conventional optimization schemes we show how a TO approach improves the energy level positioning and ordering. TO also leads to better agreement with experimental data for the strongest E1 transitions. This illustrates how small-scale models can be significantly improved with minor computational costs if orbital non-orthonormalities are considered carefully. These results should prove useful to multi-element atomic structure calculations in, for example, astrophysical opacity applications involving neutron-capture elements.