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Gdańsk University of Technology

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Publications from the year 2022

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  • Participatory co-design approach for Greencoin educational tool shaping urban green behaviors.
    • Ewa Duda
    • Helena Anacka
    • Jolanta Kowal
    • Hanna Obracht-Prondzynska
    2022 Full text

    Our main goal is to prepare assumptions of the Greencoin (GC) cybernetic system, implying pro-ecological attitudes and behavior of city residents. We used qualitative methods, including a literature review and action research -workshops attended by academics, representatives of private and business sectors, urban movements, municipal institutions’ partners, and residents. Our results defined functionalities of the GC, identified main climate challenges, and confronted city’s possibilities and expectations of its residents. Application modules were proposed to help shape pro-ecological attitudes and behaviors of city residents. The modules include educational solutions fitting into the circular economy, and metabolic approach, enabling broader inclusion in the community. Our studies contribute to and fill the gap in the stream of research and knowledge on implementations in the co-creation of application solutions that promote pro-environmental attitudes and behavior.

  • Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
    • Lelisa Wogi
    • Amruth Thelkar
    • Tesfabirhan Tahiro
    • Tadele Ayana
    • Shabana Urooj
    • Samia Larguech
    2022 Full text ENERGIES

    Abstract: Recent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction motor is designed and simulated by ANSYS Motor-CAD. In order to find the best fit method, simulation results are compared and applied to the motors for electric propulsion, considering the influence of design upon the motor performance. The six-phase squirrel cage induction motor is more energy efficient, reliable and cost effective for the electric propulsion compared to the conventional three phase motor. In this study, first the initial parameters of the six phase squirrel cage induction motor have been determined and then these parameters have been compared with optimized values by Genetic Algorithm (GA) and PSO optimization. The motor designed is optimized using efficiency and power losses as the fitness function. The six phase squirrel cage induction motor is designed using ANSYS Motor-CAD and the simulation results were also presented along with two-dimensional and three-dimensional geometry. The result shows that the weight and power loss are reduced to 161 kg and 0.9359 Kw respectively, while the efficiency and power factor are increased to 0.95 and 0.87 respectively when PSO is used. This shows that the result is promising.

  • Pedestrian detection in low-resolution thermal images
    • Aleksandra Górska
    • Patrycja Guzal
    • Iga Namiotko
    • Jacek Rumiński
    • Martyna Włoszczyńska
    • Jacek Rumiński
    2022

    Over one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use of automatic detection of pedestrians in low-resolution thermal image sequences. The data acquisition system was designed and used to collect thermal images for the needs of training of machine learning methods. The created new dataset consists of 9178 annotated, low-resolution images of pedestrians in different traffic conditions. Several deep, object detection models were adapted and trained using the new dataset together with public datasets. The best model turned out to be the adapted Faster R-CNN ResNet50 FPN (Faster Region-based Convolutional, Neural Networks Residual network50, Feature Pyramid Network) model with mean Average Precision (mAP) equal to 94.00%. It was also shown that the use of transfer learning based on the features learned from the RGB images results in mAP greater than 85.00% for all investigated algorithms. The designed system finds practical application in increasing road safety through the potential use of autonomous cars and city monitoring.

  • Pedestrian Safety at Midblock Crossings on Dual Carriageway Roads in Polish Cities
    • Piotr Szagała
    • Andrzej Brzeziński
    • Mariusz Kieć
    • Marcin Budzyński
    • Joanna Wachnicka
    • Sylwia Pazdan
    2022 Full text Sustainability

    Road crossings across two or more lanes in one direction are particularly dangerous due to limited sight distance and high vehicle speeds. To improve their safety, road authorities should provide safety treatments. These may include additional measures to reduce speed and narrow the road cross-section and the introduction of active pedestrian crossings. Equipped with flashing lights activated automatically when a pedestrian is detected, the crossings are painted red and have an anti-skid surface on approaches. The article presents an analysis of road user behaviour at pedestrian crossings on dual carriageways with a varying provision of road safety measures in some Polish cities. It also evaluates the effectiveness of the measures over time. The study was conducted before, immediately after and one year after the additional signage was introduced. The evaluation is based on how vehicle speeds changed before the pedestrian crossing, how pedestrians behaved versus the vehicle and their readiness to cross the street. The number of conflicts on selected crossings was also evaluated. The safety treatments under analysis were found to be less effective than the traditional pedestrian safety measures such as speed cushions or roads narrowed to one lane. This suggests that if used on dual carriageways the measures should only be temporary and should ultimately be replaced with traffic lights or a grade separated solution (a footbridge or tunnel) on exits from urban areas. No clear-cut conclusions about pedestrian safety can be drawn based on the traffic conflicts in question. The article is divided into the following sections: introduction with a review of the literature on pedestrian and driver behaviour studies at pedestrian crossings, including midblock crossings and dual carriageways; a description of the research method and test sites, the results, discussion of the results and conclusion.

  • Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
    • Abimbola G. Akintola
    • Abdullateef O. Balogun
    • Hammed Mojeed
    • Fatima Usman-Hamza
    • Shakirat A. Salihu
    • Kayode S. Adewole
    • Ghaniyyat B. Balogun
    • Peter O. Sadiku
    2022 Full text International Journal of Interactive Mobile Technologies

    Due to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware apps was created. Conventional ML methods are concerned with increasing classification accuracy. However, the standard classification method performs poorly in recognizing malware applications due to the unbalanced real-world datasets. In this study, an empirical analysis of the detection performance of ML methods in the presence of class imbalance is conducted. Specifically, eleven (11) ML methods with diverse computational complexities were investigated. Also, the synthetic minority oversampling technique (SMOTE) and random undersampling (RUS) are deployed to address the class imbalance in the Android malware datasets. The experimented ML methods are tested using the Malgenome and Drebin Android malware datasets that contain features gathered from both static and dynamic malware approaches. According to the experimental findings, the performance of each experimented ML method varies across the datasets. Moreover, the presence of class imbalance deteriorated the performance of the ML methods as their performances were amplified with the deployment of data sampling methods (SMOTE and RUS) used to alleviate the class imbalance problem. Besides, ML models with SMOTE technique are superior to ML models based on the RUS method. It is therefore recommended to address the inherent class imbalance problem in Android Malware detection

  • Performance Analysis of the OpenCL Environment on Mobile Platforms
    • Przemysław Falkowski-Gilski
    • Maciej Plewka
    2022

    Today’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of the OpenCL (Open Compute Language) environment on mobile devices, which is a library dedicated to high-speed parallel computing. This paper examines how smartphones can access a library that, as it turned out, is not officially supported on the Android platform, and briefly describes the evaluated library. As a part of the study, this API (Application Programming Interface) was tested in the context of the achieved computing power, memory flow rate, speed of matrix multiplication and the possibility of processing the image from the camera in real-time. The obta ined results were presented in graphical format, described and commented. We also provide an insight on applications that use this API for teaching deep neural networks, image processing, etc.

  • Performance Assessment of Using Docker for Selected MPI Applications in a Parallel Environment Based on Commodity Hardware
    • Tomasz Kononowicz
    • Paweł Czarnul
    2022 Full text Applied Sciences-Basel

    In the paper, we perform detailed performance analysis of three parallel MPI applications run in a parallel environment based on commodity hardware, using Docker and bare-metal configurations. The testbed applications are representative of the most typical parallel processing paradigms: master–slave, geometric Single Program Multiple Data (SPMD) as well as divide-and-conquer and feature characteristic computational and communication schemes. We perform analysis selecting best configurations considering various optimization flags for the applications and best execution times and speed-ups in terms of the number of nodes and overhead of the virtualized environment. We have concluded that for the configurations giving the shortest execution times the overheads of Docker versus bare-metal for the applications are as follows: 7.59% for master–slave run using 64 processes (number of physical cores), 15.30% for geometric SPMD run using 128 processes (number of logical cores) and 13.29% for divide-and-conquer run using 256 processes. Finally, we compare results obtained using gcc V9 and V7 compiler versions.

  • Performance evaluation and model-based optimization of the mainstream deammonification in an integrated fixed-film activated sludge reactor
    • Mohammad Javad Mehrani
    • Mohammad Azari
    • Burkhard Teichgraber
    • Peter Jagemann
    • Jens Schoth
    • Martin Denecke
    • Jacek Mąkinia
    2022 Full text BIORESOURCE TECHNOLOGY

    This study aimed to model and optimize mainstream deammonification in an integrated fixed-film activated sludge (IFAS) pilot plant under natural seasonal temperature variations. The effect of gradually decreasing temperature on the performance was evaluated during a winter season and a transition period to summer conditions, and the correlation of the performance parameters was investigated using principal component analysis (PCA). The optimization of intermittent aeration in the long-term (30 days) dynamic conditions with on/ off ratio and dissolved oxygen (DO) set-point control was used to maximize the N-removal rate (NRR) and Nremoval efficiency (NRE). Optimization results (DO set-point of 0.2–0.25 mgO2/L, and on/off ratio of 0.05)

  • Performance Evaluation of a Multidomain IMS/NGN Network Including Service and Transport Stratum
    • Sylwester Kaczmarek
    • Maciej Sac
    2022 Full text Applied Sciences-Basel

    The Next Generation Network (NGN) architecture was proposed for delivering various multimedia services with guaranteed quality. For this reason, the elements of the IP Multimedia Subsystem (IMS) concept (an important part of 4G/5G/6G mobile networks) are used in its service stratum. This paper presents comprehensive research on how the parameters of an IMS/NGN network and traffic sources influence mean Call Set-up Delay (E(CSD)) and mean Call Disengagement Delay (E(CDD)), a subset of standardized call processing performance (CPP) parameters, which are significant for both network users and operators. The investigations were performed using our analytical traffic model of a multidomain IMS/NGN network with Multiprotocol Label Switching (MPLS) technology applied in its transport stratum, which provides transport resources for the services requested by users. The performed experiments allow grouping network and traffic source parameters into three categories based on the strength of their effect on E(CSD) and E(CDD). These categories reflect the significance of particular parameters for the network operator and designer (most important, less important and insignificant).

  • Performance of electrochemical immunoassays for clinical diagnostics of SARS-CoV-2 based on selective nucleocapsid N protein detection: Boron-doped diamond, gold and glassy carbon evaluation
    • Wioleta Białobrzeska
    • Mateusz Ficek
    • Bartłomiej Dec
    • Silvio Osella
    • Bartosz Trzaskowski
    • Andres Jaramillo-Botero
    • Mattia Pierpaoli
    • Michał Rycewicz
    • Yanina Dashkevich
    • Tomasz Łęga
    • Natalia Malinowska
    • Zofia Cebula
    • Daniel Bigus
    • Daniel Firganek
    • Ewelina Bięga
    • Karolina Dziąbowska
    • Mateusz Brodowski
    • Marcin Kowalski
    • Mirosława Panasiuk
    • Beata Gromadzka
    • Sabina Żołędowska
    • Dawid Nidzworski
    • Krzysztof Pyrć
    • William A. Goddard III
    • Robert Bogdanowicz
    2022 Full text BIOSENSORS & BIOELECTRONICS

    The 21st century has already brought us a plethora of new threats related to viruses that emerge in humans after zoonotic transmission or drastically change their geographic distribution or prevalence. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first spotted at the end of 2019 to rapidly spread in southwest Asia and later cause a global pandemic, which paralyzes the world since then. We have designed novel immunosensors targeting conserved protein sequences of the N protein of SARS-CoV-2 based on lab-produced and purified anti-SARS-CoV-2 nucleocapsid antibodies that are densely grafted onto various surfaces (diamond/gold/glassy carbon). Titration of antibodies shows very strong reactions up to 1:72 900 dilution. Next, we showed the mechanism of interactions of our immunoassay with nucleocapsid N protein revealing molecular recognition by impedimetric measurements supported by hybrid modeling results with both density functional theory and molecular dynamics methods. Biosensors allowed for a fast (in less than 10 min) detection of SARS-CoV-2 virus with a limit of detection from 0.227 ng/ml through 0.334 ng/ml to 0.362 ng/ml for glassy carbon, boron-doped diamond, and gold surfaces, respectively. For all tested surfaces, we obtained a wide linear range of concentrations from 4.4 ng/ml to 4.4 pg/ml. Furthermore, our sensor leads to a highly specific response to SARS-CoV-2 clinical samples versus other upper respiratory tract viruses such as influenza, respiratory syncytial virus, or Epstein-Barr virus. All clinical samples were tested simultaneously on biosensors and real-time polymerase chain reactions.

  • Performance of Vector-valued Intensity Measures for Estimating Residual Drift of Steel MRFs with Viscous Dampers
    • Benyamin Mohebi
    • Farzin Kazemi
    • Neda Asgarkhani
    • Pinar Ghasemnezhadsani
    • Anahita Mohebi
    2022 Full text International Journal of Structural and Civil Engineering Research

    Viscous Dampers (VDs) are widely used as passive energy dissipation system for improving seismic performance levels especially in retrofitting of buildings. Residual Inter-story Drift Ratio (R-IDR) is another important factor that specifies the condition of building after earthquake. The values of R-IDR illustrates the possibility of retrofitting and repairing of a building. Therefore, this study aims to explore the vector-valued Intensity Measures (IMs) for predicting the R-IDR of two group of steel Moment-Resisting Frames (MRFs) with and without implementing VDs. Incremental Dynamic Analysis (IDA) was performed with considering RIDR using OpenSees software. Efficiency and sufficiency have been quantified for 18 vector-valued IMs with respect to the Residual Interstory Drift Ratio (R-IDR). Results showed that two vector-valued IMs of (Sa(T1), SaRatioM-D) and (Sa(T1), IM-D) had lower σlnSaRD|IM2 values in the R-IDR of 0.002, 0.005, 0.01, and 0.02, and they had higher FR in the mean dispersion, (σlnSaRD|IM2)avg, compared to other IMs. In addition, two vector-valued IMs of (Sa(T1), SaRatioM-D) and (Sa(T1), IM-D) achieved p-values higher than 0.05 with respect to seismic ground motion features of M, R, and Vs30, and can be used as optimal vector-valued IMs.

  • Performance-Driven Inverse/Forward Modeling of Antennas in Variable-Thickness Domains
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    2022

    Design of contemporary antenna systems is a challenging endeavor. The difficulties are partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities, but also constraints imposed upon the physical size of the radiators. Furthermore, conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise dictated by reliability, entails considerable computational expenses. This is particularly troublesome for the procedures involving repetitive EM analyses, e.g., parametric optimization. Utilization of fast surrogate models as a way of mitigating this issue has been fostered in the recent literature. Notwithstanding, construction of reliable surrogates is hindered by highly nonlinear antenna responses and even more by the utility requirements: design-ready models are to be valid over wide ranges of operating conditions and geometry parameters. Recently proposed performance-driven modeling, especially the nested kriging framework, addresses these difficulties by confining the surrogate model domain to a region that encapsulates the designs being optimum with respect to the relevant figures of interest. The result is a dramatic reduction of the number of training samples needed to render a usable model.

  • Performance-driven yield optimization of high-frequency structures by kriging surrogates
    • Anna Pietrenko-Dąbrowska
    • Paulina Kozieł
    2022 Full text Applied Sciences-Basel

    Uncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated with EM-driven statistical analysis often turn out to be unendurable. Recently, a performance-driven modeling technique has been proposed that may be employed for uncertainty quantification purposes, and enable circumventing the aforementioned difficulties. Capitalizing on this idea, this paper discusses a procedure for fast and simple surro-gate-based yield optimization of high-frequency structures. The main concept of the approach is a tailored definition of the surrogate domain, which is based on a couple of pre-optimized designs that reflect the directions featuring maximum variability of the circuit responses with respect to its dimensions. A compact size of such a domain allows for constructing an accurate metamodel therein using moderate numbers of training samples, and subsequently employ it to enhance the yield. The implementation details are dedicated to a particular type of device. Results obtained for a ring-slot antenna and a miniaturized rat-race coupler imply that the cost of yield optimization process can be reduced to few dozens of EM analyses.

  • Permeability of Waterfronts—Contemporary Approach in Designing Urban Blue Spaces
    • Anastasiia Dubinina
    • Aleksandra Wawrzyńska
    • Karolina Krośnicka
    2022 Full text Sustainability

    The constant struggle with rising sea levels and flood hazards has resulted in the change of the paradigm in shaping urban waterfronts towards increasing their permeability and creation of urban blue spaces. The aim of the paper was to indicate a new approach in designing public spaces at the sea–land interface by presenting a comparative study of the design solutions used in case of the four selected case studies: the Sea Organs in Zadar (Croatia), Norwegian National Opera and Ballet in Oslo (Norway), the Coastal Public Sauna in Helsinki (Finland) and Tel Aviv’s Central Promenade (Israel). The studied examples take into account the permeability of waterfronts (understood as a feature of the edge between water–land consisting of being soft and permeable). The authors decided to use the case study method as the main approach, analyzing such elements as: the site’s location and urban context, features of urban and architectural design (with usage of graphic methods and a qualitative description), and the land–water edge type (defined according the existing typologies). The study proved, that in recent years the designers have started to replace the vertical quay walls, which create a “rigid” water–land border, with multi-level solutions having a high degree of permeability for water.

  • Personal Branding in the Knowledge Economy: The Inter-relationship between Corporate and Employee Brands
    • Wioleta Kucharska
    2022 Full text

    https://www.taylorfrancis.com/books/mono/10.4324/9781003178248/personal-branding-knowledge-economy-wioleta-kucharska

  • Perspektywa jakości w szkolnictwie wyższym. O modelu QualHE
    • Piotr Grudowski
    2022

    Oddawana do rąk Czytelników monografia wnosi wkład w wypełnianie wspomnianej luki, przede wszystkim poprzez: • przedstawienie szerokiego kontekstu ogólnoświatowego dyskursu dotyczącego kategorii jakości w szkolnictwie wyższym w ujęciu teoriopoznawczym i w wynikach badań empirycznych; • określenie potencjału i uwarunkowań aplikacyjnych dotyczących takich koncepcji jak TQM Lean Management, Six Sigma czy Lean Six Sigma; • przedstawienie aktualnych trendów w zarządzaniu usługami publicznymi jako zbioru impulsów do zmian oraz tła dla projakościowej transformacji uczelni; • wskazanie możliwości wykorzystania opracowanych przez ISO najnowszych normatywnych systemów zarządzania; • zaakcentowanie roli kultury jakości jako elementu determinującego powodzenie wszelkich inicjatyw związanych z doskonaleniem procesów uczelni; • przedstawienie wyników kompleksowych badań interesariuszy polskiego systemu szkolnictwa wyższego na temat całokształtu projakościowych regulacji i zmian w uczelniach; • odniesienie perspektyw i wyzwań dotyczących zmian w szkolnictwie wyższym do koncepcji Przemysłu 4.0 i Jakości 4.0. Zaproponowany w książce oryginalny model systemu zarządzania jakością na uczelni – QualHE – odnosi się do wymienionych elementów, pokazując ich wzajemne relacje i dynamiczny charakter. Książka jest adresowana do badaczy zainteresowanych funkcjonowaniem systemów szkolnictwa wyższego, uczelni i poszczególnych jednostek organizacyjnych oraz kierunkami ich modernizacji. Powinna też spotkać się z zainteresowaniem praktyków – przedstawicieli kadry kierowniczej oraz pracowników działów jakości, coraz powszechniej tworzonych w strukturach uczelni. Może także stanowić kompendium wiedzy i inspirację do identyfikacji działań związanych z doskonaleniem organizacji dla osób reprezentujących różne grupy interesariuszy szkół wyższych, np. studentów, absolwentów, pracowników uczelni czy pracodawców.

  • Pharmaceuticals and other contaminants of emerging concern in Admiralty Bay as a result of untreated wastewater discharge: Status and possible environmental consequences
    • Małgorzata Szopińska
    • Joanna Potapowicz
    • Katarzyna Jankowska
    • Aneta Łuczkiewicz
    • Ola Svahn
    • Erland Björklund
    • Christina Nannou
    • Dimitra Lambropoulou
    • Żaneta Polkowska
    2022 Full text SCIENCE OF THE TOTAL ENVIRONMENT

    Considering how the impact of human activity in Antarctica is growing, the aim of this study was to conduct the first assessment of pharmaceuticals and personal care products (PPCPs), other emerging contaminants (ECs), and antibiotic resistance genes present in the western shore of the Admiralty Bay region of King George Island. In total, more than 170 substances were evaluated to assess the potential environmental risks they pose to the study area. The major evaluated source of pollutants in this study is discharged untreated wastewater. The highest PPCP concentrations in wastewater were found for naproxen (2653 ngL˗1), diclofenac (747 ngL˗1), ketoconazole (760 ngL˗1), ibuprofen (477 ngL˗1) and acetaminophen (332 ngL˗1). Moreover, the concentrations of benzotriazole (6340 ngL˗1) and caffeine (3310 ngL˗1) were also high. The Risk Quotient values indicate that azole antifungals (ketoconazole), anti-inflammatories (diclofenac, ibuprofen) and stimulants (caffeine) are the main groups responsible for the highest toxic burden. In addition, antibiotic resistance genes integrons (int 1) and sulphonamide resistance genes (sul 1–2) were detected in wastewater and seawater. These results indicate that regular monitoring of PPCPs and other ECs is of great importance in this environment. Additionally, the following mitigation strategies are suggested: (1) to create a centralised record of the medications prescribed and consumed in situ (to improve knowledge of potential contaminants without analysis); (2) to use more environmentally friendly substitutes both for pharmaceuticals and personal care products when possible (limiting consumption at the source); and (3) to apply advanced systems for wastewater treatment before discharge to the recipient (end-of-pipe technologies as a final barrier).

  • Phosphinoborinium cation: a synthon for cationic B-P bond systems
    • Kinga Kaniewska-Laskowska
    • Katarzyna Klimsiak
    • Natalia Szynkiewicz
    • Jarosław Chojnacki
    • Rafał Grubba
    2022 Full text CHEMICAL COMMUNICATIONS

    Herein, we report access to phosphinoborinium cations via heterolytic cleavage of the boron-bromide bond in bromophosphinoborane. The product of the reaction was isolated as a dimeric dication possessing a planar P2B2 core. Activation of C-H and C-P bonds in the dication led to formation of the borinium-phosphaborene adduct. Reactivity studies revealed that title cation exhibits ambiphilic properties and intramolecular frustrated Lewis pair features.

  • Phosphinophosphoranes: Mixed-Valent Phosphorus Compounds with Ambiphilic Properties
    • Natalia Szynkiewicz
    • Jarosław Chojnacki
    • Rafał Grubba
    2022 Full text INORGANIC CHEMISTRY

    Herein, we present a simple synthesis of mixed-valent phosphinophosphoranes bearing three- and five-coordinate phosphorus centers. Compounds with phosphorus–phosphorus bonds were synthesized via a reaction of lithium phosphides RR′PLi with cat2PCl (cat = catecholate), whereas derivatives with methylene-linked phosphorus centers were obtained via a reaction of phosphanylmethanides RR′CH2Li with cat2PCl. The presence of accessible lone-pair electrons on the P-phosphanyl atom of phosphinophosphoranes during the reaction of the title compounds with H3B·SMe2, where phosphinophosphorane-borane adducts were formed quantitatively, was confirmed. Furthermore, the Lewis basic and Lewis acidic properties of the phosphinophosphoranes in reactions with phenyl isothiocyanate were tested. Depending on the structure of the starting phosphinophosphorane, phosphinophosphorylation of PhNCS or formation of a five-membered zwitterionic adduct was observed. The structures of the isolated compounds were unambiguously determined by heteronuclear nuclear magnetic resonance spectroscopy and single-crystal X-ray diffraction. Moreover, by applying density functional theory calculations, we compared the Lewis basicity and nucleophilicity of diversified trivalent P-centers.

  • Photolysis for the Removal and Transformation of Pesticide Residues During Food Processing: A State-of-the-Art Minireview
    • Qian Xiao
    • Xiaoxu Xuan
    • Grzegorz Boczkaj
    • Joon Yong Yoon
    • Xun Sun
    2022 Full text Frontiers in Nutrition

    Pesticide residues are of great significant issue that exerted adverse effects on humans. There is a need for effective and non-toxic decontamination of pesticide residues during food processing. In this minireview, the recent advances in the degradation of pesticide residues by photolysis have been firstly described during food processing. The mechanisms of pesticide residues destruction by photolysis were discussed accordingly. Finally, applications of photolysis in the degradation of pesticide residues from beverages, fresh produce, and food rinse waste were also summarized.