bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of mosquito and fly derived DNA as a tool for sampling vertebrate biodiversity in suburban forests in Berlin, Germany
Authors: Danabalan Renita , Planillo Aimara , Butschkau Susanne , Deeg Sita , Pierre Gras , Thion Cincia , Calvignac‐Spencer Sébastien , Kramer‐Schadt Stephanie , Mazzoni Camila
Published: February 2023

The use of invertebrate‐derived DNA (iDNA) is a promising non‐invasive tool to monitor wildlife. While most studies have been carried out in dense tropical and sub‐tropical forests and have focused on the use of a single category of invertebrates, this study compares the use of flies and mosquitoes‐derived DNA to assess vertebrate diversity in semi‐urban environments. We conducted our sampling in four different forest plots in Berlin, Germany. Pools of flies and non‐bloodfed mosquitoes were metabarcoded using 108‐bp vertebrate‐specific 12 S rRNA (12 S‐V5) and 94‐bp mammal‐specific 16 S rRNA (16Smam) mitochondrial markers, and individual bloodfed mosquitoes were sequenced using the 340‐bp vertebrate‐specific 12 S rRNA fragment (Mam‐12 S‐340). Most sequencing was only successful for mammal species. From the fly pools, we detected 10 mammal species using 16Smam, and six species using 12 S‐V5. From the non‐bloodfed mosquito pools, we only amplified putative contaminant DNA, indicating that mosquito females without visual signs of a blood meal carry no traces of vertebrate DNA. Finally, in the bloodfed mosquitoes, we identified four mammal species. We did not find significant differences in the proportion of mammal species detected regarding the total available number of species between sampling localities. Fly samples were easier to obtain and more abundant over the sampled localities compared to mosquito samples. We conclude that, while there are a few advantages in using mosquito blood meals, the use of flies in the detection of wildlife in a suburban environment is more effective in terms of collection of samples and detection of vertebrates, although this technique is limited to few mammal species in the urban environment.
Study on the impact of carbon emission pollution on urban tourism environment
Authors: Tian Ying
Published: February 2023

The tourism industry will continue to produce carbon emissions in the process of development, which will ultimately have an impact on the tourism environment. This article aims to study the effect of carbon emission pollution on the urban tourism environment. Taking Hebei Province from 2016 to 2020 as an example, the effect of carbon emission pollution on the local tourism environment was analyzed using the carbon emission model and tourism eco‐efficiency model. The local carbon emission increased in the process of developing the tourism industry; however, carbon emissions per unit in the accommodation, catering and shopping related to the tourism industry generated more tourism economic benefits. The authors suggest to strengthen the development of tourism transportation, increase local tourism promotion, enhance the diversity of tourism specialties, and improve the level of local catering and hotel services.
Design and Optimization of a Waste Heat Recovery Organic Rankine Cycle System with a Steam–Water Dual Heat Source
Authors: Wang Shiqi , Yuan Zhongyuan , Yu Nanyang
Published: February 2023

The organic Rankine cycle (ORC) system in plants, powered by dual steam–water heat sources, has significant power generation potential and practical research value. Herein, the conditions of 700 kPa saturated steam and 650 kPa, 90 °C water heat source are considered. Four configurations of steam–water dual heat source waste heat recovery ORC systems are proposed. The independent parameters affecting the net output power of the system are obtained by developing a mathematical model and optimizing it using the particle swarm optimization method. The results show that the location of the pinch‐point temperature difference in various ORC loops and the allowable working pressure of the heat exchanger are determinants of independent parameters. The net output powers of the conventional dual‐loop ORC (CD‐ORC), single‐loop ORC (S‐ORC), split‐flow dual‐loop ORC (SFD‐ORC), and split‐flow triple‐loop ORC SFT‐ORC systems under the optimal design parameters are 2415.73, 2168.6, 2599.62, and 2716.75 kW, respectively. In addition, S‐ORC has the highest exergy efficiency of 55.17%. SFD‐ORC and SFT‐ORC have ≈48% exergy efficiency, and CD‐ORC has the lowest exergy efficiency of 45.33%.
Metal impregnation on steel converter slag as an oxygen carrier
Authors: Hildor Fredrik , Mattisson Tobias , Linderholm Carl , Leion Henrik
Published: February 2023

Oxygen carriers used in chemical looping processes operated with biofuel are affected by the inorganic matter of the fuel. It is therefore expected that the lifetime of the oxygen carrier is limited, and preferably low‐cost oxygen carriers should be used. Oxygen carriers based on iron ore or steel manufacturing waste products are available in significant quantities at low cost. However, it is common for these types of materials that their reactivity is low. This study investigates the effect of adding small amounts of more reactive elements into steel converter slag, also called LD slag.

Slag particles were wet impregnated with 2 or 5 wt.% of Ni, Cu, Mn, or Ce. The new material's morphology was evaluated using X‐Ray Diffraction and SEM‐EDS. Changes in reactivity towards CO, CH4 and the model tar molecule benzene were evaluated using a bench‐scale laboratory fluidized bed reactor.

It was observed that even small amounts of either Ni, Cu, or Mn could increase reactivity toward CO. Both Cu and Mn formed phases with LD slag that released oxygen via CLOU (chemical looping with oxygen uncoupling) and increased the conversion of methane and benzene. Ni and Ce doping also increased methane conversion but had only a minor effect on the benzene conversion. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.
The impact of cold waves and heat waves on mortality: Evidence from a lower middle‐income country
Authors: Nguyen Cuong Viet , Nguyen Manh‐Hung , Nguyen Toan Truong
Published: February 2023

We estimate the impact of temperature extremes on mortality in Vietnam, using daily data on temperatures and monthly data on mortality during the 2000–2018 period. We find that both cold and heat waves cause higher mortality, particularly among older people and those living in the hot regions in Southern Vietnam. This effect on mortality tends to be smaller in provinces with higher rates of air‐conditioning and emigration, and provinces with higher public spending on health. Finally, we estimate economic cost of cold and heat waves using a framework of willingness to pay to avoid deaths, then project the cost to the year 2100 under different Representative Concentration Pathway scenarios.
Prognostic value and clinicopathological status of PD‐L1 expression and CD8+ TILs in oral squamous cell cancer patients with or without traditional risk factors
Authors: Soopanit Thanion , Laokulrath Natthawadee , Chayopasakul Veeruth , Pongsapich Warut
Published: February 2023

Background

Non‐smokers, non‐drinkers, and non‐betel quid chewers (NSNDNBs) with oral squamous cell carcinoma (OSCC) have poor survival outcomes. Tumor microenvironment based on PD‐L1/CD8+ T cell infiltrated lymphocyte (TIL) proportion is proposed as a prognostic indicator.

Methods

Immunohistochemistry staining was performed on OSCC samples from 64 patients. The PD‐L1/CD8+ TILs were scored and stratified into four groups. Disease‐free survival (DFS) was analyzed using a Cox regression model.

Results

OSCC in NSNDNB patients was associated with female sex, T1‐2 classification, and PD‐L1 positivity. Low CD8+ TILs correlated with perineural invasion. High CD8+ TILs correlated with improved DFS. PD‐L1 positivity was not correlated with DFS. Type IV tumor microenvironment yielded the highest DFS (85%).

Conclusion

NSNDNB status relates to PD‐L1 expression regardless of CD8+ TILs infiltration. Type IV tumor microenvironment was associated with the best DFS. High CD8+ TILs resulted in better survival, while PD‐L1 positivity alone was not correlated to DFS.
Preterm birth characteristics and outcomes in Portugal, between 2010 and 2018—A cross‐sectional sequential study
Authors: Elias Cecília , Nogueira Paulo Jorge , Sousa Paulo
Published: February 2023

Introduction

According to the World Health Organization, 11% of all children are born prematurely, representing 15 million births annually. An extensive analysis on preterm birth, from extreme to late prematurity and associated deaths, has not been published. The authors characterize premature births in Portugal, between 2010 and 2018, according to gestational age, geographic distribution, month, multiple gestations, comorbidities, and outcomes.

Methods

A sequential, cross‐sectional, observational epidemiologic study was conducted, and data were collected from the Hospital Morbidity Database, an anonymous administrative database containing information on all hospitalizations in National Health Service hospitals in Portugal, and coded according to the ICD‐9‐CM (International Classification of Diseases), until 2016, and ICD‐10 subsequently. Data from the National Institute of Statistics was utilized to compare the Portuguese population. Data were analyzed using R software.

Results

In this 9‐year study, 51.316 births were preterm, representing an overall prematurity rate of 7.7%. Under 29 weeks, birth rates varied between 5.5% and 7.6%, while births between 33 and 36 weeks varied between 76.9% and 81.0%. Urban districts presented the highest preterm rates. Multiple births were 8× more likely preterm and accounted for 37%–42% of all preterm births. Preterm birth rates slightly increased in February, July, August, and October. Overall, respiratory distress syndrome (RDS), sepsis, and intraventricular hemorrhage were the most common morbidities. Preterm mortality rates varied significantly with gestational age.

Conclusion

In Portugal, 1 in 13 babies was born prematurely. Prematurity was more common in predominantly urban districts, a surprise finding that warrants further studies. Seasonal preterm variation rates also require further analysis and modelling to factor in heat waves and low temperatures. A decrease in the case rate of RDS and sepsis was observed. Compared with previously published results, preterm mortality per gestational age decreased; however, further improvements are attainable in comparison with other countries.
A meta‐analysis of neurofeedback for treating substance use disorders
Authors: Russo G. Michael , Smith Samantha , Sperandio Katharine R.
Published: February 2023

A meta‐analysis was conducted to assess the efficacy of neurofeedback (NFB) in the treatment of individuals with substance use disorder (SUD) in between‐group studies. This study reports findings from the first exhaustive search of the literature on the topic and included articles selected from a total of 58 databases/repositories. Studies were evaluated using Hedge's g as the effect size measure and were assessed for risk of bias using funnel plot, Fail‐Safe N, and Trim and Fill analysis. Ten studies, containing 30 effect sizes were evaluated to determine the overall efficacy of NFB for decreasing symptoms of SUD (N = 397), yielding a mean effect size of g = –1.49 (CI 95 = –1.95, –1.03; PI 95 = –4.37 to 1.39). This meta‐analysis provides strong evidence for the efficacy of NFB in treating SUD while also highlighting the value of wholistic client care in SUD treatment.
A general expression for the statistical error in a diffusion coefficient obtained from a solid‐state molecular‐dynamics simulation
Authors: Usler Adrian L. , Kemp Dennis , Bonkowski Alexander , De Souza Roger A.
Published: February 2023

Analysis of the mean squared displacement of species , , as a function of simulation time constitutes a powerful method for extracting, from a molecular‐dynamics (MD) simulation, the tracer diffusion coefficient, . The statistical error in is seldom considered, and when it is done, the error is generally underestimated. In this study, we examined the statistics of curves generated by solid‐state diffusion by means of kinetic Monte Carlo sampling. Our results indicate that the statistical error in depends, in a strongly interrelated way, on the simulation time, the cell size, and the number of relevant point defects in the simulation cell. Reducing our results to one key quantity—the number of particles that have jumped at least once—we derive a closed‐form expression for the relative uncertainty in . We confirm the accuracy of our expression through comparisons with self‐generated MD diffusion data. With the expression, we formulate a set of simple rules that encourage the efficient use of computational resources for MD simulations.
Pyrite (FeS2)‐decorated 1D TiO2 nanotubes in a bilayer as a sustainable photoanode for photoelectrochemical water splitting activity
Authors: Alam Noor , Zahid Muhammad
Published: February 2023

Herein, FeS2@TiO2 nanotubes photocatalyst was prepared by electrochemical anodization method followed by successive ionic layer adsorption and reaction method, and then finally annealed in a tube furnace for homogenous crystallization. The surface morphology, elemental composition, optical properties, and crystalline structure of the prepared FeS2@TiO2 nanocomposite were found out by performing scanning electron microscopy, energy dispersive X‐ray spectroscopy, X‐ray diffraction, UV–Vis diffuse reflectance spectroscopy, and fluorescence spectroscopy, respectively, while bonds vibrations and various functional groups' presence were analyzed using Raman and Fourier transform infrared spectroscopy. A higher photocurrent density of 1.59 mA/cm2 at 0.3 V versus reference electrode of Ag/AgCl (1.23 V versus reversible hydrogen electrode) using 100 mW/cm2 intensive light source was shown by 15‐FeS2@TiO2 nanotubes (uniformly loaded photoanode) while donor density (ND) of 3.68 × 10−13 cm−3 as compared to pure TiO2 NTs (0.09 mA/cm2), 05‐FeS2@TiO2 NTs (0.19 mA/cm2), 10‐FeS2@TiO2 NTs (0.53 mA/cm2) and 20‐FeS2@TiO2 NTs (0.61 mA/cm2), respectively. The exceptional photoelectrochemical activity results were attributed to the homogenous integration of FeS2 that not only increase the charge separation but also, intensively interacted with the substrate (TiO2 nanotubes), which results in an excellent photoelectrochemical activity.
Coordination challenges and promising practices for pediatric healthcare‐community partnerships: A multi‐site study
Authors: Spain Angeline K. , Korfmacher Jon , McCrae Julie S.
Published: February 2023

There have been delays integrating universal screening and referral for social needs in pediatric practice. The study investigated two frameworks for clinic‐based screen‐and‐refer practice in eight clinics. The frameworks depict different organizational strategies to bolster family access to community resources.

We conducted semi‐structured interviews with healthcare and community partners at two timepoints (n = 65) to investigate start‐up and ongoing implementation experiences, including continuing challenges.

Results highlighted common within‐clinic and clinic‐community coordination challenges across diverse settings as well as promising practices supported by the two frameworks. In addition, we identified ongoing implementation challenges that face efforts to integrate these approaches and to translate screening results into activities that help children and families.

Assessing the existing service referral coordination infrastructure of each clinic and community in early implementation is critical to screen‐and‐refer practice as this influences the continuum of supports available to meet family needs.
Self‐perceived employability and entrepreneurial and intrapreneurial intentions: Evidence from six countries
Authors: Knezović Emil
Published: February 2023

Although entrepreneurial and intrapreneurial intentions have been a hot topic recently, the role of self‐perceived employability has been neglected. This study investigates the relationship between self‐perceived employability and entrepreneurial and intrapreneurial intentions. The relationship was tested using structural equation modeling based on the primary data from 1264 participants in six countries. The results show that self‐perceived employability is significantly related to entrepreneurial intentions in all countries and intrapreneurial intentions in four out of six. The findings contribute to the neglected role of self‐perceived employability, based on which several implications have been provided.
Positive almost periodic solutions of nonautonomous evolution equations and application to Lotka–Volterra systems
Authors: Khalil Kamal
Published: February 2023

The aim of this paper is to establish some sufficient conditions ensuring the existence and uniqueness of positive (Bohr) almost periodic solutions to a class of semilinear evolution equations of the form: . We assume that the family of closed linear operators on a Banach lattice satisfies the “Acquistapace–Terreni” conditions, so that the associated evolution family is positive and has an exponential dichotomy on . The nonlinear term , acting on certain real interpolation spaces, is assumed to be almost periodic only in a weaker sense (i.e., in Stepanov's sense) with respect to , and Lipschitzian in bounded sets with respect to the second variable. Moreover, we prove a new composition result for Stepanov almost periodic functions by assuming only continuity of with respect to the second variable (see the condition Lemma 1‐(ii)). Finally, we provide an application to a system of Lotka–Volterra predator–prey type model with diffusion and time–dependent parameters in a generalized almost periodic environment.
Muramyl dipeptide alleviates estrogen deficiency‐induced osteoporosis through canonical Wnt signaling
Authors: Park Ok‐Jin , Kwon Yeongkag , Kim Jiseon , Park Chaeyeon , Yun Cheol‐Heui , Han Seung Hyun
Published: February 2023

Wnt signaling is a positive regulator of bone formation through the induction of osteoblast differentiation and down‐regulation of osteoclast differentiation. We previously reported that muramyl dipeptide (MDP) increases bone volume by increasing osteoblast activity and attenuating osteoclast activity in receptor activator of nuclear factor‐κB ligand (RANKL)‐induced osteoporotic model mice. In this study, we investigated whether MDP could alleviate post‐menopausal osteoporosis through Wnt signaling regulation in an ovariectomy (OVX)‐induced mouse osteoporosis model. MDP‐administered OVX mice exhibited higher bone volume and bone mineral density than mice of the control group. MDP significantly increased P1NP in the serum of OVX mice, implying increased bone formation. The expression of pGSK3β and β‐catenin in the distal femur of OVX mice was lower than that in the distal femur of sham‐operated mice. Yet, the expression of pGSK3β and β‐catenin was increased in MDP‐administered OVX mice compared with OVX mice. In addition, MDP increased the expression and transcriptional activity of β‐catenin in osteoblasts. MDP inhibited the proteasomal degradation of β‐catenin via the down‐regulation of its ubiquitination by GSK3β inactivation. When osteoblasts were pretreated with Wnt signaling inhibitors, DKK1 or IWP‐2, the induction of pAKT, pGSK3β, and β‐catenin was not observed. In addition, nucleotide oligomerization domain‐containing protein 2‐deficient osteoblasts were not sensitive to MDP. MDP‐administered OVX mice exhibited fewer tartrate‐resistant acid phosphatase (TRAP)‐positive cells than did OVX mice, attributed to a decrease in the RANKL/OPG ratio. In conclusion, MDP alleviates estrogen deficiency‐induced osteoporosis through canonical Wnt signaling and could be an effective therapeutic for the treatment of post‐menopausal bone loss. © 2023 The Pathological Society of Great Britain and Ireland.
Effect of graphene and MXene as 2D filler material on physico‐mechanical properties of hemp/E‐glass fibers reinforced hybrid composite: A comparative study
Authors: Priyadarshini Saigeeta , Soren Shatrughan , Durga Geeta
Published: February 2023

The present study concentrates on the mechanical, morphological, water absorption and burning behavior of hemp/E‐glass fiber reinforced hybrid composites (FRHC). The surface adhesive characteristics of the acquired bi‐directional hemp fiber mats were enhanced by treating them with an alkali solution. Furthermore, the present work extends to identify the effects of two 2‐dimensional graphene and MXene nanoparticles as filler on the hardness, flexural and tensile behavior as well as water absorption and flammability characteristics of the FRHC. The glass fiber (G), hemp fiber (H), and hemp/glass (G/H) fiber reinforced epoxy LY556 laminates were fabricated by using the hand lay‐up method followed by the vacuum bagging approach. A 30% and 12% increase in the flexural and tensile strength of the H/G hybrid composite has been observed by adding 1% of graphene as an additional reinforcement compared with the neat FRHC. However, the use of MXene as additional reinforcements shows 45% and 10% enhancement in the flexural and tensile strength of the H/G hybrid composite. In addition, the water absorption capacity of MXene‐filled G/H hybrid composites is found to be almost half of that filled with graphene. Similarly, the flammability results reveal that the burning rate of graphene‐reinforced H/G hybrid composite is 17.44 mm/min. When comparing the mechanical, water absorption, and flammability characteristics of graphene and MXene‐reinforced G/H hybrid composites, graphene gives more intensifying results than MXene. The scanning electron microscopic studies are also incorporated to investigate the fractured surface topography of the FRHC.
Tensile properties and failure mechanism of enhanced carbon nanotube/epoxy resin composite strips
Authors: Yue Chengming , Li Huigai , Xu Weihao , Zhang Yan , Wang Ping , Lyu Weibang , Li Yuanyuan
Published: February 2023

Carbon nanotube strips (CNTSs) can be used as preforms for developing high performance nanocomposites. Herein, CNT/epoxy resin (EP) composite strips with different orientations and densities were prepared by three structural treatment methods including infiltrating EP into CNTS, stretching, and pressing. Their tensile properties and failure mechanisms were analyzed. Stretching and pressing induced rearrangement of CNTs and proper resin infiltration could increase load transfer between CNTs within CNTS. Tensile strength of composite strips prepared under stretching and pressing was nine times higher than that of pristine CNTSs. Failure mechanism shifted from massive bundles pullout to brittle fracture due to polymer sticking.
Real world co‐prescribing contraindicated drugs with fluconazole and itraconazole
Authors: Je Nam Kyung , Youm Sangsu , Chun Pusoon
Published: February 2023

Purpose

This study aimed to investigate co‐prescribing of contraindicated drugs with fluconazole and itraconazole using real‐world nationwide data.

Methods

This retrospective cross‐sectional study was performed using claims data collected by the Health Insurance Review and Assessment Service (HIRA) of Korea during 2019–2020. To determine the drugs that should be avoided in patients taking fluconazole or itraconazole, Lexicomp® and Micromedex® were used. The co‐prescribed medications, co‐prescription rates, and potential clinical consequences of the contraindicated drug–drug interactions (DDIs) were investigated.

Results

Of the 197 118 prescriptions of fluconazole, 2847 co‐prescriptions with drugs classified as contraindicated DDI by either Micromedex® or Lexicomp® were identified. Further, of the 74 618 prescriptions of itraconazole, 984 co‐prescriptions with contraindicated DDI were identified. Solifenacin (34.9%), clarithromycin (18.1%), alfuzosin (15.1%), and donepezil (10.4%) were frequently found in the co‐prescriptions of fluconazole, whereas tamsulosin (40.4%), solifenacin (21.3%), rupatadine (17.8%), and fluconazole (8.8%) were frequently found in the co‐prescriptions of itraconazole. In 1105 and 95 co‐prescriptions of fluconazole and itraconazole, accounting for 31.3% of all co‐prescriptions, potential DDIs were associated with a risk of corrected QT interval (QTc) prolongation. Of the total 3831 co‐prescriptions, 2959 (77.2%) and 785 (20.5%) were classified as contraindicated DDI by Micromedex® alone and by Lexicomp® alone, respectively, whereas 87 (2.3%) were classified as contraindicated DDI by both Micromedex® and Lexicomp®.

Conclusions

Many co‐prescriptions were associated with the risk of DDI‐related QTc prolongation, warranting the attention of healthcare providers. Narrowing the discrepancy between databases that provide information on DDIs is required for optimized medicine usage and patient safety.
Resistance‐driven innovations in the discovery of bactericides: novel triclosan derivatives decorating isopropanolamine moiety as promising anti‐biofilm agents against destructive plant bacterial diseases
Authors: Zhang Jiao‐Jiao , Feng Yu‐Mei , Zhang Jun‐Rong , Xiao Wan‐Lin , Liu Shuai‐Shuai , Zhou Xiang , Zhang Heng , Wang Pei‐Yi , Liu Li‐Wei , Yang Song
Published: February 2023

BACKGROUND

Controlling bacterial infections in plants is a major challenge owing to the appearance of resistant strains. As a physical barrier, the bacterial biofilm helps bacterial infections acquire drug resistance by enabling bacteria to accommodate complex and volatile environmental conditions and avoid bactericidal effects. Thus, developing new antibacterial agents with antibiofilm potency is imperative.

RESULTS

A series of simple triclosan derivatives containing isopropanolamine moiety were elaborately designed and assessed for their antibacterial behavior. Bioassay results showed that some title compounds had excellent bioactivity against three destructive bacteria Xanthomonas oryzae pv. oryzae (Xoo), Xanthomonas axonopodis pv. citri (Xac) and Pseudomonas syringae pv. actinidiae (Psa). Notably, compound C8 displayed high bioactivities toward Xoo and Xac, with EC50 values were 0.34 and 2.11 μg mL−1, respectively. In vivo trials revealed that compound C8 exhibited excellent protective activities against rice bacterial blight and citrus bacterial canker at 200 μg mL−1, with control effectivenesses of 49.57% and 85.60%, respectively. Compound A4 had remarkably inhibitory activity toward Psa, with an EC50 value of 2.63 μg mL−1, and demonstrated outstanding protective activity with a value of 77.23% against Psa in vivo. Antibacterial mechanisms indicated that compound C8 dose‐dependently prevented biofilm formation and extracellular polysaccharide production. C8 also significantly weakened the motility and pathogenicity of Xoo.

CONCLUSION

This study contributes to the development and excavation of novel bactericidal candidates with broad‐spectrum antibacterial activity by targeting bacterial biofilm to control refractory plant bacterial diseases. © 2023 Society of Chemical Industry.
Dual‐Absorber Thin‐Film Solar Cell: A High‐Efficiency Design
Authors: Hemalatha S. , Prabu R. Thandaiah , Radhika R. , Kumar Atul
Published: February 2023

The solar cell device architecture is critical for photovoltaic action and achieving high efficiency. Herein, a dual‐absorber solar cell is demonstrated where a stack of two band‐aligned absorbers with different bandgaps facilitates absorption of a broader range of the solar spectrum resulting in higher short‐circuit current. This dual‐absorber design is analyzed and a narrow range of optimal parameters which can achieve net efficiency gain is summarized. By introducing an additional absorber–absorber interface, the interfacial defect and band offset become essential parameters for the efficient functioning of a dual‐absorber device. Single‐, double‐, and triple‐absorber configurations, their performance enhancement, and synergetic spectrum utilization are compared. The proposed dual‐absorber design is more straightforward and has comparable performance to a tandem device, thus presenting a potentially cost‐effective solar cells design.
Hierarchical bipartite formation tracking of networked perturbed robotic systems with nonlinear state‐to‐output mappings
Authors: Ge Ming‐Feng , Huang Kai‐Lun , Hu Wenfeng , Yang Chunhua , Liang Chang‐Duo
Published: February 2023

This article investigates the hierarchical bipartite formation tracking (HBFT) problem of the networked perturbed robotic system (NPRS) with dynamical uncertainties, actuator faults and nonlinear state‐to‐output mappings. Different from the traditional single‐layer formation tracking problems based on only cooperative interconnections, solving the HBFT problem implies that (a) the robots of the NPRS are divided into two layers of subnetworks, where the ones in subnetwork 1 can directly interconnect with the leader, those in subnetwork 2 can only interconnect with each other or subnetwork 1, and the ones in the different subnetworks form hierarchical formations; (b) each formation is further grouped into two complementary sets according to the cooperative and antagonistic interconnections, where the robots of each formation forms two opposite subformations; (c) for the same subnetwork, the geometric centers of the two subformations track the positive and negative states of the leader respectively. The positive state equals to the leader state, and the negative state has the elements with the same absolute value and opposite sign of the corresponding one in the leader state. Then, a uniform cooperative observer‐based fault‐tolerant control (COFTC) algorithm is designed to solve these challenging problem. By employing the Lyapunov theory, the sufficient conditions are derived for guaranteeing the convergence of the proposed COFTC algorithm. Eventually, simulation results are performed on NPRS to verify the effectiveness of the theoretical results.
Evaluation of Neuroprotective and Adjuvant Activities of Diketopiperazine‐Based Peptidomimetics
Authors: Deigin Vladislav , Premyslova Marina , Ksenofontova Olga , Yatskin Oleg , Volpina Olga
Published: February 2023

Oral delivery of peptide pharmaceuticals has long been a fundamental challenge in drug development. A new chemical platform has been developed based on branched 2,5‐diketopiperazines for creating orally active peptidomimetics. The platform includes a diketopiperazine bio‐carrier with “built‐in” functionally active peptide fragments or molecules coupled via linkers, transforming it into an orally available compound displaying the same type of activity. Based on this approach, we prepared several compounds that exhibit hemostimulating, hemosuppressing, and adjuvant activity. In this work, we screened the activity of substituted piperazine‐2,5‐dione derivatives in two experimental models: human neuroblastoma MC‐65 cells and as an adjuvant in response to ovalbumin invasion. As a result, some original cyclopeptide derivatives have demonstrated neuroprotective and adjuvant activity. The maximum neuroprotective activity was shown by cyclo‐[Glu(Ile)Glu(Trp)] and cyclo‐[AlaGlu(Trp)]; branched cyclopeptides containing a disaccharide component cyclo‐[L–Lys(N‐acetyl‐Glucosamine‐N‐acetyl‐muramyl)‐L‐Glu(L‐Trp‐OH)] and palmitic acid cyclo‐[L–Lys (Palmitoyl)‐L‐Glu(L‐Trp‐OH)] showed the highest adjuvant activity.
CFD simulation of a shell and multiple tubes condensing heat exchanger in a modified microwave plant applied for reprocessing End of Life Tires (ELTs)
Authors: Babaei‐Mahani Roohollah , Sardari Pouyan Talebizadeh , Soltani Salman Masoudi , Mohammed Hayder I. , Kuncewicz Zbigniew , Starr Christine
Published: February 2023

The condensation heat exchanger has a critical role in the microwave reduction process to separate and capture valuable by‐products after the microwave reactor. This study aims to perform a computational fluid dynamics (CFD) simulation of a condenser to assess the heat transfer performance of the heat exchanger comprehensively. The type of heat exchanger used for this study is based upon an existing industrial‐scale condenser taken from a conventional thermal pyrolysis end of tires (ELT) reprocessing plant and repurposed for integration into a 1500 kg/h ELT microwave reduction process. The condenser is a shell‐and‐multiple‐tube heat exchanger in which the syngas passes through the tubes while cold water from a cooling tower is placed inside the shell. After the simulation, the effects of inlet temperatures and mass flow rates of the gas and water are investigated. The results show that the heat transfer rate is 58 kW for the inlet air velocity of 0.25 m/s and increases due to the convective heat transfer by 32% and 55% when the air velocity rises to 0.5 and 1 m/s, respectively, for the inlet gas and water temperatures of 80 and 15°C, respectively. Additionally, because the outlet air temperature and the inlet water temperature are strongly correlated with convective heat transfer, the outlet air temperature is equivalent to 17.2, 22.3, and 29.5°C when the inlet water temperature is 15, 20, and 25°C, respectively.
Modeling of COVID‐19 death rate using various air pollutants: A multiple linear regression approach
Authors: Teja Kambhampati , Laskar Nirban , Mozumder Ruhul Amin
Published: February 2023

Air pollution is a significant health risk, especially for vulnerable populations such as children, people with chronic illnesses, the elderly, and the economically and socially disadvantaged. Furthermore, air pollution has enormous social costs that we all bear in the form of premature deaths, low productivity, sick leave, and other strains on the healthcare system. The primary sources of air pollution are traffic, home fires, and industry. Measuring NO2 levels in air pollution reveals the extent of pollution caused by traffic, particularly diesel vehicles, which are the primary source of NO2. COVID‐19 rates are rising in areas with high levels of air pollution, according to mounting evidence. Toxic contaminants can make people more susceptible to COVID‐19. The causal relationship between air pollution and COVID‐19 cases has yet to be established, but experts warn that long‐term exposure will undoubtedly make people more susceptible to lung infections. Air pollution has been linked to an increase in cancer, heart disease, stroke, diabetes, asthma, and other comorbidities by inducing cellular damage and inflammation throughout the body. All of these factors increase the risk of death in COVID‐19 patients. As a result, air quality parameters must be predicted and monitored. To predict results, this study proposes a statistical‐based machine learning approach. Using multiple linear regression (MLR), Decision Tree (D.T.), and Random Forest (R.F.), the experimental results achieved 80%, 73%, and 65% accuracy on the dataset, respectively.
Smoke suppression, flame retardancy, and fire toxicity of polypropylene containing melamine salt of pentaerythritol phosphate halloysite
Authors: Abdelkhalik Aksam , Mahmoud Manar , Nour Mohamed A. , Hassan Mohamed A. , Souaya Eglal R.
Published: February 2023

Polypropylene (PP) was melt blended with a new mono molecular intumescent flame retardant, melamine salt of pentaerythritol phosphate halloysite (MPPH) to enhance its thermal stability, flame retardancy, and smoke suppression properties. The structure of MPPH was elucidated by Fourier transform infrared (FTIR), 1H NMR, X‐ray diffraction (XRD), and energy dispersive X‐ray (EDX) analysis. PP composites results showed that MPPH increased the thermal stability of PP at high temperatures in all PP composites. The horizontal flammability test (UL94H) showed that MPPH stopped flame propagation in PP composites. Vertical burning rate test (UL94V) revealed that PP composites can attain V0 rating at loading levels 25, 30, and 35 wt.% of MPPH. Limiting oxygen index (LOI) data indicated that adding 20, 25, 30, and 35 wt.% of MPPH to PP increased the LOI value of PP (19.2%) to 27.1%, 32.5%, 35.4%, and 38.7%. MPPH succeeded in reducing the maximum specific optical density (Dsmax), mass specific optical density (MOD), and rate of smoke generation during the first 4 min (VOF4) of PP composites compared to PP alone. FTIR gas analyzer results revealed that MPPH decreased the emission of CO and CO2 in the gas phase during the combustion process. Digital photos and scanning electron microscope (SEM) images of char residues remained after the smoke density test revealed that MPPH succeeded in forming a cellular and cohesive char layer on the PP surface. The new data is expected to increase the use of PP in rigid packaging applications.
A Data-Driven Analysis of Formula 1 Car Races Outcome
Authors: Patil Ankur , Jain Nishtha , Agrahari Rahul , Hossari Murhaf , Orlandi Fabrizio , Dev Soumyabrata
Published: February 2023

There are a range of factors that affect the outcome of Formula 1 (F1) car races. Today, it is reasonable to say that F1 races are first won at the factory, and then on the track. F1 teams accumulate enormous amounts of data during races. In this paper, we propose a data-driven approach to identify the most important factors that contribute to the overall points scored by each driver in a F1 season. We perform a correlation analysis along with a principal components analysis (PCA) to identify the factors that are closely related. Furthermore, using PCA, we efficiently reduce our 21 input variables into a lower-dimensional subspace, that can explain most of the variance in our data and which is easier to comprehend. We obtain 5 years (2015–2019) of data explaining the F1 car characteristics from a publicly available website https://www.racefans.net/. We use this web-scrapped F1 race study to understand the impact of the different car features on the total points scored by a driver in the season. To the best of our knowledge, our work is the first of its kind in the area of F1 car races.
Identity Term Sampling for Measuring Gender Bias in Training Data
Authors: Sobhani Nasim , Delany Sarah Jane
Published: February 2023

Predictions from machine learning models can reflect biases in the data on which they are trained. Gender bias has been identified in natural language processing systems such as those used for recruitment. The development of approaches to mitigate gender bias in training data typically need to be able to isolate the effect of gender on the output to see the impact of gender. While it is possible to isolate and identify gender for some types of training data, e.g. CVs in recruitment, for most textual corpora there is no obvious gender label. This paper proposes a general approach to measure bias in textual training data for NLP prediction systems by providing a gender label identified from the textual content of the training data. The approach is compared with the identity term template approach currently in use, also known as Gender Bias Evaluation Datasets (GBETs), which involves the design of synthetic test datasets which isolate gender and are used to probe for gender bias in a dataset. We show that our Identity Term Sampling (ITS) approach is capable of identifying gender bias at least as well as identity term templates and can be used on training data that has no obvious gender label.
How Augmented Reality Beauty Filters Can Affect Self-perception
Authors: Isakowitsch Clara
Published: February 2023

Augmented reality is used on visual social media platforms such as Snapchat and Instagram with filters that can be applied to the user’s face. These filters detect and transform facial features by overlaying digital masks on moving faces. Augmented reality beauty filters (ARB filters) alter the appearance of the face by conforming it to current beauty ideals. Prior to the development of ARB filters selfies could only be enhanced by retroactive photo editing. However, ARB filters adapt to facial features in real time, resulting in a unique digital beautifying process. This qualitative study explores how the use of ARB filters impacts people’s perceptions of themselves. It is based on online interviews that were conducted with eight individuals. The results are analysed within the frameworks of Extended Mind Theory and Enactivism and indicate that ARB filters may have a greater impact on people’s self-perception than retroactive photo editing.
Bayesian Optimization with Multi-objective Acquisition Function for Bilevel Problems
Authors: Dogan Vedat , Prestwich Steven
Published: February 2023

A bilevel optimization problem consists of an upper-level and a lower-level optimization problem connected to each other hierarchically. Efficient methods exist for special cases, but in general solving these problems is difficult. Bayesian optimization methods are an interesting approach that speed up search using an acquisition function, and this paper proposes a modified Bayesian approach. It treats the upper-level problem as an expensive black-box function, and uses multiple acquisition functions in a multi-objective manner by exploring the Pareto-front. Experiments on popular bilevel benchmark problems show the advantage of the method.
Variable-Relationship Guided LNS for the Car Sequencing Problem
Authors: Souza Filipe , Grimes Diarmuid , O’Sullivan Barry
Published: February 2023

Large Neighbourhood Search (LNS) is a powerful technique that applies the “divide and conquer” principle to boost the performance of solvers on large scale Combinatorial Optimization Problems. In this paper we consider one of the main hindrances to the LNS popularity, namely the requirement of an expert to define a problem specific neighborhood. We present an approach that learns from problem structure and search performance in order to generate neighbourhoods that can match the performance of domain specific heuristics developed by an expert. Furthermore, we present a new objective function for the optimzation version of the Car Sequencing Problem, that better distinguishes solution quality.

Empirical results on public instances demonstrate the effectiveness of our approach against both a domain specific heuristic and state-of-the-art generic approaches.
Latent Space Cartography for Geometrically Enriched Latent Spaces
Authors: O’ Mahony Niall , Awasthi Anshul , Walsh Joseph , Riordan Daniel
Published: February 2023

There have been many developments in recent years on the exploitation of non-Euclidean geometry for the better representation of the relation between subgroups in datasets. Great progress has been made in this field of Disentangled Representation Learning, in leveraging information geometry divergence, manifold regularisation and geodesics to allow complex dynamics to be captured in the latent space of the representations produced. However, interpreting the high-dimensional latent spaces of the modern deep learning-based models involved is non-trivial. Therefore, in this paper, we investigate how techniques in Latent Space Cartography can be used to display abstract and representational 2D visualisations of manifolds.

Additionally, we present a multi-task metric learning model to capture in its output representations as many metrics as is available in a multi-faceted fine-grained change detection dataset. We also implement an interactive visualisation tool that utilises cartographic techniques that allow dimensions and annotations of graphs to be representative of the underlying factors affecting individual scenarios the user can morph and transform to focus on an individual/sub-group to see how they are performing with respect to said metrics.
Multi-Graph Convolutional Neural Network for Breast Cancer Multi-task Classification
Authors: Ibrahim Mohamed , Henna Shagufta , Cullen Gary
Published: February 2023

Mammography is a popular diagnostic imaging procedure for detecting breast cancer at an early stage. Various deep-learning approaches to breast cancer detection incur high costs and are erroneous. Therefore, they are not reliable to be used by medical practitioners. Specifically, these approaches do not exploit complex texture patterns and interactions. These approaches warrant the need for labelled data to enable learning, limiting the scalability of these methods with insufficient labelled datasets. Further, these models lack generalisation capability to new-synthesised patterns/textures. To address these problems, in the first instance, we design a graph model to transform the mammogram images into a highly correlated multigraph that encodes rich structural relations and high-level texture features. Next, we integrate a pre-training self-supervised learning multigraph encoder (SSL-MG) to improve feature presentations, especially under limited labelled data constraints. Then, we design a semi-supervised mammogram multigraph convolution neural network downstream model (MMGCN) to perform multi-classifications of mammogram segments encoded in the multigraph nodes. Our proposed frameworks, SSL-MGCN and MMGCN, reduce the need for annotated data to 40% and 60%, respectively, in contrast to the conventional methods that require more than 80% of data to be labelled. Finally, we evaluate the classification performance of MMGCN independently and with integration with SSL-MG in a model called SSL-MMGCN over multi-training settings. Our evaluation results on DSSM, one of the recent public datasets, demonstrate the efficient learning performance of SSL-MNGCN and MMGCN with 0.97 and 0.98 AUC classification accuracy in contrast to the multitask deep graph (GCN) method Hao Du et al. (2021) with 0.81 AUC accuracy.
A Transformer Architecture for Online Gesture Recognition of Mathematical Expressions
Authors: Ramo Mirco , Silvestre Guénolé C. M.
Published: February 2023

The Transformer architecture is shown to provide a powerful framework as an end-to-end model for building expression trees from online handwritten gestures corresponding to glyph strokes. In particular, the attention mechanism was successfully used to encode, learn and enforce the underlying syntax of expressions creating latent representations that are correctly decoded to the exact mathematical expression tree, providing robustness to ablated inputs and unseen glyphs. For the first time, the encoder is fed with spatio-temporal data tokens potentially forming an infinitely large vocabulary, which finds applications beyond that of online gesture recognition. A new supervised dataset of online handwriting gestures is provided for training models on generic handwriting recognition tasks and a new metric is proposed for the evaluation of the syntactic correctness of the output expression trees. A small Transformer model suitable for edge inference was successfully trained to an average normalised Levenshtein accuracy of 94%, resulting in valid postfix RPN tree representation for 94% of predictions.
Einführung in das Untersuchungsfeld
Authors: Rieck Louise Ina Hannah
Published: February 2023

Im einleitenden Kapitel skizziere ich den Untersuchungsgegenstand. Ich erkläre meine Präkonzepte und spezifiziere meine Forschungsziele. Das Forschungsdesign wird vorgestellt und methodologisch begründet. Im letzten Abschnitt beschreibe ich den inhaltlichen Aufbau der Arbeit.
Aufstellung 5: Narrativ
Authors: Rieck Louise Ina Hannah
Published: February 2023

Zum vorläufigen Abschluss meiner Forschungsreise erkunde ich mittels Aufstellung das Wirkpotenzial von Marketing für transformative Narrative: Kann Marketing dabei unterstützen, dass ein neues, zukunftsorientiertes und gesellschaftlich anschlussfähiges Konsumnarrativ entsteht?
Zusammenfassung: Orientierungswissen
Authors: Rieck Louise Ina Hannah
Published: February 2023

Im explorativen Hauptteil sind – zumindest auf meiner inneren Landkarte und soweit ich es überblicke auch auf der von Forschung und Praxis – eine ganze Reihe gehaltvoller Unterschiede entstanden, die vorher nicht greifbar waren. Diese neuen Perspektiven für Marketing fasse ich im Folgenden zusammen.
Methodenreflexion
Authors: Rieck Louise Ina Hannah
Published: February 2023

Systemische Erkundungen mittels Aufstellung führen den:die Beobachtende wieder näher an die Realität des Ganzen heran dadurch, dass die „Wirklichkeit“ im Aufstellungsraum ihre Autonomie zurückerhält. Dies macht die Methode besonders in der Transformationsforschung zu einem nützlichen Werkzeug.