bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-round encryption for COVID-19 data using the DNA key
Authors: Al-Shargabi Bassam , Fadhil Al-Husainy Mohammed Abbas
Published: November 2021

The need for a reliable and fast encryption algorithm to encrypt medical data for patients is an extremely important topic to be considered especially during pandemic times such as the pandemic COVID-19. This pandemic forced governments and healthcare institutions to monitor COVID-19 patients. All the patient's data or records are also shared among healthcare researchers to be used to help them find vaccines or cures for this pandemic. Therefore, protecting such data (images, text) or records face an everincreasing number of risks. In this paper, a novel multi-round encryption algorithm based on deoxyribonucleic acid (DNA) is proposed. The significance of the proposed algorithm comes from using a different random key to perform simple and fast encryption operations on multiple rounds to achieve a high level of confusion and diffusion effects in encrypted data. Experiments were conducted using a set of datasets of various types such as Excel sheets, images, and database tables. The experiments were conducted to test the performance and security level of the proposed encryption algorithm against well-known algorithms such as data encryption standard (DES) and advanced encryption standard (AES). The experiments show an outstanding performance regarding the encryption time, key size, information entropy, and the avalanche effects.
Hybrid power control and contention window adaptation for channel congestion problem in internet of vehicles network
Authors: Amer Hayder M. , Hadi Ethar Abduljabbar , Shihab Lamyaa Ghaleb , Al Mohammed Hawraa H. , Khami Mohammed J.
Published: November 2021

Technology such as vehicular ad hoc networks can be used to enhance the convenience and safety of passenger and drivers. The vehicular ad hoc networks safety applications suffer from performance degradation due to channel congestion in high-density situations. In order to improve vehicular ad hoc networks reliability, performance, and safety, wireless channel congestion should be examined. Features of vehicular networks such as high transmission frequency, fast topology change, high mobility, high disconnection make the congestion control is a challenging task. In this paper, a new congestion control approach is proposed based on the concept of hybrid power control and contention window to ensure a reliable and safe communications architecture within the internet of vehicles network. The proposed approach performance is investigated using an urban scenario. Simulation results show that the network performance has been enhanced by using the hybrid developed strategy in terms of received messages, delay time, messages loss, data collision and congestion ratio.
Arabic open information extraction system using dependency parsing
Authors: Mohamed Ali El-Morsy Sally , Hussein Mahmoud , Mousa Hamdy M.
Published: November 2021

Arabic is a Semitic language and one of the most natural languages distinguished by the richness in morphological enunciation and derivation. This special and complex nature makes extracting information from the Arabic language difficult and always needs improvement. Open information extraction systems (OIE) have been emerged and used in different languages, especially in English. However, it has almost not been used for the Arabic language. Accordingly, this paper aims to introduce an OIE system that extracts the relation tuple from Arabic web text, exploiting Arabic dependency parsing and thinking carefully about all possible text relations. Based on clause types' propositions as extractable relations and constituents' grammatical functions, the identities of corresponding clause types are established. The proposed system named Arabic open information extraction(AOIE) can extract highly scalable Arabic text relations while being domain independent. Implementing the proposed system handles the problem using supervised strategies while the system relies on unsupervised extraction strategies. Also, the system has been implemented in several domains to avoid information extraction in a specific field. The results prove that the system achieves high efficiency in extracting clauses from large amounts of text.
Design and implement a new secure prototype structure of e-commerce system
Authors: Abdul Hussien Farah Tawfiq , S. Rahma Abdul Monem , Abdul Wahab Hala Bahjat
Published: November 2021

The huge development of internet technologies and the widespread of modern and advanced devices lead to an increase in the size and diversity of e-commerce system development. These developments lead to an increase in the number of people that navigate these sites asking for their services and products. Which leads to increased competition in this field. Moreover, the expansion in the size of currency traded makes transaction protection an essential issue in this field. Providing security for each online client especially for a huge number of clients at the same time, causing an overload on the system server. This problem may lead to server deadlock, especially at rush time, which reduce system performance. To solve security and performance problems, this research suggests a prototype design for agent software. This agent will play the role of broker between the clients and the electronic marketplace. This is done by providing security inside the client device and converting the client’s order into a special form which is called a record form to be sent to the commercial website. Experimental results showed that this method increase system performance in terms of page loading time, transaction processing and improves the utilization of system resources.
Stochastic modelling of transition dynamic of mixed mood episodes in bipolar disorder
Authors: Kunjali Ajeeth Kumar Yashaswini , Saxena Adithya Kishore
Published: November 2021

In the present state of health and wellness, mental illness is always deemed less importance compared to other forms of physical illness. In reality, mental illness causes serious multi-dimensional adverse effect to the subject with respect to personal life, social life, as well as financial stability. In the area of mental illness, bipolar disorder is one of the most prominent type which can be triggered by any external stimulation to the subject suffering from this illness. There diagnosis as well as treatment process of bipolar disorder is very much different from other form of illness where the first step of impediment is the correct diagnosis itself. According to the standard body, there are classification of discrete forms of bipolar disorder viz. type-I, type-II, and cyclothymic. Which is characterized by specific mood associated with depression and mania. However, there is no study associated with mixed-mood episode detection which is characterized by combination of various symptoms of bipolar disorder in random, unpredictable, and uncertain manner. Hence, the model contributes to obtain granular information with dynamics of mood transition. The simulated outcome of the proposed system in MATLAB shows that resulting model is capable enough for detection of mixed mood episode precisely
Comparative study between metaheuristic algorithms for internet of things wireless nodes localization
Authors: Mohammed Rana Jassim , Abed Enas Abbas , El-gayar Mostafa Mahmoud
Published: November 2021

Wireless networks are currently used in a wide range of healthcare, military, or environmental applications. Wireless networks contain many nodes and sensors that have many limitations, including limited power, limited processing, and narrow range. Therefore, determining the coordinates of the location of a node of the unknown location at a low cost and a limited treatment is one of the most important challenges facing this field. There are many meta-heuristic algorithms that help in identifying unknown nodes for some known nodes. In this manuscript, hybrid metaheuristic optimization algorithms such as grey wolf optimization and salp swarm algorithm are used to solve localization problem of internet of things (IoT) sensors. Several experiments are conducted on every meta-heuristic optimization algorithm to compare them with the proposed method. The proposed algorithm achieved high accuracy with low error rate (0.001) and low power
consumption.
Parallel genetic approach for routing optimization in large ad hoc networks
Authors: Khankhour Hala , Abdoun Otman , Abouchabaka Jâafar
Published: November 2021

This article presents a new approach of integrating parallelism into the genetic algorithm (GA), to solve the problem of routing in a large ad hoc network, the goal is to find the shortest path routing. Firstly, we fix the source and destination, and we use the variable-length chromosomes (routes) and their genes (nodes), in our work we have answered the following question: what is the better solution to find the shortest path: the sequential or parallel method?. All modern systems support simultaneous processes and threads, processes are instances of programs that generally run independently, for example, if you start a program, the operating system spawns a new process that runs parallel elements to other programs, within these processes, we can use threads to execute code simultaneously. Therefore, we can make the most of the available central processing unit (CPU) cores. Furthermore, the obtained results showed that our algorithm gives a much better quality of solutions. Thereafter, we propose an example of a network with 40 nodes, to study the difference between the sequential and parallel methods, then we increased the number of sensors to 100 nodes, to solve the problem of the shortest path in a large ad hoc network.
Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT
Authors: Nguyen Thi Thu , Doan Phuc Thinh , Le Anh-Ngoc , Prakash Kolla Bhanu , Chowdhury Subrata , Tran Duc-Nghia , Tran Duc-Tan
Published: November 2021

In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%).
Behavioral biometric based personal authentication in feature phones
Authors: Thapliyal Amitabh , Verma Om Prakash , Kumar Amioy
Published: November 2021

The usage of mobile phones has increased multifold in the recent decades mostly because of its utility in most of the aspects of daily life, such as communications, entertainment, and financial transactions. Feature phones are generally the keyboard based or lower version of touch based mobile phones, mostly targeted for efficient calling and messaging. In comparison to smart phones, feature phones have no provision of a biometrics system for the user access. The literature, have shown very less attempts in designing a biometrics system which could be most suitable to the low-cost feature phones. A biometric system utilizes the features and attributes based on the physiological or behavioral properties of the individual. In this research, we explore the usefulness of keystroke dynamics for feature phones which offers an efficient and versatile biometric framework. In our research, we have suggested an approach to incorporate the user’s typing patterns to enhance the security in the feature phone. We have applied k-nearest neighbors (k-NN) with fuzzy logic and achieved the equal error rate (EER) 1.88% to get the better accuracy. The experiments are performed with 25 users on Samsung On7 Pro C3590. On comparison, our proposed technique is competitive with almost all the other techniques available in the literature.
An internet of things framework for real-time aquatic environment monitoring using an Arduino and sensors
Authors: Islam Md. Monirul , Kashem Mohammad Abul , Uddin Jia
Published: November 2021

Aquaculture is the farming of aquatic organisms in natural, controlled marine and freshwater environments. The real-time monitoring of aquatic environmental parameters is very important in fish farming. Internet of things (IoT) can play a vital role in the real-time monitoring. This paper presents an IoT framework for the efficient monitoring and effective control of different aquatic environmental parameters related to the water. The proposed system is implemented as an embedded system using sensors and an Arduino. Different sensors including pH, temperature, and turbidity, ultrasonic are placed in cultivating pond water and each of them is connected to a common microcontroller board built on an Arduino Uno. The sensors read the data from the water and store it as a comma-separated values (CSV) file in an IoT cloud named ThingSpeak through the Arduino microcontroller. To validate the experiment, we collected data from 5 ponds of various sizes and environments. After experimental evaluation, it was observed among 5 ponds, only three ponds were perfect for fish farming, where these 3 ponds only satisfied the standard reference values of pH (6.5-8.5), temperature (16-24 °C), turbidity (below 10 ntu), conductivity (970-1825 μS/cm), and depth (1-4) meter. At the end of this paper, a complete hardware implementation of this proposed IoT framework for a real-time aquatic environment monitoring system is presented.
Adopting MQTT for a multi protocols IoMT system
Authors: Mubdir Bilal Asaad , Bayram Hassan Mohammed Ali
Published: November 2021

Coronavirus disease (COVID-19) altered the way of caregiving and the new pandemic forced the health systems to adopt new treatment protocols in which remote follow-up is essential. This paper introduces a proposed system to link a remote healthcare unit as it is inside the hospital. Two different network protocols; a global system for mobile communication (GSM) and Wi-Fi were used to simulate the heath data transfer from the two different geographical locations, using Raspberry Pi development board and Microcontroller units. Message queuing telemetry transport (MQTT) protocol was employed to transfer the measured data from the healthcare unit to the hospital’s Gateway. The gateway is used to route the aggregated health data from healthcare units to the hospital server, doctors’ dashboards, and the further processing. The system was successfully implemented and tested, where the experimental tests show that the remote healthcare units using a GSM network consumed about 900 mWh. A high percentage of success data packets transfer was recorded within the network framework as it reaches 99.89% with an average round trip time (RTT) of 7.5 milliseconds and a data transfer rate up to 12.3 kbps.
Adaptive photovoltaic solar module based on internet of things and web-based monitoring system
Authors: Kassim Murizah , Lazim Fadila
Published: November 2021

This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module.
Classification of Arabic fricative consonants according to their places of articulation
Authors: Elfahm Youssef , Abajaddi Nesrine , Mounir Badia , Elmaazouzi Laila , Mounir Ilham , Farchi Abdelmajid
Published: November 2021

Many technology systems have used voice recognition applications to transcribe a speaker’s speech into text that can be used by these systems. One of the most complex tasks in speech identification is to know, which acoustic cues will be used to classify sounds. This study presents an approach for characterizing Arabic fricative consonants in two groups (sibilant and non-sibilant). From an acoustic point of view, our approach is based on the analysis of the energy distribution, in frequency bands, in a syllable of the consonant-vowel type. From a practical point of view, our technique has been implemented, in the MATLAB software, and tested on a corpus built in our laboratory. The results obtained show that the percentage energy distribution in a speech signal is a very powerful parameter in the classification of Arabic fricatives. We obtained an accuracy of 92% for non-sibilant consonants /f, χ, ɣ, ʕ, ћ, and h/, 84% for sibilants /s, sҁ, z, Ӡ and ∫/, and 89% for the whole classification rate. In comparison to other algorithms based on neural networks and support vector machines (SVM), our classification system was able to provide a higher classification rate.
Modified limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm for unconstrained optimization problem
Authors: Ali Muna M. M.
Published: November 2021

The use of the self-scaling Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is very efficient for the resolution of large-scale optimization problems, in this paper, we present a new algorithm and modified the self-scaling BFGS algorithm. Also, based on noticeable non-monotone line search properties, we discovered and employed a new non-monotone idea. Thereafter first, an updated formula is exhorted to the convergent Hessian matrix and we have achieved the secant condition, second, we established the global convergence properties of the algorithm under some mild conditions and the objective function is not convexity hypothesis. A promising behavior is achieved and the numerical results are also reported of the new algorithm.
A questão da Autonomia Universitária e suas vicissitudes na universidade brasileira
Authors: Saviani Dermeval
Published: November 2021

Partindo da origem e desenvolvimento da instituição universitária e da indicação dos modelos básicos de sua organização, este artigo aborda, no segundo momento, a trajetória da universidade no Brasil para, no terceiro momento, tratar das vicissitudes do princípio da Autonomia Universitária na educação brasileira. Finalmente, à guisa de conclusão, abre uma discussão sobre o significado da Autonomia Universitária e as condições para sua implementação na universidade brasileira.
Reduced Notch1 Cleavage Promotes the Development of Pulmonary Hypertension
Authors: Wang Shumin , Zhu Guofu , Jiang Dongyang , Rhen Jordan , Li Xiankai , Liu Hao , Lyu Yuyan , Tsai Patrick , Rose Yara , Nguyen Tiffany , White R. James , Pryhuber Gloria S. , Mariani Thomas J. , Li Chen , Mohan Amy , Xu Yawei , Pang Jinjiang
Published: November 2021

Clinical trials of Dll4 (Delta-like 4) neutralizing antibodies (Dll4nAbs) in cancer patients are ongoing. Surprisingly, pulmonary hypertension (PH) occurs in 14% to 18% of patients treated with Dll4nAbs, but the mechanisms have not been studied. Here, PH progression was measured in mice treated with Dll4nAbs. We detected Notch signaling in lung tissues and analyzed pulmonary vascular permeability and inflammation. Notch target gene array was performed on adult human pulmonary microvascular endothelial cells (ECs) after inhibiting Notch cleavage. Similar mechanisms were studied in PH mouse models and pulmonary arterial hypertension patients. The rescue effects of constitutively activated Notch1 in vivo were also measured. We observed that Dll4nAbs induced PH in mice as indicated by significantly increased right ventricular systolic pressure, as well as pulmonary vascular and right ventricular remodeling. Mechanistically, Dll4nAbs inhibited Notch1 cleavage and subsequently impaired lung endothelial barrier function and increased immune cell infiltration in vessel walls. In vitro, Notch targeted genes’ expression related to cell growth and inflammation was decreased in human pulmonary microvascular ECs after the Notch1 inactivation. In lungs of PH mouse models and pulmonary arterial hypertension patients, Notch1 cleavage was inhibited. Consistently, EC cell-cell junction was leaky, and immune cell infiltration increased in PH mouse models. Overexpression activated Notch1-attenuated progression of PH in mice. In conclusion, Dll4nAbs led to PH development in mice by impaired EC barrier function and increased immune cell infiltration through inhibition of Notch1 cleavage in lung ECs. Reduced Notch1 cleavage in lung ECs could be an underlying mechanism of PH pathogenesis.
Renal Denervation in Combination With Angiotensin Receptor Blockade Prolongs Blood Pressure Trough During Hemorrhage
Authors: Singh Reetu R. , McArdle Zoe , Booth Lindsea C. , May Clive N. , Head Geoff A. , Moritz Karen M. , Schlaich Markus P. , Denton Kate M.
Published: November 2021

Majority of patients with hypertension and chronic kidney disease (CKD) undergoing renal denervation (RDN) are maintained on antihypertensive medication. However, RDN may impair compensatory responses to hypotension induced by blood loss. Therefore, continuation of antihypertensive medications in denervated patients may exacerbate hypotensive episodes. This study examined whether antihypertensive medication compromised hemodynamic responses to blood loss in normotensive (control) sheep and in sheep with hypertensive CKD at 30 months after RDN (control-RDN, CKD-RDN) or sham (control-intact, CKD-intact) procedure. CKD-RDN sheep had lower basal blood pressure (BP; ≈9 mm Hg) and higher basal renal blood flow (≈38%) than CKD-intact. Candesartan lowered BP and increased renal blood flow in all groups. 10% loss of blood volume alone caused a modest fall in BP (≈6–8 mm Hg) in all groups but did not affect the recovery of BP. 10% loss of blood volume in the presence of candesartan prolonged the time at trough BP by 9 minutes and attenuated the fall in renal blood flow in the CKD-RDN group compared with CKD-intact. Candesartan in combination with RDN prolonged trough BP and attenuated renal hemodynamic responses to blood loss. To minimize the risk of hypotension-mediated organ damage, patients with RDN maintained on antihypertensive medications may require closer monitoring when undergoing surgery or experiencing traumatic blood loss.
Transfer Learning Based Co-Surrogate Assisted Evolutionary Bi-Objective Optimization for Objectives with Non-Uniform Evaluation Times
Authors: Wang Xilu , Jin Yaochu , Schmitt Sebastian , Olhofer Markus
Published: November 2021

Most existing multiobjective evolutionary algorithms (MOEAs) implicitly assume that each objective function can be evaluated within the same period of time. Typically. this is untenable in many real-world optimization scenarios where evaluation of different objectives involves different computer simulations or physical experiments with distinct time complexity. To address this issue, a transfer learning scheme based on surrogate-assisted evolutionary algorithms (SAEAs) is proposed, in which a co-surrogate is adopted to model the functional relationship between the fast and slow objective functions and a transferable instance selection method is introduced to acquire useful knowledge from the search process of the fast objective. Our experimental results on DTLZ and UF test suites demonstrate that the proposed algorithm is competitive for solving bi-objective optimization where objectives have non-uniform evaluation times.
Definiteness Effect in the PP
Authors: Kiss Katalin É.
Published: November 2021

This article demonstrates that abessive PPs impose the same type of definiteness restriction on their complements that existential predicates impose on their subjects. The definiteness effect (DE) in PPs is accounted for in the framework of the DE theory of Szabolcsi (1986a,b, 1992), who derives the DE from the incompatibility of a presuppositional subject and a logical predicate of existence that is present in a wide class of predicates (including verbs meaning ‘(cause to) come to exist in a particular fashion’ and nominal predicates meaning ‘(non)existence at a particular location’). The analysis points out this predicate of existence in the small clause complements of abessive Ps.
What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition
Authors: Żelasko Piotr , Pappagari Raghavendra , Dehak Najim
Published: November 2021

Dialog acts can be interpreted as the atomic units of a conversation, more fine-grained than utterances, characterized by a specific communicative function. The ability to structure a conversational transcript as a sequence of dialog acts—dialog act recognition, including the segmentation—is critical for understanding dialog. We apply two pre-trained transformer models, XLNet and Longformer, to this task in English and achieve strong results on Switchboard Dialog Act and Meeting Recorder Dialog Act corpora with dialog act segmentation error rates (DSER) of 8.4% and 14.2%. To understand the key factors affecting dialog act recognition, we perform a comparative analysis of models trained under different conditions. We find that the inclusion of a broader conversational context helps disambiguate many dialog act classes, especially those infrequent in the training data. The presence of punctuation in the transcripts has a massive effect on the models’ performance, and a detailed analysis reveals specific segmentation patterns observed in its absence. Finally, we find that the label set specificity does not affect dialog act segmentation performance. These findings have significant practical implications for spoken language understanding applications that depend heavily on a good-quality segmentation being available.
Acaulospora fanjing (Glomeromycota), a new species of arbuscular mycorrhizal fungi from Fanjingshan in China
Authors: HE RONG-JIAN , LONG CHUN-LI , YAO LI-MEI , JIANG LONG
Published: November 2021

Acaulospora fanjing is here described as a new species of arbuscular mycorrhizal fungi (AMF; Glomeromycota) based on morphological and phylogenetic analyses. It was associated with roots of Acer flabellatum colonizing of the massy dwarf forest to fanjing Mountain, China, and this is the only site of its occurrence known to date. A.fanjing is characterized by forming reddish orange to reddish brown globose spores of (109–)123(–138) µm diam and three layers of outer spore walls (SWL1–SWL3) and two layers of germinal walls (MW and IW). SWL1 hyaline, short–lived, evanescent, SWL2 laminate, orange to reddish orange, 2.0–3.5 μm thick and SWL3 thin, difficult to observe; MW is hyaline, bilayered (MWL1–MWL2), semiflexible; IW is hyaline, with three layers and not “beaded” structure, only the IWL2 were stained light pink in Melzer’s reagent. A.fanjing can be distinguished from all other Acaulospora species by spore size, color and spore wall structure. Phylogenetic analysis based on the AMF extended DNA barcode covering a 1.5-kb fragment of the small subunit (SSU), internal transcribed spacer region (ITS), and the large subunit (LSU) of rRNA genes places A.fanjing in the genus Acaulospora, separated from other described Acaulospora species. All available sequences in public databases suggest that this new fungal species has not yet been previously detected.
Antifungal Activity of Biogenically Synthesized Silver and Gold Nanoparticles Against Sheath Blight of Rice
Authors: Das Ankita , Dutta Pranab
Published: November 2021

Biogenically synthesized silver and gold nanoparticles were evaluated for antifungal activity against Rhizoctonia solani causing sheath blight of rice. Both the nanoparticles were tested at 1, 5, 10, 50, 100 and 200 ppm along with chemical check against the pathogen. Silver nanoparticle
(Ag NP) at 200 ppm showed the highest inhibition (73.39%) in the radial growth of R. solani, while gold nanoparticle (Au NP) at the same concentration inhibited the growth of the pathogen up to 60.83%. Study on mode of action of nanoparticle by electron microscopy showed that Ag NP
accumulate inside the fungal cells thereby cause distortion of fungal cells leading to death of the pathogen. Ag NP at 200 and 100 ppm caused complete inhibition of sclerotial germination of R. solani. Pot experiment conducted to study the efficacy of Ag NP at 200 ppm against sheath
blight of rice showed that application of Ag NP increased the plant growth parameters as compared to control, with reduced per cent disease incidence (20.00%) as compared to inoculated control R. solani (88.00%). Application of Ag NP also increased the concentration of vital secondary
metabolites like phenols, flavonoids, terpenoids and total soluble sugars.
The Importance of Nanomedicine in Prophylactic and Theranostic Intervention of Bacterial Zoonoses and Reverse Zoonoses in the Era of Microbial Resistance
Authors: Prasad Minakshi , Ghosh Mayukh , Kumar Rajesh , Brar Basanti , Surjith K. P. , Lambe Upendra P. , Ranjan Koushlesh , Banerjee Somesh , Prasad Gaya , Kumar Khurana Sandip , Kharb Pushpa
Published: November 2021

Emergence of multidrug resistance (MDR), extensively drug resistance (XDR) and pandrug resistance (PDR) strains of bacteria in communicable diseases of zoonotic and reverse zoonotic importance is the major hurdle of one health concept. Increasing level of resistance against antibiotics
among bacterial population throughout the world, slow pace of new antibacterial drug discovery and enhanced pace of resistance development by pathogenic bacteria possess major challenges for human and animal health as well as life in future. Alternative management strategy in terms of improved
prophylactic vaccine; early, easy and effective diagnostics and therapeutic drugs against those resistant bacteria is the need of the hour. In this context nanomedicine can fit into the multifaceted demands as an effective prophylactic and theranostic alternative to control the communicable
diseases in a cost effective manner in the era of microbial resistance. The current review is focused towards delineating the application of nanomaterials as vaccine or drug delivery system, diagnostics and directly acting antimicrobial therapeutic agents in combating the important zoonotic
and reverse zoonotic bacterial diseases in recent scenario along with their potential benefits, limitations and future prospects to formulate successful eradication strategies.
Nanoemulsion Formulation of Ocimum gratissimum Essential Oil and Its Antifungal Activity Against Penicillium digitatum
Authors: Mahajan Rishabh , Tandon Ritu , Kalia Anu , Mahajan Bal Vipan Chander
Published: November 2021

Plant-derived essential oils and extracts are known to be effective against many microorganisms. The essential oil obtained from fresh leaves of Ocimum gratissimum possessed promising antifungal activity against Penicillium digitatum. The antifungal potential of O.
gratissimum essential oil can be markedly improved with the use of nanotechnology. O. gratissimum essential oil based nanoformulations were prepared using non-ionic surfactant and water by ultrasonication. The process was optimized for parameters such as surfactant concentration
and sonication time to achieve minimum droplet diameter with high physical stability. Stable O. gratissimum essential oil nanoemulsions were obtained for 1:1 ratio (v/v) of essential oil and surfactant with mean droplet diameter of 259.4 nm for 10 min sonication time. Essential oil
and all nanoemulsions were evaluated for their antifungal activity against P. digitatum of kinnow fruit by poisoned food technique. The nanoemulsion (1:1, 10 min) showed the highest growth inhibition (1 × 104 CFU ml−1, 96%) against P. digitatum
followed by pure oil (13 × 104 CFU ml−1, 85%) on 15th day of incubation. Scanning electron and optical microscopy results further revealed stronger suppressive activity of O. gratissimum essential oil nanoemulsions for spore germination and hyphal elongation
of P. digitatum than pure oil.
Nano-Enabled Pesticides in Agriculture: Budding Opportunities and Challenges
Authors: Sushil Ahlawat , Kamla Malik , Nisha Kumari , Karmal Malik , Sandeep Arya
Published: November 2021

Nano enabled plant protectant is an advancement approach to deal with the difficulties of dosedependent toxicity, solubility, degradation, leaching and health issues of conventional pesticides. The main idea behind incorporation of nanoformulation is their controlled delivery and release
to prevent premature degradation of active ingredient under the influence of changing environment conditions. Nanocarriers (nanocapsules, nanospheres, micelles, nanogels, nanoemulsions, nanodispersion and inorganic material) alters the properties of active ingredients and provide controlled
release kinetics with, better dissolvability, low dose, enhanced stability and long lasting pest-control efficiency. This review critically assesses the incredible potential of various nanocarriers, their methods of preparation and biological effectiveness. It additionally features the potential
and issues with nanoformulations of botanical insecticides and essential oils. The study also accounts performances of nano-enabled products, their challenges with respect to field application and assessment of new environmental risks.
Absorption of Carbon-13 Labelled Fullerene (C60) on Rice Seedlings and Effect of Phytohormones on Growth
Authors: Guo Ke-Rui , Adeel Muhammed , Hu Feng , Xiao Zhi-Zhao , Wang Ke-Xiang , Hao Yi , Rui Yu-Kui , Chang Xue-Ling
Published: November 2021

This study explores the effects of nanomaterials in rice seedlings using carbon 13 (13C)-labelled fullerene (C60). The experiment consisted of three groups, one CK and two nano particle groups with C60: 100 mg L−1 and 20 mg L−1.
Mass spectrometry indicated higher 13C abundances in the nano particle groups compared with the CK. The 13C abundances of the 20 mg L−1 group, 100 mg L−1 group and CK were 1.0718%, 1.0715% and 1.0704%, respectively. We analyzed phytohormone
concentrations in the rice at harvest time. Decreases in the concentrations of dihydrozeatin riboside (23% and 18% for the 20 mg L−1 and 100 mg L−1 group, respectively), zeatin riboside (23% and 18%, respectively), abscisic acid (11.1% and 12.7%, respectively),
brassinolide (12.9% and 13.1%, respectively) and gibberellic acid 4 (12.9% and 13.1%, respectively) were observed compared with the CK. The gibberellic acid 3 concentrations in the 20 mg L−1 and 100 mg L−1 group increased by 12% and 7% compared with the CK,
respectively. The methyl jasmonate concentration in the 100 mg L−1 group increased by 19.4% compared with the CK. The concentration of indole-3-acetic acid in the 100 mg L−1 group decreased by 13.5% compared with the CK. There was no change on isopentenyl
adenosine concentration. This study indicates that C60 can be absorbed by rice and its effect on the growth of rice via phytohormones, including ABA, IAA, IPA, BR, GA3, GA4, DHZR, ZR and JA-ME. The results showed that, under the treatments of C60
NMs, the contents of some phytohormone in rice were decreased in comparison with CK.
Magnetic α-Fe2O3/Fe3O4 Heterostructure Nanorods: Fabrication and Cytotoxicity to A549 Cells
Authors: Pan Shuai , Yin Rui-Tong , Huang Wei , Li You , Yu Lu-Lu , Liu Rui-Jiang
Published: November 2021

The magnetic α-Fe2O3/Fe3O4 heterostructure nanorods were fabricated by an alcohol-solution direct combustion method. The influence of the calcination temperature on the composition and properties of the nanorods was investigated.
When the calcination temperature was not greater than 400 °C, the magnetic α-Fe2O3/Fe3O4 heterostructure nanorods were obtained, and the saturation magnetization (Ms) of the magnetic α-Fe2O3/Fe3O4
heterostructure nanorods decreased with the calcination temperature increasing from 250 °C to 400 °C; when the calcination temperature was equal or greater than 450 °C, α-Fe2O3 nanorods were obtained. In addition, the effects of nanorods’ concentration, nanorods’
constituent, incubation time and magnetic field on A549 cytotoxicity were investigated. The cytotoxicity of the heterostructure nanorods appeared time-dependent and concentration-dependent, and the magnetic field could enhance the cytotoxicity of nanorods to A549.
From Atmospheric Waves to Heatwaves: A Waveguide Perspective for Understanding and Predicting Concurrent, Persistent, and Extreme Extratropical Weather
Authors: White Rachel H. , Kornhuber Kai , Martius Olivia , Wirth Volkmar
Published: November 2021

A notable number of high-impact weather extremes have occurred in recent years, often associated with persistent, strongly meandering atmospheric circulation patterns known as Rossby waves. Because of the high societal and ecosystem impacts, it is of great interest to be able to accurately project how such extreme events will change with climate change, and to predict these events on seasonal-to-subseasonal (S2S) time scales. There are multiple physical links connecting upper-atmosphere circulation patterns to surface weather extremes, and it is asking a lot of our dynamical models to accurately simulate all of these. Subsequently, our confidence in future projections and S2S forecasts of extreme events connected to Rossby waves remains relatively low. We also lack full fundamental theories for the growth and propagation of Rossby waves on the spatial and temporal scales relevant to extreme events, particularly under strongly nonlinear conditions. By focusing on one of the first links in the chain from upper-atmospheric conditions to surface extremes—the Rossby waveguide—it may be possible to circumvent some model biases in later links. To further our understanding of the nature of waveguides, links to persistent surface weather events and their representation in models, we recommend exploring these links in model hierarchies of increasing complexity, developing fundamental theory, exploiting novel large ensemble datasets, harnessing deep learning, and increased community collaboration. This would help increase understanding and confidence in both S2S predictions of extremes and of projections of the impact of climate change on extreme weather events.
A Note on the Depth of Sidelobe Contamination in Acoustic Doppler Current Profiles
Authors: Lentz S. J. , Kirincich A. , Plueddemann A. J.
Published: November 2021

Acoustic Doppler current profilers (ADCP) do not provide reliable water velocity measurements near the sea surface or bottom because acoustic sidelobe reflections from the boundary contaminate the Doppler velocity measurements. The apparent depth of the center of the sidelobe reflection is zsl = ha[1 − cos(θ)], where ha is the distance from the ADCP acoustic head to the sea surface and θ is the ADCP beam angle. However, sidelobe contamination extends one and a half ADCP bins below zsl as the range gating of the acoustic return causes overlap between adjacent ADCP bins. Consequently, the contaminated region z < zsl + 3Δz/2 is deeper than traditionally suggested, with a dependence on bin size Δz. Direct observations confirming both the center depth of the sidelobe reflection and the depth of contamination are presented for six bottom-mounted, upward-looking ADCPs. The sidelobe reflection is isolated by considering periods of weak wind stresses when the sea surface is smooth and there is nearly perfect reflection of the main beams away from the ADCP and hence little acoustic return from the main beams to the ADCP.
Factors Contributing to Guilty Plea Wrongful Convictions: A Quantitative Analysis of Australian Appellate Court Judgments
Authors: Nash Caitlin , Dioso-Villa Rachel , Porter Louise
Published: November 2021

Criminal defendants can face significant pressures to plead guilty, but wrongful conviction scholarship has largely overlooked the study of guilty pleas. This study content analyzed 139 Australian appellate court judgments in which a guilty plea conviction was overturned, investigating the types of errors involved in these convictions, and the stage of the criminal justice process at which the errors occurred. The findings revealed that errors occurred during the police investigation, pretrial preparations, and formal court procedures, with the most frequent errors involving incorrect or inappropriate charges, inadequate legal representation, and the courts erroneously accepting a guilty plea. The findings raise important implications regarding the adequacy of safeguards to ensure guilty pleas are appropriate or factually and legally accurate.
Young Enough for the Maximum: Discretionary Release Decisions in the Post-Miller Era
Authors: Kokkalera Stuti S. , Singer Simon I. , Cehreli Damla
Published: November 2021

Based on U.S. Supreme Court decisions recognizing adolescence, we examined the likelihood of parole in one state for a population of candidates whose ages ranged from 14 to 21 at time of offense. Logistic regressions tested age on release, controlling for offense, adolescence-related, and rehabilitative variables. Contrary to expectations, a parole candidate’s age at time of offense is not associated with release nor did age interact with culpability and rehabilitation measures. Instead, victim and prosecutorial opposition is related to a lower likelihood of release where the opposition effect is greater for those 18 years and older at time of offense. These findings reiterate the need for comparative research on parole decision-making as it may vary by time and place.
Developing Teams in a Virtual Environment: A Generative Approach
Authors: Pavez Ignacio , Neves Ernesto
Published: November 2021

At the beginning of 2020, the operations of the Finance Hub of the Americas (FHoA) at pharmaceutical company GlaxoSmithKline (GSK) were suddenly forced to shift entirely from face-to-face to remote work. To handle this challenge, an FHoA team started a team development process aimed at strengthening teamwork in virtual environments. The intervention was grounded in the principles of generative leadership and dialogic organization development. Through a scholar-practitioner collaboration that focused on identifying the drivers of the successful transition to remote work, we build a three-step process of team development using the metaphor of organic growth: (1) sowing, (2) nurturing, and (3) flourishing. Using GSK's example, we illustrate how this process became a simple but powerful strategy to help teams thrive in a virtual environment. The core of the process uses generative questions to configure a structured but adaptable process that can be easily implemented in different contexts and situations.
Theoretical modeling of longitudinal piezoelectric characteristic for cellular polymers
Authors: Najihi Ikrame , Ennawaoui Chouaib , Hajjaji Abdelowahed , Boughaleb Yahia
Published: November 2021

Efficient energy harvesting is a difficult challenge that consists in the development of systems allowing charging autonomous and low-power devices. In addition to traditional piezoelectric polymers, mono-crystals, and ceramics, cellular electrets offer consistent solutions by converting wasted vibration energy from the environment to usable electrical energy. This paper presents an electromechanical model to study the energy harvesting capability of cellular polymers. The theoretical study models the response of these materials to investigate the effect of different parameters on the piezoelectric coefficient d33, particularly. The model considers the percentage of porosity, surface charge density in each polymer–gas surface, the properties of the polymer matrix and the gas encapsulated in the pores, and the Young’s modulus of the porous film. For poly(ethylene-co-vinyl acetate), the results showed that the piezoelectric performance of the film declines with the increase of the film thickness. However, the variation of the d33 as a function of the percentage of porosity is exponential and can achieve 4.24 pC/N for a porosity of 80%. Compared to a previously published experiment, the theoretical results have proven a good agreement with only 3.3% error.
Complete remission of combined pulmonary large cell neuroendocrine carcinoma: a case report
Authors: Xu Jian , Feng Qi , Chen Yong , Liu Xiu-lan , Jiang Ou
Published: November 2021

Pulmonary large cell neuroendocrine carcinoma (LCNEC), which accounts for approximately 1% of all lung cancers, is a rare and highly aggressive malignancy with a poor prognosis. Therefore, it is important to devise an effective treatment strategy. In the treatment of locally advanced complex LCNEC, it is unique to first administer radiotherapy combined with albumin-bound paclitaxel plus carboplatin, followed by durvalumab for immune maintenance treatment after concurrent radiotherapy and chemotherapy to achieve complete remission. We report a 54-year-old man who smoked and who felt chest tightness for 2 weeks and was diagnosed as having combined pulmonary LCNEC. For patients with locally advanced pulmonary LCNEC, chemoradiotherapy increases overall survival. After surgical resection and chemoradiotherapy, our patient achieved complete remission. Durvalumab was then started to consolidate the treatment. After six courses of immune maintenance therapy, the patient developed grade 2 immune-related pneumonitis and took prednisone orally until the symptoms resolved, and then reached complete remission again. The patient achieved complete remission, which was a challenge with this rare carcinoma, through albumin-bound paclitaxel plus platinum-based chemotherapy combined with radiotherapy and durvalumab for immune maintenance therapy. This approach may provide a treatment option for locally advanced combined pulmonary LCNEC.
“Everything Is in the Lab Book”: Multimodal Writing, Activity, and Genre Analysis of Symbolic Mediation in Medical Physics
Authors: Doody Sara , Artemeva Natasha
Published: November 2021

Writing and genre scholarship has become increasingly attuned to how various nontextual features of written genres contribute to the kinds of social actions that the genres perform and to the activities that they mediate. Even though scholars have proposed different ways to account for nontextual features of genres, such attempts often remain undertheorized. By bringing together Writing, Activity, and Genre Research, and Multimodal Interaction Analysis, the authors propose a conceptual framework for multimodal activity-based analysis of genres, or Multimodal Writing, Activity, and Genre (MWAG) analysis. Furthermore, by drawing on previous studies of the laboratory notebook (lab book) genre, the article discusses the rhetorical action the genre performs and its role in mediating knowledge construction activities in science. The authors provide an illustrative example of the MWAG analysis of an emergent scientist’s lab book and discuss its contributions to his increasing participation in medical physics. The study contributes to the development of a theoretically informed analytical framework for integrative multimodal and rhetorical genre analysis, while illustrating how the proposed framework can lead to the insights into the sociorhetorical roles multimodal genres play in mediating such activities as knowledge construction and disciplinary enculturation.