bluuebunny/crossref_metadata_2025 huggingface dataset:
Shear Behavior of RC Beams Strengthened by External Vertical Prestressing Rebar
Authors: Li Ying , Wu Meizhong , Wang Weiqi , Xue Xingwei
Published: March 2021

Shear design is an important part of structural design. External vertical prestressing rebars (EVPRs) have proven to be an effective way to enhance structural shear resistance. The objectives of this study are to simulate EVPR strengthening of concrete beams using a nonlinear three‐dimensional finite element model and to explore its shear enhancement features under different EVPR stirrup ratios, vertical compressive stress degrees, and optimal arrangements of EVPRs. Concrete, common reinforced bars, and EVPRs use solid, steel, and truss elements, respectively. In addition, the total strain crack model is used to characterise the concrete. The results indicate that the EVPR stirrup ratio can reduce the diagonal crack width and improve the shear capacity, and the vertical compressive stress degree can effectively control crack development in the initial loading. A “small‐area EVPR dense arrangement” is the recommended EVPR configuration method. Both experiments and numerical analyses show that EVPRs can effectively improve the shear performance of concrete.
Tone Recognition Database of Electronic Pipe Organ Based on Artificial Intelligence
Authors: Zhao Shuyi
Published: March 2021

In the past few decades, artificial intelligence technology has experienced rapid development, and its application in modern industrial systems has grown rapidly. This research mainly discusses the construction of a database of electronic pipe organ tone recognition based on artificial intelligence. The timbre synthesis module realizes the timbre synthesis of the electronic pipe organ according to the current timbre parameters. The audio time domain information (that is, the audio data obtained by file analysis) is framed and windowed, and fast Fourier transform (FFT) is performed on each frame to obtain the frequency domain information of each frame. The harmonic peak method based on improved confidence is used to identify the pitch, obtain the fundamental tone of the tone, and calculate its multiplier. Based on the timbre parameters obtained in the timbre parameter editing interface, calculate the frequency domain information of the synthesized timbre of each frame, and then perform the inverse Fourier transform to obtain the time domain waveform of each frame; connect the time domain waveforms of different frames by the cross-average method to obtain the time-domain waveform of the synthesized tone (that is, the audio data of the synthesized tone). After collecting the sound of the electronic pipe organ, the audio needs to be denoised, and the imported audio file needs to be parsed to obtain the audio data information. Then, the audio data are frequency-converted and the timbre characteristic information is analyzed; the timbre parameters are obtained through the human-computer interaction interface based on artificial intelligence, and the timbre of the electronic pipe organ is generated. If the timbre effect is not satisfactory, you can re-edit the timbre parameters through the human-computer interaction interface to generate timbre. During the experiment, the overall recognition rate of 3762 notes and 286 beats was 88.6%. The model designed in this study can flexibly generate electronic pipe organ sound libraries of different qualities to meet the requirements of sound authenticity.
Study of the Relationship between ICU Patient Recovery and TCM Treatment in Acute Phase: A Retrospective Study Based on Python Data Mining Technology
Authors: Wu Zhiqun , Wang Xue , Pan Renlong , Huang Xiufu , Li Yuhan
Published: March 2021

Background. Data was mined with the help of an artificial intelligence system based on Python, data was collected, and a database was established using a Python crawler, and the relationship between the outcome of neurosurgery ICU patients and treatment using traditional Chinese medicine was ascertained through data management and statistical processing. Method. The source data cases (n = 2237) were selected. By following the experimental design, data (n = 739) were obtained through artificial intelligence processing, including n = 480 in the group with traditional Chinese medicine treatment and n = 259 in the group without traditional Chinese medicine treatment. An evaluation was carried out using characteristics of patents’ ICU stays and summated rating scales. Results. There were statistical differences in 5 evaluation items (

P
<
0.05

), and other comparison items also showed data with results favoring the outcomes in the intervention group using traditional Chinese medicine. Discussion. Traditional Chinese medicine as an alternative medical protocol effectively alleviates the stress and treatment fatigue brought about by modern medicine. Artificial intelligence data mining is a favorable medium to quantify this. Python will play a greater role in future clinical research because of its own characteristics.
Giant Abdominal Lipoma in Adult
Authors: Cinar Ozcan Nihal , Edizsoy Akay , Colak Tahsin
Published: March 2021

Lipomas arising from the omentum are extremely rare in adults. Omental lipomas are typically asymptomatic, but very large ones may cause nonspecific abdominal symptoms and discomfort. Rarely they can cause omental torsion and present with an acute abdomen. We report a 41-year-old female patient with a giant lipoma (

40
×
26
×
8
 
cm

and 11,520 g) who presented with mild abdominal discomfort. Workup included abdominal ultrasound (USG) and magnetic resonance imaging (MRI). Surgical resection was performed without complication. No recurrence was observed during 4-year follow-up.
Pancreaticopleural Fistula as a Rare Cause of Both-Sided Pleural Effusion
Authors: Chmielecki Jan , Kościński Tomasz , Banasiewicz Tomasz
Published: March 2021

A pancreaticopleural fistula is a rare cause of pleural effusion. It is a complication of chronic or acute pancreatitis. It is rarely formed to the right or both pleural cavities. Diagnosis and proper treatment often turn out to be difficult and require the cooperation of a multidisciplinary team. The authors present the case of a 59-year-old patient treated for recurrent pleural effusion of unknown origin, first to the left and then to the right pleural cavity. After many months of treatment, the diagnosis of a pancreaticopleural fistula was made. The patient underwent surgery, which finally led to a successful complete recovery. Pancreaticopleural fistula should always be considered in patients with pleural effusion of unknown origin.
New Benzoxazole Derivatives as Antiprotozoal Agents: In Silico Studies, Synthesis, and Biological Evaluation
Authors: Abdelgawad Mohamed A. , Al-Sanea Mohammad M. , Zaki Mohamed A. , Mohamed Enas I. A. , Khan Shabana I. , Tekwani Babu L. , Chittiboyina Amar G , Khan Ikhlas A , Al-Warhi Tarfah , Aljaeed Nada , Alotaibi Ohoud J. , Alkhaldi Abdulsalam A. M. , Elshemy Heba A. H.
Published: March 2021

Background. Benzoxazole derivatives have different biological activities. In pursuit of designing novel chemical entities with antiprotozoal and antimicrobial activities, benzoxazolyl aniline was utilized as a privileged scaffold of a series of (3-benzoxazole-2-yl) phenylamine derivatives, 3-benzoxazoloyl acetamide, and butyramide derivatives. Methods. These novel analogs were synthesized in straightforward simple chemistry without any quantitative chromatographic separations in reasonable yields. The biological evaluation of all target compounds as potential antimalarial, antileishmanial, antitrypanosomal, and antimicrobial agents was performed by various well-established cell-based methods. Results. Compounds 6d and 5a showed promising biological screening data. The amidation of 3-benzoxazolyl aniline 1 with the chloroacetyl functional group resulted in a good antimalarial activity and showed moderate inhibitory activities against leishmanial and trypanosomal spp. Moreover, chloroacetyl functionalization of benzoxazolyl aniline serves as a good early goal for constructing and synthesizing new antimicrobial and antiprotozoal agents. The molecular docking study rationalizes the relative inhibitory activity of compound 5a as an antimalarial agent with the deregulation of PfPNP activity which has emerged as a major mechanism of these targets.
A Routing Algorithm for the Sparse Opportunistic Networks Based on Node Intimacy
Authors: Xu Gang , Wang Xinyue , Zhang Na , Wang Zhifei , Yu Lin , He Liqiang
Published: March 2021

Opportunistic networks are becoming more and more important in the Internet of Things. The opportunistic network routing algorithm is a very important algorithm, especially based on the historical encounters of the nodes. Such an algorithm can improve message delivery quality in scenarios where nodes meet regularly. At present, many kinds of opportunistic network routing algorithms based on historical message have been provided. According to the encounter information of the nodes in the last time slice, the routing algorithms predict probability that nodes will meet in the subsequent time slice. However, if opportunistic network is constructed in remote rural and pastoral areas with few nodes, there are few encounters in the network. Then, due to the inability to obtain sufficient encounter information, the existing routing algorithms cannot accurately predict whether there are encounters between nodes in subsequent time slices. For the purpose of improving the accuracy in the environment of sparse opportunistic networks, a prediction model based on nodes intimacy is proposed. And opportunistic network routing algorithm is designed. The experimental results show that the ONBTM model effectively improves the delivery quality of messages in sparse opportunistic networks and reduces network resources consumed during message delivery.
HPLC/MS-MS Identification of Oak Quercus aegilops Root Tannins
Authors: Amr Ayed S. , Ahmad Mousa N. , Zahra Jalal A. , Abdullah Mai A.
Published: March 2021

Tannins are natural polyphenolic compounds widely distributed in the plant kingdom in the leaves, bark, fruits, and other parts. They have various biological functions in humans and animals and are used mainly in the pharmaceutical and cosmetic industries. The aim of this work was to isolate, extract, purify, and identify the tannins from the root bark of a common oak tree (Quercus aegilops L.) in Jordan and around the Mediterranean. The results showed that at least one form of ellagitannin (ellagic acid ester), quercitrin, afzelechin, valoneic acid, trigalloyl glucose, and catechin was identified in addition to two unidentified compounds. Results of this work can help in developing an ESI MS/MS search library for the constituents of the tannins of oak (Quercus aegilops L.) root bark.
Microbiome Analysis of More Than 2,000 NHS Bowel Cancer Screening Programme Samples Shows the Potential to Improve Screening Accuracy
Authors: Young Caroline , Wood Henry M. , Fuentes Balaguer Alba , Bottomley Daniel , Gallop Niall , Wilkinson Lyndsay , Benton Sally C. , Brealey Martin , John Cerin , Burtonwood Carole , Thompson Kelsey N. , Yan Yan , Barrett Jennifer H. , Morris Eva J.A. , Huttenhower Curtis , Quirke Philip
Published: March 2021

Purpose:

There is potential for fecal microbiome profiling to improve colorectal cancer screening. This has been demonstrated by research studies, but it has not been quantified at scale using samples collected and processed routinely by a national screening program.

Experimental Design:

Between 2016 and 2019, the largest of the NHS Bowel Cancer Screening Programme hubs prospectively collected processed guaiac fecal occult blood test (gFOBT) samples with subsequent colonoscopy outcomes: blood-negative [n = 491 (22%)]; colorectal cancer [n = 430 (19%)]; adenoma [n = 665 (30%)]; colonoscopy-normal [n = 300 (13%)]; nonneoplastic [n = 366 (16%)]. Samples were transported and stored at room temperature. DNA underwent 16S rRNA gene V4 amplicon sequencing. Taxonomic profiling was performed to provide features for classification via random forests (RF).

Results:

Samples provided 16S amplicon-based microbial profiles, which confirmed previously described colorectal cancer–microbiome associations. Microbiome-based RF models showed potential as a first-tier screen, distinguishing colorectal cancer or neoplasm (colorectal cancer or adenoma) from blood-negative with AUC 0.86 (0.82–0.89) and AUC 0.78 (0.74–0.82), respectively. Microbiome-based models also showed potential as a second-tier screen, distinguishing from among gFOBT blood-positive samples, colorectal cancer or neoplasm from colonoscopy-normal with AUC 0.79 (0.74–0.83) and AUC 0.73 (0.68–0.77), respectively. Models remained robust when restricted to 15 taxa, and performed similarly during external validation with metagenomic datasets.

Conclusions:

Microbiome features can be assessed using gFOBT samples collected and processed routinely by a national colorectal cancer screening program to improve accuracy as a first- or second-tier screen. The models required as few as 15 taxa, raising the potential of an inexpensive qPCR test. This could reduce the number of colonoscopies in countries that use fecal occult blood test screening.
Toward More Complete Prognostication for Patients with Clonal Hematopoiesis
Authors: Spitzer Barbara , Levine Ross L.
Published: March 2021

The study of clonal hematopoiesis is rapidly evolving, with the highest prevalence in aging populations and wide-ranging implications for health and disease, including an increased risk of subsequent myeloid malignancies and cardiovascular disease. In their article, Feusier and colleagues report on an expanded driver mutation list for capture of higher-risk clonal hematopoiesis mutations implicated in leukemia transformation. They also describe the prevalence of clonal hematopoiesis in several additional large studies, including, most importantly, in the pediatric context, which has not yet been extensively studied with respect to clonal hematopoiesis and clonal hematopoiesis–related sequelae.

See related article by Feusier et al., p. 226.
Kynurenine Relaxes Arteries of Normotensive Women and Those With Preeclampsia
Authors: Worton Stephanie A. , Pritchard Harry A.T. , Greenwood Susan L. , Alakrawi Mariam , Heazell Alexander E.P. , Wareing Mark , Greenstein Adam , Myers Jenny E.
Published: March 2021

Rationale:

Activation of the kynurenine pathway of tryptophan catabolism by infection and inflammation contributes to the development of systemic hypotension. Commercially-available kynurenine has direct vasorelaxant effects on arteries from several species and reduces systemic blood pressure when administered to normotensive or hypertensive rats.

Objectives:

To determine whether kynurenine promotes relaxation of human resistance arteries from normotensive and hypertensive pregnant women and to identify the vascular mechanism of its effects.

Methods and Results:

In isolated omental and myometrial resistance arteries from normotensive pregnant women, kynurenine (1 mmol/L) significantly reduced U46619-induced constriction (omentum N=14,
P
=2.4×10
−3
; myometrium N=21–25,
P
=2.6×10
−4
) and relaxed preconstricted arteries (N=53,
P
=1.0×10
−11
; N=20,
P
=8.8×10
−3
). Vasorelaxation persisted following endothelium removal (N=7,
P
=1.6×10
−4
) but was completely prevented by inhibition of large-conductance Ca
2+
-activated K
+
channels (BK
Ca
) channels with iberiotoxin (N=9,
P
=5.7×10
−4
) or paxilline (N=10,
P
=2.1×10
−17
). Accordingly, in isolated vascular smooth muscle cells from omental arteries, kynurenine increased the BK
Ca
current (n=5–8,
P
=0.022) and the amplitude of spontaneous transient outward currents (n=6,
P
=0.031) but did not affect spontaneous transient outward current frequency. Kynurenine also increased Ca
2+
spark frequency of pressurized omental arteries (n=8,
P
=0.031). Vasorelaxant effects of kynurenine persisted following inhibition of ryanodine receptors (N=7,
P
=0.48) but were moderately reduced by inhibition of adenylate cyclase (N=9,
P
=0.024). In arteries from women with preeclampsia, kynurenine similarly attenuated vasoconstriction (N=15,
P
=1.3×10
−5
) and induced BK
Ca
-mediated vasodilation (N=16,
P
=2.0×10
−4
). Vasorelaxation in response to kynurenine and a specific BK
Ca
activator, NS11021, was absent in fetal-derived placental resistance arteries in normal pregnancy and preeclampsia.

Conclusions:

Kynurenine dilates systemic arteries from multiple territories via BK
Ca
activation. Notably, the vasorelaxatory capacity of kynurenine is preserved in preeclampsia, suggesting this approach may have translational potential for the treatment of hypertension in pregnancy. The data warrant further investigation of the potential to exploit this endogenous vasorelaxant as a new treatment for hypertensive pathologies.
The Left Angular Gyrus Is Causally Involved in Context-dependent Integration and Associative Encoding during Narrative Reading
Authors: Branzi Francesca M. , Pobric Gorana , Jung JeYoung , Lambon Ralph Matthew A.
Published: March 2021

The role of the left angular gyrus (AG) in language processing remains unclear. In this study, we used TMS to test the hypothesis that the left AG causally supports the processes necessary for context-dependent integration and encoding of information during language processing. We applied on-line TMS over the left AG to disrupt the on-line context-dependent integration during a language reading task, specifically while human participants integrated information between two sequentially presented paragraphs of text (“context” and “target” paragraphs). We assessed the effect of TMS on the left AG by asking participants to retrieve integrated contextual information when given the target condition as cue in a successive memory task. Results from the memory task showed that TMS applied over the left AG during reading impaired the formation of integrated context-target representation. These results provide the first evidence of a causal link between the left AG function, on-line information integration, and associative encoding during language processing.
Dopamine Precursor Depletion in Healthy Volunteers Impairs Processing of Duration but Not Temporal Order
Authors: Chassignolle Morgane , Jovanovic Ljubica , Schmidt-Mutter Catherine , Behr Guillaume , Giersch Anne , Coull Jennifer T.
Published: March 2021

Studies in animals and humans have implicated the neurotransmitter dopamine in duration processing. However, very few studies have examined dopamine's involvement in other forms of temporal processing such as temporal order judgments. In a randomized within-subject placebo-controlled design, we used acute phenylalanine/tyrosine depletion (APTD) to reduce availability of the dopamine precursors tyrosine and phenylalanine in healthy human volunteers. As compared to a nutritionally balanced drink, APTD significantly impaired the ability to accurately reproduce interval duration in a temporal reproduction task. In addition, and confirming previous findings, the direction of error differed as a function of individual differences in underlying dopamine function. Specifically, APTD caused participants with low baseline dopamine precursor availability to overestimate the elapse of time, whereas those with high dopamine availability underestimated time. In contrast to these effects on duration processing, there were no significant effects of APTD on the accuracy of discriminating the temporal order of visual stimuli. This pattern of results does not simply represent an effect of APTD on motor, rather than perceptual, measures of timing because APTD had no effect on participants' ability to use temporal cues to speed RT. Our results demonstrate, for the first time in healthy volunteers, a dopaminergic dissociation in judging metrical (duration) versus ordinal (temporal order) aspects of time.
Revisiting the Syntax of Monsters in Uyghur
Authors: Major Travis
Published: March 2021

Shklovsky and Sudo (2014) propose a syntactic analysis of Uyghur indexical shift, a process by which embedded indexicals such as the counterparts of you and I are interpreted relative to the reported context, as opposed to the present discourse context. Introducing novel data, I offer an alternative analysis: namely, that there are two distinct types of tensed embedded clause that differ in clause structure, size, and the functional heads present within the structure. I correlate these properties with case, agreement, and indexical shift.
Jung’s and Groddeck’s Analytic Practice
Authors: Balenci Marco
Published: March 2021

This paper shows that Georg Groddeck and Carl Gustav Jung shared a common cultural background, in which Carl Gustav Carus’s theory of the psyche was preeminent. Accordingly, they emphasized symbolization and unconscious creativity. These aspects affected their clinical work, aimed at pioneering therapies: Jung with schizophrenics, Groddeck treating physical diseases. They overcame the limits of the psychoanalysis of their time and, going beyond neurosis, discovered the pre-Oedipal period and the fundamental role of mother-child relationship. While Freud’s technique was based on a one-person paradigm, both Jung and Groddeck considered analytic therapy as a dialectical process, ushering in a two-person paradigm. Therefore, they did not use the couch; a setting that is assessed in the light of recent research on mirror neurons. It is also highlighted that the analytic groups influenced by Groddeck and Jung have developed similar ideas in both theory and technique; a fact that may induce further studies on the history of depth psychology.
Te genus Siphula Fr. (Icmadophilaceae, Lichenized Fungi) in Venezuela
Authors: MARCANO VICENTE
Published: March 2021

Seven species of Siphula Nylander have been found in Venezuela (including Páramos and Guayana Highlands). Three species from the Guayana Highlands viz. S. chimantensis V. Marcano, S. subsimplex V. Marcano and S. subpteruloides V. Marcano are described as new to science. A key to the species is presented together with data on morphology, chemistry, variation, taxonomy, habitat and distribution. The data indicate that of the taxa reported from Venezuela, four are known only from the Guayana Highlands, one is known only from the neotropics, and two are pantropical. The high concentration of Siphula species seen in the Guayana Highlands suggests that this region constitutes an important centre for speciation and endemism for the genus.
Modified Data Storage and Replication Mechanism with Frequent Use-Case Based Indexing
Authors: Selvaraj P. , Kannan Venkatesh , Voisin Bruno
Published: March 2021

The real time applications demands high speed and reliable data access from the remote database. An effective logical data management strategy that handles simultaneous connections with better performance negotiation is inevitable. This work considers an e-health care application that
proposes MongoDB based modified indexing and performance tuning methods. To cope with certain high frequency use case and its performance mandates, a flexible and efficient logical data management may be preferred. By analysing the data dependency, data decomposition concerns and the performance
requirements of the specific use case of the medical application, a logical schema may be customized on an ala-carte basis. This work focused on the flexible logical data modeling schemes and its performance factors of the NoSql DB. The efficiency of unstructured data base management in storing
and retrieving the e-health care data was analysed with a web based tool. To enable faster data retrieval and query processing over the distributed nodes, a Spark based storage engine was built on top of the MongoDB based data storage management. With Spark tool, the database has been made
distributed as master–slave structures with suitable data replication mechanisms. In such distributed database the fail-over also implemented with the suitable replication mechanism. This work considered MongoDB based flexible schema modeling and Spark based distributed computation with
multiple chunks of data. The flexible data modeling scheme with MongoDB with the on-demand Spark based computation framework was proposed. To facilitate the eventual consistency, scalability aspects of the e-health care applications, use case based indexing was proposed. With the effective
data management, faster query processing the horizontal scalability has been increased. The overall efficiency and scalability of the proposed logical data management approach was analysed. Through the simulation studies, the proposed approach has been claimed to boost the performance of the
bigdata based application to a considerable extent.
Nelder Mead with Grasshopper Optimization Algorithm for Node Localization in Wireless Sensor Networks
Authors: Santhosh M. , Sudhakar P.
Published: March 2021

Node localization in wireless sensor network (WSN) becomes essential to calculate the coordinate points of the unknown nodes with the use of known or anchor nodes. The efficiency of the WSN has significant impact on localization accuracy. Node localization can be considered as an optimization
problem and bioinspired algorithms finds useful to solve it. This paper introduces a novel Nelder Mead with Grasshopper Optimization Algorithm (NMGOA) for node localization in WSN. The Nelder-Mead simplex search method is employed to improve the effectiveness of GOA because of its capability
of faster convergence. At the beginning, the nodes in WSN are arbitrarily placed in the target area and then nodes are initialized. Afterwards, the node executes the NMGOA technique for estimating the location of the unknown nodes and become localized nodes. In the subsequent round, the localized
nodes will be included to the collection of anchor nodes to perform the localization process. The effectiveness of the NMGOA model is validated using a series of experiments and results indicated that the NMGOA model has achieved superior results over the compared methods.
Analysis of Plant Disease Detection and Classification Models: A Computer Vision Perspective
Authors: Jayaprakash K. , Balamurugan S. P.
Published: March 2021

Presently, rapid and precise disease identification process plays a vital role to increase agricultural productivity in a sustainable manner. Conventionally, human experts identify the existence of anomaly in plants occurred due to disease, pest, nutrient deficient, weather conditions.
Since manual diagnosis process is a tedious and time consuming task, computer vision approaches have begun to automatically detect and classify the plant diseases. The general image processing tasks involved in plant disease detection are preprocessing, segmentation, feature extraction and
classification. This paper performs a review of computer vision based plant disease detection and classification techniques. The existing plant disease detection approaches including segmentation and feature extraction techniques have been reviewed. Additionally, a brief survey of machine
learning (ML) and deep learning (DL) models to identify plant diseases also takes place. Furthermore, a set of recently developed DL based tomato plant leaf disease detection and classification models are surveyed under diverse aspects. To further understand the reviewed methodologies, a detailed
comparative study also takes place to recognize the unique characteristics of the reviewed models.
A Real and Accurate Fake Product Detection System and Generate Original Reviews Using Data Mining Mechanism
Authors: Bhargavi Ch. V. , Mani G. , Jyothi G. , Rao K. Venkat , Lydia E. Laxmi
Published: March 2021

Most of the people requires genuine information about the online product. Before spending their economy on particular product can analyze the various reviews in the website. In this scenario, they did not identify whether the product may be fake or genuine. In general, some reports
in the websites are good, company technical people itself add these for making the product famous. These people belong to media and social organization teams, they give reviews with a good rating by their own firm. Online purchasers did not identify the fake product because of this falsification
in the reviews of the website. In this research,the SVM classification mechanism has been used for detect the fake reviews by using IP address. This implementation helpful for users find out the correct review of online product. In this accuracy is improved by 98.79%, F1-Score increases by
10%.
Light Weight Cryptography Based Encrypted Multiple Secret Share Creation for Biometrics Images
Authors: Gunasekaran Elavarasi , Muthuraman Vanitha
Published: March 2021

Owing to the rapid growth of information technologies, a rising need for cybersecurity and biometric technologies is increasingly evolving. Biometrics image protection is an important problem as digital images and medical details are distributed via public networks. This research work
proposed a threshold-based share creation scheme for Biometrics images. To enhance the security level of the shares, each shares are encrypted by Light Weight Cryptography (LWC)-Stream Cipher method. To increase the stream cipher encryption efficiency, optimal keys are selected by Ant Lion
Optimization (ALO) technique. The benefit of consuming stream ciphers is that the speed of execution is maximum over block cipher and less complex. The benefit of the suggested stream cipher approach is that the decoding of the keys in the keystream and the characters in the plain text denotes
decrypted biometrics image will improve device reliability. From the implementation results proposed model achieves the maximum PSNR with the security of Biometrics images, compared to other existing techniques.
Emotional Tweets Analysis on Social Media with Short Text Classification Using Various Machine Learning Techniques
Authors: Basha Shaik Rahamat , Rao M. Surya Bhupal , Reddy P. Kiran Kumar , Kumar G. Ravi
Published: March 2021

Online Social media are a huge source of regular communication since most people in the world today use these services to stay communicating with each other in their modern lives. Today’s research has been implemented on emotion recognition by message. The majority of the research
uses a method of machine learning. In order to extract information from the textual text written by human beings, natural language processing (NLP) techniques were used. The emotion of humans may be expressed when reading or writing a message. Human beings are willing, since human life is
filled with a variety of emotions, to feel various emotions. This analysis helps us to realize the use of text processing and text mining methods by social media researchers in order to classify key data themes. Our experiments presented that the two main social networks in the world are conducting
text-based mining on Facebook and Twitter. In this proposed study, we categorized the human feelings such as joy, fear, love, anger, surprise, sadness and thankfulness and compared our results using various methods of machine learning.
TCHCN: Trust Computation for Hierarchical Clustering Network to Improve Network Lifetime in Wireless Sensor Network
Authors: Manasa P. , Shaila K. , Venugopal K. R.
Published: March 2021

Network Lifetime of sensor node plays a fundamental role in Wireless Sensor Networks, since they drain out energy during the communication. The hierarchical networks assist in hindering energy loss by exchanging the information at various levels. The Hierarchical levels formed avoid
overburdening of single level cluster zones and helps the network to retain energy of cluster level heads. Malicious attack disturbs the regular functionality of a routing algorithm and deviates QoS performance in the network. The existing LEACH-Mobile protocol adopts low energy clustering
techniques but, falls short in providing security of the network when there is malicious attack. The proposed Trust Computation for Hierarchical Clustering Network protocol proves itself to be trustworthy by having various trust measuring metrics. It enhances the lifetime by adopting low energy
hierarchical protocol and shows improvement of 12% in terms of energy consumption.
Counter Based Authentication Verification to Secure Patient Data in Cloud
Authors: Vikram A. , Gopinath G.
Published: March 2021

Hospital patient record that is stored in public cloud demands high level of security and access control. To guarantee the proper user access, an authentication scheme is required that can follow up data access. In this paper, counter based authentication verification is introduced.
This method utilizes token generation and counter strategy. Elliptic curve based digital signature is employed in token generation. Along with the generated token, the data is encrypted and a counter value is appended to it. Whenever an authorized user views or modifies the stored data, the
counter value is updated. Thus, this method significantly identifies an unauthorized data access.
Blockchain Solution for Evidence Forgery Detection
Authors: Kumar B. L. V. Vinay , Kumar K. Raja
Published: March 2021

Rapidly improving video editing software tools have made video content manipulation feasible. Consequently malicious attackers are trying to manipulate the videos. Detecting video tampering is a major need for many applications. In this paper we propose a model called Evidence chain
based on Blockchain to ensure the credibility of the video. Unlike bitcoin which is a digital currency the Proposed system documents video hash by using hash based technology and elliptic curve cryptography. Video segments are hashed and stored in chronological order as a chain of blocks which
are detectable and non-altering guaranteeing the validity of the video information. This research is significant in establishing the trust between any two parties.
Morpholine- and Thiomorpholine-Based Amidodithiophosphonato Nickel Complexes: Synthesis, Characterization, P–N Cleavage, Antibacterial Activity and Silica Nano-Dispersion
Authors: Podda Enrico , Carla Aragoni M. , Arca Massimiliano , Atzeni Giulia , Coles Simon J. , Ennas Guido , Isaia Francesco , Lippolis Vito , Orru Germano , Scano Alessandra , Orton James B. , Pintus Anna , Scano Alessandra
Published: March 2021

The reactivity of thiomorpholinium P-(4-methoxyphenyl)-N-thiomorpholin-amidodithiophosphonate (S-MorH+2)(S-Mor-adtp−) and morpholinium P-(4-methoxyphenyl)-N-morpholin-amidodithiophosphonate (O-MorH+2)(O-Mor-adtp−)
towards nickel (II) dichloride hexahydrated is presented and the hydrolysis of the relevant metal complexes investigated. The hydrolytic products (S-MorH+2)2 [Ni(dtp)2]2− and (O-MorH+2)2[Ni(dtp)2]2−
were characterized by means of FT-IR, 1H, and 31P NMR and XRD and the experimented P–N cleavage investigated and elucidated by means of DFT calculations. The antimicrobial activity of the neutral nickel complex [Ni(S-Mor-adtp)2] was tested against
a set of Gram-positive and Gram-negative bacteria alongside with its nanodispersion in a silica matrix. The complex [Ni(S-Mor-adtp)2] did not show antibacterial activity, whilst the nano-dispersed sample [Ni(S-Mor-adtp)2]_SiO2 demonstrated inhibition
to growth of Staphylococcus aureus. The nanocomposites were fully characterized by means of XRPD, TGA, SEM and dinitrogen sorption techniques.
The Fabrication of Poly(Σ-caprolactone)–Poly(ethylene oxide) Sandwich Type Nanofibers Containing Sericin-Capped Silver Nanoparticles as an Antibacterial Wound Dressing
Authors: İnal Murat , Gün Gök Zehra , Perktaş Name , Elif Kartal Gozde , Banu Verim Naciye , Murat Sevgi , Apaydın Tuğçe , Yiğitoğlu Mustafa
Published: March 2021

In this study, antibacterial, synthetic poly(Σ-caprolactone)–poly(ethylene oxide) (PCL–PEO) multilayer nanofibers were produced by an electrospinning method. The material was synthesized in 3 layers. The upper–lower protective layers were produced by PCL
nanofibers and the intermediate layer was produced from PEO nanofiber containing sericin-capped silver nanoparticles (S-AgNPs). The electrospinning conditions in which nano-sized, smooth, bead-free fibers were obtained was determined to be an applied voltage of 20 kV, a flow rate of 8 μL/min
and a distance between the collector and the needle tip of 22 cm for the PCL layer (dissolved at a 12% g/mL concentration in a chloroform:methanol (3:2) solvent mixture) layer. For the S-AgNPs doped PEO layer (dissolved at a 3.5% g/mL concentration in water), the corresponding conditions were
determined to be 20 kV, 15 μL/min and 20 cm. To characterize the three-layer material that consisted of PCL and S-AgNPs doped PEO layers, FTIR and SEM analyses were performed, and the water retention capacity, in situ degradability and antibacterial activity of the material
was investigated. According to SEM analysis, the fibers obtained were found to be nano-sized, smooth and bead-free and the average size of the nanofibers forming the PCL layer was 687 nm while the average size of the fibers forming the PEO layer was 98 nm. Antibacterial activity tests were
performed using gram-positive (Staphylococcus aureus ATCC 6538) and gram-negative (Escherichia coli ATCC 25922) bacteria and the resulting biomaterial was found to have antimicrobial effect on both gram-negative and gram-positive bacteria. It was determined that the 3-layer material
obtained in this study can be used as a wound dressing.
Using Vinegar Residue-Based Carrier Materials to Improve the Biodegradation of Phenanthrene in Aqueous Solution
Authors: Zhang Lei , Yan Jinyuan , Xiao Zhixing , Tang Susu , Chen Yunliang , Sun Gangzheng , Wang Weidong , Yu Yadong
Published: March 2021

A large amount of vinegar residue (VR) is generated every year in China, causing serious environmental pollutions. Meanwhile, as a kind of persistent organic pollutants, polycyclic aromatic hydrocarbons (PAHs) ubiquitously exist in environments. With a goal of reusing VR and reducing
PAHs pollutions, we herein isolated one B. subtilis strain, ZL09-26, which can degrade phenanthrene and produce biosurfactants. Subsequently, raw VR was dried under different temperatures (50 °C, 80 °C, 100 °C and 120 °C) or pyrolyzed under 350 °C and 700 °C,
respectively. After being characterized by various approaches, the treated VR were mixed with ZL09-26 as carriers to degrade phenanthrene. We found that VR dried at 50 °C (VR50) was the best in promoting the growth of ZL09-26 and the degradation of phenanthrene. This result may be attributed
to the residual nutrients, suitable porosity and small surface charge of VR50. Our results demonstrate the potential of VR in the biodegradation of phenanthrene, which may be meaningful for developing new VR-based approaches to remove PAHs in aqueous environments.
Study of the Effect Epidermal Growth Factor Nanoparticles in the Treatment of Diabetic Rat Ulcer Skin and Regeneration
Authors: Qi Xiuli , Huan Yuchao , Si Hong , Zou Jianfei , Mu Zhen
Published: March 2021

This study’s objective is to analyze the effect of epidermal growth factor (EGF) nanoparticles on the healing of diabetic skin wounds and also, simultaneously, to investigate the mechanism of EGF nanoparticles to promote healing. In this manuscript, EGF nanoparticles were prepared,
and also the drug loading rate of EGF nanoparticles was measured. In the meantime, a diabetic skin wound model was prepared with the use of rats. Then, the rats were split into four groups: EGF nanogroup, EGF group, empty particle group, and control group. Additionally, the results indicate
that this study was successful in preparing EGF nanoparticles with a stable performance, and the drug was released for 24 hours. The wound healing in the EGF nanoparticle group was quicker than that in the EGF group. Furthermore, the area of EGF receptor-positive cells in the wound surface
of the EGF nanogroup was higher than that of the EGF group, with the results demonstrating that EGF nanoparticles upregulated the expression of EGF receptors in wound surface cells, promoted wound surface healing, and had better efficacy than EGF.
Perceived Fit and User Behavior in Activity-Based Work Environments
Authors: Hoendervanger Jan Gerard , Van Yperen Nico W. , Mobach Mark P. , Albers Casper J.
Published: March 2021

While activity-based working is gaining popularity worldwide, research shows that workers frequently experience a misfit between the task at hand and their work setting. In the current study, experience sampling data were used to examine how perceived fit in activity-based work environments is related to user behavior (i.e., the use of work settings and setting-switching). We found that workers’ perceived fit was higher when they used closed rather than open work settings for individual high-concentration work. Furthermore, more frequent setting-switching was related to higher perceived fit. Unexpectedly, however, this relation was observed only among workers low in activity-switching. These findings indicate that user behavior may indeed be relevant to creating fit in activity-based work environments. To optimize workers’ perceived fit, it seems to be particularly important to facilitate and stimulate the use of closed work settings for individual high-concentration work.
#ChinaMustexplain: Global Tweets, COVID-19, and Anti-Black Racism in China
Authors: Ouassini Anwar , Amini Mostafa , Ouassini Nabil
Published: March 2021

One of the consequences of the emergence of COVID-19 has been the glaring racial and ethnic disparities that have defined the course of the spread of the virus. As a recent migrant-minority community in China, the Black community’s experience has been defined by vulgar racism, exploitation, and stigmatization. In the context of COVID-19, the Black community in China was again a target of multiple racial projects which sought to label their bodies as diseased and physical presence as a threat to the viability and safety of the Han majority. The global response was to mobilize online to expose how the Chinese government is systematically facilitating discriminatory policies against Black migrants in China. In the present paper, we explore how Twitter was utilized to mobilize awareness about anti-Black racism in China. We first present a brief history of African migration to China and then discuss the Han racial ideologies that are inspiring the anti-Black racism. We then use latent Dirichlet allocation as a topic modeling algorithm to extract underlying themes to discuss how anti-Black racism in the COVID-19 context was framed and subsequently challenged by the global community. Finally, we conclude with a brief discussion on COVID-19 and the future of the Black community in China.
Does living together or apart matter? A longitudinal analysis of relationship formation in later life in association with health, well-being, and life satisfaction
Authors: Ševčíková Anna , Juhová Dana Seryjová , Blinka Lukas , Gottfried Jaroslav , Elavsky Steriani , Ťápal Adam
Published: March 2021

Despite a growing body of research on later-life relationship formation, little is known about the health predictors and outcomes of later-life Living-Apart-Together (LAT) relationships. A LAT living arrangement is understood to be a possible way for older adults with age-related limits to partner and balance the consequences of being single. Using both selection and resource models to capture the links between health and relationship status, we analyzed unpartnered people 50+ from the longitudinal Survey of Health, Ageing and Retirement in Europe. We examined who entered LAT or cohabiting relationships between Time 1 and 2, who remained unpartnered, and what effect the transition into one of these statuses had on the well-being of those who remained in that status at Time 3. The respondents in LAT relationships did not differ from their cohabiting counterparts in health indicators before the relationship formation, nor was there a difference in life satisfaction and well-being 2 years after partnering. Compared to unpartnered persons, LAT respondents reported better self-perceived health before relationship formation and slightly higher life satisfaction 2 years later. Health status does not influence the choice for a relationship form, but a LAT relationship may constitute a resourceful living arrangement in later life, which provides some support for both the selection and resource models.
Counting crime: Discounting victims?
Authors: Hall Matthew
Published: March 2021

This paper sets out to critically explore the connections drawn by Her Majesty’s Inspectorate of Constabulary and Fire & Rescue Services between police adherence to national crime recording standards and the provision of service and support by the police to victims of crime. The goal of the paper is to identify what assumptions are being made by Her Majesty’s Inspectorate of Constabulary and Fire & Rescue Services concerning how and why ‘accurate’ crime recording impacts upon victims and to test those assumptions against the broader victimological literature. In so doing, the paper will also shed light on the progress made by police services in this regard since significant concerns were raised about the impact of ‘poor’ crime recording on victims of crime by Her Majesty’s Inspectorate of Constabulary in its 2014 report Crime-recording: Making the victim count.
Student Interest in Client-Sponsored Projects: The Quest for Engagement in Marketing Research Courses
Authors: Yuksel Mujde , Smith Andrew N. , Smith Robert S. , Bicen Pelin , Wilson Elizabeth J. , Weiner Jay
Published: March 2021

Student engagement is regarded as a critical educational outcome. However, it has proven to be elusive to educators within technical domains, such as marketing research and analytics, which has inspired the exploration of experiential course design elements. Client-sponsored projects (CSPs) have become a popular tactic to meet this objective in such courses. The authors utilize a mixed-methods design to examine CSPs and their effectiveness in marketing research and analytics courses. In Study 1, qualitative research yields student insights regarding the desired characteristics of a CSP. Study 2 illustrates that CSPs boost student engagement through perceptions of course relevance. However, students’ subjective interest in the client represented a boundary condition for this effect. That is, CSPs did not offer value to students who lacked inherent interest in the client. In Study 3, a discrete choice model analysis outlined what attributes make clients interesting for students. Finally, Study 4 utilizes a field experiment to identify project-framing tactics that increase student interest through enhanced client familiarity. A series of recommendations are provided to maximize the efficacy of CSPs to marketing research and analytics courses.
Levels of Uncertainty in Infrastructure Asset Management
Authors: Hessami Amir R. , Anderson Stuart D. , Smith Roger E.
Published: March 2021

The management of infrastructure assets is often challenged by uncertain factors such as changing weather trends and usage patterns. To reliably maintain the assets above a specified level of service, the extent of this uncertainty should be identified, and adequate methods for analyzing the risk factors should be implemented. The analysis of risk is well-defined in the field of strategic management. In the current study, four levels of uncertainty that are widely discussed in strategic management were used as a benchmark to determine the levels of uncertainty in infrastructure asset management. These levels range from known issues, to statistically predictable factors, to complete indeterminacy. The current methods of treating uncertainty in infrastructure asset management were reviewed to determine how they overlap with the four levels of uncertainty and whether or not asset managers handle this uncertainty in an optimal fashion. The current approaches in asset management were found to be primarily deterministic and probabilistic. A shortcoming was found in regard to the incorporation of risk analysis into asset management planning for large-scale networks. The researchers concluded that the level of uncertainty present in asset management at the network planning level can be best described as a range and addressed through the use of representative scenarios within that range.