bluuebunny/crossref_metadata_2025 huggingface dataset:
A new look on CSI imperfection in downlink NOMA systems
Authors: Le Anh-Tu , Do Dinh-Thuan
Published: May 2021

Observing that cooperative scheme benefits to non-orthogonal multiple access (NOMA) systems, we focus on system performance analysis of downlink. However, spectrum efficiency is still high priority to be addressed in existing systems and hence this paper presents full-duplex enabling in NOMA systems. Other challenge needs be considered related to channel state information (CSI). In particular, we derive closedform expressions of outage probability for such NOMA systems under the presence of CSI imperfection. Furthermore, to fully exploit practical environment, we provide system model associated with Nakagami-m fading. The Monte-Carlo simulations are conducted to verify the exactness of considered systems.
Performance analysis of beam divergence propagation through rainwater and snow pack in free space optical communication
Authors: Ali Mustafa H. , Ajel Rehab I. , Abdul-kader Hussain Samira
Published: May 2021

In the present work the future communication requirements need to fulfill with high data rate, FSO (free space optic) with it is tremendous potential is the solution. This research observed the effectiveness analysis of FSO systems by modifying one of the most important FSO parameters beam divergence, under the most affected weather attenuating condition Rainwater and snow pack. The simulation is obtained and analyzed under single channels CSRZ-FSO (carrier-suppressed return-to-zero/free space optical) systems having capacity of 40 Gbps between two transceivers with variable distance. The connection is presently under 5 meteorological turbulences (light rain, medium rain, wet snow, heavy rain and dry snow). The results show the heavy rain and dry snow have a very high attenuation carried out in terms of Q-factor. this result led us to conclude that small divergence offers significant performance improvement for FSO link and this performance decrease every time the beam divergence increase, Therefore, to build inexpensive and reliable transmission media, we go with new method that still in the experiment area called hybrid RF/FSO (radio frequency/free space optical) that compatible with atmospherically status.
An energy-efficient flow shop scheduling using hybrid Harris hawks optimization
Authors: Utama Dana Marsetiya , Widodo Dian Setiya
Published: May 2021

The energy crisis has become an environmental problem, and this has received much attention from researchers. The manufacturing sector is the most significant contributor to energy consumption in the world. One of the significant efforts made in the manufacturing industry to reduce energy consumption is through proper scheduling. Energy-efficient scheduling (EES) is a problem in scheduling to reduce energy consumption. One of the EES problems is in a flow shop scheduling problem (FSSP). This article intends to develop a new approach to solving an EES in the FSSP problem. Hybrid Harris hawks optimization (hybrid HHO) algorithm is offered to resolve the EES issue on FSSP by considering the sequence-dependent setup. Swap and flip procedures are suggested to improve HHO performance. Furthermore, several procedures were used as a comparison to assess hybrid HHO performance. Ten tests were exercised to exhibit the hybrid HHO accomplishment. Based on numerical experimental results, hybrid HHO can solve EES problems. Furthermore, HHO was proven more competitive than other algorithms.
Implementation of an electronic nose for classification of synthetic flavors
Authors: Radi Radi , Barokah Barokah , Rohmah Dwi Noor , Wahyudi Eka , Adhityamurti Muhammad Danu , Yuroto Putro Joko Purwo Leksono
Published: May 2021

Classification and identification of synthetic flavor become routine activities in the flavor and food industry due to its application. As a modern olfactory technology, electronic nose (e-nose) has the possibility to be applied in these activities. This study aimed to evaluate an e-nose for classifying synthetic flavors. In this study, an e-nose was designed with an array of gases sensors as the main sensing component and principal component analysis (PCA) for the pattern recognition software. This research was started with preparation of the hardware, continued with preparation of sample, data collection, and analysis. There were nine samples of synthetic flavors with different aroma, namely: grapes, strawberry, mocha, pandanus, mango, jackfruit, orange, melon, and durian. The data collection process includes three stages, i.e. flushing, collecting, and purging of 2 min, 3 min, 2 min respectively. These sensor responses were then analyzed for forming aroma patterns. Four pre-treatment methods were applied for the aroma pattern formation: absolute data, normalize of absolute data, relative data, and normalize of relative data. With the PCA for evaluation, the results showed that the absolute data treatment provided the best results, indicated from the distribution of aroma patterns that were grouped according to the type of samples.
Real-time monitoring system for weather and air pollutant measurement with HTML-based UI application
Authors: Megantoro Prisma , Pramudita Brahmantya Aji , Vigneshwaran P. , Yurianta Abdufattah , Winarno Hendra Ari
Published: May 2021

This article discusses devising an IoT system to monitor weather parameters and gas pollutants in the air along with anHTML web-based application. Weather parameters measured include; speed and direction of the wind, rainfall, air temperature and humidity, barometric pressure, and UV index. On the other side, the gases measured are; ammonia, hydrogen, methane, ozone, carbon monoxide, and carbon dioxide. This article is introducing a technique to send all parameter data. All parameters read by each sensor are converted into a string then joined into a string dataset, where this dataset is sent to the server periodically. On the UI side, the dataset that has been downloaded from the server-parsed for processing and then displayed. This system uses Google Firebase as a real-time database server for sensor data. Also, using the GitHub platform as a web hosting. The web application uses the HTML programming platform. The results of this study indicate that the device operates successfully to provide information about the weather and gases condition as real-time data.
Revised web impact factor analysis of Timor Leste University website during COVID-19 pandemic
Authors: Wahyuningrum Tenia , Kartiko Condro , Wardhana Ariq Cahya , Soares Teotino Gomes
Published: May 2021

The global coronavirus disease 2019 (COVID-19) pandemic requires the Timor Leste government to make a school from home policy. This policy has encouraged several universities to improve the quality of their distance learning services. However, it seems that the government has not gone deep enough to conduct a preliminary study on each university website's readiness to face this. Based on previous research, the university website impact factor is one of the criteria for increasing webometrics rankings. Still, it is not explained in detail the types of referring pages and domains that can affect webometrics rankings. This research investigates the extent to which R-WIF affects webometrics and examines the factors that can improve the university website's quality. We surveyed the revised web impact factor (R-WIF) at seven universities in Timor Leste to determine their academic sites' relative standing. The results show, although some universities have increased the number of backlinks, the webometrics university ranking prefers backlinks that come from high-authorization sites such as .edu and .gov. The correlation value indicates this phenomenon between R-WIF and Webometrics of 0.464, which means moderate. Universities in Timor Leste need to implement several strategies to improve Webometrics rankings, especially visibility.
The development of a virtual simulator for a novel design surgical tool in endoscopic endonasal transsphenoidal surgery
Authors: Nillahoot Nantida , Pillai Branesh M. , Chumnanvej Sorayouth , Suthakorn Jackrit
Published: May 2021

Endoscopic endonasal transsphenoidal surgery (EETS) is a standard procedure to treat the pituitary adenoma, a tumor in the pituitary gland that causes malfunction of hormones. Although the method is substantially minimal invasive, the surgeon may encounter intricacies. The major challenges are narrow surgery pathway, limited working area, lack of case studies for practicing, steep learning curve owing to the intricate steps, and the tool insertion risk. To ease the neurosurgeons, this research focuses on the development and testing of the surgical simulator based on the pathway guidance and the interchangeable surgical instrument tooltip. The system was tested in human cadaver-based experiments with interchangeability in terms of function and the performance of the simulator in terms of the benefits. The experiments demonstrate the augmentation in the learning skill of the user through the simulator based on the completion time assessment and the error reduction. Furthermore, the satisfaction level of the interchangeable surgical tool, which was found using sliding switch and gripper scored 71.40%, the interchangeable tooltip function, which is a novel function to participants scored 85.6% and the practical use had 77%. The geometric aspect of the interchangeable tool scored lowest (62.80%) and was found to be moderate among the neurosurgeons.
Design and comparative analysis of three phase, four phase and six phase switched reluctance motor topologies for electrical vehicle propulsion
Authors: Vuddanti Sandeep , Karknalli Vinod , Salkuti Surender Reddy
Published: May 2021

Switched reluctance motor (SRM) is attracting the scientific community in recent days because of its special structural benefits. Good research work has been conducted on this machine since the ages. It has evolved as an alternative to the conventional electrical machines in variable speed drives due to rugged architecture, high-speed operation, four quadrants, lack of magnet, and adaptability to harsh surroundings. This paper reviews different topologies of SRM for electric vehicle (EV) application and a comparative study of suitable machines for electric vehicle propulsion. This paper elaborates on the design methodology and the analysis of various phases of operation of SRMs. During the design procedure, the finite element method (FEM) of optimization is used to enhance motor performance. In this study, the three different phase (3, 4 6) motors are analyzed in machine design software and finite element analysis outcomes and SRM simulation approach are discussed.
Bigradient neural network-based quantum particle swarm optimization for blind source separation
Authors: Salman Hussein M. , M. Al-Qurabat Ali Kadhum , Riyadh Finjan Abd Alnasir
Published: May 2021

An independent component analysis (ICA) is one of the solutions of a blind source separation problem. ICA is a statistical approach that depends on the statistical properties of the mixed signals. The purpose of the ICA method is to demix the mixed source signals (observation signals) and rcovering those signals. The abbreviation of the problem is that the ICA needs for optimizing by using one of the optimization approaches as swarm intelligent, neural neworks, and genetic algorithms. This paper presents a hybrid method to optimize the ICA method by using the quantum particle swarm optimization method (QPSO) to optimize the Bigradient neural network method that applies to separate mixed signals and recover sources signals. The results of an implement this work prove that this method gave good results comparing with other methods such as the Bigradient neural network and the QPSO method, based on several evaluation measures as signal-to-noise ratio, signal-to-distortion ratio, absolute value correlation coefficient, and the computation time.
Spatial analysis model for traffic accident-prone roads classification: a proposed framework
Authors: Vitianingsih Anik Vega , Suryana Nanna , Othman Zahriah
Published: May 2021

The classification method in the spatial analysis modeling based on the multi-criteria parameter is currently widely used to manage geographic information systems (GIS) software engineering. The accuracy of the proposed model will play an essential role in the successful software development of GIS. This is related to the nature of GIS used for mapping through spatial analysis. This paper aims to propose a framework of spatial analysis using a hybrid estimation model-based on a combination of multi-criteria decision-making (MCDM) and artificial neural networks (ANNs) (MCDM-ANNs) classification. The proposed framework is based on the comparison of existing frameworks through the concept of a literature review. The model in the proposed framework will be used for future work on the traffic accident-prone road classification through testing with a private or public spatial dataset. Model validation testing on the proposed framework uses metaheuristic optimization techniques. Policymakers can use the results of the model on the proposed framework for initial planning developing GIS software engineering through spatial analysis models.
Measure the effectiveness of information systems with the naïve bayes classifier method
Authors: Triayudi Agung , Sumiati Sumiati , Dwiyatno Saleh , Karyaningsih Dentik , Susilawati Susilawati
Published: May 2021

Technological advances at this time are developing very fast, information systems became the frontline in technological advancements, the need for information systems to support jobs is increasingly high. However, its implementation for users does not have a significant impact, so that it needs to be reviewed and re-evaluated in the use of the information system built. The naive bayes classifier method can provide "effective" and "ineffective" conclusions and is used as material for evaluation and improvement. The purpose of this study is to contribute to measuring the effectiveness of the information system, to solve problems with the naïve bayes classifier method approach which has advantages in the process of classifying data and predicting data. From the test results three times, training has been conducted using 100 data, accuracy value of 84.82% and error 15.18%.
Hepatitis classification using support vector machines and random forest
Authors: Aurelia Jane Eva , Rustam Zuherman , Wirasati Ilsya , Hartini Sri , Saragih Glori Stephani
Published: May 2021

Hepatitis is a medical condition defined by inflammation of the liver. It can be caused by infection of the liver by hepatitis viruses or is of unknown aetiology. There are 5 main hepatitis viruses, such as virus types A, B, C, D and E. The infection may occur with limited or no symptoms, but also may include some symptoms like abdominal pain, dark urine, extreme fatigue, jaundice, nausea or vomiting. Because Indonesia is a large archipelago, the prevalence of viral infections varies greatly by region of acute hepatitis patients. This research uses data of hepatitis examination result with amount of 113 data and 5 features. The method that used is support vector machines (SVM) and random forest method. SVM is the classification method that uses discriminant hyper-plane, dividing to classes. meanwhile, random forest is a tree-based ensemble depending on a collection of random variables. SVM and random forest (RF) are applied to predict hepatitis data, and then the results will be compared.
Performance comparison between naive bayes and k- nearest neighbor algorithm for the classification of Indonesian language articles
Authors: Winarti Titin , Indriyawati Henny , Vydia Vensy , Christanto Febrian Wahyu
Published: May 2021

The match between the contents of the article and the article theme is the main factor whether or not an article is accepted. Many people are still confused to determine the theme of the article appropriate to the article they have. For that reason, we need a document classification algorithm that can group the articles automatically and accurately. Many classification algorithms can be used. The algorithm used in this study is naive bayes and the k-nearest neighbor algorithm is used as the baseline. The naive bayes algorithm was chosen because it can produce maximum accuracy with little training data. While the k-nearest neighbor algorithm was chosen because the algorithm is robust against data noise. The performance of the two algorithms will be compared, so it can be seen which algorithm is better in classifying documents. The comes about obtained show that the naive bayes algorithm has way better execution with an accuracy rate of 88%, while the k-nearest neighbor algorithm has a fairly low accuracy rate of 60%.
QoS routing in cluster OLSR by using the artificial intelligence model MSSP in the big data environnment
Authors: Oubaha Jawad , Lakki Noureddine , Ouacha Ali
Published: May 2021

The most complex problems, in data science and more specifically in artificial intelligence, can be modeled as cases of the maximum stable set problem (MSSP). this article describes a new approach to solve the MSSP problem by proposing the continuous hopfield network (CHN) to build optimized link state protocol routing (OLSR) protocol cluster. our approach consists in proposing in two stages: the first acts at the level of the choice of the OLSR master cluster in order to quickly make a local minimum using the CHN, by modeling the MSSP problem. As for the second step, the objective is the improvement of the precision making a solution of efficient at the first rank of neighborhood as a linear constraint, and at the end, to find the resolution of the model using the CHN. We will show that this model determines a good solution of the MSSP problem. To test the theoretical results, we propose a comparison with a classic OLSR.
Pancreatic cancer classification using logistic regression and random forest
Authors: Rustam Zuherman , Zhafarina Fildzah , Saragih Glori Stephani , Hartini Sri
Published: May 2021

In the medical field, technology machinery is needed to solve several classification problems. Therefore, this research is useful to solve the problem of the medical field by using machine learning. This study discusses the classification of pancreatic cancer by using regression logistics and random forest. By comparing the accuracy, precision, recall (sensitivity), and F1-score of both methods, then we will know which method is better in classifying the pancreatic cancer dataset that we get from Al-Islam Hospital, Bandung, Indonesia. The results showed that random forest has better accuracy than logistic regressions. It can be seen with maximum accuracy of logistic regressions 96.48 with 30% data training and random forest 99.38% with 20% of data training.
Deintensification or No Statin Treatment Is Associated With Higher Mortality in Patients With Ischemic Stroke or Transient Ischemic Attack
Authors: Dearborn-Tomazos Jennifer L. , Hu Xin , Bravata Dawn M. , Phadke Manali A. , Baye Fitsum M. , Myers Laura J. , Concato John , Zillich Alan J. , Reeves Mathew J. , Sico Jason J.
Published: May 2021

Background and Purpose:

Practice guidelines recommend that most patients receive moderate- or high-potency statins after ischemic stroke or transient ischemic attack (TIA) of atherosclerotic origin. We tested the association of different patterns of potency for prescribed statin therapy—assessed before admission and at hospital discharge for ischemic stroke or TIA—on mortality in a large, nationwide sample of US Veterans.

Methods:

The study population included patients with an ischemic stroke or TIA occurring during 2011 at any of the 134 Veterans Health Administration facilities. We used electronic outpatient pharmacy files to identify statin dose at hospital admission and within 7 days after hospital discharge. We categorized statin dosing as low, moderate, or high potency; moderate or high potency was considered at goal. We created 6 mutually exclusive groups to reflect patterns of statin potency from hospital admission to discharge: goal to goal, low to goal, goal to low or goal to none (deintensification), none to none, none to low, and low to low. We used logistic regression to compare 30-day and 1-year mortality across statin potency groups.

Results:

The population included 9380 predominately White (71.1%) men (96.3%) who were hospitalized for stroke or TIA. In this sample, 34.1% of patients (n=3194) were discharged off a statin medication. Deintensification occurred in 14.0% of patients (n=1312) and none to none in 20.5% (n=1924). Deintensification and none to none were associated with a higher odds of mortality as compared with goal to goal (adjusted odds ratio 1-year mortality: deintensification versus goal to goal, 1.26 [95% CI, 1.02–1.57]; none to none versus goal to goal, 1.59 [95% CI, 1.30–1.93]). Adjustments for differences in baseline characteristics using propensity weighted scores demonstrated similar results.

Conclusions:

Underutilization of statins, including no treatment or underdosing after stroke (deintensification), was observed in approximately one-third of veterans with ischemic stroke or TIA and was associated with higher mortality when compared with patients who were at goal for statin prescription dosing.
Hierarchical Learning of Statistical Regularities over Multiple Timescales of Sound Sequence Processing: A Dynamic Causal Modeling Study
Authors: Fitzgerald Kaitlin , Auksztulewicz Ryszard , Provost Alexander , Paton Bryan , Howard Zachary , Todd Juanita
Published: May 2021

Our understanding of the sensory environment is contextualized on the basis of prior experience. Measurement of auditory ERPs provides insight into automatic processes that contextualize the relevance of sound as a function of how sequences change over time. However, task-independent exposure to sound has revealed that strong first impressions exert a lasting impact on how the relevance of sound is contextualized. Dynamic causal modeling was applied to auditory ERPs collected during presentation of alternating pattern sequences. A local regularity (a rare p = .125 vs. common p = .875 sound) alternated to create a longer timescale regularity (sound probabilities alternated regularly creating a predictable block length), and the longer timescale regularity changed halfway through the sequence (the regular block length became shorter or longer). Predictions should be revised for local patterns when blocks alternated and for longer patterning when the block length changed. Dynamic causal modeling revealed an overall higher precision for the error signal to the rare sound in the first block type, consistent with the first impression. The connectivity changes in response to errors within the underlying neural network were also different for the two blocks with significantly more revision of predictions in the arrangement that violated the first impression. Furthermore, the effects of block length change suggested errors within the first block type exerted more influence on the updating of longer timescale predictions. These observations support the hypothesis that automatic sequential learning creates a high-precision context (first impression) that impacts learning rates and updates to those learning rates when predictions arising from that context are violated. The results further evidence automatic pattern learning over multiple timescales simultaneously, even during task-independent passive exposure to sound.
Scutellospora deformata (Scutellosporaceae), a new species of Gigasporales from the Mediterranean sand dunes of Spain

Authors: GUILLÉN ALBERTO , SERRANO-TAMAY FERNANDO JAVIER , PERIS JUAN BAUTISTA , ARRILLAGA ISABEL
Published: May 2021

A new species S. deformata, that occurs in six locations of marine sand dunes along the eastern Mediterranean coast of Spain is described and illustrated from spores. In the field, the species occurred in the rhizosphere of Ammophila arenaria (Poaceae), Elymus farctus (Poaceae), Otanthus maritimus (Asteraceae), and Echinophora spinosa (Apiaceae). Morphological characters related with outer, middle and inner wall of the glomerospores as well as phylogenetic analysis (partial SSU, ITS1-5.8S region and the partial LSU nrDNA) support the hypothesis that the fungus is a new species of the Scutellosporaceae.
Erratum: Di Pietro, R., Kuzmanović, N., Lakušić, D., Viciani, D., Fortini, P. & Iamonico, D. (2021) Nomenclatural and taxonomic notes on some names of Sesleria sect. Argenteae (Poaceae) from Italy and the Balkans. Phytotaxa 494 (1): 89–102.
Authors: DI PIETRO ROMEO , IAMONICO DUILIO , KUZMANOVIC NEVENA
Published: May 2021

In our recent paper, we noticed a mistake concerning figure 2 (Di Pietro et al. 2021: 93). According to the caption, figure 2 should represent the sheet FI051890 (a lectotype of Sesleria nitida var. tenoreana f. visianii). In fact, in the place of the sheet FI051890, a figure containing two herbarium specimens deposited in PAD (PAD-HD00955 and PAD-HD00956) was erroneously published. These two PAD specimens were discussed in the paper (Di Pietro et al. 2021: 94) where it was highlighted that these could not be considered with certainty as original material for Sesleria nitida var. tenoreana f. visianii Pampanini (1917: 4).We here, correct the mistake and publish the image of lectotype of Sesleria nitida var. tenoreana f. visianii (FI051890, Fig. 1).
Taxonomic application of macro and micro morphological characters of seeds in Astragalus L. (Galegeae, Fabaceae) in India
Authors: KASHYAP SHIVANI , SAHU CHANDAN KUMAR , VERMA ROHIT KUMAR , CHAUDHARY LAL BABU
Published: May 2021

Due to large size and enormous morphological plasticity, the taxonomy of the genus Astragalus is very complex and challenging. The identification and grouping of species chiefly based on macromorphological characters become sometimes difficult in the genus. In the present study, the micromorphology of the seeds of 30 species belonging to 14 sections of Astragalus from India has been examined applying scanning electron microscopy (SEM) along with light microscopy (LM) to evaluate their role in identification and classification. Attention was paid to colour, shape, size and surface of seeds. The overall size of the seeds ranges from 1.5–3.2 × 0.8–2.2 mm. The shape of the seeds is cordiform, deltoid, mitiform, orbicular, ovoid and reniform. The colour of seeds varies from brown to blackish-brown to black. Papillose, reticulate, ribbed, rugulate and stellate patterns were observed on the seed coat surface (spermoderm) among different species. The study reveals that the seed coat ornamentations have evolved differently among species and do not support the subgeneric and sectional divisions of the genus. However, they add an additional feature to the individual species, which may help in identification in combination with other macro-morphological features.
Taxonomic notes on a pirate spider occurring in China (Araneae, Mimetidae)
Authors: LIU JINXIN , XU XIANG , MARUSIK YURI M. , YIN HAIQIANG
Published: May 2021

Based on molecular analysis (12S rRNA, 16S rRNA, 18S rRNA and histone H3) and morphological characters, it was found that Ero juhuaensis Xu, Wang & Wang, 1987 is misplaced and belongs to Mimetus Hentz, 1832. A new combination is suggested, Mimetus juhuaensis (Xu et al., 1987) new combination. The male of M. juhuaensis is described for the first time. Detailed descriptions and illustrations of both sexes, as well as a distribution map of all known species of Mimetidae Simon, 1881 from China are provided.
Notes on Indian wolf spiders: I. Genus Evippa Simon, 1882 (Araneae: Lycosidae, Evippinae)
Authors: SANKARAN PRADEEP M. , CALEB JOHN T.D. , SEBASTIAN POTHALIL A.
Published: May 2021

Indian wolf spider species of the genus Evippa Simon, 1882 based on the type material available in the National Zoological Collection, Zoological Survey of India, Kolkata are revised. One new synonymy is recognised: Evippa mandlaensis Gajbe, 2004 syn. nov. is synonymised with Wadicosa fidelis (O. Pickard-Cambridge, 1872). All the type material examined are imaged and supplementary descriptions for Evippa shivajii Tikader & Malhotra, 1980, Evippa sohani Tikader & Malhotra, 1980, and Evippa solanensis Tikader & Malhotra, 1980 are provided.
Preoperative Staging Diagnosis of Colorectal Cancer Based on Multi-Row Spiral CT
Authors: Zhao Yuwen , Ge Yujie , He Qunfeng
Published: May 2021

Colorectal cancer is a common malignant tumor of digestive tract, and its incidence has increased significantly in recent years. The 5-year survival rate of patients with early local colorectal cancer is more than 90%, with local invasion of about 68%, and distant metastasis of less
than 10%. Therefore, early diagnosis and early treatment is an effective means for the prevention and treatment of colorectal cancer. At present, X-ray air-barium double contrast radiography and fiberoptic endoscope are most commonly used in the examination of colorectal tumors in the world.
These two methods have the advantages of simple operation, intuition and low cost. However, it is limited to judge the depth of tumor invasion, whether to break through the serosa, lymphatic metastasis, and distant metastasis. In this work, it can be confirmed that the measurement of preoperative
tumor vascular volume reconstruction density is feasible in the preoperative evaluation of colorectal cancer, it will provide clinicians with more valuable information about preoperative tumor staging. Besides, multi-slice spiral CT has the advantages of less trauma, high speed, and clear
image. It can not only judge the location of the tumor, the depth, and extent of tumor invasion, and show distant organ metastasis, but also has good application value in tumor staging. In this paper, the clinical data and MSCT imaging data of patients with colorectal cancer were analyzed
retrospectively, and the value of MSCT in the diagnosis of colorectal cancer was discussed.
Monitoring of Motor Nerve Function Rehabilitation in Patients with Upper Extremity Hemiplegia Based on Functional Magnetic Resonance Imaging
Authors: Zhang Ding , Liu Gang , Huang Liemi , Zhang Lun , Gui Xinghua , Tao Jiping , Zeng Pengli , Ding Min
Published: May 2021

Through functional magnetic resonance imaging (fMRI) technology, it is planned to use complex brain network technology to track brain functional imaging tracking treatment of stroke hemiplegia with scalp acupuncture. Functional magnetic resonance imaging (fMRI) can continuously monitor
the rehabilitation process of motor nerve function in patients with stroke and upper limb hemiplegia, and explore the mechanism of brain plasticity changes at different levels of neural function cortex, motor function neural circuit, and behavior level. First, the fMRI test uses a block design,
and the subjects complete the movement of the thumb and index finger. After completing the dysfunction assessment, fMRI data collection was performed on the patient before the CIMT treatment using a magnetic resonance apparatus, and a second fMRI data collection was performed 2 weeks after
the CIMT treatment; only one fMRI data collection was performed on the volunteers. The functional magnetic resonance data was processed using the AFNI software package, and the functional scores of subjects were calculated using SPSS software. Second, studying the remodeling of residual brain
tissue and functional compensation pathways can help to further clarify the recovery mechanism of motor function after stroke hemiplegia. Finally, compulsory exercise therapy can effectively improve upper limb motor dysfunction in stroke patients. The forced use of upper extremities during
treatment induces the reorganization and compensation of cerebral cortical functional areas. This change in brain functional areas is consistent with the increase of upper extremity movement and improvement of motor function, fMRI can provide neuronal reorganization after exercise therapy
evidence with compensation.
Study on the Application of 1.5T Magnetic Resonance Imaging Image Fusion in the Staging of Rectal Cancer
Authors: Lv Jiexia , Yu Huajun
Published: May 2021

Rectal cancer is a common gastric testicular malignancy, and surgical resection is the most effective treatment. The depth of local tumour filtration, lymph node metastasis and distant metastasis are all factors that influence the prognosis of rectal cancer surgery. MRI has the advantages
of high-resolution, multidirectional, multi-angle, multiparameter imaging and zero radiation in soft tissue, so you can estimate the depth of tumour filtration and lymph node metastasis more accurately than ultrasound or CT. Today, it is a standard method for pre-operative imaging of rectal
cancer. In this study, patients with rectal cancer have been studied from May 2020 to May 2021. 75 Patients were scanned at an arrow-shaped position and cross-sectional images, which are strictly vertical to the rectal wall, were designed after improvement at tumour level. The position of
the coronal image is strictly vertical to the horizontal position. In this way, partial volume effects can be avoided and the depth of tumour filtration accurately evaluated. This helps surgeons determine the horizontal position of the tumor based on MRI images. To avoid the volume effect,
the cross-section line must be vertical to the tumour axis. This study shows that in T3 tumours it is particularly important to measure the minimum level between the tumour and the rectal mesioma phase. The histology of the resected samples showed that if the distance between the tumor and
the rectal mestrincular fascia exceeds 1 mm, the frequency of local recurrence is greatly reduced. If the distance between the tumor and the rectal mesiole fascia is less than 1 mm, the risk of local recurrence is greatly increased. Therefore, tumours with a straight mesosis of 1 mm or less
margin-positive are called.
Dissipating and reflecting internal waves
Authors: Shakespeare Callum J. , Arbic Brian K. , Hogg Andrew McC.
Published: May 2021

Internal waves generated at the seafloor propagate through the interior of the ocean, driving mixing where they break and dissipate. However, existing theories only describe these waves in two limiting cases. In one limit, the presence of an upper boundary permits bottom-generated waves to reflect from the ocean surface back to the seafloor, and all the energy flux is at discrete wavenumbers corresponding to resonant modes. In the other limit, waves are strongly dissipated such that they do not interact with the upper boundary and the energy flux is continuous over wavenumber. Here, a novel linear theory is developed for internal tides and lee waves that spans the parameter space in between these two limits. The linear theory is compared with a set of numerical simulations of internal tide and lee wave generation at realistic abyssal hill topography. The linear theory is able to replicate the spatially-averaged kinetic energy and dissipation of even highly non-linear wave fields in the numerical simulations via an appropriate choice of the linear dissipation operator, which represents turbulent wave breaking processes.
Consumer Ethicality Perception and Legitimacy: Competitive Advantages in COVID-19 Crisis
Authors: Payne Gregory , Blanco-González Alicia , Miotto Giorgia , del-Castillo Cristina
Published: May 2021

The article aims to analyze the cause–effect relationship between Brand Ethicality Perception (CPE), legitimacy and purchase intention during the COVID-19 first wave, taking into consideration the mediation effect of the country of residence. Data collection was based on a survey launched during the COVID-19 lockdown in Madrid and New York. To analyze the established hypotheses and to test the multigroup analysis, we applied a structural modelling with SmartPLS. The research contributes to the field of brand management, and specifically of ethical branding, since it will analyze how stakeholders’ expectations fulfillment is key to build a consistent and valued brand meaning in crisis’ situations, demonstrating that ethical behaviors are key for gaining corporate legitimacy and, therefore, for improving business performances.
‘Wasn’t offered one, too poorly to ask for one’ – Reasons why some patients do not receive a psychosocial assessment following self-harm: Qualitative patient and carer survey
Authors: Quinlivan Leah , Gorman Louise , Littlewood Donna L , Monaghan Elizabeth , Barlow Stephen J , Campbell Stephen , Webb Roger T , Kapur Nav
Published: May 2021

Objective:

Psychosocial assessment following self-harm presentations to hospital is an important aspect of care. However, many people attending hospital following self-harm do not receive an assessment. We sought to explore reasons why some patients do not receive a psychosocial assessment following self-harm from the perspective of patients and carers.

Methods:

Between March and November 2019, we recruited 88 patients and 14 carers aged ⩾18 years from 16 mental health trusts and community organisations in the United Kingdom, via social media, to a co-designed qualitative survey. Thematic analyses were used to interpret the data.

Results:

Patients’ reasons for refusing an assessment included long waiting times, previous problematic interactions with staff and feeling unsafe when in the emergency department. Two people refused an assessment because they wanted to harm themselves again. Participants reported organisational reasons for non-assessment, including clinicians not offering assessments and exclusion due to alcohol intoxication. Other patients felt they did not reach clinically determined thresholds because of misconceptions over perceived heightened fatality risk with certain self-harm methods (e.g. self-poisoning vs self-cutting).

Conclusion:

Our results provide important insights into some of the reasons why some people may not receive a psychosocial assessment following self-harm. Parallel assessments, compassionate care and specialist alcohol services in acute hospitals may help reduce the number of people who leave before an assessment. Education may help address erroneous beliefs that self-injury and self-harm repetition are not associated with greatly raised suicide risk.
Comparing the social networks of service users with long term mental health needs living in community with those in a general adult in-patient unit
Authors: Rusca Roberto , Onwuchekwa Ike-Foster , Kinane Catherine , MacInnes Douglas
Published: May 2021

Background:

Relationships are vital to recovery however, there is uncertainty whether users have different types of social networks in different mental health settings and how these networks may impact on users’ wellbeing.

Aims:

To compare the social networks of people with long-term mental illness in the community with those of people in a general adult in-patient unit.

Method:

A sample of general adult in-patients with enduring mental health problems, aged between 18 and 65, was compared with a similar sample attending a general adult psychiatric clinic. A cross-sectional survey collected demographic data and information about participants’ social networks. Participants also completed the Short Warwick Edinburgh Mental Well-Being Scale to examine well-being and the Significant Others Scale to explore their social network support.

Results:

The study recruited 53 participants (25 living in the community and 28 current in-patients) with 339 named as important members of their social networks. Both groups recorded low numbers in their social networks though the community sample had a significantly greater number of social contacts (7.4 vs. 5.4), more monthly contacts with members of their network and significantly higher levels of social media use. The in-patient group reported greater levels of emotional and practical support from their network.

Conclusions:

People with serious and enduring mental health problems living in the community had a significantly greater number of people in their social network than those who were in-patients while the in-patient group reported greater levels of emotional and practical support from their network. Recommendations for future work have been made.
Oral Candida Predicts Streptococcus mutans Emergence in Underserved US Infants
Authors: Alkhars N. , Zeng Y. , Alomeir N. , Al Jallad N. , Wu T.T. , Aboelmagd S. , Youssef M. , Jang H. , Fogarty C. , Xiao J.
Published: May 2021

Despite the cariogenic role of Candida suggested from recent studies, oral Candida acquisition in children at high risk for early childhood caries (ECC) and its association with cariogenic bacteria Streptococcus mutans remain unclear. Although ECC disproportionately afflicts socioeconomically disadvantaged and racial-minority children, microbiological studies focusing on the underserved group are scarce. Our prospective cohort study examined the oral colonization of Candida and S. mutans among 101 infants exclusively from a low-income and racial-minority background in the first year of life. The Cox hazard proportional model was fitted to assess factors associated with the time to event of the emergence of oral Candida and S. mutans. Oral Candida colonization started as early as 1 wk among 13% of infants, increased to 40% by 2 mo, escalated to 48% by 6 mo, and remained the same level until 12 mo. S. mutans in saliva was detected among 20% infants by 12 mo. The emergence of S. mutans by year 1 was 3.5 times higher (hazard ratio [HR], 3.5; confidence interval [CI], 1.1–11.3) in infants who had early colonization of oral Candida compared to those who were free of oral Candida ( P = 0.04) and 3 times higher (HR, 3.0; CI, 1.3–6.9) among infants whose mother had more than 3 decayed teeth ( P = 0.01), even after adjusting demographics, feeding, mother’s education, and employment status. Infants’ salivary S. mutans abundance was positively correlated with infants’ Candida albicans ( P < 0.01) and Candida krusei levels ( P < 0.05). Infants’ oral colonization of C. albicans was positively associated with mother’s oral C. albicans carriage and education ( P < 0.01) but negatively associated with mother’s employment status ( P = 0.01). Future studies are warranted to examine whether oral Candida modulates the oral bacterial community as a whole to become cariogenic during the onset and progression of ECC, which could lead to developing novel ECC predictive and preventive strategies from a fungal perspective.
Exploring the Impact of Animal Involvement in the Learning Experiences of Learners Mainly With Autism in the English West Midlands Region: A Qualitative Study
Authors: Zenenga Abide , Phillips Jenny , Nyashanu Mathew , Ekpenyong Mandu Stephen
Published: May 2021

Learners with autism are affected by different challenges during learning. There is a growing focus on education to facilitate learners to become more self-resilient by involving animals in learning spaces. This qualitative study explored the impact of animal involvement on the learning experiences of learners with autism. Twenty diaries, 32 questionnaires, and 40 guided narratives and pictorial voices were used to collect data. The study found that learners demonstrated improved communication, imagination, empathy, motivation, calculation skills, responsibility, and well-being while interacting with animals. The study concluded that involving animals in the learning spaces has significant positive impact on learners.
Exploring the prevalence of personality disorder and the feasibility of using the SAPAS as a screening tool for personality disorder in an emergency department in India
Authors: Sen Piyal , Barnicot Kirsten , Podder Priyanka , Dasgupta Indraneel , Gormley Mariko
Published: May 2021

Background

Personality disorders (PD) lead to frequent emergency department (ED) visits. Existing studies have evaluated high-risk ED populations in Western settings. PD screening tools, such as the Standardized Assessment of Personality – Abbreviated Scale (SAPAS), have thus far only been validated in Western populations.

Aims

This study aimed to establish the screened prevalence of PD, and to evaluate the performance of the SAPAS as a screening tool within an ED setting in India.

Methods

The study took place in the ED of a private multi-speciality hospital in Kolkata, India. All attendees were approached during two days per week over three months, except those who were medically unfit to participate. The SAPAS and the International Personality Disorder Examination (IPDE) were translated into Bengali and then used as screening tools for PD and as the reference standard for PD diagnosis.

Results

Out of 120 ED attendees approached, 97 participated (48 men and 49 women), of whom 24% met the criteria for a diagnosis of PD. A cut-off score of 4 on the SAPAS provided the best trade-off between sensitivity and specificity for detecting PD.

Conclusion

The prevalence of PD was similar to Western samples, and the SAPAS showed promise for use in a non-Western setting.
Esophagitis dissecans superficialis associated with acute transoral paraquat poisoning: Clinical study of 15 cases
Authors: Tao Xiaogen , Yu Guangcai , Guo Wei , Kan Baotian , Song Lingli , Li Hai , Jian Xiangdong
Published: May 2021

To analyze the clinical characteristics and therapeutic effects of transoral paraquat poisoning combined with Esophagitis dissecans superficialis (EDS). A retrospective observational study was conducted on paraquat poisoning patients between January 1, 2011 and August 30, 2016 in Qilu hospital. Fifteen patients with EDS were enrolled in this study. The clinical characteristics, prognosis, and pathological features of esophageal necrosis mucosa of these patients were retrospectively analyzed and summarized. Esophageal mucosal dissection occurs mainly within 3–8 days after transoral paraquat poisoning in 15 patients. Dosage of paraquat is range from 50 to 100 ml. Most patients have physical problems with swallowing before the intramural esophageal dissection occurred. And there are other symptoms, including sore throat or dysphagia (100%), nausea and vomiting (86.7%), heartburn or upper abdominal pain (73.3%), hematemesis (60%), abdominal distension (20%) and cough frequently (6.7%). In death group, most patients demonstrate features of the multiple organ failure when the esophageal mucosal stripping happened, including lung injury, renal failure, and hepatic failure. The shape of esophageal dissection was tubular in 60%, irregular in 40%, and they vary in size. Pathological examination showed extensive injury, necrosis and hemorrhage of digestive tract epithelium, and obvious inflammatory reaction of epithelial tissue. Transoral paraquat poisoning has certain damage to the patient’s esophageal mucosa, and some may be complicated with EDS, and the prognosis is poor, especially when combined with multiple organ dysfunction. Esophageal damage is mainly located in the esophageal mucosa and have different degrees. Special attention should be paid on such patients.
The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System
Authors: Schneider-Kamp Anna
Published: May 2021

Transitions from one level of care to another are complex processes that pose medical and organizational risks and depend on care integration between different providers. This qualitative study investigated user experiences with an existing digital system for care integration between hospitals and nursing homes, and the potential of artificial intelligence to contribute to its optimization. The findings reveal challenges regarding (a) untimely information, (b) irrelevant information, (c) confusing information, (d) missing information, (e) information overload, and (f) information multiplicity. Artificial intelligence could address these by (i) identifying and verifying low-quality information, (ii) targeting information for different user groups, (iii) visually summarizing relevant information, and (iv) jointly presenting multiple versions. The implications of these findings extend beyond the context of care integration, presenting empirical evidence for the importance of qualitative health research in, and a model for, determining the scope and design of future artificial intelligence solutions to optimize (health)care processes.