Search results for: semantic clinical classification

Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Suzannah Sharif, Aznie Aida Ahmad, Maznah Ismail

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Cocoa bean is the raw material for products such as cocoa powder and chocolate. Cocoa bean contains polyphenol which has been shown in several clinical studies to confer beneficial health effects. However studies showed that cocoa polyphenol absorption in the human intestinal tracts are very low. Therefore nanoemulsion may be one way to increase the bioavailability of cocoa polyphenol. This study aim to characterize nanoemulsion incorporating crude cocoa polyphenol produced using high energy technique. Cocoa polyphenol was extracted from fresh freeze-dried cocoa beans from Malaysia. The particle distribution, particle size, and zeta potential were determined. The emulsion was also analysed using transmission electron microscope to visualize the particles. Solubilization study was conducted by titrating the nanoemulsion into distilled water or 1% surfactant solution. Result showed that the nanoemulsion contains particle which have narrow size distribution. The particles size average at 112nm with zeta potential of -45mV. The nanoemulsions behave differently in distilled water and surfactant solution.

Keywords: cocoa, nanoemulsion, cocoa polyphenol, solubilisation study

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Mohiuddin Sakib, Fatin Nihal, Rabeya Akter, Anisul Haque, Munsur Rahman, Wasif-E-Elahi

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Surge generating cyclones are one of the deadliest natural disasters that threaten the life of coastal environment and communities worldwide. Due to the geographic location, ‘low lying alluvial plain, geomorphologic characteristics and 710 kilometers exposed coastline, Bangladesh is considered as one of the greatest vulnerable country for storm surge flooding. Bay of Bengal is possessing the highest potential of creating storm surge inundation to the coastal areas. Bangladesh is the most exposed country to tropical cyclone with an average of four cyclone striking every years. Frequent cyclone landfall made the country one of the worst sufferer within the world for cyclone induced storm surge flooding and casualties. During the years from 1797 to 2009 Bangladesh has been hit by 63 severe cyclones with strengths of different magnitudes. Though detailed studies were done focusing on the specific cyclone like Sidr or Aila, no study was conducted where vulnerable areas of exposed coast were identified based on the strength of cyclones. This study classifies the vulnerable areas of the exposed coast based on storm surge inundation depth and area due to cyclones of varying strengths. Classification of the exposed coast based on hazard induced cyclonic vulnerability will help the decision makers to take appropriate policies for reducing damage and loss.

Keywords: cyclone, landfall, storm surge, exposed coastline, vulnerability

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Authors: Amedeo D'Angiulli, Kylie Schibli

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Traditionally, children’s brain development research has emphasized the limitative aspects of disability and impairment, electing as an explanatory model the classical clinical notions of brain lesion or functional deficit. In contrast, Positive Educational Neuroscience (PEN) is a new approach that emphasizes strengths and human flourishing related to the brain by exploring how learning practices have the potential to enhance neurocognitive flexibility through neuroplastic overcompensation. This mini-review provides an overview of PEN and shows how it links to the concept of neurocognitive flexibility. We provide examples of how the present concept of neurocognitive flexibility can be applied to special education by exploring examples of neuroplasticity in the learning domain, including: (1) learning to draw in congenitally totally blind children, and (2) music training in children from disadvantaged neighborhoods. PEN encourages educators to focus on children’s strengths by recognizing the brain’s capacity for positive change and to incorporate activities that support children’s individual development.

Keywords: neurocognitive development, positive educational neuroscience, sociocultural approach, special education

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Authors: Aliza Lee, Mark Wilt, John Bonk, Scott Floyd, Bradley Hoffman, Karen Uchmanowicz

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Bipartite medial cuneiforms are relatively rare but may play a significant role in biomechanical and gait abnormalities. It is believed that a bipartite medial cuneiform may alter the available range of motion due to its larger morphological variant, thus limiting the metatarsal plantarflexion needed to achieve adequate hallux dorsiflexion for normal gait. Radiographic and clinical assessments were performed on 2 patients who reported foot pain along the first ray. Both patients had visible bipartite medial cuneiforms on MRI. Using gait plate and Metascan™ analysis, both were noted to have four measurements far beyond the expected range. Medial and lateral heel peak pressure, hallux peak pressure, and 1st metatarsal peak pressure were all noted to be increased. These measurements are believed to be increased due to the hindrance placed on the available ROM of the 1st ray by the increased size of the medial cuneiform. A larger patient population would be needed to fully understand this developmental anomaly.

Keywords: bipartite medial cuneiforms, cuneiform, developmental anomaly, gait abnormality

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Authors: Luljeta Gashi, Naser Ramadani, Zana Deva, Dafina Gexha-Bunjaku

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The official HIV/AIDS data in Kosovo are based on HIV case reporting from health-care services, the blood transfusion system and Voluntary Counselling and Testing centres. Between 1986 and 2014, are reported 95 HIV and AIDS cases, of which 49 were AIDS, 46 HIV and 40 deaths. The majority (69%) of cases were men, age group 25 to 34 (37%) and route of transmission is: heterosexual (90%), MSM (7%), vertical transmission (2%) and IDU (1%). Based on existing data and the UNAIDS classification system, Kosovo is currently still categorised as having a low-level HIV epidemic. Even though with a low HIV prevalence, Kosovo faces a number of threatening factors, including increased number of drug users, a stigmatized and discriminated MSM community, high percentage of youth among general population (57% of the population under the age of 25), with changing social norms and especially the sexual ones. Methods: Data collection was done using self administered structured questionnaires amongst 249 high school students. Data were analysed using the Statistical Package for Social Sciences (SPSS). Results: The findings revealed that 68% of students know that HIV transmission can be reduced by having sex with only one uninfected partner who has no other partners, 94% know that the risk of getting HIV can be reduced by using a condom every time they have sex, 68% know that a person cannot get HIV from mosquito bites, 81% know that they cannot get HIV by sharing food with someone who is infected and 46% know that a healthy looking person can have HIV. Conclusions: Seventy one percent of high school students correctly identify ways of preventing the sexual transmission of HIV and who reject the major misconceptions about HIV transmission. The findings of the study indicate a need for more health education and promotion.

Keywords: Kosovo, KPAR, HIV, high school

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Yiding Qu, Svetlana V. Komarova

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Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.

Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer

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Authors: Qudsiya Baig

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Empathy yields an unparalleled therapeutic value within patient physician interactions. Medical research is inundated with evidence to support that a physician’s ability to empathise with patients leads to a greater willingness to report symptoms, an improvement in diagnostic accuracy and safety, and a better adherence and satisfaction with treatment plans. Furthermore, the Institute of Medicine states that empathy leads to a more patient-centred care, which is one of the six main goals of a 21st century health system. However, there is a paradox between the theoretical significance of empathy and its presence, or lack thereof, in clinical practice. Recent studies have reported that empathy declines amongst students and physicians over time. The three most impactful contributors to this decline are: (1) disagreements over the definitions of empathy making it difficult to implement it into practice (2) poor consideration or regulation of empathy leading to burnout and thus, abandonment altogether, and (3) the lack of diversity in the curriculum and the influence of medical culture, which prioritises science over patient experience, limiting some physicians from using ‘too much’ empathy in the fear of losing clinical objectivity. These issues were investigated by conducting a fully inductive thematic narrative analysis of patient narratives in the UK to evaluate the behaviours and attitudes that patients associate with empathy. The principal enquiries underpinning this study included uncovering the factors that affected experience of empathy within provider-patient interactions and to analyse their effects on patient care. This research contributes uniquely to this discourse by examining the phenomenon of empathy directly from patients’ experiences, which were systematically extracted from a repository of online patient narratives of care titled ‘CareOpinion UK’. Narrative analysis was specifically chosen as the methodology to examine narratives from a phenomenological lens to focus on the particularity and context of each story. By enquiring beyond the superficial who-whatwhere, the study of narratives prescribed meaning to illness by highlighting the everyday reality of patients who face the exigent life circumstances created by suffering, disability, and the threat of life. The following six themes were found to be the most impactful in influencing the experience of empathy: dismissive behaviours, judgmental attitudes, undermining patients’ pain or concerns, holistic care and failures and successes of communication or language. For each theme there were overarching themes relating to either a failure to understand the patient’s perspective or a success in taking a person-centred approach. An in-depth analysis revealed that a lack of empathy was greatly associated with an emotive-cognitive imbalance, which disengaged physicians with their patients’ emotions. This study hereby concludes that competent providers require a combination of knowledge, skills, and more importantly empathic attitudes to help create a context for effective care. The crucial elements of that context involve (a) identifying empathy clues within interactions to engage with patients’ situations, (b) attributing a perspective to the patient through perspective-taking and (c) adapting behaviour and communication according to patient’s individual needs. Empathy underpins that context, as does an appreciation of narrative, and the two are interrelated.

Keywords: empathy, narratives, person-centred, perspective, perspective-taking

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Authors: Umm-E-Hani, Faiza Babar, Hanif Durad

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Malware-detecting approaches suffer many limitations, due to which all anti-malware solutions have failed to be reliable enough for detecting zero-day malware. Signature-based solutions depend upon the signatures that can be generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions that have been trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning-based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI-based anti-malware solutions that have been trained with enough samples targeted a selected feature vector, thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier-mentioned shortcomings. Our proposed framework, which is based on automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54 % over test data.

Keywords: malware, auto encoders, automated feature engineering, classification

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Authors: Aleena Rena Onozuka, Patompong Satapornpong

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Introduction: In a Human Leukocyte Antigen (HLA)’s immune response, HLA alleles (HLA class I and class II) play a crucial role in fighting against pathogens. HLA-B*15:01 allele had a significant association with asymptomatic COVID-19 infection (p-value = 5.67 x 10-5 ; OR = 2.40 and 95% CI = 1.54 - 3.64). There was also a notable linkage between HLA-B*51:01 allele and critically ill patients with COVID-19 (p-value = 0.007 and OR = 3.38). This study has described the distribution of HLA marker alleles in Thais and sub-groups. Objective: We want to investigate the prevalence of HLA-B*15:01 and HLA-B*51:01 alleles in the Thai population. Materials and Methods: 200 healthy Thai population were included in this study from the College of Pharmacy, Rangsit University. HLA-B alleles were genotyped using the sequence-specific oligonucleotides process (PCR-SSOs). Results: We found out that HLA-B*46:01 (12.00%), HLA-B*15:02 (9.25%), HLA-B*40:01 (6.50%), HLA-B*13:01 (6.25%), and HLA-B* 38:02 (5.50%) alleles were more common than other alleles in Thai population. HLA-B*46:01 and HLA-B*15:02 were the most common allele found across four regions. Moreover, the frequency of HLA-B*15:01 and HLA-B*51:01 alleles were similarly distributed in Thai population (0.50, 5.25 %) and (p-value > 0.05), respectively. The frequencies of HLA-B*15:01 and HLA-B*51:01 alleles were not significantly different from other populations compared to the Thai population. Conclusions: We can screen for HLA-B*15:01 and HLA-B*51:01 alleles to determine the symptoms of COVID-19 since they are universal HLA-B markers. Importantly, the database of HLA markers indicates the association between HLA frequency and populations. However, we need further research on larger numbers of COVID-19 patients and in different populations.

Keywords: HLA-B*15:01, HLA-B*51:01, COVID-19, HLA-B alleles

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Authors: Jessica Maiuolo, Irene Bava, Micaela Gliozzi, Vincenzo Mollace

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Doxorubicin is an anthracycline that is commonly used as a chemotherapy drug due to its cytotoxic effects. The clinical use of doxorubicin is limited due to its known cardiotoxic effects. Polyphenols have a wide range of beneficial properties, and particular importance is given to Oleuropein, one of the main polyphenolic compounds of olive oil. The biological mechanisms involved and the role of the endoplasmic reticulum were examined. Olive oil extract and Oleuropein were able to decrease the damage induced by exposure to doxorubicin. In particular, this natural compound was found to reduce cell mortality and oxidative damage, increase lipid content, and decrease the concentration of calcium ions that escaped from the endoplasmic reticulum. In addition, the direct involvement of this cellular organelle was demonstrated by silencing the ATF6 arm of the Unfolded Protein Response, which was activated after treatment with doxorubicin. The protection afforded by pre-treatment with the natural compound of interest, following the early damage induced by DOXO, provided valuable information regarding the potential use of these substances along with chemotherapy treatment.

Keywords: Olea europea L., oleuropein, doxorubicin, endoplasmic reticulum, nutraceutical support

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Authors: Ki-Yeo Kim

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Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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Authors: M. Kasusse, M. Rosette, E. Burke, C. Mwangi, R. Batamwita, N. Tumwesigye, S. Aisu

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A cross-sectional survey to ascertain the capacity of laboratory persons in using ICTs was conducted in 15 Ugandan districts (July-August 2013). A self-administered questionnaire served as data collection tool, interview guide and observation checklist. 69 questionnaires were filled, 12 interviews conducted, 45 HC observed. SPSS statistics 17.0 and SAS 9.2 software were used for entry and analyses. 69.35% of participants find it difficult to access a computer at work. Of the 30.65% who find it easy to access a computer at work, a significant 21.05% spend 0 hours on a computer daily. 60% of the participants cannot access internet at work. Of the 40% who have internet at work, a significant 20% lack email address but 20% weekly read emails weekly and 48% daily. It is viable/feasible to pilot informatics projects as strategies to build bridges develop skills for e-health landscape in laboratory services with a bigger financial muscle.

Keywords: ICT behavior, clinical laboratory persons, Sub-Saharan Africa, Uganda

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Authors: Ratchaneewan Salao, Steven W. Edwards, Kiatichai Faksri, Kanin Salao

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Background: A two-dose regimen of COVID-19 vaccination (inactivated whole virion SARS-CoV-2 and adenoviral vector) has been widely used. Side effects are very low, but several adverse effects have been reported. Methods: A 40-year-old female patient, with a previous history of thyroid goitre, developed severe neck pain, headache, nausea and fatigue 7-days after receiving second vaccination with Vaxzevria® (Oxford-AstraZeneca). Clinical and laboratory findings, including thyroid function tests and ultrasound of thyroid glands, were performed. Results: Her left thyroid gland was multinodular enlarged, and severely tender on palpation. She had difficulty in swallowing and had tachycardia but no signs of hyperthyroidism. Laboratory results supported a diagnosis of subacute thyroiditis. She was prescribed NSAID (Ibuprofen 400 mg) and dexamethasone for 3-days and her symptoms resolved. Conclusions: Although this is an extremely rare event, physicians may encounter more cases of this condition due to the extensive vaccination program using this combination of vaccines.

Keywords: SARS-CoV-2, adenoviral vector vaccines, vaccination, subacute thyroiditis

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Authors: Thitaporn Thoopputra, Tipaporn Pongmesa, Shuchuen Li

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Aims: To evaluate the application of non-invasive diabetes risk assessment tool in community pharmacy setting. Methods: Thai diabetes risk score was applied to assess individuals at risk of developing type 2 diabetes. Interactive computer-based risk screening (IT) and paper-based risk screening (PT) tools were applied. Participants aged over 25 years with no known diabetes were recruited in six participating pharmacies. Results: A total of 187 clients, mean aged (+SD) was 48.6 (+10.9) years. 35% were at high risk. The mean value of willingness-to-pay for the service fee in IT group was significantly higher than PT group (p=0.013). No significant difference observed for the satisfaction between groups. Conclusions: Non-invasive risk assessment tool, whether paper-based or computerized-based can be applied in community pharmacy to support the enhancing role of pharmacists in chronic disease management. Long term follow up is needed to determine the impact of its application in clinical, humanistic and economic outcomes.

Keywords: community pharmacy, intervention, prevention, risk assessment, type 2 diabetes

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Authors: Chijindu Okpalaoka, Charles Chinedu Onuselogu

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COVID-19, humanity's coronavirus disease caused by SARS-CoV-2, was first detected in late 2019 in Wuhan, China. COVID-19 lacked an established conventional pharmaceutical therapy, and as a result, the outbreak quickly became an epidemic affecting the entire World. Only a qPCR assay is reliable for diagnosing COVID-19. Clustered, regularly interspaced short palindromic repeats (CRISPR) technology is being researched for speedy and specific identification of COVID-19, among other therapeutic techniques. Apart from its therapeutic capabilities, the CRISPR technique is being evaluated to develop antiviral therapies; nevertheless, no CRISPR-based medication has been approved for human use to date. Prophylactic antiviral CRISPR in living being cells, a Cas 13-based approach against coronavirus, has been developed. While this method can be evolved into a treatment approach, it may face substantial obstacles in human clinical trials for licensure. This study discussed the potential applications of CRISPR-based techniques for developing a speedy and accurate feasible treatment alternative for the COVID-19 virus.

Keywords: COVID-19, CRISPR technique, Cas13, SARS-CoV-2, prophylactic antiviral

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Authors: Haoqi Gao, Koichi Ogawara

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Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method.

Keywords: retinal vascular segmentations, generative ad-versarial network, cyclegan, fundus images

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Authors: Tianqi Wu, Min Wang

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Research investigating language acquisition from a constructionist perspective has demonstrated that language is learned as constructions at various linguistic levels, which is related to factors of frequency, semantic prototypicality, and form-meaning contingency. However, previous research on construction learning tended to focus on clause-level constructions such as verb argument constructions but few attempts were made to study morpheme-level constructions such as the progressive construction, which is regarded as a source of acquisition problems for English learners from diverse L1 backgrounds, especially for those whose L1 do not have an equivalent construction such as German and Chinese. To trace the developmental trajectory of Chinese EFL learners’ use of the progressive with respect to verb frequency, verb-progressive contingency, and verbal prototypicality and generality, a learner corpus consisting of three sub-corpora representing three different English proficiency levels was extracted from the Chinese Learners of English Corpora (CLEC). As the reference point, a native speakers’ corpus extracted from the Louvain Corpus of Native English Essays was also established. All the texts were annotated with C7 tagset by part-of-speech tagging software. After annotation all valid progressive hits were retrieved with AntConc 3.4.3 followed by a manual check. Frequency-related data showed that from the lowest to the highest proficiency level, (1) the type token ratio increased steadily from 23.5% to 35.6%, getting closer to 36.4% in the native speakers’ corpus, indicating a wider use of verbs in the progressive; (2) the normalized entropy value rose from 0.776 to 0.876, working towards the target score of 0.886 in native speakers’ corpus, revealing that upper-intermediate learners exhibited a more even distribution and more productive use of verbs in the progressive; (3) activity verbs (i.e., verbs with prototypical progressive meanings like running and singing) dropped from 59% to 34% but non-prototypical verbs such as state verbs (e.g., being and living) and achievement verbs (e.g., dying and finishing) were increasingly used in the progressive. Apart from raw frequency analyses, collostructional analyses were conducted to quantify verb-progressive contingency and to determine what verbs were distinctively associated with the progressive construction. Results were in line with raw frequency findings, which showed that contingency between the progressive and non-prototypical verbs represented by light verbs (e.g., going, doing, making, and coming) increased as English proficiency proceeded. These findings altogether suggested that beginning Chinese EFL learners were less productive in using the progressive construction: they were constrained by a small set of verbs which had concrete and typical progressive meanings (e.g., the activity verbs). But with English proficiency increasing, their use of the progressive began to spread to marginal members such as the light verbs.

Keywords: Construction learning, Corpus-based, Progressives, Prototype

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Wondale Getinet Alemu, Lillian Mwanri, Clemence Due, Telake Azale, Anna Ziersch

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Background: Mental illness is one of the most severe, chronic, and disabling public health problems that affect patients' Quality of life (QoL). Improving the QoL for people with mental illness is one of the most critical steps in stopping disease progression and avoiding complications of mental illness. Therefore, we aimed to assess the QoL and its determinants in patients with mental illness in outpatient clinics in Northwest Ethiopia in 2023. Methods: A facility-based cross-sectional study was conducted among people with mental illness in an outpatient clinic in Ethiopia. The sampling interval was decided by dividing the total number of study participants who had a follow-up appointment during the data collection period (2400) by the total sample size of 638, with the starting point selected by lottery method. The interviewer-administered WHOQOL BREF-26 tool was used to measure the QoL of people with mental illness. The domains and Health-Related Quality of Life (HRQoL) were identified. The indirect and direct effects of variables were calculated using structural equation modeling with SPSS-28 and Amos-28 software. A p-value of < 0.05 and a 95% CI were used to evaluate statistical significance. Results: A total of 636 (99.7%) participants responded and completed the WHOQOL-BREF questionnaire. The mean score of overall HRQoL of people with mental illness in the outpatient clinic was (49.6 ± 10 Sd). The highest QoL was found in the physical health domain (50.67 ±9.5 Sd), and the lowest mean QoL was found in the psychological health domain (48.41±10 Sd). Rural residents, drug nonadherence, suicidal ideation, not getting counseling, moderate or severe subjective severity, the family does not participate in patient care, and a family history of mental illness had an indirect negative effect on HRQoL. Alcohol use and psychological health domain had a direct positive effect on QoL. Furthermore, objective severity of illness, having low self-esteem, and having a history of mental illness in the family had both direct and indirect effects on QoL. Furthermore, sociodemographic factors (residence, educational status, marital status), social support-related factors (self-esteem, family not participating in patient care), substance use factors (alcohol use, tobacco use,) and clinical factors (objective and subjective severity of illness, not getting counseling, suicidal ideation, number of episodes, comorbid illness, family history of mental illness, poor drug adherence) directly and indirectly affected QoL. Conclusions: In this study, the QoL of people with mental illness was poor, with the psychological health domain being the most affected. Sociodemographic factors, social support-related factors, drug use factors, and clinical factors directly and indirectly, affect QoL through the mediator variables of physical health domains, psychological health domains, social relation health domains, and environmental health domains. In order to improve the QoL of people with mental illnesses, we recommend that emphasis be given to addressing the scourge of mental health, including the development of policy and practice drivers that address the above-identified factors.

Keywords: quality of life, mental wellbeing, mental illness, mental disorder, Ethiopia

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Authors: Naima Nur, Safa Islam, Saeema Islam, Md. Faridul Alam

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Background: The worldwide increase in pediatric presumptive tuberculosis (TB) is the most life-threatening challenge in effectively controlling TB. The objective of this study was to determine the proportion of presumptive TB and the factors associated with it. Methods: A cross-sectional study was conducted between March and November 2013 at ICDDR-Bangladesh. Two hundred twelve pulmonary and extra-pulmonary specimens were collected from 84 suspected pediatric patients diagnosed with TB based on their clinical symptoms/radiological findings. Presumptive TB and confirmed TB were considered presumptive TB and non-presumptive TB and were isolated by smear-microscopy, culture, and GeneXpert. Logistic regression was used to analyze associations between outcome and predictor variables. Results: The proportion of presumptive TB was 85.7%, and 14.3% of non-presumptive TB. In presumptive TB, vaccine scars, family TB history, and school-going children were 16.6%, 33.3%, and 56.9%, respectively. In contrast, vaccine scars and family TB history were 8.3%, and school-going children were 58.3% in non-presumptive TB. Significant factors did not appear in the logistic regression analysis. Conclusion: Despite the high proportion of presumptive TB, there was no statistically significant between presumptive TB and non-presumptive TB.

Keywords: presumptive tuberculosis, confirmed tuberculosis, patient's characteristics, diagnosis

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Authors: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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Authors: A. Bouzekri, H. Benmassaud

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Aurès region is one of the arid and semi-arid areas that have suffered climate crises and overexploitation of natural resources they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and its spatiotemporal changes in the Aurès between 1987 and 2013, for this work, we adopted a method of analysis based on the exploitation of the images satellite Landsat TM 1987 and Landsat OLI 2013, from the supervised classification likelihood coupled with field surveys of the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover maps from 1987 and 2013, one can extract a spatial map change of different land cover units. The results show that between 1987 and 2013 vegetation has suffered negative changes are the significant degradation of forests and steppe rangelands, and sandy soils and bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013 allows us to understand the extensive or regressive orientation of vegetation and soil, this map shows that dense forests give his place to clear forests and steppe vegetation develops from a degraded forest vegetation and bare, sandy soils earn big steppe surfaces that explain its remarkable extension. The analysis of remote sensing data highlights the profound changes in our environment over time and quantitative monitoring of the risk of desertification.

Keywords: remote sensing, spatiotemporal, land use, Aurès

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Authors: Saghar Karimi, Mohammad Saeed Ahrari Khafi, Amin Abolhasani Foroughi

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In recent decades, keeping exotic species as pet animals has become widespread. Turtles are exotic species from chelonians, which are interested by many people. Caspian pond and European pond turtles from Emydidea family are commonly kept as pets in Iran. Presence of the shell in turtles makes achievement to a comprehensive clinical examination impossible. Respiratory system is one of the most important structures to be examined completely. Presence of the air in the respiratory system makes radiography the first modality to think of; however, image quality would be affected by the shell. Computed tomography (CT) as a radiography-based and non-invasive technique provides cross-sectional scans with little superimposition. The aim of this study was to depict normal computed tomographic anatomy of the respiratory system in Caspian Pond Turtle. Five adult Caspian pond turtle were scanned using a 16-detector CT machine. Our results showed that computed tomography is able to well illustrated different parts of respiratory system in turtle and can be used for detecting abnormalities and disorders.

Keywords: anatomy, computed tomography, respiratory system, turtle

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Authors: Xu Zhang

Abstract:

This article unveils an indicator of language contact between English and Cantonese in one of the Outer Circle Englishes, Hong Kong (HK) English, through an empirical investigation into 1000 tokens from the Global Web-based English (GloWbE) corpus, employing frequency analysis and logistic regression analysis. It is perceived that Cantonese and general Chinese are contextually marked by an integral underlying thinking pattern. Chinese speakers exhibit a reliance on semantic context over syntactic rules and lexical forms. This linguistic trait carries over to their use of English, affording greater flexibility to formal elements in constructing English sentences. The study focuses on the syntactic positioning of the focusing subjunct ‘also’, a linguistic element used to add new or contrasting prominence to specific sentence constituents. The English language generally allows flexibility in the relative position of 'also’, while there is a preference for close marking relationships. This article shifts attention to Hong Kong, where Cantonese and English converge, and 'also' finds counterparts in Cantonese ‘jaa’ and Mandarin ‘ye’. Employing a corpus-based data-driven method, we investigate the syntactic position of 'also' in both HK and GB English. The study aims to ascertain whether HK English exhibits a greater 'syntactic freedom,' allowing for a more distant marking relationship with 'also' compared to GB English. The analysis involves a random extraction of 500 samples from both HK and GB English from the GloWbE corpus, forming a dataset (N=1000). Exclusions are made for cases where 'also' functions as an additive conjunct or serves as a copulative adverb, as well as sentences lacking sufficient indication that 'also' functions as a focusing particle. The final dataset comprises 820 tokens, with 416 for GB and 404 for HK, annotated according to the focused constituent and the relative position of ‘also’. Frequency analysis reveals significant differences in the relative position of 'also' and marking relationships between HK and GB English. Regression analysis indicates a preference in HK English for a distant marking relationship between 'also' and its focused constituent. Notably, the subject and other constituents emerge as significant predictors of a distant position for 'also.' Together, these findings underscore the nuanced linguistic dynamics in HK English and contribute to our understanding of language contact. It suggests that future pedagogical practice should consider incorporating the syntactic variation within English varieties, facilitating leaners’ effective communication in diverse English-speaking environments and enhancing their intercultural communication competence.

Keywords: also, Cantonese, English, focus marker, frequency analysis, language contact, logistic regression analysis

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Authors: Jasminka Mujic, Karin Milde-Langosch, Volkmar Mueller, Mirza Suljagic, Tea Becirevic, Jozo Coric, Daria Ler

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MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients.

Keywords: breast cancer, biomarker, HGF/MET, MACC1

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: P. J. Sweeney, T. Ahtoniemi, J. Puoliväli, T. Laitinen, K. Lehtimäki, A. Nurmi, D. Wells

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Duchenne muscular dystrophy (DMD) is caused by an X linked mutation in the dystrophin gene; lack of dystrophin causes a progressive muscle necrosis which leads to a progressive decrease in mobility in those suffering from the disease. The MDX mouse, a mutant mouse model which displays a frank dystrophinopathy, is currently widely employed in pre clinical efficacy models for treatments and therapies aimed at DMD. In general the end-points examined within this model have been based on invasive histopathology of muscles and serum biochemical measures like measurement of serum creatine kinase (sCK). It is established that a “critical period” between 4 and 6 weeks exists in the MDX mouse when there is extensive muscle damage that is largely sub clinical but evident with sCK measurements and histopathological staining. However, a full characterization of the MDX model remains largely incomplete especially with respect to the ability to aggravate of the muscle damage beyond the critical period. The purpose of this study was to attempt to aggravate the muscle damage in the MDX mouse and to create a wider, more readily translatable and discernible, therapeutic window for the testing of potential therapies for DMD. The study consisted of subjecting 15 male mutant MDX mice and 15 male wild-type mice to an intense chronic exercise regime that consisted of bi-weekly (two times per week) treadmill sessions over a 12 month period. Each session was 30 minutes in duration and the treadmill speed was gradually built up to 14m/min for the entire session. Baseline plasma creatine kinase (pCK), treadmill training performance and locomotor activity were measured after the “critical period” at around 10 weeks of age and again at 14 weeks of age, 6 months, 9 months and 12 months of age. In addition, kinematic gait analysis was employed using a novel analysis algorithm in order to compare changes in gait and fine motor skills in diseased exercised MDX mice compared to exercised wild type mice and non exercised MDX mice. In addition, a morphological and metabolic profile (including lipid profile), from the muscles most severely affected, the gastrocnemius muscle and the tibialis anterior muscle, was also measured at the same time intervals. Results indicate that by aggravating or exacerbating the underlying muscle damage in the MDX mouse by exercise a more pronounced and severe phenotype in comes to light and this can be picked up earlier by kinematic gait analysis. A reduction in mobility as measured by open field is not apparent at younger ages nor during the critical period, but changes in gait are apparent in the mutant MDX mice. These gait changes coincide with pronounced morphological and metabolic changes by non-invasive anatomical MRI and proton spectroscopy (1H-MRS) we have reported elsewhere. Evidence of a progressive asymmetric pathology in imaging parameters as well as in the kinematic gait analysis was found. Taken together, the data show that chronic exercise regime exacerbates the muscle damage beyond the critical period and the ability to measure through non-invasive means are important factors to consider when performing preclinical efficacy studies in the MDX mouse.

Keywords: Gait, muscular dystrophy, Kinematic analysis, neuromuscular disease

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