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Assisted reproductive technologies (ARTs) have become a widely utilized medical technology for treating infertility worldwide. However, societies and countries have applied these technologies in accordance with their cultural practices and belief systems. This paper presents an overview of ART providers in Bangladesh and analyzes their online content in addressing potential infertile couples. Examining the topic within the context of socio-economic and public health challenges in Bangladesh, particularly overpopulation, poverty, and lack of education, the research conducted a web content analysis of ART providers in Bangladesh from July 1 to September 1, 2023. Twenty active ART providers were identified using Google searches and an exploratory key. The analysis considered locations, landing page information, ethical standards, quality certification, foreign affiliations, and success rates. The findings revealed a concentration of centers in urban areas, raising concerns about equitable access. The absence of regulation and guidelines, coupled with the lack of ART clinic registration, highlighted potential risks to patient well-being. Landing page statements utilized highly emotive language and ambiguous terms, raising ethical concerns. The absence of explicit mention of quality standards, including ISO 9001:2000 certification, indicated potential gaps in transparency. Foreign affiliations were employed for credibility, raising concerns of misleading advertising. Limited and ambiguous reporting of success rates posed challenges for informed decision-making. Evident exploitative and commercialized practices raised concerns about potentially commodifying reproductive services. The study emphasizes the need for regulatory frameworks, transparency in reporting, adherence to ethical advertising, and increased cultural sensitivity to enhance the ethical standards of ART providers in Bangladesh., Competing Interests: Conflict of InterestThe author declares no competing interests., (© National University of Singapore and Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Inflammatory bowel disease is a multifaceted condition that is influenced by nutritional, microbial, environmental, genetic, psychological, and immunological factors. Polyphenols and polysaccharides have gained recognition for their therapeutic potential. This review emphasizes the biological effects of polyphenols and polysaccharides, and explores their antioxidant, anti-inflammatory, and microbiome-modulating properties in the management of inflammatory bowel disease (IBD). However, polyphenols encounter challenges, such as low stability and low bioavailability in the colon during IBD treatment. Hence, polysaccharide-based encapsulation is a promising solution to achieve targeted delivery, improved bioavailability, reduced toxicity, and enhanced stability. This review also discusses the significance of covalent and non-covalent interactions, and simple and complex encapsulation between polyphenols and polysaccharides. The administration of these compounds in appropriate quantities has proven beneficial in preventing the development of Crohn's disease and ulcerative colitis, ultimately leading to the management of IBD. The use of polyphenols and polysaccharides has been found to reduce histological scores and colon injury associated with IBD, increase the abundance of beneficial microbes, inhibit the development of colitis-associated cancer, promote the production of microbial end-products, such as short-chain fatty acids (SCFAs), and improve anti-inflammatory properties. Despite the combined effects of polyphenols and polysaccharides observed in both in vitro and in vivo studies, further human clinical trials are needed to comprehend their effectiveness on inflammatory bowel disease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Assisted Reproductive Technologies (ARTs) have been practiced in Islamic societies within married couples since their introduction. However, there are divergent views over the issue of third-party donation among Sunni and Shia scholars. This paper illustrates the different perspectives of Shia Muslims surrounding, sperm, egg, and embryo donation and ethical aspects thereof. The study reveals that there are different views regarding sperm, egg, and embryo donation among the Shia religious leaders around the world. Many Shia religious scholars, including the Iranian supreme religious leader Ali Hussein Khamenei allow sperm, egg, and embryo donation with certain conditions. However, the conditions stipulated by Shia religious scholars contradict the ethical and legal practices of sperm, egg, and embryo donation. Regarding sperm and egg donation, they declared that the donor child would inherit from a third-party donor and the commissioning parents would be adoptive parents. Thus, according to them, donor anonymity is impossible. Moreover, the Iranian act on embryo donation did not stipulate the right and responsibilities of the donor child and recipient couples and did not clarify the nature and number of embryos that can be donated and implanted. The paper argues that the lack of laws and guidelines on sperm, egg, and embryo donation raises many ethical problems. Based only on religious rulings, third-party donation has been practiced without foreseeing the well-being and safety of donor children, donors, and recipient couples., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

The gut barrier plays an important role in health maintenance by preventing the invasion of dietary pathogens and toxins. Disruption of the gut barrier can cause severe intestinal inflammation. As a natural source, milk is enriched with many active constituents that contribute to numerous beneficial functions, including immune regulation. These components collectively serve as a shield for the gut barrier, protecting against various threats such as biological, chemical, mechanical, and immunological threats. This comprehensive review delves into the active ingredients in milk, encompassing casein, α-lactalbumin, β-lactoglobulin, lactoferrin, the milk fat globular membrane, lactose, transforming growth factor, and glycopeptides. The primary focus is to elucidate their impact on the integrity and function of the gut barrier. Furthermore, the implications of different processing methods of dairy products on the gut barrier protection are discussed. In conclusion, this study aimed to underscore the vital role of milk and dairy products in sustaining gut barrier health, potentially contributing to broader perspectives in nutritional sciences and public health.

The processing characteristics of yogurt are closely related to the composition and arrangement of exopolysaccharides (EPS) in lactic acid bacteria (LAB). To fully understand and develop the functional properties of EPS and to study the effect of EPS molecular weight on yogurt and its mechanism, the physicochemical properties of high molecular weight EPS-LH43, medium molecular weight EPS-LH13, and low molecular weight EPS-LH23, as well as the gel properties and protein conformation of yogurt, were determined and analyzed in this experiment. The results indicate that EPS-LH43 and EPS-LH13 are both composed of mannose, rhamnose, galacturonic acid, glucose, and galactose. EPS-LH23 is composed of mannose, galacturonic acid, glucose, and galactose. Their Number-average Molecular Weight is 5.21 × 10 6  Da, 2.39 × 10 6  Da and 3.76 × 10 5  Da, respectively. In addition, all three types of EPS have good thermal stability and can improve the stability of casein. In addition, the analysis of the texture, particle size, potential, water holding capacity, rheology, low field nuclear magnetic resonance, microstructure, and flavor characteristics of yogurt confirmed the relationship between the molecular weight of LAB EPS and the gel properties of yogurt. Fluorescence spectrophotometer and circular dichroism analysis indicate that the different molecular weights of LAB EPS have different effects on protein structure, which is an intrinsic factor leading to significant differences in the gel properties of the three types of fermented milk. These findings provide new references for enhancing the understanding of the structure-activity relationship of EPS and indicate that EPS-LH43 can be used to improve the gel properties of dairy products., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This paper addresses the problem of feature encoding for gait analysis using multimodal time series sensory data. In recent years, the dramatic increase in the use of numerous sensors, e.g., inertial measurement unit (IMU), in our daily wearable devices has gained the interest of the research community to collect kinematic and kinetic data to analyze the gait. The most crucial step for gait analysis is to find the set of appropriate features from continuous time series data to accurately represent human locomotion. This paper presents a systematic assessment of numerous feature extraction techniques. In particular, three different feature encoding techniques are presented to encode multimodal time series sensory data. In the first technique, we utilized eighteen different handcrafted features which are extracted directly from the raw sensory data. The second technique follows the Bag-of-Visual-Words model; the raw sensory data are encoded using a pre-computed codebook and a locality-constrained linear encoding (LLC)-based feature encoding technique. We evaluated two different machine learning algorithms to assess the effectiveness of the proposed features in the encoding of raw sensory data. In the third feature encoding technique, we proposed two end-to-end deep learning models to automatically extract the features from raw sensory data. A thorough experimental evaluation is conducted on four large sensory datasets and their outcomes are compared. A comparison of the recognition results with current state-of-the-art methods demonstrates the computational efficiency and high efficacy of the proposed feature encoding method. The robustness of the proposed feature encoding technique is also evaluated to recognize human daily activities. Additionally, this paper also presents a new dataset consisting of the gait patterns of 42 individuals, gathered using IMU sensors.

Probiotic products that contain lactobacilli have long histories of safe use as Lactobacillus strains have many physiological functions in the gastrointestinal tract (GIT). However, the viability of probiotics can be affected by food processing and the adverse environment. This study investigated the O/W (Oil-in-water emulsions) emulsions formed by coagulation of casein/GA (Gum Arabic) complexes for Lactiplantibacillus plantarum microencapsulation, and the stability of the strains during gastrointestinal environment were also determined. The results showed that the particle size of the emulsion decreased from 9.72 μm to 5.48 μm when the GA concentration increased from 0 to 2 (w/v), and the emulsion particles were found to be more uniform as observed by CLSM (Confocal Laser Scanning Microscope). The surface of this microencapsulated casein/GA composite forms smooth, dense agglomerates and has high viscoelasticity, which effectively improved casein's emulsifying activity (8.66 ± 0.17 m 2 /g). After the casein/GA complexes microencapsulation, a higher viable count was detected after gastrointestinal digestion in vitro, and the activity of L. plantarum is more stable (about 7.51 log CFU/mL) during 35 days of storage at 4 °C. The results of study will help to design lactic acid bacteria encapsulation systems based on the GIT environment for the oral delivery strategy., Competing Interests: Declaration of competing interest The authors confirm that they have no conflicts of interest with respect to the work described in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Despite persistent challenges, Bangladesh's dairy sector has been noticeable for a few decades. Although agriculture is the major contributor to GDP, dairy farming may play a crucial role in the economy by creating jobs, ensuring food security, and boosting the protein content of people's diets. This research aims to identify the direct and indirect factors influencing dairy product purchase intention amongst Bangladeshi consumers. Data were collected online using Google forms, and the convenience sampling technique was used to reach the consumers. The total sample size was 310. The collected data were analyzed using descriptive and multivariate techniques. Structural Equation Modeling results reveal that marketing mix and attitude are statistically significant with the intention to purchase dairy products. Also, the marketing mix influences the consumers' attitudes, subjective norms, and perceived behavioral control. However, there is no significant association between perceived behavioral control and subjective norm on intention to purchase. The findings suggest developing better products, ensuring reasonable pricing, performing promotional strategies, and proper placement to attract and increase consumers' intention to purchase dairy products., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Although fresh-cut button mushrooms are popular with consumers, quality deterioration presents a significant shelf-life challenge. In this study, fresh-cut button mushrooms were treated with 0.25 g/L l - cysteine (l - Cys) and evaluated in terms of quality, physiology, and transcriptome sequencing. The results indicated that l-Cys application significantly delayed the browning degree of fresh-cut button mushrooms and reduced weight loss. l-Cys treatment reduced the malondialdehyde content, lipoxygenase activity, and reducing sugar levels while enhancing the soluble protein and total phenolic content. Furthermore, l - Cys treatment reduced the O 2 - generation rate and H 2 O 2 accumulation while enhancing the catalase activity. Moreover, l - Cys improved the superoxide dismutase, glutathione reductase, and phenylalanine ammonia-lyase activities while reducing those of polyphenol oxidase and peroxidase. Additionally, l-Cys treatment increased endogenous H 2 S production and AbCBS enzyme activity while decreasing AbCSE enzyme activity. Notably, additional treatment with 1 mM propargylglycine significantly reduced the effect of l-Cys. Moreover, transcriptome sequencing analysis indicated that the differentially expressed genes in the l-Cys group were primarily related to the reactive oxygen species metabolism, oxidoreductase process, membrane integrality, and sulfur metabolism. These findings suggested that l-Cys treatment delayed the aging and extended the shelf life of fresh-cut button mushrooms by regulating the active oxygen species metabolism and water loss and stimulating endogenous H 2 S production.

The impact of culture and religion on sexual and reproductive health and behavior has been a developing area of study in contemporary time. Therefore, it is crucial for people using reproductive procedures to understand the religious and theological perspectives on issues relating to reproductive health. This paper compares different perspectives of three Abrahamic faiths, i.e., Judaism, Christianity, and Islam on ARTs. Procreation, family formation, and childbirth within the context of marriage have all been advocated by these three major religions of the world. Judaism permits the use of all assisted reproductive technologies when the oocyte and sperm come from the husband and wife, respectively. The different denominations of Christianity have diverse views on reproductive practices. Although the Vatican does not approve of assisted reproduction, Protestant, Anglican, and other religious groups are free to use it. ARTs are acceptable in Sunni Islam, although they can only be carried out if the couples are married. Shia Islam, however, permits third-party donations to married couples under specific restrictions. This comparison reveals that while the three major world religions utilize assisted reproduction in distinct ways, there are also many comparable aspects of each religion., Competing Interests: Conflict of InterestThe authors declare no competing interests., (© National University of Singapore and Springer Nature Singapore Pte Ltd. 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Human activity recognition (HAR) aims to recognize the actions of the human body through a series of observations and environmental conditions. The analysis of human activities has drawn the attention of the research community in the last two decades due to its widespread applications, diverse nature of activities, and recording infrastructure. Lately, one of the most challenging applications in this framework is to recognize the human body actions using unobtrusive wearable motion sensors. Since the human activities of daily life (e.g., cooking, eating) comprises several repetitive and circumstantial short sequences of actions (e.g., moving arm), it is quite difficult to directly use the sensory data for recognition because the multiple sequences of the same activity data may have large diversity. However, a similarity can be observed in the temporal occurrence of the atomic actions. Therefore, this paper presents a two-level hierarchical method to recognize human activities using a set of wearable sensors. In the first step, the atomic activities are detected from the original sensory data, and their recognition scores are obtained. Secondly, the composite activities are recognized using the scores of atomic actions. We propose two different methods of feature extraction from atomic scores to recognize the composite activities, and they include handcrafted features and the features obtained using the subspace pooling technique. The proposed method is evaluated on the large publicly available CogAge dataset, which contains the instances of both atomic and composite activities. The data is recorded using three unobtrusive wearable devices: smartphone, smartwatch, and smart glasses. We also investigated the performance evaluation of different classification algorithms to recognize the composite activities. The proposed method achieved 79% and 62.8% average recognition accuracies using the handcrafted features and the features obtained using subspace pooling technique, respectively. The recognition results of the proposed technique and their comparison with the existing state-of-the-art techniques confirm its effectiveness.

Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.

Multi-focus image fusion is the process of combining focused regions of two or more images to obtain a single all-in-focus image. It is an important research area because a fused image is of high quality and contains more details than the source images. This makes it useful for numerous applications in image enhancement, remote sensing, object recognition, medical imaging, etc. This paper presents a novel multi-focus image fusion algorithm that proposes to group the local connected pixels with similar colors and patterns, usually referred to as superpixels, and use them to separate the focused and de-focused regions of an image. We note that these superpixels are more expressive than individual pixels, and they carry more distinctive statistical properties when compared with other superpixels. The statistical properties of superpixels are analyzed to categorize the pixels as focused or de-focused and to estimate a focus map. A spatial consistency constraint is ensured on the initial focus map to obtain a refined map, which is used in the fusion rule to obtain a single all-in-focus image. Qualitative and quantitative evaluations are performed to assess the performance of the proposed method on a benchmark multi-focus image fusion dataset. The results show that our method produces better quality fused images than existing image fusion techniques.

Introduction Non-ST segment elevation myocardial infarction (NSTEMI) is becoming more common than ST segment elevation myocardial infarction (STEMI) and data regarding presence of underlying multivessel coronary artery disease (MVCAD) in these patients is consistent in locoregional population that leads to lethal delays in proper management. Therefore, in the current study, we aimed to evaluate the frequency of MVCAD in NSTEMI with markedly raised troponin T levels. This will help to identify patients that should be labeled as high risk and must be referred for coronary revascularization on priority basis, so that clinical outcomes can be improved in these patients. Methods This cross-sectional research study was carried out at Chaudhary Pervaiz Elahi Institute of Cardiology, Multan over a period of one year. A total of 326 patients with history of chest discomfort within past 48 hours of presentation or angina equivalent symptoms and cardiac troponin T more than 500 ng/l were included in the study. Coronary angiography was done within 72 hours of same hospital admission. The outcome variable i.e. MVCAD was determined. Results Mean age of patients was 50.74 ± 7.75 years with range of 30 to 60 years. MVCAD was found in 107 (32.82%) patients, whilst there was no MVCAD in 219 (67.18%) patients. Moreover, no significant association of MVCAD was noted with age or smoking. Conclusion We found presence of MVCAD in a considerable number of patients presenting with NSTEMI. The key to detect the underlying presence of MVCAD in these patients is lifted troponin T levels. Therefore, we conclude that any patient with elevated troponin T levels, even in the absence of ST segment elevation, should undergo cardiac catheterization to detect presence of MVCAD as this subset of patients can benefit from early revascularization including coronary artery bypass graft (CABG) surgery., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2020, Hashmi et al.)

Image fusion is a process that integrates similar types of images collected from heterogeneous sources into one image in which the information is more definite and certain. Hence, the resultant image is anticipated as more explanatory and enlightening both for human and machine perception. Different image combination methods have been presented to consolidate significant data from a collection of images into one image. As a result of its applications and advantages in variety of fields such as remote sensing, surveillance, and medical imaging, it is significant to comprehend image fusion algorithms and have a comparative study on them. This paper presents a review of the present state-of-the-art and well-known image fusion techniques. The performance of each algorithm is assessed qualitatively and quantitatively on two benchmark multi-focus image datasets. We also produce a multi-focus image fusion dataset by collecting the widely used test images in different studies. The quantitative evaluation of fusion results is performed using a set of image fusion quality assessment metrics. The performance is also evaluated using different statistical measures. Another contribution of this paper is the proposal of a multi-focus image fusion library, to the best of our knowledge, no such library exists so far. The library provides implementation of numerous state-of-the-art image fusion algorithms and is made available publicly at project website.

Movement analysis of human body parts is momentous in several applications including clinical diagnosis and rehabilitation programs. The objective of this research is to present a low-cost 3D visual tracking system to analyze the movement of various body parts during therapeutic procedures. Specifically, a marker based motion tracking system is proposed in this paper to capture the movement information in home-based rehabilitation. Different color markers are attached to the desired joints' locations and they are detected and tracked in the video to encode their motion information. The availability of this motion information of different body parts during the therapy can be exploited to achieve more accurate results with better clinical insight, which in turn can help improve the therapeutic decision making. The proposed framework is an automated and inexpensive motion tracking system with execution speed close to real time. The performance of the proposed method is evaluated on a dataset of 10 patients using two challenging matrices that measure the average accuracy by estimating the joints' locations and rotations. The experimental evaluation and its comparison with the existing state-of-the-art techniques reveals the efficiency of the proposed method.

Introduction Our objective was to determine the severity frequency of coronary artery disease (CAD) in prediabetes patients undergoing coronary angiography (CAG) in a catheterization laboratory. Materials and methods This descriptive comparative study was conducted on patients who were planned for elective CAG in the hospital from January 2019 to November 2019. The study includes patients age ≥40 years undergoing elective CAG with or without percutaneous coronary intervention/percutaneous transluminal coronary angioplasty. There were 458 patients (381 men and 77 women) in this study that were categorized into three groups on the basis on their glycated hemoglobin (HbA1c) levels: group I (n = 143) as non-diabetes, group II (n = 110) as prediabetes, and group III (n = 205) as diabetes. The severity of CAD was determined using the Gensini score. Results A total of 458 patients were included. Of these, 44.97% had hypertension; n = 36 (25.17%), n = 48 (43.63%), and n = 122 (59.51%) in group I, group II and group III, respectively (P = .0001). A total of 214 (46.72%) had a smoking history. There was a strong family history of CAD in group II (n = 29, 26.36%) and group III (n = 43, 20.98%). Group II and group III patients had a higher extension of CAD than group I (P = .01). Group II (n = 27, 41.54) and group III (n = 65, 50.39%) had a higher frequency of deployment of two stents compared to group I. Conclusion Coronary artery atherosclerosis disease increases parallel to the HbA1c severity and smoking. The present study emphasizes prediabetes as an independent risk factor for CAD., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2020, Zarif et al.)

Malaria is caused by Plasmodium parasite. It is transmitted by female Anopheles bite. Thick and thin blood smears of the patient are manually examined by an expert pathologist with the help of a microscope to diagnose the disease. Such expert pathologists may not be available in many parts of the world due to poor health facilities. Moreover, manual inspection requires full concentration of the pathologist and it is a tedious and time consuming way to detect the malaria. Therefore, development of automated systems is momentous for a quick and reliable detection of malaria. It can reduce the false negative rate and it can help in detecting the disease at early stages where it can be cured effectively. In this paper, we present a computer aided design to automatically detect malarial parasite from microscopic blood images. The proposed method uses bilateral filtering to remove the noise and enhance the image quality. Adaptive thresholding and morphological image processing algorithms are used to detect the malaria parasites inside individual cell. To measure the efficiency of the proposed algorithm, we have tested our method on a NIH Malaria dataset and also compared the results with existing similar methods. Our method achieved the detection accuracy of more than 91% outperforming the competing methods. The results show that the proposed algorithm is reliable and can be of great assistance to the pathologists and hematologists for accurate malaria parasite detection., Competing Interests: Conflict of interestThe authors declare they have no conflict of interests., (© Indian Society for Parasitology 2019.)

The lung tumor is among the most detrimental kinds of malignancy. It has a high occurrence rate and a high death rate, as it is frequently diagnosed at the later stages. Computed Tomography (CT) scans are broadly used to distinguish the disease; computer aided systems are being created to analyze the ailment at prior stages productively. In this paper, we present a fully automatic framework for nodule detection from CT images of lungs. A histogram of the grayscale CT image is computed to automatically isolate the lung locale from the foundation. The results are refined using morphological operators. The internal structures are then extracted from the parenchyma. A threshold-based technique is proposed to separate the candidate nodules from other structures, e.g., bronchioles and blood vessels. Different statistical and shape-based features are extracted for these nodule candidates to form nodule feature vectors which are classified using support vector machines. The proposed method is evaluated on a large lungs CT dataset collected from the Lung Image Database Consortium (LIDC). The proposed method achieved excellent results compared to similar existing methods; it achieves a sensitivity rate of 93.75%, which demonstrates its effectiveness.

Background Type 2 diabetes mellitus (T2DM) is associated with acute coronary syndrome, and elevated blood glucose levels on hospital admission may influence outcomes in patients with ST-elevated myocardial infarction (STEMI). We conducted this study to determine the prognostic outcome of hyperglycemia at admission on in-hospital outcomes of STEMI patients with and without T2DM. Methods This prospective study was conducted from June 13, 2018, to October 12, 2019, and included patients older than 18 years diagnosed with STEMI. For our purposes, hyperglycemia was defined as blood glucose levels >140 mg/dl. Hypertension was considered as systolic blood pressure >140 mmHg or diastolic pressure > 90 mmHg. The predictive value of glycemia on admission for outcomes was assessed via patient mortality following thrombolysis or percutaneous coronary intervention (PCI). Results Our study included 256 patients (196 men, 76.5%; 60 women, 23.5%) with a mean age of 55 ± 11 years. A total of 92 patients (35.9%) were admitted with known T2DM diagnoses: 72 of them had hyperglycemia and 20 patients had euglycemia (p = 0.0001). Post-PCI mortality was six (18.8%) in the hyperglycemic group and one (2.2%) in the euglycemic group (p = 0.03). In-hospital mortality was higher in the hyperglycemic group (n = 12, 12.5%) compared to the euglycemic group (n = 6, 3.7%; p = 0.015). Significant risk factors of mortality for STEMI patients with hyperglycemia on admission were age 60 years or older (odds ratio [OR], 5.63 [1.54-20.58]; p = 0.007), heart failure on admission (OR, 6.84 [1.85-25.22)]; p = 0.003), T2DM (OR, 4.14 [0.50-33.96]; p = 0.05), and presenting with renal failure (OR, 6.78 [1.74-26.42]; p = 0.009). Conclusion Thrombolysis and PCI are effective and safe treatments in STEMI patients. Hyperglycemia has a great adverse impact on hospital outcomes in patients with or without T2DM. STEMI patients with hyperglycemia on hospital admission have higher mortality rates., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2020, Shahid et al.)

Movement analysis of infants' body parts is momentous for the early detection of various movement disorders such as cerebral palsy. Most existing techniques are either marker-based or use wearable sensors to analyze the movement disorders. Such techniques work well for adults, however they are not effective for infants as wearing such sensors or markers may cause discomfort to them, affecting their natural movements. This paper presents a method to help the clinicians for the early detection of movement disorders in infants. The proposed method is marker-less and does not use any wearable sensors which makes it ideal for the analysis of body parts movement in infants. The algorithm is based on the deformable part-based model to detect the body parts and track them in the subsequent frames of the video to encode the motion information. The proposed algorithm learns a model using a set of part filters and spatial relations between the body parts. In particular, it forms a mixture of part-filters for each body part to determine its orientation which is used to detect the parts and analyze their movements by tracking them in the temporal direction. The model is represented using a tree-structured graph and the learning process is carried out using the structured support vector machine. The proposed framework will assist the clinicians and the general practitioners in the early detection of infantile movement disorders. The performance evaluation of the proposed method is carried out on a large dataset and the results compared with the existing techniques demonstrate its effectiveness.

A neurological illness is t he disorder in human nervous system that can result in various diseases including the motor disabilities. Neurological disorders may affect the motor neurons, which are associated with skeletal muscles and control the body movement. Consequently, they introduce some diseases in the human e.g. cerebral palsy, spinal scoliosis, peripheral paralysis of arms/legs, hip joint dysplasia and various myopathies. Vojta therapy is considered a useful technique to treat the motor disabilities. In Vojta therapy, a specific stimulation is given to the patient's body to perform certain reflexive pattern movements which the patient is unable to perform in a normal manner. The repetition of stimulation ultimately brings forth the previously blocked connections between the spinal cord and the brain. After few therapy sessions, the patient can perform these movements without external stimulation. In this paper, we propose a computer vision-based system to monitor the correct movements of the patient during the therapy treatment using the RGBD data. The proposed framework works in three steps. In the first step, patient's body is automatically detected and segmented and two novel techniques are proposed for this purpose. In the second step, a multi-dimensional feature vector is computed to define various movements of patient's body during the therapy. In the final step, a multi-class support vector machine is used to classify these movements. The experimental evaluation carried out on the large captured dataset shows that the proposed system is highly useful in monitoring the patient's body movements during Vojta therapy., (Copyright © 2018 Elsevier B.V. All rights reserved.)

For adolescent patients with end-stage hip disease, the choice between total hip arthroplasty (THA) and arthrodesis is complex; the clinical evidence is not definitive, and there are difficult trade-offs between clear short-term benefits from THA and uncertain long-term risks. We surveyed nearly 700 members of the Pediatric Orthopedic Society of North America and the American Association of Hip and Knee Surgeons. Respondents chose between a recommendation of THA or arthrodesis in four clinical vignettes. A clear majority of surgeons recommended THA in two of the vignettes, however opinion was somewhat divided in one vignette (overweight adolescent) and deeply divided in another (adolescent destined for manual labor job). Across all vignettes, recommendations varied systematically according to surgeons' age and their attitudes regarding tradeoffs between life stages., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The future of novel 3D display technologies largely depends on the design of efficient techniques for 3D video representation and coding. Recently, multiple view plus depth video formats have attracted many research efforts since they enable intermediate view estimation and permit to efficiently represent and compress 3D video sequences. In this paper, we present spatiotemporal occlusion compensation with panorama view (STOP), a novel 3D video coding technique based on the creation of a panorama view and occlusion coding in terms of spatiotemporal offsets. The panorama picture represents the most of the visual information acquired from multiple views using a single virtual view, characterized by a larger field of view. Encoding the panorama video with state-of-the-art HECV and representing occlusions with simple spatiotemporal ancillary information STOP achieves high-compression ratio and good visual quality with competitive results with respect to competing techniques. Moreover, STOP enables free viewpoint 3D TV applications whilst allowing legacy display to get a bidimensional service using a standard video codec and simple cropping operations.

In this study, chitosan and nano-chitosan were used as flocculants agents for harvesting microalga Nannochloropsis sp. chitosan was modified to nano-chitosan by crosslinking with sodium tripolyphosphate. The effects of type and dosage of flocculants and the pH of the culture were investigated on biomass recovery. Optimum dosages for both bio-flocculants were found. The results showed that the dosage of flocculant consumption decreases by 40% and biomass recovery increases by 9% when nano-chitosan instead of chitosan is used as flocculant agent. Also, the recycled water from the harvesting process was reused which increases the growth of microalgae by about 7%. Finally, the cost analysis of harvesting process showed the feasibility of using nano-chitosan as flocculation agent., (Copyright © 2013 Elsevier Ltd. All rights reserved.)