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Abstract Knee osteoarthritis (KOA) represents a well-documented degenerative arthropathy prevalent among the elderly population. KOA is a persistent condition, also referred to as progressive joint Disease, stemming from the continual deterioration of cartilage. Predominantly afflicting individuals aged 45 and above, this ailment is commonly labeled as a “wear and tear” joint disorder, targeting joints such as the knee, hand, hips, and spine. Osteoarthritis symptoms typically increase gradually, contributing to the deterioration of articular cartilage. Prominent indicators encompass pain, stiffness, tenderness, swelling, and the development of bone spurs. Diagnosis typically involves the utilization of Radiographic X-ray images, Magnetic Resonance Imaging (MRI), and Computed Tomography (CT) Scan by medical professionals and experts. However, this conventional approach is time-consuming, and also sometimes tedious for medical professionals. In order to address the limitation of time and expedite the diagnostic process, deep learning algorithms have been implemented in the medical field. In the present investigation, four pre-trained models, specifically CNN, AlexNet, ResNet34 and ResNet-50, were utilized to predict the severity of KOA. Further, a Deep stack ensemble technique was employed to achieve optimal performance resulting to the accuracy of 99.71%.

Background Conflict and violence lead to the displacement of millions of people. A significant number of those who are exposed to potentially traumatic events, such as conflict and violence, may develop post-traumatic stress disorder (PTSD) and other mental health or behavioral conditions. This study plans to estimate the prevalence and associated factors of PTSD and generalized anxiety disorder (GAD) among internally displaced persons residing in different relief camps during Manipur violence. Materials and Methods Community-based cross-sectional study was conducted among internally displaced persons (IDPs) residing in relief camps located in Imphal East District of Manipur using a pretested, semistructured, validated questionnaire consisting of PTSD checklist for DSM 5 (PCL-5) and the Generalized Anxiety Disorders Assessment tool (GAD-7). The study was approved by the Institutional Ethics Committee. Results More than half (65.8%) of the respondents were found to have PTSD. One-fourth of the respondents (24.8%) were found to have moderate anxiety, and 15.2% have severe anxiety. Female gender, age between 20 and 59 years, marital status, and employment status after conflict were found to be significantly associated with PTSD. Marital status and witnessed destruction of property were found to be significantly associated with GAD. Around 3/4th of the respondents (235, 75.8%) reported witnessing destruction and burning of property, and 29 (9.4%) reported witnessing death of family members or friends. Around 58 (18.7%) were currently separated from family, and 25 (8.1%) had experienced some kind of trauma at the time of displacement. Conclusion A majority of the participants have PTSD, whereas 15.2% have severe anxiety. Efforts and interventions should be made to improve the psychological well-being through psychological support and counseling from mental health professionals and provision of vocational training for income generation for the IDPs.

Abstract Canine vector-borne infections (CVBIs) are a global health problem. The military working dogs of Sri Lanka die at an early age, and CVBIs have been a leading speculated cause. We examined CVBIs in the working dogs of the Sri Lanka air force (SLAF) and free-roaming dogs (FRDs) and privately owned dogs (PODs) country-wide. Giemsa-stained smears were prepared and conventional PCR-positive DNA was subjected to sequencing and phylogeny. Of the 668 dogs sampled, 212 (31.7%) had one or more CVBIs. The prevalence of infections among the FRDs (40.0%) was significantly higher than SLAF working dogs (30.0%; χ2 = 10.5216; p = 0.0012) and PODs (26.2%; χ2 = 5.3414, p = 0.0208) but not between SLAF dogs and PODs (χ2 = 1.7655, p = 0.1838). Many infected dogs were asymptomatic (57.4%), which was higher among the FRDs. Seven infectious agents were identified: Babesia gibsoni, B. canis, Ehrlichia canis, Anaplasma platys, Leishmania sp., Hepatozoon canis, and filaria worms. The most common infection was B. gibsoni (13.8%), followed by E. canis (9.9%). Three tick species: Rhipicephalus linneai, Rhipicephalus haemaphysaloides and Haemophysalis bispinosa were found infesting the dogs. The SLAF dogs were thoroughly quarantined upon arrival, but the infection prevalence was similar to PODs.

Purpose: The caruncle is a unique anatomical site in the human body, comprising various structures derived from the surface ectoderm and mesoderm. Caruncular lesions can range from benign to malignant and present challenges in accurate diagnosis and timely management due to their hidden nature and proximity to the lacrimal sac. This study aims to provide a comprehensive description of caruncular lesions, presenting the first Indian case series on this topic. Methods: Ethical approval was obtained, and data collection was conducted at a tertiary care center in India. A retrospective analysis was performed on 44 patients with caruncular lesions treated between 2013 and 2020. Detailed patient histories, clinical examinations, slit lamp imaging, and excision biopsies were conducted. Histopathological examination of the specimens was carried out. Results: The study included 42 cases of caruncular lesions, with a mean age of 31.09 years. The majority of cases were male (54.54%). Benign lesions accounted for 84.09% of the cases, while premalignant and malignant lesions accounted for 11.36% and 4.54%, respectively. Papilloma and nevus were the most common lesions, with 11 cases each. All caruncular lesions were successfully and completely excised without complications. Histopathological examination confirmed the accuracy of the diagnoses, with an 84.09% concordance rate between clinical assessment and pathological diagnosis. Conclusion: This case series reveals a predominance of benign lesions among individuals in their early thirties. The successful excision of all lesions with a high concordance rate between clinical assessment and histopathological diagnosis underscores the importance of timely and accurate management.

This study investigates parents' perspectives towards using English as a medium of instruction (EMI). Hundred and seventeen (117) parents who had children studying at higher education institutions (HEIs) in the Sultanate of Oman answered a questionnaire featuring 40 items with a 5-point Likert-scale response key. Findings indicate that, while many parents displayed favorable attitudes towards implementing EMI in HEIs, approximately half of them asserted that their children's English is not good enough to cope with EMI. Therefore, most of them believed that some courses at least should follow Arabic medium instruction. The study explores the advantages and disadvantages of EMI, and findings reveal that the majority of the respondents identify more advantages. It was also found out that the respondents assisted their children in several ways to cope with EMI. For instance, by financing their children to learn English in private institutions, encouraging children to translate their course materials into the Arabic language, and seeking the support of parents' friends to explain doubts and what children have not understood in the classroom.

Rhododendron Linnaeus, 1753, the largest genus of woody plants in the Northern Hemisphere, includes some of the most significant species in horticulture. Rhododendron ambiguum Hemsl, 1911, a member of subsection Triflora Sleumer 1947, exemplifies typical alpine Rhododendron species. The analysis of the complete chloroplast genome of R. ambiguum offers new insights into the evolution of Rhododendron species and enhances the resolution of phylogenetic relationships. This genome is composed of 207,478 base pairs, including a pair of inverted repeats (IRs) of 47,249 bp each, separated by a large single-copy (LSC) region of 110,367 bp and a small single-copy (SSC) region of 2,613 bp. It contains 110 genes: 77 protein-coding genes, 29 tRNAs, four unique rRNAs (4.5S, 5S, 16S, and 23S), with 16 genes duplicated in the IRs. Comparative analyses reveal substantial diversity in the Rhododendron chloroplast genome structures, identifying a fourth variant pattern. Specifically, four highly divergent regions (trnI-rpoB, ndhE-psaC, rpl32-ndhF, rrn16S-trnI) were noted in the intergenic spacers. Additionally, 76 simple sequence repeats were identified. Positive selection signals were detected in four genes (cemA, rps4, rpl16, and rpl14), evidenced by high Ka/Ks ratios. Phylogenetic reconstruction based on two datasets (shared protein-coding genes and complete chloroplast genomes) suggests that R. ambiguum is closely related to R. concinnum Hemsley, 1889. However, the phylogenetic positions of subsection Triflora Pojarkova, 1952 species remain unresolved, indicating that the use of complete chloroplast genomes for phylogenetic research in Rhododendron requires careful consideration. Overall, our findings provide valuable genetic information that will enhance understanding of the evolution, molecular biology, and genetic improvement of Rhododendron spieces.

Abstract Identifying novel cellulose fiber bio-composites has become a vital initiative in the exploration of sustainable materials due to increased global concern for the environment. This growing focus on eco-friendly materials has gathered significant attention in recent years. The current investigation deals with one such material, Helicteres isora reinforced Polylactic acid composites. Surface chemical treatment of fiber is one of the most effective methods to modify the hydrophilic fiber to increase its compatibility with the polymer matrix. Sodium hydroxide was used as a pre-treatment chemical to remove any impurities from the fiber surface. Pre-treated fibers were treated with Methacryl silane and Potassium permanganate solution to chemically modify the fiber surface. Density, void content and water absorption behavior of the composites were analyzed as per the standard procedure. Tensile and flexural tests were conducted to evaluate the mechanical strength, modulus, and flexibility of the unidirectional composites. Thermogravimetric and differential thermal analyses were performed to investigate the thermal stability, melting behavior and degradation profiles of prepared composites. A study of failure mechanisms and morphology of the fractured surface through photographs and SEM images revealed fiber splitting and delamination as the dominant reasons behind the failure of composites under tensile loading. Silane-treated Helicteres isora fiber-reinforced Polylactic acid composite exhibited lower water absorption and higher tensile strength than its counterparts. Untreated fiber composite showed maximum flexural strength among the tested composites. By collectively evaluating the results of the tests and properties of the composites, silane-treated fiber-reinforced Polylactic acid composites stands out as the most favorable choice.

Cataract, an age-related eye disease, poses a significant ophthalmological public health challenge in both developed and developing nations. Tailoring treatment or surgery plans helps accurately categorise the cataract's developmental stage. Precise cataract grading helps in diagnosing cataracts and subsequently scheduling surgical intervention. In this project endeavour, a solution is presented to automate the cataract grading process utilizing slit lamp bio-microscope data sets acquired through smartphones. This innovation is particularly valuable for novice practitioners and non-specialist doctors/experts who may struggle with proficiently interpreting cataract progression, leading to potential misdiagnoses. To address this challenge, a Neural Network model is harnessed to automatically predict the grade of cataracts. The study employs multi-class image classification models, including the Convolutional neural network (CNN) model, the Efficient Net B0 model, and the ResNet50 model, for this purpose. Notably, the ResNet50 model outperforms the other models in terms of accuracy and prediction capability for the provided data set. Achieving an accuracy rate of 0.8611, the ResNet50 model demonstrates superior performance in classifying cataract grades, after augmenting the data set with 544 images. This performance comparison establishes the ResNet50 model as the most robust choice among the considered models and data sets.

Abstract Background Understanding how landscape characteristics affect animal movement is essential for conservation in human-dominated habitats. A fundamental question is how monoculture agroforests, including rubber and tea plantations, affect wildlife and its movement. Experimental translocations represent an important technique to assess animals’ habitat selection while moving through agricultural matrices, especially when complemented with observations of birds’ natural movements, and with “control” translocations, in which birds are moved within their natural habitat such as forest. Yet, experimental translocations have been little used for birds outside the Western Hemisphere. Methods We conducted experimental translocations and home-range measurements on an understory forest specialist, Brown-capped Babbler (BCBA, Pellorneum fuscocapillus), and a forest generalist, Tickell’s Blue Flycatcher (TBFL, Cyornis tickelliae). These species were studied in three rubber plantations, which also included some open areas mostly planted with tea, and in three forest reserves of Sri Lanka. Results Four of the five BCBAs translocated within disturbed habitats (rubber plantations) could not return to their capture locations. However, all four individuals within undisturbed habitats (forest reserves) successfully returned to their point of origin within 10.5 daytime hours. In contrast, all TBFLs returned to their capture locations in both disturbed (n = 7) and undisturbed habitats (n = 3) within 11.3 daytime hours. A Cox-proportional survival model demonstrated that the percentage of rubber cover decreased return time, similar to the effect of open-area cover. The home range surveys (n = 13 for BCBA, n = 10 for TBFL) revealed that very little of the birds’ natural home-ranges was covered by rubber (0.2% for BCBA, 13.1% for TBFL at 50% Kernel Density Estimates KDE). Home range size for BCBA was approximately half the size in disturbed habitats compared to undisturbed ones, although there was no significant difference between habitats for TBFL. Conclusions We conclude that rubber plantations can be impermeable to understory habitat specialist birds, and even generalist species may avoid them long-term. Our findings highlight the potential utility of strips of native vegetation, particularly those featuring understory layers, as corridors to facilitate the movement of forest specialists in landscapes dominated by rubber plantations and other types of disturbed habitats.

This study is a joint research project carried out in two different academic institutions in Oman during the COVID-19 pandemic. The research aims to identify the perceptions of teaching faculty and administrators on the advantages and disadvantages of online education. It also explores how the training process for online teaching occurs and what support is provided afterwards. Qualitative methodology was adopted and data were collected through semi-structured interviews from a representative sample of teaching faculty and administrators from both institutions. Interview data were thematically analyzed using NVivo qualitative analysis software. Findings suggest that participants perceive more disadvantages of online education than the advantages demonstrating a rather negative perception. The training was decided mainly by administrators and focused on essential technical skills. Participants expressed a need for effective online pedagogical training. Short, practical sessions suitable for teachers at different skill and experience levels were suggested by the participants as well as informal peer support groups for continuous professional development after the training. There was some indication of administrative support in mainly infrastructure areas, which can be improved by employing specialist online education support staff. Further, peer support through formal committees or informally through colleagues was found to be accessible and practical. Findings from this study and the literature review can be used in other international contexts for effective provision of online education.

Seed predation by rodents relies on the abundance of available seeds and seed traits like sizes and tannin-content. Here, by tracking the fates of 2400 tagged seeds of two sympatric tree species Quercus wutaishanica and Corylus heterophylla with varying size and tannin content, we assessed rodents’ preference for specific seed traits. Meanwhile, we set the ratio of large to small seeds within species as 9:1, 7:3, 5:5, 3:7, and 1:9, respectively, to examine rodent behavior in response to seed relative frequencies. We found that: 1) rodents preferentially hoarded C. heterophylla seeds with lower-tannins after dispersal while Q. wutaishanica seeds with higher-tannins are more often eaten in situ or after dispersal. Peeling seed coat is an adaptive strategy for rodents to avoid high tannins, particularly for Q. wutaishanica. 2) Rodents prioritize small seeds over large ones for Q. wutaishanica whereas significant differences were not observed for C. heterophylla. Rodents commonly eat small seeds after successful dispersal and prefer to hoard larger ones over long distances. 3) Positive frequency-dependent selection was observed for both seed types. Our results suggest that the selection of seeds by rodents is determined by seed tannins and sizes, and changes in seed size frequencies could alter the interaction between trees and rodents from predation towards mutualism.

Background: Fear of childbirth (FOC) is a feeling of uncertainty and anxiousness before, during or after delivery which may increase the risk of various physical problems and mental disorders thereby affecting maternal and infant morbidity and mortality. Objectives: To estimate the prevalence of fear of childbirth and to determine its associated factors among pregnant women. Methodology: A hospital-based cross-sectional study was conducted among pregnant women attending ante-natal clinic of a tertiary-care hospital in Imphal-East District of Manipur. A 30-item questionnaire was used for data collection. Descriptive statistics, univariate and multivariate logistic regression analysis were performed to test for association taking all variables with p < 0.2 for model building for the adjusted analysis. A p value

Purpose: To critically review the clinical factors, dosimetry, and their correlation with early outcomes in patients with chordomas and chondrosarcomas treated with pencil beam scanning (PBS) proton beam therapy (PBT). Methods and Materials: Consecutive 64 patients diagnosed with chordoma or chondrosarcoma treated at our center were studied. Patient, tumor, and treatment-related factors including dosimetry were captured. Early and late toxicities and early outcomes were evaluated and correlated with clinical and dosimetric factors using standard statistical tools. Results: The median age of patients was 39 years (range, 4-74 years), and most common site was skull base (47%), followed by sacrum (31%) and mobile spine (22%). The median prescription dose to the high-risk clinical target volumes for chordoma and chondrosarcoma was 70.4 cobalt gray equivalent (CGE) and 66 CGE at 2.2 CGE per fraction, respectively. At presentation, 55% presented after a recurrence/progression of which 17% had received previous radiation and 32% had a significant neural compression. At the time of PBT, 25% of patients had suboptimal neural separation. Three-fourths of patients had at least an acceptable target coverage. Although 11% had a tier 1 compromise (gross tumor volume [GTV] D98 < 90%), 14% had a tier 2 compromise (GTVD98 < 59 CGE). With a median follow-up of 27.5 months, 2-year local control and progression-free survival was 86.7% and 81.8% for chordomas and 87.5% and 77.1% for chondrosarcomas, respectively. Residual GTV of >25 cm3 and a tier 2 compromise were associated with inferior local control (hazard ratio [HR], 0.19; P = .019; HR, 0.061; P = .022, respectively) and progression-free survival (HR, 0.128; P = 0.014; HR, 0.194; P =.025, respectively) on multivariate analysis. Despite multiple surgeries, a majority presented with recurrent disease and previous radiations and grade 3 acute and late toxicities were limited and comparable with others in the literature. Conclusions: Despite multiple surgeries, adequate neural separation was challenging to achieve. Severe dosimetric compromise (GTV D98 < 59 CGE) led to inferior early outcomes. Adequate neural separation is key to avoiding dosimetric compromise and achieving optimal local control.

ABSTRACT The discovery of Replication Competent Circular DNA molecules in mammalian cells and tissues is being linked to debilitating diseases, such as multiple sclerosis (MS), bovine spongiform encephalopathy (BSE), and colorectal cancer (CRC). These circular DNA molecules, otherwise known as bovine meat and milk factors (BMMFs) and Slow Progressive Hidden INfections of variable (X) latency (SPHINX), bear significant (80%) sequence similarity with the plasmids of Acinetobacter baumannii strains. Nanostructures, such as bacterial outer membrane vesicles (OMVs) serve as vehicles for transporting biomolecular cargo and have the potential to facilitate interkingdom lateral mobility of DNA. Strengthening the proposed hypothesis, this study demonstrates that OMVs derived from A. baumannii DS002 carrying four plasmids and genome (pTS236) of phage, AbDs1, successfully reached different parts of the body, including the central nervous system, following the injection of fluorescein isothiocyanate (FITC)-labeled OMVs into experimental mice. Out of the four OMV-associated plasmids, three (pTS4586, pTS9900, and pTS134338) were identified within the lumen, and the fourth one (pTS11291) was found on the surface of OMVs. In addition to the indigenous plasmids, the phage-encoded protein, Orf96, anchored on the surface of the OMVs by establishing a strong interaction with the OMV-associated porin, OmpA. Intriguingly, a subset of labeled OMVs, when incubated with Neuro2A cells, translocated across the membrane and reached to the cytoplasmic space of the cells. Collectively, the experimental evidence presented herein underscores the promising potential of OMVs as vehicles for delivering molecular cargo containing plasmids and phage genomes to diverse mammalian tissues and cells.IMPORTANCESeveral independent studies have demonstrated the existence of replication competent circular DNA molecules of bacterial and viral origin in mammalian cells and tissues. However, studies about their origin and lateral mobility to mammalian cells are scarce. Our work describes the existence of circular DNA, similar to that of DNA molecules identified in mammalian cells, OMVs derived from soil isolate of A. baumannii DS002. Furthermore, the work also provides visual evidence that demonstrates the passage of labeled OMVs to different organs of experimental mice within hours after intravenously administering OMVs into experimental mice. Some of the labeled OMVs have even crossed the membrane of Neuro2A, suggesting the existence of interkingdom horizontal mobility between bacteria and mammals.

Background and aims: Proton therapy (PRT) for Head Neck Cancer (HNC), in view of the Bragg peak, spares critical structures like oral mucosa better than IMRT. In PRT, mouth-bites, besides immobilising and separating mucosal surfaces, may also negate the end-of-range effect. We retrospectively analysed the details and dosimetric impact of mouth-bites in PRT for HNC. Materials and methods: The data of consecutive HNC patients treated with IMPT from May 2020 to August 2022 were studied retrospectively. Details of the mouth-bite used, compliance and resultant mucosal separation were noted. Further analysis, restricted to previously unirradiated patients, comprised volumetric dosimetric data pertaining to the mouth-bite and distal mucosal surfaces. High LET zones, corresponding to 6–12 keV/micron, for mouth-bite doses above 30 Gy, were recalculated from existing plans. Results: A mouth-bite was used in 69 of 80 consecutively treated patients, ranging from 8 to 42 mm in thickness, and 12 to 52 mm in the resultant mucosal sparing. In 42 patients in whom the mouth-bite V 32 Gy was > 0, median Dmean, absolute V32, V39, V50 and V60 GyE (Gray Equivalent) of the mouth bite was 35.65 GyE (Range: 2.65 – 60 GyE), 10 cc (Range: 0.1 – 32 cc), 7.6 cc (Range: 0.1 – 30.8 cc), 5.7 cc (Range: 0.2 – 29.2 cc) and 1.45 cc (Range: 0.2 – 18.1 cc) respectively, all significantly more than the spared adjacent mucosal surface. In absence of a mouth-bite, the spared mucosa would have at least partially received the high dose received by the mouth-bite. High LET zones were noted in 12 of 48 mouth-bites. Conclusion: In PRT for HNC, mouth-bites play a vital role in improving the sparing of mucosa outside the target.

Abstract Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015–2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.

The increasing global demand for sustainable materials has led to the enthusiasm for the usage of novel plant-based fibers as raw materials. This study focuses on characterizing Helicteres isora fibers to comprehend their substantial reinforcement potential in polymeric composites. The study investigates fibers derived from Helicteres isora, subjected to Alkali treatment, Methacryl silane treatment, and Potassium permanganate treatment. The investigation involves a comprehensive characterization of these fibers, including study of physical, chemical, thermal and tensile properties, aiming to understand the impact of different chemical treatments. Characterization studies encompass infrared spectroscopy and X-ray diffraction to determine changes in functional groups and crystallinity of fibers. Physical characteristics, including morphology and surface properties, are examined through techniques such as optical and scanning electron microscopy. The alkali-treated fibers exhibit 4% and 30% increase in tensile strength and modulus, respectively. Silane-treated fiber has shown an 18% reduction in water absorption compared to untreated fiber. This study provides a thorough investigation of the physical, chemical, thermal and mechanical characteristics of the untreated and chemically treated Helicteres isora fibers. The findings contribute to a deeper understanding of the potential applications of these treated natural fibers in diverse applications.

Considering the current growth of design and development activities in micro/mini-Unmanned Aerial Vehicles (UAVs), there is a significant need for thin, durable and lightweight composites for their structural applications. Robust and impact-resistant materials are deemed mandatory concerning the harsh operational conditions where these UAVs are employed. Numerical models for composite materials at various loading conditions can bring up tremendous pace in various design and manufacturing aspects of such competent and tailored engineering materials. Numerical simulations of low velocity flatwise Charpy impact are performed on carbon/aramid hybrid laminates. The modelling is based on representative volume element (RVE) micro-scale property homogenisation in ANSYS Workbench, followed by macroscale impact analysis in ABAQUS/EXPLICIT. The damage propagation was determined using the Hashin failure criteria. The numerically predicted results were validated against the experimental data concerning the energy absorbed and impact strength. The results provided by the modelling are in good correlation with the experimental observations. The numerically obtained force-time data correlated the damage propagation and failure modes observed in the post-impact damage morphology in the laminate during the non-instrumented Charpy test.

ABSTRACTThe growing concern for environmentally friendly biomaterials has spurred interest in natural fibers as a viable alternative to synthetic fibers in various industrial applications. Chemical treatment of natural fibers is necessary in cases where it is desired to enhance their properties and make them more suitable for various industrial applications. These treatments can remove impurities, increase fiber roughness for better adhesion, and modify surface chemistry, ultimately improving characteristics like tensile strength, thermal stability, and compatibility with matrix materials in composites. In this study, chemical treatments, including Sodium Hydroxide, Ammonium Hydroxide, and Potassium Permanganate, were applied to the Bamboo fibers to modify the fiber structure. The tensile strength, morphological characteristics, and degree of crystallinity of the treated fibers were examined. Results revealed that 5% Sodium Hydroxide treatment for 2 hours significantly improved tensile strength and crystallinity compared to other treatments. Chemical composition analysis, XRD, and FTIR analyses confirmed the removal of impurities and amorphous substances. Density measurements indicated a reduction in volume due to the elimination of low molecular weight impurities, leading to increased fiber density. This research provides valuable insights for the development of sustainable biomaterials in the construction and automotive industries such as wall panels, dashboards and door panels.

Dirofilariasis, caused by the nematode Dirofilaria spp., poses significant challenges in diagnosis due to its diverse clinical manifestations and complex life cycle. This comprehensive literature review focuses on the evolution of diagnostic methodologies, spanning from traditional morphological analyses to modern emerging techniques in the context of dirofilariasis diagnosis. The review traces the historical progression of diagnostic modalities, encompassing traditional approaches such as microscopic examination, serological tests (including ELISA and IFA), radiographic imaging, ultrasonography, and necropsy, which laid the foundation for subsequent advancements. The integration of molecular diagnostics marks a significant turning point in dirofilariasis diagnosis with the adoption of polymerase chain reaction (PCR) assays and real-time PCR (qPCR) facilitating enhanced sensitivity and specificity. Furthermore, recent strides in next-generation sequencing (NGS) technologies, including whole–genome sequencing (WGS), targeted sequencing (TS), metagenomic sequencing (MS), and RNA sequencing (transcriptome sequencing), have revolutionized the landscape of dirofilariasis diagnostics. Emerging techniques such as loop-mediated isothermal amplification (LAMP), digital PCR (dPCR), and digital microfluidics are also explored for their potential to augment diagnostic accuracy. The review addresses challenges associated with standardizing molecular protocols, tackling false positives/negatives, and discusses the advantages and limitations of each technique. By providing a comprehensive overview of dirofilariasis diagnostic strategies, from traditional to cutting-edge methods, this review aims to enhance understanding of the disease’s diagnostic landscape. The insights gained have implications for improved disease management and guide future research endeavors toward refining diagnostic protocols and advancing therapeutic interventions.

Introduction: The clinical implementation of deep inspiratory breath-hold (DIBH) radiotherapy to reduce cardiac exposure in patients with left-sided breast cancer is challenging with helical tomotherapy(HT) and has received little attention. We describe our novel approach to DIBH irradiation in HT using a specially designed frame and manual gating, and compare cardiac substructure doses with the free-breathing (FB) technique. Material and methods: The workflow incorporates staggered junctions and a frame that provides tactile feedback to the patient and monitoring for manual cut-off. The treatment parameters and clinical outcome of 20 patients with left-sided breast cancer who have undergone DIBH radiotherapy as a part of an ongoing prospective registry are reported. All patients underwent CT scans in Free Breathing (FB) and DIBH using the in-house Respiframe, which incorporates a tactile feedback-based system with an indicator pencil. Plans compared target coverage, cardiac doses, synchronizing treatment with breath-hold and avoiding junction repetition. MVCT scans are used for patient alignment. Results: The mean dose (Dmean) to the heart was reduced by an average of 34 % in DIBH-HT compared to FB-HT plans (3.8 Gy vs 5.7 Gy). Similarly, 32 % and 67.8 % dose reduction were noted in the maximum dose (D0.02 cc) of the left anterior descending artery, mean 12.3 Gy vs 18.1 Gy, and mean left ventricle V5Gy 13.2 % vs 41.1 %, respectively. The mean treatment duration was 451.5 sec with a median 8 breath-holds; 3 % junction locations between successive breath-holds were replicated. No locoregional or distant recurrences were observed in the 9-month median follow-up. Conclusion: Our workflow for DIBH with Helical-Tomotherapy addresses patient safety, treatment precision and challenges specific to this treatment unit. The workflow prevents junction issues by varying daily breath-hold durations and avoiding junction locations, providing a practical solution for left-sided breast cancer treatment with HT.

BackgroundThe most widely used copper intrauterine device (IUD) in the world (the TCu380A), and the only product available in many countries, causes side effects and early removals for many users. These problems are exacerbated in nulliparous women, who have smaller uterine cavities compared to parous women. We compared first-year continuation rates and reasons/probabilities for early removal of the TCu380A versus a smaller Belgian copper IUD among nulliparous users.MethodsThis 12-month interim report is derived from a pre-planned interim analysis of a sub population and focused on key secondary comparative endpoints. In this participant-blinded trial at 16 centres in the USA, we randomised participants aged 17-40 in a 4:1 ratio to the NT380-Mini or the TCu380A. In the first year, participants had follow-up visits at 6-weeks and 3, 6, and 12-months, and a phone contact at 9 months; we documented continued use, expulsions, and reasons for removal. Among participants with successful IUD placement, we compared probabilities of IUD continuation and specific reasons for discontinuation using log-rank tests. This trial is registered with ClinicalTrials.gov number NCT03124160 and is closed to recruitment.FindingsBetween June 1, 2017, and February 25, 2019, we assigned 927 nulliparous women to either the NT380-Mini (n = 744) or the TCu380A (n = 183); the analysis population was 732 (NT380-Mini) and 176 (TCu380A). Participants using the NT380-Mini, compared to the TCu380A, had higher 12-month continuation rates (78·7% [95% CI: 72·9-84·5%] vs. 70·2% [95% CI: 59·7-80·7], p = 0·014), lower rates of removal for bleeding and/or pain (8·1% vs. 16·2%, p = 0·003) and lower IUD expulsion rates (4·8% vs. 8·9%, p = 0·023), respectively.InterpretationThe NT380-Mini offers important benefits for a nulliparous population compared to the TCu380A in the first twelve months, when pivotal experiences typically occur. Higher continuation rates with the NT380-Mini may avert disruptions in contraceptive use and help users avoid unintended pregnancy.FundingBill & Melinda Gates Foundation, Eunice Kennedy Shriver National Institute of Child Health and Human Development, and Mona Lisa, N.V. (Belgium).

Identifying lung sound signal patterns is essential for detecting and monitoring respiratory diseases. Existing approaches for analyzing respiratory sounds need domain specialists. Therefore, an accurate and automated lung sound classification tool is required. In this paper, we have developed an automatic diagnostic system to classify these signals. It can support healthcare systems in low-resource environments with limited resources and a shortage of qualified medical professionals. This paper presents an eigenvectors-based data augmentation method to enhance the detection rate of automatic diagnostic systems. This proposed method provides noise-free data samples with the principal components that capture the most significant variations in the data. In the classification process, various machine learning-based classifiers are employed along with spectrogram-based features.

The cardiovascular system is responsible for carrying the blood along with nutrition and oxygen throughout the body. This system consists of heart, blood, and blood vessels. The experts, or doctors called as cardiologists, analyze the sounds of heart’s (lub-dub) beat and flow of blood to diagnose Cardio Vascular Disease (CVD) using a traditional stethoscope and phonological cardiogram technique. Through the stethoscope, the cardiologist will listen to vibration produced by heart beat and heart beat sound and murmur sound are popularly known as phonocardiogram (PCG) signals, which are being recorded for medical diagnosis purposes using a stethoscope. The development of a technique for the automatic recognition of HVD’s assists the experts in recognizing the CVD effectively in the initial stage itself from PCG signals. There are many tools available to help doctors in a clinical setting for the accurate diagnose the CVD in a less time. The main aim of this proposed work is to provide an Artificial Intelligence (AI) based PCG signal analysis for the automatic and early detection of various cardiac conditions using supervised and unsupervised Recurrent Neural Network (RNN) based Bidirectional Long Short-Term Memory (Bi-LSTM) Machine Learning (ML) algorithm. Along with this algorithm, Generative Adversarial Networks (GAN’s) is considered because they can create fresh, high-quality, pseudo-real data that resembles their training set which has been demonstrated by using their two unique networks: Discriminator Network (DN) and the Generator Network (GN). The proposed method is tested using heart sound signals from the well-known, freely accessible PhysioNet and Kaggle datasets. The Experimental results are validated based accuracy, precision, F1-score, sensitivity, and specificity.

In patients with ischemic brain stroke, collateral circulation plays a crucial role in selecting patients suitable for endovascular therapy. The presence of well-developed collaterals improves the patient’s chances of recovery. In clinical practice, the presence of collaterals is diagnosed on a Computed Tomography Angiography scan. The radiologist grades it on the basis of subjective visual assessment, which is prone to interobserver and intraobserver variability. Computer-based methods of collateral assessment face the challenge of non-uniform scan volume, leading to manual selection of slices, meaning that the most imperative slices have to be manually selected by the radiologist. This paper proposes a multilevel multimodal hierarchical framework for automated collateral scoring. Specifically, we propose deploying a Convolutional Neural Network for image selection based on the visibility of collaterals and a multimodal model for comparing the occluded and contralateral sides of the brain for collateral scoring. We also generate a patient-level prediction by integrating automated machine learning in the proposed framework. While the proposed multimodal predictor contributes to Artificial Intelligence, the proposed end-to-end framework is an application in engineering. The proposed framework has been trained and tested on 116 patients, with five-fold cross-validation, achieving an accuracy of 91.17% for multi-class collateral scores and 94.118% for binary class collateral scores. The proposed multimodal predictor achieved a weighted F1 score of 0.86 and 0.95 on multi-class and binary-class collateral scores, respectively. The proposed framework is fast, efficient, and scalable for real-world deployments. Automated evaluation of collaterals with attention maps for explainability would complement radiologists’ efforts. Code for the proposed framework is available at: https://github.com/rishiraj-cs/collaterals_ML_MM.

Effective research has been aimed at increasing the distributed compute dependent Software Define Network (SDN) with high-level Intelligent - Internet of Things (I-IoT). Wireless sensor networks come with a set of resource restrictions. Still, only a few functions are often configured such as energy restraint and the concerted demands that are vital for IoT application routing performance. A major technique for solving the expansion of network scalability by applying Mobile Sink (MS). The construction of data transmission optimal path, the detection of an optimal set data-gathering points $O_{DG} $ and MS scheduled with dynamic networks for energy-efficient techniques, that the network’s lifetime in enormous complications, principally in large-scale IoT networks. The research work proposes an Research Objective: i) Develop an energy-efficient routing technique for large-scale I-IoT networks within a cloud-based SDN system. ii) Optimize network scalability, lower-level routing, and load balancing using Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). The prime aim of cloud-based SDN with AI is to determine: a lower level routing in the perception layer, a load-balanced Cluster Table (CT), an optimal $O_{DG} $ points, and MS optimal paths $O_{MSpath} $ . The main contribution of proposed routing is i) Energy Minimization (EM): The proposed routing minimizes energy dissemination by the Cluster Head (CH) in critical conditions (EM-CH). ii) Enhanced Energy Balance (EEB): The EC-based SDN, considering both Optimal Data-Gathering ( $O_{DG}$ ) and Mobile Sink (MS) advancements, achieves enhanced energy balance during network routing (EEB-SDN). Research results validate the proposed model stability that improves the network lifetime up to 63%, the energy usage in the network is reduced up to 78%, the high volume data loaded to the MS up to 95%, and the delay of the $O_{MSpath} $ by 69% when compared with various model.