Miracle-dz/UniFAR-FTUs huggingface dataset:
Common Diagnostic Challenges and Pitfalls in Segmental Colitis Associated with Diverticulosis (SCAD)

Segmental colitis associated with diverticulosis (SCAD) is characterized by inflammation involving the sigmoid inter-diverticular mucosa, sparing the proximal colon and rectum. Due to the heterogeneity of clinical manifestations and endoscopic and histological findings, SCAD diagnosis might be challenging in clinical practice. This narrative review aimed to report the SCAD diagnostic criteria adopted in different studies, highlighting the current challenges and main pitfalls in its diagnosis. We analysed fourteen studies, mainly prospective observational studies. Haematochezia and rectal bleeding were the main complaints leading to diagnosis, followed by diarrhoea. An accurate endoscopic description was performed in 86% of studies, while a standardised biopsy sampling protocol (sigma, proximal colon and rectum) was scarcely adopted, being complete only in 28.5% of studies. The evaluation of concomitant drugs potentially inducing colitis was carried out in only 57% of studies. Great heterogeneity in sigmoid endoscopic (edema, erythema, erosions, ulcers, mucosal friability) and histological findings (chronic and/or acute inflammatory infiltrate) was observed. We showed that SCAD diagnosis is often based on not fully adequate macroscopic colonic description and scant biopsy protocol sampling. An accurate clinical and endoscopic evaluation, with an adequate sampling biopsy protocol, with attention to differential diagnosis, seemed to be crucial for a prompt SCAD diagnosis.
Novel PCR-RFLP for detecting single nucleotide polymorphism in exon1 of GPR54 gene and its association with age at first kidding in goats*

*Part of Ph.D. work Present address: 1Assistant Professor (radhikag@kvasu.ac.in), Department of Animal Genetics and Breeding, 5Professor (mercey@kvasu.ac.in), Department of Statistics, College of Veterinary and Animal Sciences, 2,4Professor (raghavan @kvasu.ac.in, aravindakshantv@kvasu.ac.in), 3Research Associate (stephytns@gmail.com), 6Associate Professor (thirupathy@kvasu.ac.in), CASAGB, Mannuthy. KiSS peptides are considered as upstream regulators of gonadotropin releasing hormone (GnRH) neurons which regulate reproduction. KiSS peptins, peptide products of KiSS1 gene act as ligands of the G-Protein Coupled Receptor 54 gene [GPR54] otherwise termed as KiSS1R. Studies in human and mice confirmed the role of KiSS1 and GPR54 genes in reproductive maturation and function. Possible associations between variations in KiSS 1 and GPR54 genes with litter size and sexual precocity in goats were reported (Feng et al. 2010, Hou et al. 2011). Malabari and Attapady Black are two native goat breeds of Kerala, India and have definite difference in reproductive function. Malabari goats have high prolificacy with higher twinning percentage (Anonymous 2004). Age at first kidding (AFK) was also significantly lower in Malabari goats compared to Attapady Black (Stephen et al. 2005). Hence an effort was made to explore the polymorphism of exon 1 of GPR54 in Malabari and Attappadi Black goats and to analyse the association between SNP, if any, with AFK and litter size (LS) in these animals. Goats (120) including Attappady Black (50) and Malabari (70) were used for study. Genomic DNA was isolated from venous jugular blood using standard phenolchloroform extraction procedure (Sambrook et al. 1989). Primers were chosen from available literature (Feng et al. 2010) and custom synthesized commercially to amplify exon 1 of GPR54 gene. Forward primer : 5’GGCAATGCAGCCCTTGTC 3’ Reverse primer : 5’ ACCGATGTAGAAGTTGGTCAC 3’ Polymerase chain reaction (PCR) was performed with a total volume of 20 μl, containing 150 ng of DNA template, 2 μl 10X PCR buffer, 1.2 mM MgCl2, 10pM of each primer, 200μM of dNTP and 1 unit of Taq DNA polymerase. The Indian Journal of Animal Sciences 85 (9): 1056–1058, September 2015/Short communication https://doi.org/10.56093/ijans.v85i9. 51760
Convolutional Neural Networks Adapted for Regression Tasks: Predicting the Orientation of Straight Arrows on Marked Road Pavement Using Deep Learning and Rectified Orthophotography

Arrow signs found on roadway pavement are an important component of modern transportation systems. Given the rise in autonomous vehicles, public agencies are increasingly interested in accurately identifying and analysing detailed road pavement information to generate comprehensive road maps and decision support systems that can optimise traffic flow, enhance road safety, and provide complete official road cartographic support (that can be used in autonomous driving tasks). As arrow signs are a fundamental component of traffic guidance, this paper aims to present a novel deep learning-based approach to identify the orientation and direction of arrow signs on marked roadway pavements using high-resolution aerial orthoimages. The approach is based on convolutional neural network architectures (VGGNet, ResNet, Xception, and DenseNet) that are modified and adapted for regression tasks with a proposed learning structure, together with an ad hoc model, specially introduced for this task. Although the best-performing artificial neural network was based on VGGNet (VGG-19 variant), it only slightly surpassed the proposed ad hoc model in the average values of the R2 score, mean squared error, and angular error by 0.005, 0.001, and 0.036, respectively, using the training set (the ad hoc model delivered an average R2 score, mean squared error, and angular error of 0.9874, 0.001, and 2.516, respectively). Furthermore, the ad hoc model’s predictions using the test set were the most consistent (a standard deviation of the R2 score of 0.033 compared with the score of 0.042 achieved using VGG19), while being almost eight times more computationally efficient when compared with the VGG19 model (2,673,729 parameters vs VGG19′s 20,321,985 parameters).
14C Ages of a Varved Last Glacial Maximum Section Off Pakistan

In a core off Pakistan, we obtained 38 14C analyses by accelerator mass spectrometry (AMS) from a 4.4-m-thick, expanded, annually-laminated Last Glacial Maximum (LGM) section, bracketed by bioturbated intervals ascribed to the Heinrich-1 (H1) and Heinrich-2 (H2) equivalent events (52 14C analyses between 24–15 kyr BP). A floating varve age scale, anchored to the oxygen isotope record of the layer-counted GISP2 ice core at the H2/LGM boundary, results in an annually dated record for the LGM from 23,450–17,900 cal BP. The floating varve scale of the LGM provides us with a tentative calibration of local marine AMS 14C age dates to calendar years.
Measuring outcomes of rehabilitation among the elderly—a feasibility study

A feasible system for measuring patient outcomes of rehabilitation is required for assessing the real-world cost-effectiveness of rehabilitation. This study aims to assess the feasibility of measuring outcomes of rehabilitation among elderly individuals with early-stage Alzheimer's. We used the principles of Design Science to construct a set of metrics consisting of standardized PROM (Patient-Reported Outcome Measure) questionnaires, clinician-reported measures, and observational measures of functioning. We used standardized questionnaires whenever possible to ensure the validity and reliability of the questionnaires. The set of metrics was piloted on 16 individuals living at home with regular home care services. After the pilot, we further refined the set of metrics based on relevance, sensitivity to change, and applicability. We found that measurement was feasible and we propose the final set of metrics as a minimum set, which could be further improved upon by addition of metrics relevant to each subgroup of elderly individuals. We also found that using self-reported questionnaires in this population is not without difficulties. We therefore suggest that the role of informal caregivers be considered, and that accessibility of outcome questionnaires be improved.
Proper choice of hyperparameters in reservoir computing of chaotic maps

Reservoir computing (RC) are powerful to learn and predict dynamical behaviors. However, it has been found that both the reservoir size and the hyperparameters can greatly affect the learning ability of RC on dynamical systems, the mechanism of which still remains unclear. This paper discusses the influence of hyperparameters of RC with different sizes of reservoir on learning typical chaotic maps. An analytic method is purposed to obtain the hyperparameters that can exhibit better learning ability of RC by analyzing high order derivatives of the error loss function. In the case of RC with one or two nodes, the well-performing hyperparameters are analytically obtained for learning the logistic map, which are consistent with numerical results. The analytic method also shows its ability in RC with multiple nodes to learn singer and sine chaotic maps. This work provides deeper insight in learning and predicting behaviors of RC as well as presents guidance for the selection of hyperparameters of RC to learn chaotic systems.
Compiling for Encrypted Computing: Obfuscation but Not in Name

Encrypted computing is the emerging science and technology of processors that take encrypted inputs to encrypted outputs via encrypted intermediates (at nearly conventional speeds). The aim is to make user data in general-purpose computing secure against the operator and operating system as potential adversaries. A stumbling block has always been that memory addresses are data and good encryption means the encrypted value varies randomly, and that makes hitting any target in memory problematic without address decryption, but decryption anywhere on the memory path would open up many easily exploitable vulnerabilities. This paper `solves compilation' for processors without address decryption, covering all of ANSI C while satisfying the required security properties and opening up encrypted computing for the standard software toolchain and infrastructure. An `obfuscation' for this context is quantified exactly, leading to an argument that security against polynomial-time attacks has been achieved for user data, with or without encryption.
Exploring mental well-being, the emotional impact of visual impairment and experiences of prejudice and discrimination among adults from minority ethnic communities in the UK

Background Visual impairment (V.I.) has been associated with a negative impact on mental health outcomes, including a process of grief among those who lose their sight. Older adults with V.I. who had experienced discrimination have been found to be at increased risk of depression, loneliness, poorer life satisfaction and poorer quality of life. Adults from minority ethnic communities (MEC) may be at increased risk of V.I. and yet, research on the experiences of MEC adults with V.I. remains limited. This article forms part of a series which explores issues and status among MEC adults living with V.I. in the UK. Methods A secondary analysis of V.I. Lives survey data was performed to explore mental well-being assessed by the short Warwick-Edinburgh Mental Well-being scale (SWEMWBS), the emotional impact of V.I. , and prejudice and discrimination among a matched control sample of 77 MEC and 77 adults from white communities (WC). Participants were matched by age, gender, UK region and urban/rural setting. Subgroup analyses were also conducted for the two largest MEC subgroups, Asian (n = 46) and black participants (n = 22). Results There were few statistically significant differences between the groups. MEC participants were significantly more likely than WC participants to rate emotional support to come to terms with their V.I. as important and to feel optimistic about their V.I. but they were significantly less likely to agree that they were receiving the level of emotional support they needed to get on with their life. Within the MEC group, participants from Asian communities had significantly poorer mental well-being, and they were also significantly more likely to agree that the general public were often prejudiced against people with V.I. and less likely to feel optimistic about their V.I. than black participants. Conclusion Although there were few statistically significant differences, participants from Asian communities were more likely to report poor mental and emotional well-being, and experiences of discrimination, than black and white participants. In contrast, participants from black communities fared the same as, or in some cases better than, white participants. Future research will need to confirm these findings and explore reasons for these.
Effect of stepped Si (001) substrate on Cu thin film growth

The growth processes of Cu thin film on stepped Si(001) substrate were investigated using molecular dynamics simulation. The modified embedded atom method was used to describe the atomic interaction between Cu-Cu, Si-Si, and Si-Cu. In this study, four different Si(001) substrate configurations were examined: (i) flat Si(001) substrate; (ii) stepped Si surface with 3-monoatomic layers step; (iii) Stepped Si surface with 5-monoatomic layers step; (iiii) stepped surface with 7-monoatomic layers. Our aim here is to investigate the effect of stepped substrate on the structure, the surface roughness, and the morphology of deposited Cu thin film. The results show that the Cu film obtained has a crystalline structure based on the radial distribution function. In addition, the morphology of Cu film is not smooth for the different stepped substrates. More precisely, the surface roughness increases when the substrate presents a step and rises with the augmentation of the step height. On the other hand, our results reveal that the penetration of Cu atoms in the simplest case of the flat configuration is limited to the top layer of the substrate. While for the stepped substrate, our findings show that the penetration in the stepped substrate is more important and deeper within the upper terrace compared to the lower terrace. Furthermore, the numerical calculations demonstrate that the step height has no significant effect on the penetration of Cu atoms on the Si(001) stepped substrate. These results are appropriate for the deposition of copper atoms into the stepped substrate of silicon.
Holographic Description of Noncommutative Schwinger Effect

We consider the phenomenon of spontaneous pair production in presence of an external electric field for noncommutative Yang Mills theories. Using Maldacena's holographic conjecture the threshold electric field for pair production is computed from the quark-antiquark potential for noncommutative theories. As an effect of noncommutativity, the threshold electric field is seen to be smaller than its commutative counterpart. We also estimate the correction to the pair production rate of quark-antiquark pairs to the first order of the noncommutative deformation parameter. Our result bears resemblance with an earlier work (based on field theoretic methods).
Effects of Four Photo-Selective Colored Hail Nets on an Apple in Loess Plateau, China

Hail, known as an agricultural meteorological disaster, can substantially constrain the growth of the apple industry. Presently, apple orchards use a variety of colored (photo-selective) hail nets as a preventative measure. However, it is unclear which color proves most effective for apple orchards. This study provides a systematic investigation of the impact of four photo-selective colored hail nets (white, blue, black, and green; with white being the control) on the microenvironment of apple orchards, fruit tree development, fruit quality, and yield over a two-year period (2020–2021). Different photo-selective nets do not evidently alter the intensity of light, although the nets’ shading effects decrease in the order from black to green to blue. Among them, blue nets increased the proportion of blue light, while green nets enhanced the proportion of green light. On the other hand, black, green, and blue nets diminished the proportion of red and far-red light. Such photo-selective nets effectively lowered soil temperature but did not have an impact on relative humidity and air temperature. Encasing apple trees with blue nets promoted growth, increasing shoot length, thickness, leaf area, and water content, while simultaneously decreasing leaf thickness. Black nets had comparable effects, although the impacts of green nets were inconsistent. Different photo-selective nets did not significantly influence the leaf shape index or overall chlorophyll content. However, black and green nets reduced the chlorophyll a/b ratio, while blue nets slightly boosted this ratio. Additionally, blue nets proved beneficial for apple trees’ photosynthesis. With the employment of a principal component analysis and comprehensive evaluation, this study concludes that blue nets offer the most favorable environmental conditions for apple growth while protecting apple orchards against hail, compared to black, white, and green nets.
Unleashing the power of complement activation: unraveling renal damage in human anti-glomerular basement membrane disease

Anti-glomerular basement membrane (GBM) disease is a rare but life-threatening autoimmune disorder characterized by rapidly progressive glomerulonephritis with or without pulmonary hemorrhage. Renal biopsies of anti-GBM patients predominantly show linear deposition of IgG and complement component 3 (C3), indicating a close association between antigen-antibody reactions and subsequent complement activation in the pathogenesis of the disease. All three major pathways of complement activation, including the classical, lectin, and alternative pathways, are involved in human anti-GBM disease. Several complement factors, such as C3, C5b-9, and factor B, show a positive correlation with the severity of the renal injury and act as risk factors for renal outcomes. Furthermore, compared to patients with single positivity for anti-GBM antibodies, individuals who are double-seropositive for anti-neutrophil cytoplasmic antibody (ANCA) and anti-GBM antibodies exhibit a unique clinical phenotype that lies between ANCA-associated vasculitis (AAV) and anti-GBM disease. Complement activation may serve as a potential “bridge” for triggering both AAV and anti-GBM conditions. The aim of this article is to provide a comprehensive review of the latest clinical evidence regarding the role of complement activation in anti-GBM disease. Furthermore, potential therapeutic strategies targeting complement components and associated precautions are discussed, to establish a theoretical basis for complement-targeted therapies.
Nonlinear Associations between Physical Function, Physical Activity, Sleep, and Depressive Symptoms in Older Adults

The purpose of this study is to examine how physical function, physical activity, and sleep are related to depressive symptoms in older adults using a nonlinear model. The participants were 283 Korean older adults aged 65 and older who met the study inclusion criteria. Depressive symptoms were measured using the shortened version of the Geriatric Depression Scale in Korean (SGDS-K). Physical activity and sleep time were objectively quantified by continuously monitoring participants over 20 consecutive days using a triaxial accelerometer. Physical function was evaluated using five distinct measurements: grip strength, gait speed, the Timed Up and Go Test (TUG), the Six-Minute Walk Test (SMWT), and the Five Times Sit to Stand Test (FTSST). The SMWT, gait speed, and MVPA exhibited a nonlinear relationship with depressive symptoms. However, other physical functions showed linear relationships. Also, sleep time showed a U-shaped trend starting at approximately 390 min. After adjusting for age, sex, drinking, and smoking in the logistic regression model, SMWT, MVPA, and sleep time were significantly associated with depressive symptoms. The outcomes highlight the importance of considering multiple factors in understanding depression among the elderly, particularly the intricate interactions between these elements and biological rhythms.
Disease Prediction Using a Modified Multi-Layer Perceptron Algorithm in Diabetes

This paper presents an adaptation of the Multi-Layer Perceptron (MLP) algorithm for use in predicting diabetes risk. The aim is to enhance the accuracy and generalizability of the model by incorporating preprocessing techniques, dimensionality reduction using Principal Component Analysis (PCA), and improvements in optimization and regularization. Several factors, including glucose level, pregnancy, blood pressure, and body mass index, are taken into account when analyzing the PIMA Indian Diabetes dataset. Modern optimization methods, dropout regularization, and an adaptive learning rate are incorporated into the modified MLP model to fine-tune the model's weights and boost its predictive abilities. The effectiveness of the modified MLP algorithm is evaluated by comparing its performance with baseline machine learning methods and the original MLP algorithm in terms of accuracy, sensitivity, and specificity. The results of this study can improve the quality of healthcare provided to people at risk for developing diabetes and thus contribute to the development of better prediction models for the disease.
Behaviour change, the itchy spot of healthcare quality improvement: How can psychology theory and skills help to scratch the itch?

Despite the clear utility and transferability, National Health Service (NHS) quality improvement initiatives have yet to benefit fully from what is already known within health psychology. Thus far, evidence from established, seminal behaviour change theory and practice have been ignored in favour of newly developed models and frameworks. Further, whilst there is a growing interest in what is commonly referred to as ‘human factors’ of change and improvement, there is scant transferability of known psychologically informed implementation skills into routine NHS Improvement practice. The science and practice of healthcare improvement is growing, and the behaviour change aspect is critical to sustainable outcomes. Therefore, this paper offers practical guidance on how seminal psychological behaviour change theory and motivational interviewing (a person-centred skills-based approach specifically developed to support people through change) can be combined to better address individual and organisational change within a healthcare improvement context.
Fine-scale measurement of reactive solutes in armoured riverbed sediments

3. METHODS We used DET to give 1cm resolution reactive solute (NO3 -, SO4 2-, Fe and Mn) concentration profiles for the upper 15cm of the riverbed. Sample sites were established along the length of the zone of elevated hydrological flux and pore water solutes (Figure 1 and 2). Field deployment of DET probes in the armoured riverbed, and extraction and analysis of solutes, followed the methodology of Ullah et al. (2012).