Miracle-dz/UniFAR-FTUs huggingface dataset:
The involvement of microRNAs in HCV and HIV infection

Approximately 2.3 million people are suffering from human immunodeficiency virus (HIV)/hepatitis C virus (HCV) co-infection worldwide. Faster disease progression and increased mortality rates during the HIV/HCV co-infection have become global health concerns. Effective therapeutics against co-infection and complete infection eradication has become a mandatory requirement. The study of small non-coding RNAs in cellular processes and viral infection has so far been beneficial in various terms. Currently, microRNAs are an influential candidate for disease diagnosis and treatment. Dysregulation in miRNA expression can lead to unfavorable outcomes; hence, this exact inevitable nature has made various studies a focal point. A considerable improvement in comprehending HIV and HCV mono-infection pathogenesis is seen using miRNAs. The prominent reason behind HIV/HCV co-infection is seen to be their standard route of transmission, while some pieces of evidence also suspect viral interplay between having a role in increased viral infection. This review highlights the involvement of microRNAs in HIV/HCV co-infection, along with their contribution in HIV mono- and HCV mono-infection. We also discuss miRNAs that carry the potentiality of becoming a biomarker for viral infection and early disease progression.
Current Advances in the Development of Hydrogel-Based Wound Dressings for Diabetic Foot Ulcer Treatment

Diabetic foot ulcers (DFUs) are one of the most prevalent complications associated with diabetes mellitus. DFUs are chronic injuries that often lead to non-traumatic lower extremity amputations, due to persistent infection and other ulcer-related side effects. Moreover, these complications represent a significant economic burden for the healthcare system, as expensive medical interventions are required. In addition to this, the clinical treatments that are currently available have only proven moderately effective, evidencing a great need to develop novel strategies for the improved treatment of DFUs. Hydrogels are three-dimensional systems that can be fabricated from natural and/or synthetic polymers. Due to their unique versatility, tunability, and hydrophilic properties, these materials have been extensively studied for different types of biomedical applications, including drug delivery and tissue engineering applications. Therefore, this review paper addresses the most recent advances in hydrogel wound dressings for effective DFU treatment, providing an overview of current perspectives and challenges in this research field.
Income inequality and human capital allocation

This study discusses the relationship between income inequality and human capital allocation in China. We categorise income inequality into intersectoral (state-versus non-state owned) and intergenerational income inequality. Based on relevant theoretical assumptions and empirical tests using existing regional data, we find that income inequality influences regional human capital allocation in China in three ways. First, intersectoral income inequality has a negative impact on regional human capital mismatch (i.e., inconsistency between job skill requirements and workers ’ actual skills). Second, intergenerational income inequality positively affects regional human capital mismatch. Third, the interaction of intersectoral and intergenerational income inequality has a negative impact on human capital mismatch. Thus, we observe differences in the net impact of intersectoral and intergenerational income inequality on human capital mismatch in China. The net impact of intersectoral income inequality on human capital mismatch is persistently negative, while the impact of intergenerational income inequality on human capital mismatch is contingent upon the degree of regional intersectoral income inequality. However, the imbalance in China ’ s regional development creates discrepancies in the relationship between improvement in income equality across regions and optimisation of human capital allocation. Thus, the process of formulating relevant policies must be regional, long-term based, and phased.
The expanding roles of neuronal nitric oxide synthase (NOS1)

The nitric oxide synthases (NOS; EC 1.14.13.39) use L-arginine as a substrate to produce nitric oxide (NO) as a by-product in the tissue microenvironment. NOS1 represents the predominant NO-producing enzyme highly enriched in the brain and known to mediate multiple functions, ranging from learning and memory development to maintaining synaptic plasticity and neuronal development, Alzheimer’s disease (AD), psychiatric disorders and behavioral deficits. However, accumulating evidence indicate both canonical and non-canonical roles of NOS1-derived NO in several other tissues and chronic diseases. A better understanding of NOS1-derived NO signaling, and identification and characterization of NO-metabolites in non-neuronal tissues could become useful in diagnosis and prognosis of diseases associated with NOS1 expression. Continued investigation on the roles of NOS1, therefore, will synthesize new knowledge and aid in the discovery of small molecules which could be used to titrate the activities of NOS1-derived NO signaling and NO-metabolites. Here, we address the significance of NOS1 and its byproduct NO in modifying pathophysiological events, which could be beneficial in understanding both the disease mechanisms and therapeutics.
Deep Learning-Based Mental Health Model on Primary and Secondary School Students' Quality Cultivation

The purpose was to timely identify the mental disorders (MDs) of students receiving primary and secondary education (PSE) (PSE students) and improve their mental quality. Firstly, this work analyzes the research status of the mental health model (MHM) and the main contents of PSE student-oriented mental health quality cultivation under deep learning (DL). Secondly, an MHM is implemented based on big data technology (BDT) and the convolutional neural network (CNN). Simultaneously, the long short-term memory (LSTM) is introduced to optimize the proposed MHM. Finally, the performance of the MHM before and after optimization is evaluated, and the PSE student-oriented mental health quality training strategy based on the proposed MHM is offered. The results show that the accuracy curve is higher than the recall curve in all classification algorithms. The maximum recall rate is 0.58, and the minimum accuracy rate is 0.62. The decision tree (DT) algorithm has the best comprehensive performance among the five different classification algorithms, with accuracy of 0.68, recall rate of 0.58, and F1-measure of 0.69. Thus, the DT algorithm is selected as the classifier. The proposed MHM can identify 56% of students with MDs before optimization. After optimization, the accuracy is improved by 0.03. The recall rate is improved by 0.19, the F1-measure is improved by 0.05, and 75% of students with MDs can be identified. Diverse behavior data can improve the recognition effect of students' MDs. Meanwhile, from the 60th iteration, the mode accuracy and loss tend to be stable. By comparison, batch_size has little influence on the experimental results. The number of convolution kernels of the first convolution layer has little influence. The proposed MHM based on DL and CNN will indirectly improve the mental health quality of PSE students. The research provides a reference for cultivating the mental health quality of PSE students.
A Learning-based Control Architecture for Socially Assistive Robots Providing Cognitive Interventions

Due to the world’s rapidly growing elderly population, dementia is becoming increasingly prevalent. This poses considerable health, social, and economic concerns as it impacts individuals, families and healthcare systems. Current research has shown that cognitive interventions may slow the decline of or improve brain functioning in older adults. This research investigates the use of intelligent socially assistive robots to engage individuals in personcentered cognitively stimulating activities. Specifically, in this thesis, a novel learning-based control architecture is developed to enable socially assistive robots to act as social motivators during an activity. A hierarchical reinforcement learning approach is used in the architecture so that the robot can learn appropriate assistive behaviours based on activity structure and personalize an interaction based on the individual’s behaviour and user state. Experiments show that the control architecture is effective in determining the robot’s optimal assistive behaviours for a memory game interaction and a meal assistance scenario.
A Novel Interposer Channel Structure with Vertical Tabbed Vias to Reduce Far-End Crosstalk for Next-Generation High-Bandwidth Memory

In this paper, we propose and analyze a novel interposer channel structure with vertical tabbed vias to achieve high-speed signaling and low-power consumption in high-bandwidth memory (HBM). An analytical model of the self- and mutual capacitance of the proposed interposer channel is suggested and verified based on a 3D electromagnetic (EM) simulation. We thoroughly analyzed the electrical characteristics of the novel interposer channel considering various design parameters, such as the height and pitch of the vertical tabbed via and the gap of the vertical channel. Based on the frequency-dependent lumped circuit resistance, inductance, and capacitance, we analyzed the channel characteristics of the proposed interposer channel. In terms of impedance, insertion loss, and far-end crosstalk, we analyzed how much the proposed interposer channel improved the signal integrity characteristics compared to a conventional structure consisting of micro-strip and strip lines together. Compared to the conventional worst case, which is the strip line, the eye-width, the eye-height, and eye-jitter of the proposed interposer channel were improved by 17.6%, 29%, and 9.56%, respectively, at 8 Gbps. The proposed interposer channel can reduce dynamic power consumption by about 28% compared with the conventional interposer channel by minimizing the self-capacitance of the off-chip channel.
Utjecaj informacije na provedbu zaštite zdravlja i sigurnost na radu

Rad prikazuje analizu osnovnih postavki teorije informacija s težištem na njezin utjecaj na provedbu zaštite zdravlja i sigurnosti na radu. Koncept informacije danas se koristi u gotovo svim područjima unutar vlastitog konteksta. Pri tome je taj koncept primjene specifičan fenomen koji proizlazi iz naravi neke znanstvene discipline. Prvi dio rada prikazuje povezanost teorije informacije s provedbom zdravlja i sigurnosti na radu, uz definiranje cilja, svrhe, zadataka i metoda istraživanja. U drugom dijelu rada prikazuju se osnovne postavke teorije informacije uz definiranje informacije u području semiotike. Osim toga, razmatra se sintaktički, semantički, pragmatički i estetski aspekt informacije i utjecaj navedenog u području zaštite zdravlja i sigurnosti na radu. Ističe se utjecaj informacije na provedbu zaštite zdravlja i sigurnost na radu, posebno s aspekta točnog prenošenja i razumijevanja svih relevantnih informacija. Zaštita zdravlja i sigurnost na radu sastavni je dio svakog radnog procesa, pri čemu je značaj prijenosa točnih i aktualnih informacija svakim danom sve važniji. Stoga se zaključuje da je utjecaj informacija na provedbu zaštite zdravlja i sigurnost na radu vrlo velik, a u nekim situacijama i presudan za sigurno obavljanje poslova i radnih zadataka.
Effect of Oregano (Lippia graveolens) Essential Oil as a Phytogenic Feed Additive on Productive Performance, Ruminal Fermentation, and Antioxidant Activity in Lamb Meat

The objective of this study was to evaluate the inclusion of oregano essential oil (OEO) as a phytogenic feed additive in the diet of lambs on the productive performance, ruminal pH, ammoniacal nitrogen production, volatile fatty acids, nitrogen balance, carcass yield, backfat thickness, loin eye (Longissimus dorsi) area, shelf life, and antioxidant activity of the meat. Thirty-nine Suffolk × Hampshire lambs (19 ± 3.7 kg live weight) were used in a completely randomized design with three treatments (n = 13) consisting of 0, 0.02, and 0.04% OEO in the diet. The inclusion of OEO in the diet did not affect (p > 0.05) the productive performance due to the treatments; similarly, no differences (p > 0.05) were observed in the ruminal variables and nitrogen balance. Backfat thickness and loin eye area had similar results (p > 0.05), and the antioxidant activity in meat was improved (p < 0.05) with the inclusion of OEO. Shelf life and crude protein content increased (p < 0.05) with the inclusion of OEO in the diet and with the passing of storage days. Dry matter was affected (p < 0.05) by the storage time, with a decrease observed on day 24. pH, ether extract, and ash were not affected (p > 0.05). It is concluded that the productive performance, ruminal variables, nitrogen balance, loin eye area, backfat thickness, and carcass yield were not affected by the inclusion of OEO. However, crude protein remained stable and antioxidant activity improved, increasing the shelf life of lamb meat.
The Influence of the Belt and Road Initiative on the Technological Upgrade of Enterprises in Countries and Regions along the Belt and Road: Study based on Difference-in-difference Model

Remarkably, the Belt and Road Initiative has increasingly injected important impetus into the economic growth of countries and regions along the Belt and Road. However, how such a growth model affects local businesses? In this regard, this paper constructs a Difference-in-difference (DID) model based on whether the Belt and Road Initiative can promote the technological upgrading of countries and regions along the Belt and Road. The data of listed companies in countries and regions along the Belt and Road Initiative from 2013 to 2020 are used for verification. It is found that the Belt and Road Initiative can significantly promote the technological upgrading of listed companies in countries and regions along the Belt and Road, represented by the number of patents granted. This conclusion implies that the implementation of the Belt and Road Initiative will promote the common development of countries and regions along the Belt and Road, and provides theoretical support for promoting the high-quality development of the Belt and Road. In the meantime, amid the implementation of the Belt and Road Initiative, relevant countries ought to strengthen communication and negotiation, consolidate and deepen cooperation, expand the sphere of influence and adhere to the innovation-driven development strategy, so as to build the Belt and Road Initiative into a platform for the implementation of a community with a shared future for mankind.
Model-Based Software Development – Autocode to Autosar

Designing software functions using the modelbased methodology and making it compliant with Autosar (AUTomotive Open System ARchitecture) and meeting the coding standard is a challenge. There are many functional blocks in the model design where transforming Autocode to Autosar is difficult for one discipline to dive through. This paper intends to breach the gap in understanding the development workflow of Autocode modeling, coding standard impact with Autocode, and Autocode complex blocks such as non-volatile memory service port, server-client interface, digital Input-output block, calibration, display memory block, etc. using the real-time simple example with a brief overview. This paper also provides function autocode modeling suggestion, so the function is being developed more effectively.
Nutritional rickets and vitamin D deficiency: consequences and strategies for treatment and prevention

ABSTRACT Introduction Rickets is typically characterized by bone deformities due to defective bone mineralization and chondrocyte maturation in growing bones. However, infantile rickets often goes unrecognized, because the skeletal abnormalities are more subtle and often can only be detected radiologically. Nutritional rickets is a major public health concern in several regions worldwide. It is most commonly caused by vitamin D and/or calcium deficiency. Area covered We provide an overview of historical perspective, epidemiology, and pathophysiology of nutritional rickets. Additionally, we outline diagnostic approaches and highlight challenges in radiographic diagnosis of rickets. Finally, we present strategies for prevention and treatment of rickets. Expert opinion Despite the evidence from clinical databases that rickets is a rare disease, it is likely that rickets is clinically underdiagnosed as studies designed to screen healthy children for radiographic evidence of rickets reported surprisingly much higher prevalence. It has been reported that some of the radiologic features of rickets can be misinterpreted as fractures. To prevent nutritional rickets, most if not all infants and young children, should receive vitamin D from formulas and foods that are fortified with vitamin D or supplementation to achieve a serum 25-hydroxyvitamin D of at least 20 ng/mL as recommended by the Institute of Medicine. It has been recommended by the Endocrine Society that to achieve maximum bone health for children and adults, a serum concentration of 25-hydroxyvitamin D should be at least 30 ng/mL and preferably 40–60 ng/mL. Pregnant women who are unable to obtain an adequate amount of vitamin D from sunlight exposure and natural and fortified diets should take a vitamin D supplement of 1500–2000 IUs daily as recommended by the Endocrine Society since it has been demonstrated that 600 IUs daily will not maintain a circulating 25-hydroxyvitamin D of at least 20 ng/mL and most pregnant women. If lactating women take approximately 6400 IUs of vitamin D daily, they provide enough vitamin D in their milk to satisfy their infant’s requirement thereby preventing rickets.
Color Doppler and Ankle-brachial Index in the Diagnosis of Peripheral Artery Disease in Type II Diabetic Subject

Objective: To determine the association of color doppler and ankle-brachial index (ABI) in the diagnosis of peripheral artery disease in type ii diabetic subject. Methods: The study was carried out at ultrasound department of Advanced Radiology Clinic (ARC), Karachi, from January 2020 to December 2020. Patients of diagnosed diabetes mellitus for at least 4 years of either gender between 30-70 years of age were included. All patients were instructed to avoid heavy exercise, smoking and caffeinated beverages before the examination for at the minimum of two hours. All the cases underwent Standard Doppler examination of lower limb peripheral arteries performed by radiologist having experience of more than 10 years. Spectral waveform analysis was evaluated and presence of Biphasic flow or monophasic flow on color Doppler was labelled as peripheral artery disease. The ABI was computed for each patient by measuring the systolic blood pressure in supine position starting with the right arm then proceeding towards right leg, left leg, and finally for the left arm. ABI is a ratio obtained from dividing the higher of the ankle blood pressures for each leg by the highest of the right and left arm’s brachial systolic blood pressures. It was labelled as peripheral artery disease if the value was <0.9. This information along with the demographics was entered in the Performa by the researcher. Data was analyzed by using SPSS Version 26. Result: Mean age of enrolled participants was 58.21±6.74 year. There were 78.6% were males and 21.4% were females; mean duration of diabetes was 11.24±5.62 years. Out of all 121 cases were diagnosed color doppler and 118 cases found positive on ABI. Although ankle-brachial index shows almost similar diagnosis like color doppler ultrasound in the assessment of peripheral arterial disease (P-0.649). Conclusion: This study concludes that ankle-brachial index is a feasible, non-invasive technique almost similar to color Doppler ultrasound method for the detection of peripheral arterial disease. The ankle-brachial index technique is most important in periphery areas where color Doppler ultrasound is not available.
Automatic facies detection based on oilfield core images

Abstract This paper proposes a machine learning method for automatically detecting and identifying facies from digital images of the oil well core. The method is based on artificial neural networks, specifically, pre-trained deep convolutional neural networks, improved using histogram of oriented gradients and local binary pattern methods. AlexNet, Inception, MobileNet, Xception, and DenseNet extract features from images. An algorithm based on the behavior of fireflies selects the most informative features. The k-nearest neighbors, support vector machines, and random forest methods are considered as classifiers. The proposed approach uses a model that has been trained and tested on a core rock samples dataset of > 23,000 images related to four facies as coal, sandstone, siltstone, and shale. The experimental results show that the proposed HOG + LBP + DenseNet model combined with a random forest is better than support vector machines and k-nearest neighbors methods regarding facies recognition from core photographs and the precision (95.5%), recall (96.46%), and F-measure (95.98%) metrics.
Spatial match-mismatch across four trophic levels of the Benguela upwelling zone during an ecosystem shift.

1. Remote-sensing measurements of marine primary productivity are widely used to predict the distribution and movements of marine top predators, despite the fact that predators do not feed directly on phytoplankton but several trophic levels higher up the food chain. 2. To test for potential links between primary productivity and top-predator feeding hotspots, we assessed spatial match–mismatch across four trophic levels of the Benguela upwelling zone (south-east Atlantic). The food chain studied consisted of phytoplankton, zooplankton (copepods), pelagic fish (anchovies and sardines) and two top predators (Cape gannets Morus capensis and human fisheries). 3. Remote-sensing data of sea-surface temperature (SST) and chlorophyll_a concentration were used as indices of phytoplankton abundance throughout the study area. Copepod biomass and pelagic fish density were determined during at-sea surveys in the South African section of the Benguela using net tows and hydro-acoustics, respectively. Seabird (Cape gannet) home ranges and foraging zones were assessed from two Namibian breeding colonies (Mercury and Ichaboe) and two South African colonies (Lambert's Bay and Malgas) using global positioning system (GPS) tracking. Industrial fishing for anchovies and sardines was investigated using South African landing statistics and logbooks. 4. Our spatial analyses revealed a strong match of seabird at-sea habitat and zones of high primary productivity throughout the southern Benguela. Conversely, there was a marked spatial mismatch between copepods and pelagic fish, as well as between pelagic fish, seabirds and human fisheries: copepods were present in the southern Benguela but pelagic fish usually feeding upon them were located further east (Indian Ocean), outside of the Benguela sensu stricto. Consequently, the majority of these pelagic fish were out of reach for seabirds and fisheries confined to the southern Benguela. 5. Synthesis and applications. Our study demonstrates the impact of an ecosystem shift across one of the world's most productive marine ecosystems and highlights the limitations of using remote-sensed patterns of primary productivity to interpret the foraging behaviour of marine top predators. These findings underline the importance of a better knowledge of food web spatial dynamics to support ecosystem-based fisheries management and the conservation of marine top predators.