Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Exercise Affect Telomere Length? A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background and objectives: Telomere length is an indicator of biological aging, and it shortens during cell division. A short telomere length is associated with various age-related diseases and mortality. It is suggested that physical activity has a positive effect on the rate of telomere length shortening. Materials and Methods: Related studies, published in electronic databases, were searched with keywords, including exercise, telomere length, and randomized controlled trial. The data were weighted and pooled through a fixed-effect model. Results: Of the total 49 studies searched, 7 studies with 939 participants were considered suitable, and were analyzed qualitatively and quantitatively. Exercise is beneficial to telomere length. Aerobic exercise was effective as the type of exercise (MD, −0.03; 95% CI, −0.04 to −0.01). In addition, exercise for more than 6 months, with a change in lifestyle, is beneficial for telomere length (MD, −0.02; 95% CI, −0.04 to −0.01). Conclusions: The type and duration of exercise for positive improvement in telomere length is aerobic exercise for more than 6 months.
Women’s experience of post-natal care: A study from Uttarakhand, India

ABSTRACT Although significant strides have been made in improving maternal and child health outcomes following the millennium development goals, India's progress has been slow, as reflected by its relatively high maternal and child mortality rates. This calls for investigation into the quality of care (QOC) offered to women during pregnancy and childbirth. This study uses primary data to evaluate women's experience of the postnatal care they receive in order to understand maternal perceptions about QOC in Uttarakhand, India. Specifically, we try to measure women's satisfaction with postnatal care and construct a maternal satisfaction index. We also attempt to understand the demographic, socio-economic and obstetric factors that affect them. Results show that a sufficient number of postnatal checks for both the mother and baby were done, while they felt the length of stay in health facilities had been adequate and they had adequate privacy during these processes. These emerged as the most important components of maternal satisfaction. Factors such as women's working status, place of residence, number of children born, pregnancy and delivery related complications, and planned place of delivery were important for their satisfaction. This study may have policy implications to help bridge the supply-demand gaps in the QOC framework.
Bantuan Sosial Sedekah Nasi Bungkus di Masa Pandemi Covid-19 Oleh Pusat Pengelolaan Dana Sosial

Pandemi Covid-19 telah berpengaruh pada perekonomian Indonesia. Banyak masyarakat yang terdampak mata pencahariannya atau beberapa mulai menganggur dan sebagian masyarakat berpindah ke sektor informal. Oleh karena itu, untuk meringankan beban masyarakat terdampak akibat pandemi Covid-19, tim Pusat Pengelolaan Dana Sosial Universitas Airlangga dan Sedekah Squad bermitra untuk memberikan bantuan sosial sedekah nasi bungkus kepada masyarakat di masa pandemi ini. Kegiatan pengabdian masyarakat ini sejalan dengan tujuan SDGs yaitu untuk mensejahterakan kehidupan masyarakat. Persiapan pembagian sedekah nasi bungkus dimulai dari observasi atau mengamati daerah masyarakat yang akan menjadi sasaran bantuan. Kemudian memprioritaskan masyarakat sekitar kampus dan daerah yang kumuh di Surabaya. Tahap terakhir adalah persiapan yaitu menyiapkan dan menyediakan nasi bungkus yang akan dibagikan ke masyarakat. Sebanyak total 614 nasi bungkus disalurkan selama bulan April 2021. Penyaluran dilaksanakan satu minggu sekali di Hari Jumat. Minggu pertama menyalurkan 183 nasi bungkus, minggu kedua menyalurkan 147 nasi bungkus, minggu ketiga menyalurkan 147 nasi bungkus, dan minggu keempat menyalurkan 137 nasi bungkus. Masyarakat sekitar kampus Universitas Airlangga dan daerah-daerah lainnya di Kota Surabaya seperti Kenjeran, Keputih dan Jalan Merr sangat merasa terbantu atas program ini.
Current Social Perception of and Value Attached to Nursing Professionals’ Competences: An Integrative Review

In order to develop nurses’ identities properly, they need to publicise their professional competences and make society aware of them. For that, this study was conducted to describe the competences that society currently attributes to nursing professionals and how nursing is valued in society. This review was based on the conceptual framework by Whittemore and Knafl. The literature search was conducted using PubMed, WOS, and CINAHL databases, and the search strategy was based on a combination of natural language and standardised keywords, with limits and criteria for inclusion, exclusion, and quality. The results of the studies were classified and coded in accordance with the competence groups of the professional profile described in the Tuning Educational Structures in Europe programme. Fourteen studies were selected. The most commonly reported competence groups were as follows: nursing practice and clinical decision making; and communication and interpersonal competences. Nursing is perceived as a healthcare profession dedicated to caring for individuals. Its other areas of competence and its capacity for leadership are not well known. In order to develop a professional identity, it is essential to raise awareness of the competences that make up this professional profile.
Impact of Ocean Warming, Overfishing and Mercury on European Fisheries: A Risk Assessment and Policy Solution Framework

Previous studies have shown that multiple-environmental stressors are expected to have significant and geographically differential impacts on the health and abundance of marine species. In this paper, we analyze the combined impacts of ocean warming, overfishing and mercury pollution in European waters by projecting the impacts of climatic and non-climate drivers on marine species in European waters. Our findings suggest that the impacts vary widely depending on different species and their mean temperature tolerance (MTT). We find for instance, that more than 5 temperate benthopelagic species including, bobtail squids (Sepiida) frogfishes (Lophius) great Atlantic scallop (Pecten maximus) red mullet (Mullus barbatus barbatus) and common octopus (Octopus vulgaris) are affected (i.e., weakens their resilience to climate change) by the increase in sea surface temperature (SST) under RCP 8.5 in 2050 and 2100. Mercury contamination was estimated to increase in some species (e.g., ∼50% in swordfish), exceeding mercury consumption guideline thresholds (>1 mg/kg). This negative impact may limit the capacity of fisheries and marine ecosystem to respond to the current climate induced pollution sensitivity. An implication of our study is that the international community should strengthen a global ban on mercury emissions under the mandate of the Minamata Convention, comparable to the United Nations framework for persistent organic pollutant emission sources. Ongoing global efforts aimed at minimizing carbon footprint and mercury emissions need to be enhanced in concert with a reduction in fishing intensity to maintain effective conservation measures that promote increased resilience of fisheries to climate change and other stressors.
Perceptions of Officer Roles in School Resource Officer Programs

ABSTRACT Although research on the effectiveness of school resource officers (SROs) remains mixed, the number of SROs in the U.S. continues to grow. We interviewed 18 SROs, SRO supervisors, and school leaders from exemplar programs to explore SRO role perceptions. Analysis revealed three themes: (1) SROs support a safe learning environment via multiple roles; (2) common SRO roles are law enforcer, educator, community liaison, and emergency manager; and (3) additional roles are site-specific. Our findings suggest a need to articulate expected SRO roles and recognize SROs often play multiple, overlapping roles to support a safe environment for student learning.
Fabrication and Investigation of Spectral Properties of a Dielectric Slab Waveguide Photonic Crystal Based Fano-Filter

In this paper, we discuss the fabrication of a dielectric photonic crystal (PhC)-based Fano-filter device, as well as a numerical investigation of its spectral characteristics. The process parameters affecting the structural and physical properties of the fabricated device are discussed in detail, along with their influence on the spectral properties of the filter. The considered experimental problem is a three-layered PhC structure, fabricated using focused ion-beam (FIB) technology, designed to operate in the near-infrared (NIR) range. The studied parameters include the shape of PhC elements, depth of the structures, cladding layer thicknesses, and the refractive index of the material. Numerical design and simulations are performed using an open-source python-based Finite-difference time-domain (FDTD) simulation tool. The proposed optical filter device operates based on the principle of guided-mode resonance, and achieved a maximum quality factor value in the range of 800.
The Effect of Periodontal Treatment on Clinical and Biological Indicators, Quality of Life, and Oral Health in Rheumatoid Arthritis Patients: A Quasi-Experimental Study

Non-surgical periodontal therapy (NSPT) has been shown to have systemic effects. It has been suggested that, similar to rheumatoid arthritis (RA), periodontitis (PD) has an impact on general health, in terms of psychological, physical, and social aspects. This study determines the effect of periodontal treatment in RA activity, health-related quality of life, and oral health self-perception before and after periodontal treatment in RA patients. A quasi-experimental, prospective, non-randomized study was conducted, and 52 patients were included in the study. Periodontal parameters and the instruments disease activity score-28 (DAS-28), SF-36, and OHIP-14 were measured at baseline and at 3 months after NSPT. All differences were statistically assessed. The study protocol was registered in Clinical Trials (NCT04658615). No statistically significant differences were found in the scores of DAS-28 before and after the intervention in the group with PD and reduced periodontium. When the effect of periodontal treatment was analyzed in the group of 29 patients who were followed up, it was found that there were statistically significant differences before and after in variables such as psychological distress, emotional role, and mental health, which indicates an improvement in the scores of these variables. NSPT influenced the health-related quality of life measured with SF-36 and OHIP-14 in patients with RA. In conclusion, NSPT has an effect on self-reported quality of life and health indicators more than the RA activity as measured with DAS-28. However, the clinical effect of periodontal treatment in RA patients provides important data to support periodontal care in patients.
Using Convolutional Neural Network for Image Classification and Segmentation

Image segmentation and Image Classification are two fundamental tasks in computer vision. In this thesis, a novel segmentation algorithm based on a deformable model and robust estimation is introduced to produce reliable segmentation results. The algorithm is extended to handle touching objects and partially occluded image segmentation. Although current conventional image classification methods have been widely applied to realistic problems, there are some issues with their implementation, including unsatisfactory results, poor classification accuracy, and a lack of adaptive capacity. This approach has been used to isolate the two processes of image feature extraction and classification into two stages. The deep learning model possesses a strong learning capability, which enables it to incorporate the feature extraction and classification processes, thereby improving the image classification accuracy. This thesis explores various machine learning methods to improve the model's performance. The primary objective is to discover the accuracy of the various networks on the datasets and to evaluate the consistency of each of these deep learning predictions. Nonetheless, there are limitations to this approach: first, it is difficult to perform accurate approximation in the advanced model. The second point is that the deep learning model comes with poor accuracy in its classifier. So, this paper introduces the idea of using different datasets and models of the deep learning network and comprehensively utilizes it to determine the best test accuracy for the images. In this paper, a deep neural network primarily based on Keras and TensorFlow is deployed using python. The two datasets are used to compare to determine which has the maximum accurate and fine time for processing. And a VGG-16 model method based on the optimized kernel function is proposed to replace the classifier in the deep learning model. The experimental results show that the proposed method not only has higher average accuracy than other mainstream methods but also can be good adapted to various image databases. Compared with other deep learning methods, it can better solve the problems of complex function approximation and poor classifier effectiveness, thus further improving image classification accuracy.
Evolutionary Analysis of Dipeptidyl Peptidase I

Human dipeptidyl peptidase I (DPPI) belongs to the family of papain-like cysteine peptidases. Its distinctive features are the unique exclusion domain which enables the eponymous activity and homotetramerization of DPPI, and its dependence on chloride ions for enzymatic activity. The oligomeric state of DPPI is unique in this family of predominantly monomeric peptidases. However, a distant DPPI ortholog from Plasmodium falciparum has been shown to be monomeric, indicating that the oligomeric state of DPPI varies between lineages. The aim of this work was to study the evolution of DPPI, with particular attention to the structural features that determine its characteristic enzymatic activity and preferences, and to reconstruct the evolution of its oligomerization. We analyzed fifty-seven selected sequences of DPPI and confirmed its presence in three lineages, namely, Amorphea (including animals and Amoebozoa), Alveolates and the metamonad Giardia. The amino acid residues that bind the chloride ion are highly conserved in all species, indicating that the dependence on chloride ions for activity is an evolutionarily conserved feature of DPPI. The number of N-glycosylation sites is significantly increased in animals, particularly vertebrates. Analysis of homology models and subunit contacts suggests that oligomerization is likely restricted to DPPIs in the Amorphea group.
User Experience Innovation: User Centered Design that Works

User Experience Innovation is a book about creating novel and engaging user experiences for new products and systems. User experience is what makes devices such as Apple's iPhone and systems such as Amazon.com so successful. iPhone customers don't buy just a phone; they buy into an experience enabled by the device. Similarly, Amazon.com customers enter a world of book reviews, interesting recommendations, instant downloads to their Kindle, and one-click purchasing. Products today are focal points, and it is the experience surrounding the product that matters the most. User Experience Innovation helps you create the right sort of experience around your products in order to be successful in the marketplace. The approach inUser Experience Innovation is backed by 18 years of experience from an author holding more than 100 patents relating to user experience. This is a book written by a practitioner for other practitioners. You'll learn 17 specific methods for creating innovation; these methods run the gamut from targeting user needs to relieving pain points, to providing positive surprises, to innovating around paradoxes. Each method is one that the author has used successfully. Taken together, they can help you create truly successful user experience innovations to benefit your company or organization, and to help you grow as an experienced expert and innovator in your own right. Provides 17 proven methods for innovating around user experience Helps you think beyond the product to the sum total of a customer's experience Written by an experienced practitioner holding more than 100 user-experience patents What youll learn Identify target users, their needs, and core tasks Relieve pain points and innovate around conflicting user needs Provide positive surprises and a good first impression Create compelling ecosystems surrounding your products Develop context-awareness in your products Win the battle against organizational challenges Who this book is for User Experience Innovationis for product designers, product managers, application and web designers, and developers responsible for creating products and influencing their design and operation. User Experience Innovation encourages you to look at the big picture surrounding your product and service and how it is used, helping you create a successful user experience that leads to a larger, more satisfied, intensely loyal customer base.
Solar Powered Fault Detection System for Railway Tracks

Indian Railways has one of the world's largest networks. Train movement is always reliant on railway rails alone. If one of these rails develops a crack, it becomes a huge issue. Many railway accidents occur as a result of the presence of a crack. The most difficult aspect of a railway analysis is detecting structural faults. If these flaws aren't addressed early on, they could lead to a series of derailments, resulting in a significant loss of life and property. The proposed railway track error detection system detects faulty railway tracks automatically and without the need for human intervention. This project intends to create a solar based autonomous railway track crack detection vehicle that uses a microcontroller and ultrasonic sensors to detect cracks along its journey. The ultrasonic sensor detects the fracture and objects, sending the information to the microcontroller, which quickly stops the train. Solar panels are utilized in this vehicle to absorb solar energy [1], which is then transformed into electrical energy, which is then used to charge a lead acid battery, which then provides the necessary power to a DC motor. This energy is subsequently sent to the DC motor, which drives the wheels. Sensors are utilized to detect cracks, and if a crack is detected, the system will halt and sound an alarm.
Graph Substructure Assembling Network With Soft Sequence and Context Attention

There has been a surge of researchers’ interest in building predictive models over graphs. However, the overwhelming complexity of graph space often makes it challenging to extract interpretable and discriminative structural features for graph classification. In this work, we propose a new graph neural network model called Substructure Assembling Network (SAN) to learn graph representations for classification. The key innovation is a unified Substructure Assembling Unit (SAU), which is a variant of Recurrent Neural Network (RNN) designed to hierarchically assemble useful pieces of graph components so as to fabricate discriminative substructures. A key challenge is that SAUs need to process the neighbors of a node sequentially while no natural order is defined therein. SAN tries to make the model insensitive to neighborhood orders by randomly shuffling neighborhood sequences in training. However, this could suffer high variance, especially when the neighborhood size is large. Hence, we further propose to equip SAN with a novel module named Soft Sequence with Context Attention (SSCA). SAN-SSCA employs the proposed context attention technique to learn the best “soft” permutation of the neighbors w.r. t. classification. It helps the model achieve higher accuracy as well as lower variance. Experiments confirm the effectiveness of SAN-SSCA.
Light Absorption Enhancement and Laser-Induced Damage Ability Improvement of Aluminum Alloy 6061 with Non-Porous Alumina/CdSe@Al2O3/SiO2 Functional Gradient Films

Numerical calculations of ultraviolet to near-infrared absorption spectra by cadmium selenide quantum dots (CdSe QDs) doped in anodic aluminum oxide pores were performed using a finite-difference time-domain model. The height, diameter, and periodic spacing of the pores were optimized. Light absorption by the dots was enhanced by increasing the height and decreasing the diameter of the pores. When the height was less than 1 μm, visible light absorption was enhanced as the spacing was reduced from 400 nm to 100 nm. No enhancement was observed for heights greater than 6 μm. Finally, the optical mode coupling of the aluminum oxide and the quantum dots was enhanced by decreasing the pore diameter and periodic spacing and increasing the height. Laser ablation verified light absorption enhancement by the CdSe QDs. The experiments verified the improvement in the laser-induced damage ability with a nanosecond laser at a wavelength of 355 nm after aluminum alloy 6061 was coated with functional films and fabricated based on numerical calculations.
Short Communication: Morphological diversity and the addition of golden snail protein: Its effect on flavonoid content on Echinacea purpurea

Abstract. Ferdyana WC, Widiyastuti Y, Pujiasmanto B, Sakya AT, Yunus A. 2021. Short Communication: Morphological diversity and the addition of golden snail protein: Its effect on flavonoid content on Echinacea purpurea. Biodiversitas 23: 62-66. Echinacea purpurea is a subtropical medicinal plant that contains flavonoids. Flavonoids function as antioxidants and immunomodulators. However, information on the method to increase flavonoid content in E. purpurea is still limited. The golden snail protein increases flavonoid content. The purpose of this study was to determine the best accession and optimal concentration of golden snail protein on biomass production and flavonoid content in E. purpurea. The study used a Factorial Completely Randomized Design (CRD). The first factor was three accessions of E. purpurea (A1, A2, A3); the second factor was 5 levels of the addition of golden snail protein (0 mL/L/week, 10 mL/L/week, 20 mL/L/week, 30 mL/L/week, and 40 mL /L/week). There were differences in morphological characters of three E. purpurea accessions, i.e., stem and the shape of the flower crown. Accession 2 had the highest flavonoid content except for the 10 mL/L/week treatment. The highest increase in flavonoid content in three accessions was obtained in the treatment of 10 mL/L/week gold snail protein by 19% flavonoid content compared to control treatment (0 mL/L/week). The concentration of 0 mL/l/week or control had the lowest flavonoid content.
Evaluating the Oral-Health-Related Quality of Life of Oral Submucous Fibrosis Patients before and after Treatment Using the OHIP-14 Tool

The objective of the present study was to assess the oral-health-related quality of life (OHRQoL) of oral submucous fibrosis (OSMF) patients before and after standard treatment. A convenient sampling technique was used to recruit the clinically diagnosed patients of OSMF (n = 130). Based on the medical treatment, the patients were randomly divided into two study groups (group A and B). The group A patients received submucosal intralesional injections of dexamethasone (2 mL; 4 gm/mL), while group B patients received hyaluronidase (1500 IU). Both the group A and B patients received respective medical therapy biweekly for a period of five weeks. At the follow up visit (6 months), the impact of treatment on OHRQoL was assessed using the Oral Health Impact Profile-14 (OHIP-14). Data were analyzed by a chi-square test for quantitative variables and an independent t-test for qualitative variables. The comparison of all clinical parameters before and after treatment was performed by a paired t-test. The results after treatment showed that there was a significant improvement in all domains of OHIP-14 (p = 0.001) except psychological disability (p = 0.243). In addition, the OHRQoL of patients was significantly improved following the treatment.