Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence of a vegan diet for health benefits and risks – an umbrella review of meta-analyses of observational and clinical studies

Abstract To summarize and evaluate the evidence on the health impact of a vegan diet, we conducted an umbrella review of systematic reviews and meta-analyses. PubMed, Cochrane Library, Web of Science and Epistemonikos were searched up to September 2021. Meta-analyses were recalculated by using a random effects model. The certainty of evidence (CoE) was evaluated by the GRADE approach. For the general healthy population, a vegan diet was effective for reducing body weight [MD (95% CI): −2.52 kg (−3.06, −1.98), n = 8 RCTs; moderate CoE] and was associated with further health benefits (with low CoE), including a lower risk of cancer incidence [SRR (95% CI): 0.84 (0.75, 0.95), n = 2] and a trend for lower risk of all-cause mortality [SRR (95% CI): 0.87 (0.75, 1.01), n = 2], as well as lower ApoB levels [MD (95% CI): −0.19 µmol/L (−0.23, −0.15), n = 7 RCTs). The findings suggested adverse associations for a vegan diet with risk of fractures [SRR (95% CI): 1.46 (1.03, 2.07), n = 3; low CoE]. For persons with diabetes or at high CVD risk, a vegan diet reduced measures of adiposity, total cholesterol, LDL and improved glycemic control (CoE moderate to low). A vegan diet may have the potential for the prevention of cardiometabolic health, but it may also impair bone health. More well-conducted primary studies are warranted.
Novel anti-windup of a current regulator of a surface-mounted permanent-magnet motor for flux-weakening control

This paper proposes a novel antiwindup method of current regulator for the drive system of a surface-mounted permanent-magnet synchronous motor at flux-weakening region. It is designed in conjunction with the synchronous-frame proportional and integral current regulator and the space vector pulse width modulation. The difference between the regulator output voltage and the saturated voltage on the q-axis of the regulator is used for flux-weakening control, which modifies the d-axis current reference. With this method, the antiwindup and the flux-weakening control can be achieved simultaneously. Since the proposed method utilizes the dc-link voltage more efficiently, it makes the motor generate higher output torque than the conventional antiwindup and/or flux-weakening control methods under the same voltage and current limitation. The effectiveness of this method is confirmed by computer simulations and experiments
Constructing an electrical microenvironment based on electroactive polymers in the field of bone tissue engineering

Abstract The process of bone tissue repair and regeneration must occur in a suitable electrical microenvironment, which is one of the most important microenvironments. Electroactive materials appropriately simulate the bioelectric nature of bone and provide the electrical microenvironment required for bone repair, which accelerates bone repair and regeneration. The concept of electrical stimulation-induced osteogenesis promotes the development of electroactive materials as orthopedic implants. This article reviews the general bioelectric phenomena in organisms and the electrical response of natural bone, and briefly explains the promotion of bone regeneration by the electrical microenvironment. Electroactive materials in the field of bone tissue engineering are divided into two categories, such as piezoelectric polymers and conductive polymers, and the material properties, research progress, and applications of each will be described in detail. This article analyzes the limitations of piezoelectric and conductive materials for constructing an electrical microenvironment, reveals the potential of these two materials for overcoming the application limitations of a single type of electroactive material, and discusses the principles. The future challenges and developmental prospects of electroactive materials are discussed. This review comprehensively emphasizes the important characteristics of electroactive biomaterials and points out the direction of development for composite applications of different electroactive materials. Graphical Abstract
Increasing the competency focus using a project-driven strategy

Accounting educators continue to look for efficient ways to introduce personal competencies into the curriculum. Prior literature contains numerous suggestions on how faculty can implement a single personal competency, such as written communication. This chapter describes our strategy for integrating a variety of personal competencies using team projects. We implement this strategy by selecting projects that are content oriented and not only involve critical thinking but also address students’ skills related to written and oral communication, technology, teamwork, and leadership. We offer guidance on how to implement this project-oriented strategy and also provide selected tools for streamlining the assessment of student performance, such as sample grading rubrics and an online survey for evaluating team leader and team member performance. Feedback suggests that students perceived an improvement in their competencies as a result of the course's activities. While we bundled a variety of personal competencies within a managerial cost accounting course, instructors can easily adapt our strategy to any course in the curriculum.
Skin dryness induced in the KK-Ay/TaJcl type 2 diabetes mouse model deteriorates following dapagliflozin administration.

Various diabetic drugs have been developed as the number of patients with type 2 diabetes has increased. Sodium-glucose cotransporter (SGLT)-2 inhibitors have been developed as novel therapeutic agents. However, SGLT-2 inhibitors cause skin dryness. The mechanism through which SGLT-2 inhibitors cause skin dryness is unknown. The purpose of this study was to investigate the mechanism through which dapagliflozin, a SGLT-2 inhibitor, induces skin dryness. Specific pathogen-free KK-Ay/TaJcl (type 2 diabetes model) mice were orally administered with SGLT-2 inhibitor (dapagliflozin) daily for 4 weeks at a dose of 1 mg/kg/day. Skin dryness induced in KK-Ay/TaJcl mice became severe after dapagliflozin administration. Dapagliflozin treatment decreased collagen type I and hyaluronic acid levels in mice; additionally, it affected the TGF-β/hyaluronan synthase pathway, further reducing hyaluronic acid levels. The results indicate that the reduction in hyaluronic acid levels plays an important role in the occurrence of dry skin in diabetes.
Predicting Electricity Imbalance Prices and Volumes: Capabilities and Opportunities

Electricity imbalance pricing provides the ultimate incentive for generators and suppliers to contract with one another ahead of time and deliver against their obligations. As delivery time approaches, traders must judge whether to trade-out a position or settle it in the balancing market at the as-yet-unknown imbalance price. Forecasting the imbalance price (and related volumes) is therefore a necessity in short-term markets. However, this topic has received surprisingly little attention in the academic literature despite clear need by practitioners. Furthermore, the emergence of algorithmic trading demands automated forecasting and decision-making, with those best able to extract predictive information from available data gaining a competitive advantage. Here we present the case for developing imbalance price forecasting methods and provide motivating examples from the Great Britain’s balancing market, demonstrating forecast skill and value.
Building confidence in crowdsourced data for biological monitoring and policy making as part of FP7 Project COBWEB

There is a great deal of potential for crowdsourcing to contribute environmental data for the benefit of scientific research as well as governance and policy making (Brabham 2013, Sutherland et al. 2013). Harnessing the power of the crowd to provide volunteered geographic information (VGI) (Goodchild 2007) using mobile technology, is an exciting prospect for professionals with an interest in acquiring data that is georeferenced in space and time that can be used to better understand and manage the natural environment. Although the process itself is not new, (Butcher 1990), the number of applications where crowdsourcing is demonstrably a powerful and efficient method of creating data, validating data products and contributing to science and governance have increased dramatically in recent years driven largely by developments in technology and access to online data (Fritz et al. 2012). The use of VGI for biological monitoring of plants and habitats is a challenging area as vegetation science is a specialist area requiring skills in plant identification and assessments that can take years to develop, however there are some applications. Projects like iSpot 1 provide a platform for the crowd to contribute observations and to have them validated by experts and mobile applications like PlantTracker 2 enable the user to record the location of invasive species in the UK; Leaf Watch 3 has helped scientists in two universities in the UK to monitor the spread of disease in Britain’s horse-chestnut trees. Other recent applications include the use of mobile devices to collect data about plants on the ground; this then contributes to scientific research in plant phenology (Whitsitt et al. 2010). There are many projects and programmes where VGI is being used in the biological monitoring of birds, insects and animals and some successful examples from the UK include the British Trust for Ornithology Bird Track Apps 4 , OPAL Surveys 5 and the UK Ladybird Survey 6 . Mobile applications can be designed alongside interested parties and stakeholder groups that empower the ‘crowd’ to collect data that will contribute to biological monitoring and ultimately to plug gaps for evidence-based policy making (Roy et al. 2012). The work introduced here presents a platform and infrastructure to support VGI and enable data to be gathered for a range of relevant uses, quality checked and published and, then for that data to be searchable and reusable.
Online monitoring of generator damping using dissipation energy flow computed from ambient data

Online monitoring of generator damping assists in identifying wrong parameters or detrimental changes in generator control systems that may reduce damping ratios of power system oscillation modes. An approach for generator damping estimation using ambient data during normal operation of power systems is proposed. The ambient phasor measurement data at generator terminal is collected and filtered, and then the dissipation energy flow (DEF) into the generator is computed. The rate of change of the DEF represents the rate of transient energy dissipation of the generator and is used to estimate the generator damping. Test results show the validity and possible applications of the approach. A more comprehensive online monitoring system of small-signal stability can be constructed using the approach together with system mode estimation methods.
Lighting and the visual environment for seniors and the low vision population

RP-28-16 is intended to increase the designers understanding of age-related vision loss and the importance of their design decisions that could impact the safety and independence of this growing sector of the population. In the 2007 edition, applications were primarily directed at housing and senior care facilities but in the 2016 edition, coverage has been expanded to new areas of interest including offices, hospitality, healthcare, commercial and places of assembly. RP-28-16 has also been revised to serve a wider range of users, including individuals, design professionals, owners/managers of commercial buildings, code and regulatory agencies and legislative bodies. It is well understood that healthcare costs will increase as our elderly population ages. As the United States braces for this huge economic impact, appropriate lighting and a supportive visual environment should be considered as a preventive measure to reduce the risk of falls, sleep disorders and long-term care, and therefore given a top priority by all code officials, governmental agencies and the tax-paying public.
That was close! A counterfactual simulation model of causal judgments about decisions

How do people make causal judgments about other’s deci- sions? Prior work has argued that judging causation requires going beyond what actually happened and simulating what would have happened in a relevant counterfactual situation. Here, we extend the counterfactual simulation model of causal judgments for physical events, to explain judgments about other agents’ decisions. In our experiments, an agent chooses what path to take to reach a goal. In Experiment 1, participants either made hypothetical judgments about whether the agent would succeed were it to take a certain path, or counterfactual judgments about whether the agent would have suc- ceeded had it taken a different path. In Experiment 2, participants made causal judgments about whether the agent suc- ceeded or failed because of the path that it took. Our computational model accurately captured participants’ judgments in both experiments and we find that causal judgments are better explained by counterfactuals rather than hypotheticals.
P4DDPI: Securing P4-Programmable Data Plane Networks via DNS Deep Packet Inspection

—One of the main roles of the Domain Name System (DNS) is to map domain names to IP addresses. Despite the importance of this function, DNS traffic often passes without being analyzed, thus making the DNS a center of attacks that keep evolving and growing. Software-based mitigation ap- proaches and dedicated state-of-the-art firewalls c a n become a bottleneck and are subject to saturation attacks, especially in high-speed networks. The emerging P4-programmable data plane can implement a variety of network security mitigation approaches at high-speed rates without disrupting legitimate traffic.This paper describes a system that relies on programmable switches and their stateful processing capabilities to parse and analyze DNS traffic solely in the data plane , and subsequently apply security policies on domains according to the network administrator. In particular, Deep Packet Inspection (DPI) is leveraged to extract the domain name consisting of any number of labels and hence, apply filtering rules (e.g., blocking malicious domains). Evaluation results show that the proposed approach can parse more domain labels than any state-of-the-art P4-based approach. Additionally, a significant performance gain is attained when comparing it to a traditional software firewall -pfsense-, in terms of throughput, delay, and packet loss. The resources occupied by the implemented P4 program are minimal, which allows for more security functionalities to be added.
Prevalence and Distribution of Dental Caries in Patients Undergoing Extraction of Permanent Teeth: An Institutional Study

An increase in the prevalence of dental caries has been observed, which can be attributed to a change in lifestyle that involves increased consumption of sugary food, carbonated drinks, and lack of awareness towards proper oral health maintenance. Dental caries is one of the most prevalent chronic oral diseases which lead to tooth loss, affecting all age groups causing a major public health concern. It is important to acknowledge the causes of dental caries prevent it from deteriorating and hence reduce the number of extractions in future. The aim of the study was to investigate the prevalence and distribution of dental caries in patients undergoing extraction of permanent teeth at Saveetha Dental College and Hospitals. In this retrospective cross-sectional study, digital case records of all patients who underwent extractions of permanent teeth due to dental caries in Saveetha Dental College and Hospital from June 2019 to March 2020 were reviewed. Demographic details of patients and the extracted tooth numbers were recorded from digital case records. Retrieved data was analyzed using IBM SPSS Software Version 20.0. Descriptive statistics and tests of association for categorical variables by Chi square tests were done and results were obtained. P value<0.05 was considered statistically significant. 6808 patients underwent 16,955 extractions of permanent teeth due to dental caries in Saveetha Dental College, out of which the prevalence of extraction due to dental caries was more in the third molars, in the age group of 41-50 years with a male predilection. On comparing the association of extractions (tooth number) with age and gender of the patients, the results were statistically significant. (Pearson’s Chi Square test, p<0.05). Within the limits of the present study, it can be concluded that the prevalence of extraction due to dental caries was more in the third molars, in the age group of 41-50 years with a male predilection.
Determination of the Eff ects of Silage Type, Silage Consumption, Birth Type and Birth Weight on Fattening Final Live Weight in Kıvırcık Lambs with MARS and Bagging MARS Algorithms

Th is study was carried out to determine the eff ect of silage type, silage consumption, birth type (single or twin) and birth weight on live weight at the end of fattening in Kıvırcık lambs. In the experiment, 40 male Kıvırcık lambs aged 2.5-3 months were used and the animals were fattened for 56 days. During the fattening period, the lambs fed with 5 diff erent types of silage (100% sunfl ower silage, 75% sunfl ower + 25% corn silage, 50% sunfl ower + 50% corn silage, 25% sunfl ower + 75% corn silage, 100% corn silage) pure and mixed in diff erent proportions and concentrate feed. Data on fattening results were analyzed with MARS and Bagging MARS algorithms. Th e main objective of this research is to predict fattening final live weight (FFLW) of lambs using Multivariate Adaptive Regression Splines (MARS) and Bagging MARS algorithms as a nonparametric regression technique. Live weight value was modeled based on factors such as birth type, birth weight, silage type and silage consumption. Correlation coefficient (r), determination coefficient (R2), Adjust R2, Root-meansquare error (RMSE), standard deviation ratio (SD ratio), mean absolute percentage error (MAPE), mean absolute deviation (MAD), and Akaike Information Criteria (AIC) values of MARS algorithm predicting live weight were as follows: 0.9986, 0.997, 0.977, 0.142, 0.052, 0.2389, 0.086 and -88 respectively. Like statistics for Bagging MARS algorithm were 0.754, 0.556, 0.453, 1.8, 0.666, 3.96, 1.47 and 115 respectively. It was observed that MARS and Bagging MARS algorithms have revealed correct results according to goodness of fit statistics. In this study it has been determined that the MARS algorithm gives better results in live weight modeling.
Recursive Neural Networks Review

In this review, we propose a generalization of recursive neural networks that operates over recursive structures. We discuss major contributions of researchers in applying recursive neural networks to different problems. Due to many theoretical implications, recursive neural networks are believed to be powerful models. In addition, recursive networks learn high-level representations from explicit inputs thus, it is successful in many deep learning tasks where the input is a structure. We also tend in this review to connect convolution neural network and recurrent neural network to a more general model that stand differently from feed-forward neural networks.
Poster: Visualization Result of String-based CPU Architecture Independent IoT Malware Clustering

—This paper presents a visualization result of un-supervised clustering using IoT malware datasets acquired by IoTPOT [4], [5]. The problems of IoT malware are a wide variety of CPU platforms and the rapid evolve of variants from the same family. For supporting the rapid analysis of IoT malware, this paper proposes a CPU-independent string-based clustering method. In the analysis process, we found 25 samples that contained a unique string among 4000 samples
Structurisation and Visualisation of Design Space for Launch Vehicle with Hybrid Rocket Engine

A single-stage launch vehicle with hybrid rocket engine has been conceptually designed by using design informatics, which has three points of view, i.e., problem definition, optimisation, and data mining. The primary objective of the present design is that the down range and the duration time in the lower thermosphere are sufficiently secured for the aurora scientific observation, whereas the initial gross weight is held down to the extent possible. The multidisciplinary design optimisation was performed by using a hybrid evolutionary computation. Data mining was also implemented by using a self-organising map and the stratum-type association analysis. Polypropylene and liquid oxygen with swirling flow are adopted as solid fuel and liquid oxidiser, respectively. The condition of single-time ignition is assumed in flight sequence. Consequently, the design information regarding the tradeoffs, the behaviours of the design variables in the design space to become the non-dominated solutions, and the implication of the design variables for the objective functions have been obtained in order to quantitatively differentiate the advantage of hybrid rocket engine. The structurisation of the design space has been implemented in order to observe the effectiveness of the local regions of each design variable.
Porting uintah to heterogeneous systems

The Uintah Computational Framework is being prepared to make portable use of forthcoming exascale systems, initially the DOE Aurora system through the Aurora Early Science Program. This paper describes the evolution of Uintah to be ready for such architectures. A key part of this preparation has been the adoption of the Kokkos performance portability layer in Uintah. The sheer size of the Uintah codebase has made it imperative to have a representative benchmark. The design of this benchmark and the use of Kokkos within it is discussed. This paper complements recent work with additional details and new scaling studies run 24x further than earlier studies. Results are shown for two benchmarks executing workloads representative of typical Uintah applications. These results demonstrate single-source portability across the DOE Summit and NSF Frontera systems with good strong-scaling characteristics. The challenge of extending this approach to anticipated exascale systems is also considered.
Live weight and bone growth from birth to 15 months of age in pure-bred and cross-bred Jersey and

Live weight and liveweight gain of dairy heifers has been described in New Zealand and overseas, however, the change in stature and pattern of proximal and distal bone growth has, to date, received little attention. This study describes the proportional changes in stature with live weight, in a cohort of commercial dairy heifers (Holstein-Friesian, Jersey, and Holstein-Friesian-Jersey crossbred) from birth to 15 months of age. Comparisons of height, length, girth, and distal and proximal forelimb length (stature) revealed that at the same live weight, these parameters differed among breeds (P<0.05), however, the magnitude of the differences among breeds was consistently less than 1 cm. As heifer live weight increased, the contribution of the distal limb to increases in height decreased, which is consistent with knowledge that physeal closure in cattle occurs earlier in distal limb bones, such as the metacarpus, than in proximal limb bones, such as the humerus. In addition, the understanding of proximal and distal growth in cattle identifies when heifers are most susceptible to growth checks.