Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge of physical education teachers’ toward tooth avulsion in Tehran, Iran

BACKGROUND AND AIM : Teeth are always faced with different traumas and all those traumas, which cause teeth to exit their sockets, are classified as avulsion. Avulsion most commonly occurs in 7-11 year olds. If sports tutors have enough information regarding replantation, they could play a significant role in prognosis of treatment. The purpose of this study was to assess physical education teachers’ level of knowledge regarding avulsion of teeth in Tehran’s Primary Schools, Iran, in 2012. METHODS : This was a cross-sectional study which used a questionnaire consisting three parts including 21 questions. The first part was about demographic information; the second part was about traumatic lesion to tooth and the third part was about process of avulsed teeth protection. The questionnaire was completed by a random sample of volunteer sports tutors in Tehran Primary Schools. Collected data were analyzed using the SPSS software using the chi-square test. RESULTS : About 160 subjects participated, 67.1% of the tutors had mid-level knowledge regarding the second part of the questionnaire, and 64.1% had a low level of knowledge regarding the third part. In relation to the second and third part of the questionnaire, a statistically significant relationship was observed between the age of the tutors and their level of information (P < 0.050). There was also a significant relationship between the level of information about the third section of the survey and the amount of experience the tutors had about avulsion (P < 0.050). CONCLUSION: The results indicate a low level of knowledge in sports tutors in dealing with avulsed teeth and suitable media for transferring the teeth. Suitable educational programs for these tutors could be very useful in enhancing their knowledge and pertaining traumatized teeth.
WhatsApp Application: An Effective Tool for Outof- Class Activity

In the digital era of education, use of ICT is found to be vital in different levels and different types of education to improve teaching-learning process. Now, due to rapid increase in smart phone and internet users a new paradigm shift in learning is m-learning. Even social networking and instant messengers become very much popular in communication and also in education. This study focuses on effective use of WhatsApp Application as an out-of-class activity for campus placement preparation for third year engineering students. Daily around 30-40 minutes WhatsApp Activity was conducted where one student posted technical questions after rigorous study and remaining students posted answers to these questions in 30 minutes duration. This was followed by assessment and discussions. This activity was completely of students for the students and by the students. After analysis, we found that students found more interest in WhatsApp activity and were more active in WhatsApp activity than In-class activity. During this activity students learnt managerial, technical and communication skills. Hence, WhatsApp can be used as an effective tool for out-of-class activity for multiple purposes like sharing information, assessment, discussions, feedback, flipped classroom concept etc.
Drought may severely reduce the ability of wild Asian Elephants Elephas maximus (Mammalia: Proboscidea: Elephantidae) to resist opportunistic infections

The present study was conducted to assess the microbial quality of water in forest waterholes in different seasons and its possible impact on wild animals, at Bandipur and Nagarahole Tiger Reserve forests in the state of Karnataka, India, during the year 2012 which evidenced drought, and the year 2014 which witnessed normal rainfall in these forests. The forests recorded the death of 39 wild elephants during April and May of 2012. One ailing elephant was confirmed to have high fever, diarrhoea, leucocytosis, and symptoms of colic. Water samples collected from major waterholes during the peak drought showed higher numbers of coliforms and several species of opportunistic bacteria including species of Vibrio and Campylobacter. In the year 2014–15, with normal rainfall, the death of less than 10 wild elephants was documented during April to May, 2015. We collected water samples from 20 major waterholes every month from June 2014 to May 2015 and assessed the water quality. We found that the microbial water quality improved in rainy season (June–September), started deterioration in winter (October–January) and became poor in summer (February–May). Though, the water during the summer of 2014–15 was equally of poor microbial quality as seen during peaks of droughts, the elephant deaths were relatively lower, signifying the role of normal rainfall in forests which provides the availability of fodder and water, which determines the general body condition and ability to resist opportunistic infections. We discuss the measures suggested and implemented from this study and their utilities at ground level.
Intelligent Algorithm-Based Magnetic Resonance for Evaluating the Effect of Platelet-Rich Plasma in the Treatment of Intractable Pain of Knee Arthritis

The application of intelligent algorithms in the treatment of intractable pain of patients with platelet-rich plasma (PRP) knee osteoarthritis by magnetic resonance was investigated. The automatic diagnosis of magnetic resonance knee osteoarthritis was established with multiple intelligent algorithms, including gray projection algorithm, adaptive binarization algorithm, and active shape model (ASM). The difference between automatic magnetic resonance detection indexes of the patients with knee osteoarthritis and artificial measurement results was analyzed. The included patients received PRP treatment. Knee osteoarthritis MRI osteoarthritis knee scores (KOA MOAKS) and Western Ontario and McMaster Universities arthritis index (WOMAC) before and after treatment were compared. The results showed that the results of knee osteoarthritis scores, inferior angle of femur, superior angle of tibia, and tibiofemoral angle (TFA) by automatic magnetic resonance diagnostic model were entirely consistent with artificial detection results. After the treatment, the total scores of knee lateral area, interior area, central area, and patellar area were all remarkably lower than those before the treatment (P < 0.05). After the treatment, knee KOA MOAKS scores and WOMAC scores were both lower than those before the treatment (P < 0.05). Visual analogue scale (VAS) scores 1 week, 2 weeks, and 3 weeks after the treatment were decreased compared with those before the treatment (P < 0.05). Relevant studies indicated that intelligent algorithm-based automatic magnetic resonance diagnostic knee osteoarthritis model showed good utilization values, which could provide the reference and basis for the treatment of the patients with knee osteoarthritis.
Estimating forest above‐ground biomass with terrestrial laser scanning: Current status and future directions

Improving the global monitoring of above‐ground biomass (AGB) is crucial for forest management to be effective in climate mitigation. In the last decade, methods have been developed for estimating AGB from terrestrial laser scanning (TLS) data. TLS‐derived AGB estimates can address current uncertainties in allometric and Earth observation (EO) methods that quantify AGB. We assembled a global dataset of TLS scanned and consecutively destructively measured trees from a variety of forest conditions and reconstruction pipelines. The dataset comprised 391 trees from 111 species with stem diameter ranging 8.5 to 180.3 cm and AGB ranging 13.5–43,950 kg. TLS‐derived AGB closely agreed with destructive values (bias <1%, concordance correlation coefficient of 98%). However, we identified below‐average performances for smaller trees (<1,000 kg) and conifers. In every individual study, TLS estimates of AGB were less biased and more accurate than those from allometric scaling models (ASMs), especially for larger trees (>1,000 kg). More effort should go to further understanding and constraining several TLS error sources. We currently lack an objective method of evaluating point cloud quality for tree volume reconstruction, hindering the development of reconstruction algorithms and presenting a bottleneck for tracking down the error sources identified in our synthesis. Since quantifying AGB with TLS requires only a fraction of the efforts as compared to destructive harvesting, TLS‐calibrated ASMs can become a powerful tool in AGB upscaling. TLS will be critical for calibrating/validating scheduled and launched remote sensing initiatives aiming at global AGB mapping.
Electrical Design for Manufacturability Solutions: Fast Systematic Variation Analysis and Design Enhancement Techniques

Since the scaling of physical dimensions has been faster than the optical wavelengths or equipment tolerances in the manufacturing line, process variability has significantly increased. This, in turn, has led to unreliable design, unpredictable manufacturing, and low yields. The results of these physical variations are circuit metric variations such as performance and power, known as the parametric yield. Source of variations are either systematic (for example, metal dishing and lithographic proximity effects) or random (for example, material variations and dopant fluctuations). The former can be modeled and predicted, whereas the random variations are inherently unpredictable. There are several pattern-dependent process effects which are systematic in nature. These can be detected and compensated for during the physical design to aid manufacturability, and hence improve yield. This thesis focuses on ways to mitigate the impact of systematic variations on design and manufacturing by establishing a bidirectional link between the two. The motivation for doing so is to reduce design guardband and cost, and improve manufacturability and yield. The primary objectives in this research are to develop computer-aided design (CAD) tools for Design for Manufacturability (DFM) solutions that enable designers to conduct more rapid and more accurate systematic variation analysis, with different design enhancement techniques. Four main CAD tools are developed throughout my thesis. The first CAD tool facilitates a quantitative study of the impact of systematic variations for different circuits’ electrical and geometrical behavior. This is accomplished by automatically performing an extensive analysis of different process variations (lithography and stress) and their dependency on the design context. Such a tool helps to explore and evaluate the systematic variation impact on any type of design (analog or digital, very dense or less dense, large chips or small ones, and technology ”A” versus technology ”B”). Secondly, solutions in the industry focus on the ”design and then fix philosophy”, or ”fix during design philosophy”, whereas the next CAD tool involves the ”fix before design philosophy”. Here, the standard cell library is characterized in different design contexts, different resolution enhancement techniques, and different process conditions, generating a fully DFM-aware standard cell library using a newly developed methodology that dramatically reduce the required number of silicon simulations. Several experiments are conducted on 65nm and 45nm designs, and demonstrate more robust and manufacturable designs that can be implemented by using the DFM-aware standard cell library. Thirdly, a novel electrical-aware hotspot detection solution, is developed by using a device parameter-based matching technique since the state-of-the-art hotspot detection
Charging demand for electric vehicle based on stochastic analysis of trip chain

With its popularisation, electric vehicle (EV) has been part of the important load of smart grid. The analysis on charging demands of EVs is the basis of the study of influences on power grid and charging infrastructures planning. Charging demand calculation is based on the precise analysis on the driving law of users. This study proposes a method based on the stochastic simulation of trip chain to solve the existing problem. First, the concept and characteristic variables (trip start time, driving time, parking duration, driving distance and trip purpose) of trip chain are introduced. Second, the probability distribution models of these variables are established considering their correlative relationships. Third, using Monte Carlo method, the complete trip chains are simulated, and then the spatial–temporal distributions of charging demands are calculated. Finally, based on the National household trip survey data, and according to the proposed method, charging demands in different areas are studied. The results show that the proposed method can accurately simulate the driving law of users and reflect spatial–temporal distribution characteristics of charging demands, and different charging scenarios will lead to different forms of charging demand distribution, which will exert different impacts on power system.
Pilot Trial of Arginine Deprivation Plus Nivolumab and Ipilimumab in Patients with Metastatic Uveal Melanoma

Simple Summary Uveal melanoma is a rare subtype of malignant melanoma. It is known to rapidly metastasize, with the liver being the most frequently affected organ. Due to differences from melanoma arising in the skin, such as a lower number of mutations, it responds poorly to immune checkpoint blockade, a treatment approach reinvigorating the patient’s immune system to eliminate the cancer. We here investigated the safety and tolerability of a new combination treatment consisting of two established immunotherapy medications (ipilimumab and nivolumab) with the addition of an experimental arginine depleting medication, pegylated arginine deiminase (ADI-PEG 20), which is thought to make uveal melanoma more amenable to immunotherapy. This novel treatment approach was found to be safe and well-tolerated but did not improve the clinical outcome beyond the expected limited efficacy of approved immunotherapy alone. Abstract Metastatic uveal melanoma (UM) remains challenging to treat, with objective response rates to immune checkpoint blockade (ICB) being much lower than in primary cutaneous melanoma (CM). Besides a lower mutational burden, the overall immune-excluded tumor microenvironment of UM might contribute to the poor response rate. We therefore aimed at targeting deficiency in argininosuccinate synthase 1, which is a key metabolic feature of UM. This study aims at investigating the safety and tolerability of a triple combination consisting of ipilimumab and nivolumab immunotherapy and the metabolic therapy, ADI-PEG 20. Nine patients were enrolled in this pilot study. The combination therapy was safe and tolerable with an absence of immune-related adverse events (irAE) of special interest, but with four of nine patients experiencing a CTCAE grade 3 AE. No objective responses were observed. All except one patient developed anti-drug antibodies (ADA) within a month of the treatment initiation and therefore did not maintain arginine depletion. Further, an IFNg-dependent inflammatory signature was observed in metastatic lesions in patients pre-treated with ICB compared with patients with no pretreatment. Multiplex immunohistochemistry demonstrated variable presence of tumor infiltrating CD8 lymphocytes and PD-L1 expression at the baseline in metastases.
Outcomes of clinico-radiologically advanced cancer (cT4b) of buccal mucosa: a retrospective analysis of 104 patients

Although guidelines recommend non-surgical management for cT4b patients, recent studies have shown that upfront surgery in carefully selected patients can be performed with acceptable long-term survival benefit. In this study, we analysed the survival outcome of curative intent treatment on cT4b patients. Data from 104 patients who were staged cT4b and underwent upfront surgery for squamous cell carcinoma of buccal mucosa were retrospectively analysed. Outcome measures were locoregional recurrence-free survival (LRFS), disease-free survival (DFS) and overall survival (OS). The study cohort comprised 104 patients who had a median age of 52.5 years (range 27–81 years) and included 81 males (77.9%). Thirty-six patients had masticator space involvement on final histopathology, designating them as pT4b. Contrast enhanced computed tomography scan demonstrated 91.67% sensitivity in identifying masticator space involvement, albeit with a lower accuracy of 31.7%. Pathologically, clear margins were achieved in 79 (76%) patients. 62 (59.7%) and 20 (19.2%) patients received adjuvant radiotherapy (RT) and adjuvant chemoradiotherapy respectively. 2-year LRFS, DFS and OS were 61.8%, 60% and 68.1%, respectively. On multivariate analyses, involved margins (hazard ratio (HR) 28.766, p = 0.006), pN2b status (HR 4.68, p = 0.027) and perineural invasion (PNI) (HR 3.001, p = 0.027) showed statistically significant impact on LRFS, involved margins (HR 28.859, p = 0.008) and pN2b status (HR 4.018, p = 0.004) affected DFS. Involved margins (HR 14.139, p = 0.023) and pN2b status (HR 3.166, p = 0.025) showed statistically significant impact on OS. In conclusion, upfront surgery is a feasible option for patients with carcinoma of the buccal mucosa with the involvement of the masticator space. Survival outcomes are better in patients where resection is achieved with clear margins, and regional disease is limited to a single cervical lymph node.
The Association Between Cardiometabolic Risk Factors and Frailty in Older Adults: A Systematic Review

Abstract Background and Objectives Enhanced management and prevention of frailty depend on our understanding of the association between potentially modifiable risk factors and frailty. However, the associations between potentially modifiable cardiometabolic risk factors and frailty are not clear. The purpose of this review was to appraise and synthesize the current evidence examining the associations between the cardiometabolic risk factors and frailty. Research Design and Methods Multiple databases, including MEDLINE (via PubMed), Embase (via Elsevier), and Web of Science (via Clarivate), were searched extensively. Studies that examined cardiometabolic risk factors and frailty as main predictors and outcome of interest, respectively, among older adults (≥60 years) were included. The Joanna Briggs Institute critical appraisal tools were used to evaluate the quality of studies. PRISMA (2020) guided this review, and findings were synthesized without meta-analysis. This systematic review was registered in PROSPERO (CRD42021252565). Results Twelve studies met the eligibility criteria and were included in the review. Abdominal obesity, hyperglycemia, and multiple co-occurring cardiometabolic risk factors were associated with the increased likelihood of frailty in older adults. There was inconsistency across the studies regarding the associations between dyslipidemia, elevated blood pressure, and frailty. Discussion and Implications Understanding the association between cardiometabolic risk factors and frailty can have translational benefits in developing tailored interventions for the prevention and management of frailty. More studies are needed to validate predictive and clinically significant associations between single and specific combinations of co-occurring cardiometabolic risk factors and frailty.
Speaker-Targeted Synthetic Speech Detection

Text-to-speech (TTS) and voice conversion (VC) technologies are evolving quickly towards realistic-sounding human-like voices. As this technology improves, so does the opportunity for malpractice in speaker identiﬁcation (SID) via spooﬁng, the process of impersonating a voice biometric via synthesis. More data typically equates to a more realistic voice model, which poses an issue for well-known subjects, such as politicians and celebrities, who have vast amounts of multimedia available on-line. Detection of synthetic speech has relied on signal processing techniques that focus on the generation of new acoustic features and train deep-learning models to detect when an audio ﬁle has been manipulated through the characterization of un-natural changes or artifacts. However, these techniques do not use any information from the speaker they are evaluating. This paper proposes to incorporate information from the speaker-of-interest (SoI) into the models to avoid speciﬁc spooﬁng attacks for certain vulnerable people as a logical access (LA) control tool. The wealth of data for well-known people can also be used to train a speaker-speciﬁc spooﬁng detector with a higher level of accuracy than a speaker-independent model. The paper proposes a new xResNet-PLDA system and compares it to three different baseline systems: a state-of-the-art speaker identiﬁcation system, an xResNet system trained to discriminate between bonaﬁde and fake speech, and a speaker identiﬁcation system in which the PLDA and calibration models were trained with bonaﬁde and fake speech. We evaluated the systems in two different scenarios — a cross-validation scenario and a hold-out scenario — with three different databases. We show how the proposed system outperforms dramatically the baseline systems in each scenario and for each database. Finally, we show how using a small amount of the SoI’s speech to adapt global calibration parameters improves the performance of the system, especially in unseen conditions.
Rural households’ attitude to diversification into non-farm enterprises in Katsina State, Nigeria

The study investigated the rural households’ attitude to diversification into non-farm enterprises in Katsina State, Nigeria. A multistage sampling procedure was used to select 256 farmers for the study. Data were obtained with the aid of questionnaire and analyzed using percentage and regression analysis. The most positive attitude was “that non-farm enterprise is a crucial pathway to food security for rural households”. It was closely followed by “non-farm enterprise is a source of agricultural household savings used for food purchase in hard times” and “non-farm enterprise provides a means to cope or survive when farming fails”. Farmers expressed positive attitude to diversification into non-farm enterprises and do not depend on agriculture as a sole means of livelihood but diversified income sources; the diversified farmers had higher income level. Government should support the existing non-farm enterprises and encourage creation of new ones; also improve formal credit access. Furthermore, technical support and skills acquisition training programs should be provided to enhance the performance and efficiency of non-farm enterprises in rural areas.
Contagious COVID‐19 policies: Policy diffusion during times of crisis

Abstract The COVID‐19 crisis demanded rapid, widespread policy action. In response, nations turned to different forms of social distancing policies to reduce the spread of the virus. These policies were implemented globally, proving as contagious as the virus they are meant to prevent. Yet, variation in their implementation invites questions as to how and why countries adopt social distancing policies, and whether the causal mechanisms driving these policy adoptions are based on internal resources and problem conditions or other external factors such as conditions in other countries. We leverage daily changes in international social distancing policies to understand the impacts of problem characteristics, institutional and economic context, and peer effects on social distancing policy adoption. Using fixed‐effects models on an international panel of daily data from 2020, we find that peer effects, particularly mimicry of geographic neighbors, political peers, and language agnates drive policy diffusion and shape countries' policy choices.