Miracle-dz/UniFAR-FTUs huggingface dataset:
A reassessment of archaeological human remains recovered from rock shelters in Cathkin Peak, South Africa

ABSTRACT Various skeletons from the uThukela region of the uKhahlamba-Drakensberg Mountains of South Africa were excavated from rock shelters there during the early part of the twentieth century, with limited accompanying data or analysis. This paper analyses and reports on nine such graves (eight of which contained human remains), excavated during 1931 near Cathkin Peak. The remains are currently housed in the Raymond A. Dart Archaeological Human Remains Collection, University of the Witwatersrand, Johannesburg. Most of the skeletons were radiocarbon-dated to between the fourteenth and mid-seventeenth centuries, but one is older and dates to between the seventh and ninth centuries AD. Remains recovered from the various shelters included those of both adults and children, males and females, indicating that these rock shelters were used for the burials of, and were possibly occupied by, a wide variety of individuals over a long period of time. Skeletal analyses revealed several signs of disease and trauma, attesting to some hardships living in this region of South Africa. Stable isotope analyses of carbon and nitrogen indicate a predominantly plant-based diet. Originally it was thought that these individuals’ remains represented those of the historic amaZizi people, however, radiocarbon dates indicate that they are contemporaneous with the Moor Park phase of the Blackburn branch, which predates the amaZizi by several decades. Of interest is the fact that one individual predates the Moor Park phase. This is significant and sheds some light on the movement of people from KwaZulu-Natal into the interior. Future ancient DNA analysis will provide more information on the origin and genetic relationship of these individuals.
Return and volatility spillover between India, UK, USA and European stock markets: The Brexit impact

The 2016 Brexit referendum created potential turmoil in financial markets. The purpose of this study is to examine the impact of the Brexit referendum on the return and volatility spillover between the EU, the UK, and the USA stock markets and the Indian stock market during the pre- and post-Brexit referendum period. The VAR and bivariate GARCH BEKK models were employed. The study results suggest that before the Brexit referendum, Indian stock market returns made no significant return spillover on the other markets. On the contrary, following the referendum, Indian stock returns significantly spilled over to France, Germany, the UK, and the USA stock market returns. The study results also identified a substantial increase in the bidirectional volatility spillover between India-France, India-UK, and India-USA during the post-Brexit referendum period. Therefore, the investors’ opportunity to invest simultaneously in India, UK, EU, and US stock markets for portfolio diversification is limited. India was affected mainly by its own past shocks before the Brexit referendum. However, after the Brexit referendum, Indian markets are getting more and more integrated with other markets. In order to reap the diversification benefits, a prudent investment strategy will need to be developed in the future, especially during times of economic and political uncertainty and market crisis.
Karakterisasi Selulosa dari Kulit Buah Kakao (Theobroma cacao L.) pada Berbagai Konsentrasi Hidrogen Peroksida dan Suhu Proses Bleaching

Cocoa pod husk (CPH) is a byproduct of cocoa processing that is abundant and has a low economical value. CPH cellulose can be obtained using the delignification and bleaching process. This study aimed to determine the effect of hydrogen peroxide (H2O2) concentration and bleaching process temperature on the characteristics of CPH cellulose and to determine the best treatment to extract CPH cellulose. This research uses a factorial randomized block design, consists of two factors. The first factor is H2O2 concentration, which consists of 10%, 20%, and 30%. The second factor is bleaching temperature, which consists of 60oC, 80oC, and 100oC. The data were analyzed by analysis of variance and continued with the Tukey test. The observed variables were yield, whiteness index, cellulose, hemicellulose, and lignin content. Best treatments were determined using the effectiveness index. The results showed that H2O2 concentration and bleaching process temperature had a significant effect on yield, whiteness index, cellulose, and lignin content of a bleached CPH. Bleaching temperature had a significant effect, but H2O2 concentration had an insignificant effect on hemicellulose content. Interactions between treatments had a significant effect on whiteness index and cellulose content but had no significant effect to yield, hemicellulose, and lignin content of a bleached CPH. The best treatment was obtained using a combination of 30% H2O2 and 100oC bleaching temperature, resulting in 16.88±0.12% yield, 59.67±0.50% whiteness index, 70.40±0.44% cellulose, 6.33±0.19% hemicellulose, and 4.49±0.46% lignin content. Keywords : cellulose, cocoa pod husk, bleaching, hydrogen peroxide, temperature
How we talk(ed) about it: Ways of speaking about computational architecture

If we understand architecture as a three-part system formed by the building, its image, or drawings and images describing buildings, and the critical discourse around architecture, then the texts or ways of speaking about architecture play a key role in understanding the field and its development. By analysing a corpus of around 4.6 million words from texts written between 2005 and 2020 that form a part of critical discourse in computational architecture (understood as the result of the intense digitalization of the field), this paper aims to map ways of speaking about computational architecture. This contributes to architectural theory and might help gain a better understanding of the evolution of the digitalization of construction in general. Findings show that computational architecture is surrounded by a specific way of speaking, hybridized with words from fields such as biology, neuroscience, arts and humanities, and engineering. While some topics such as ‘sustainability’ or ‘biology’ come up consistently in the discourse, others, such as ‘people’ or ‘human’, have periods when they are more and less popular. After highlighting open research questions, the paper concludes by presenting a map of periodic and recurring topics in ways of speaking about computational architecture over the last 15 years, thus tracking and documenting long-term trends, and illuminating patterns in the broader field of digital construction.
COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling (Preprint)

BACKGROUND COVID-19 vaccines are one of the most effective preventive strategies for containing the pandemic. Having a better understanding of the public’s conceptions of COVID-19 vaccines may aid in the effort to promptly and thoroughly vaccinate the community. However, because no empirical research has yet fully explored the public’s vaccine awareness through sentiment–based topic modeling, little is known about the evolution of public attitude since the rollout of COVID-19 vaccines. OBJECTIVE In this study, we specifically focused on tweets about COVID-19 vaccines (Pfizer, Moderna, AstraZeneca, and Johnson & Johnson) after vaccines became publicly available. We aimed to explore the overall sentiments and topics of tweets about COVID-19 vaccines, as well as how such sentiments and main concerns evolved. METHODS We collected 1,122,139 tweets related to COVID-19 vaccines from December 14, 2020, to April 30, 2021, using Twitter’s application programming interface. We removed retweets and duplicate tweets to avoid data redundancy, which resulted in 857,128 tweets. We then applied sentiment–based topic modeling by using the compound score to determine sentiment polarity and the coherence score to determine the optimal topic number for different sentiment polarity categories. Finally, we calculated the topic distribution to illustrate the topic evolution of main concerns. RESULTS Overall, 398,661 (46.51%) were positive, 204,084 (23.81%) were negative, 245,976 (28.70%) were neutral, 6899 (0.80%) were highly positive, and 1508 (0.18%) were highly negative sentiments. The main topics of positive and highly positive tweets were planning for getting vaccination (251,979/405,560, 62.13%), getting vaccination (76,029/405,560, 18.75%), and vaccine information and knowledge (21,127/405,560, 5.21%). The main concerns in negative and highly negative tweets were vaccine hesitancy (115,206/205,592, 56.04%), extreme side effects of the vaccines (19,690/205,592, 9.58%), and vaccine supply and rollout (17,154/205,592, 8.34%). During the study period, negative sentiment trends were stable, while positive sentiments could be easily influenced. Topic heatmap visualization demonstrated how main concerns changed during the current widespread vaccination campaign. CONCLUSIONS To the best of our knowledge, this is the first study to evaluate public COVID-19 vaccine awareness and awareness trends on social media with automated sentiment–based topic modeling after vaccine rollout. Our results can help policymakers and research communities track public attitudes toward COVID-19 vaccines and help them make decisions to promote the vaccination campaign.
Fault Diagnosis of a Propeller Using Sub-Nyquist Sampling and Compressed Sensing

The fault diagnosis of rotating machinery is generally performed using methods that employ vibration and sound. These methods are simple and accurate. However, all of these methods measure vibration data on the basis of the sampling theorem. Thus, they require a high measurement frequency, resulting in a large data volume and expensive measurement equipment. In recent years, a method that uses compressed sensing has been proposed to solve this problem, but it requires dedicated hardware to realize random sampling. To overcome this drawback, we developed a random start uniform sampling method (RSUSM) and combined it with compressed sensing (CS). RSUSM is a method of measuring data at a fixed frequency with a random start time. Numerical experiments demonstrate how the specific constant changes for each RSUSM parameter. This allows us to know the limit of how many measurement points are required for the number of non-zero components. We also applied CS by RSUSM to the sound pressure measurement results of the failed propeller, and found that the signal could be recovered less than 25% error even in a noisy real environment within the aforementioned limit. In this case, we found that the measurement frequency could be compressed to 1/80th of the frequency required by the sampling theorem, and the measurement data size to 1%. This approach is expected to diagnose faults in more rotating machines by significantly reducing the costs associated with data collection and storage.
Bicuspid Aortic Valve Stenosis: From Pathophysiological Mechanism, Imaging Diagnosis, to Clinical Treatment Methods

Bicuspid aortic valve (BAV) is the most frequent congenital anomaly and has a natural evolution toward aortic regurgitation or stenosis due to the asymmetrical valve function associated with an evolutive ascending aortopathy. Several BAV classifications exist describing the presence and number of raphe, amount and location of calcium, and the symmetry of the functional cusps. The impact of BAV morphology on transcatheter aortic valve implantation (TAVI) outcomes still remains little investigated. Pivotal randomized trials comparing TAVI with surgery have excluded BAV until yet. However, data from registries and observational studies including highly selected patients have shown promising results of TAVI in BAV. With this review, we aimed at describing anatomical and pathophysiological characteristics of BAV, discussing the main aspects to assess diagnostic imaging modalities, and giving an overview of TAVI outcomes and technical considerations specific to BAV morphology.
Risk of Four Geriatric Syndromes: A Comparison of Mental Health Care and General Hospital Inpatients

An observational, cross-sectional study is conducted to compare elevated risk scores of four geriatric syndromes (falls, malnutrition, physical impairment, delirium) in older hospitalized psychiatric patients (n=178) with patients hospitalized in a general hospital (n=687). The median age of all patients was 78 years (IQR 73.3–83.3), 53% were female. After correction for age and gender, we found significantly more often an elevated risk in the mental health care group, compared to the general hospital group of falls (Odds Ratio (OR) = 1.75; 95% Confidence Interval (CI) 1.18–2.57), malnutrition (OR = 4.12; 95% CI 2.67–6.36) and delirium (OR = 6.45; 95% CI 4.23–9.85). The risk on physical impairment was not statistically significantly different in both groups (OR = 1.36; 95% CI.90–2.07). Older mental health care patients have a higher risk to develop geriatric syndromes compared to general hospital patients with the same age and gender, which might be explained by a higher level of frailty.
Delivering Cognitive Stimulation Therapy (CST) Virtually: Developing and Field-Testing a New Framework

Purpose This feasibility and pilot study aimed to develop and field-test a 14-session virtual Cognitive Stimulation Therapy (vCST) programme for people living with dementia, developed as a result of services moving online during the COVID-19 pandemic. Methods The vCST protocol was developed using the existing group CST manual, through stakeholder consultation with people living with dementia, caregivers, CST group facilitators and dementia service managers. This protocol was then field-tested with 10 groups of people living with dementia in the Brazil, China (Hong Kong), India, Ireland and the UK, and feedback on the protocol was gathered from 14 facilitators. Results Field testing in five countries indicated acceptability to group facilitators and participants. Feedback from these groups was used to refine the developed protocol. The final vCST protocol is proposed, including session materials for delivery of CST over videoconferencing and a framework for offering CST virtually in global settings. Conclusion vCST is a feasible online intervention for many people living with dementia. We recommend that it is offered to those unable to access traditional in-person CST for health reasons, lack of transport or COVID-19 restrictions. Further research is needed to explore if participant outcomes are comparable to in-person CST groups.
Optimal Group Preventive Maintenance Model for Complex Systems

Maintenance of complex systems is different from maintenance of individual units,because there are economic and failure dependence between units in the system.The optimal maintenance intervals of the units are not necessarily optimal in view of the entire system.For this reason,group preventive maintenance is presented for complex systems.First,maintenance cost and availability are analyzed.The optimal group preventive maintenance model is then proposed for complex systems.Subject to hazard,the model minimizes maintenance cost and maximizes availability.Finally,an air conditioning system is presented as an example in the case study,and the result shows effectiveness of the model.
Implementation of Autonomous Driving Algorithms on a Miniature Robot

The proposed work mainly attempts to implement numerous image processing algorithms on TurtleBot3 Waffle Pi for autonomous driving using Robot Operating System (ROS). The image processing algorithms used in this work for developing a vision-based system for autonomous driving. Before actual implementation on hardware, the algorithms are first tested in simulation. The time-synchronized data feed is collected from the sensors of the robot. Then the collected data is further processed to perform controlling actions using actuators. The robot's performance is tested and optimized for the same algorithms by varying different parameters in simulation and on a real robot.
Comparison of the Efficacy of Transconjunctival Incision with Lateral Canthotomy and Intraoral Vestibular Incision for Management of Infra-orbital Rim Fracture

Background: The treatment of an infraorbital rim fracture necessitates careful consideration. There several different techniques which are implicated with exposure of the infraorbital rim having its own sets of merits and demerits. Here, we intend to compare two incisions used for the management of fracture of the infraorbital rim. Objectives: The focus of this study is to compare and analyze the efficacy of transconjunctival and intraoral incisions in terms of time taken for fracture exposure, adequacy of exposure and fixation, and post-operative complications such as soft tissue injury, chemosis, infraorbital nerve paresthesia, ectropion, scleral show, lagophthalmos, and wound dehiscence. Methodology: Two groups with 10 patients requiring open reduction and internal fixation of infraorbital rim fracture in each group will be included in the study. The patients will be divided randomly into Group A consisting of patients undergoing open reduction and internal fixation using transconjunctival incision or Group B consisting of patients undergoing open reduction and internal fixation using intraoral incision. The two approaches will be compared on the basis of time taken for exposure of fracture site, adequacy of exposure and fixation and post operative complications like soft tissue injury, chemosis, infraorbital nerve paresthesia, ectropion, sclera show, lagophthalmos and wound dehiscence. Expected Results: The efficacy of intraoral incision would be better than transconjunctival incision as it would lead to lesser post operative ocular complications like chemosis, ectropion etc.
Enhanced Recovery After Surgery for Pediatric Cleft Repair: A Systematic Review and Meta-Analysis

Objective: Perform a systematic review assessing the efficacy of enhanced recovery after surgery (ERAS) protocols for cleft palate repair. Primary outcomes included hospital length of stay, readmission rates, and postoperative narcotic use. Secondary outcomes included complications, time to initial postoperative oral intake, and pain scores. Data Sources: Cohort and randomized studies of ERAS protocols pertaining to cleft palate repair were identified by systematic review of Medline, Scopus, Embase, and grey literature. Review Methods: Data extracted included patient demographics, clinical care protocols, complication rates, postoperative narcotic use, time to initial postoperative oral intake, hospital length of stay, family satisfaction, and 30-day readmission. Meta-analysis was used to compare outcomes between patients enrolled in ERAS protocols versus those in conventional care pathways. Results: Eight hundred sixty-five articles were screened, and 5 studies met full inclusion criteria. A total of 425 patients were included. Patients in ERAS protocols saw a mean reduction of – 23.96 hours in length of stay compared to controls (95% confidence interval [CI]: – 26.4, – 20.6). Patients in ERAS protocols also had decreased total morphine consumption (mean difference [MD]: – 3.88 mg; CI: – 4.31, – 3.45), and decreased time to first initial feed compared to controls (MD: – 3.88 hours; CI: – 4.3, – 3.5). There was no difference in readmission rates or complication rates between ERAS and control groups. Conclusions: ERAS protocols have seen limited use in pediatric patients. The present study sought to assess the impact of ERAS protocols following primary palatoplasty. Our results indicate decreased hospital length of stay, postoperative opioid consumption, and time to feeding, without increasing readmission rates or complication rates.
Review on Face Detection and Recognition Technology Based on Neural Network

In this paper, feature extraction and facial recognition are studied in order to resolve problems like highdimension problem, small size samples and no-linear separable problem that exist in facial recognition technology. In the part of feature extraction we use a HGPP algorithm, to extract the input features in building a face recognition system. The neural network, which represents brilliant performance on small training sets, non-linear separable and high-dimension pattern recognition problems in the recognition stage, is used for pattern classification. The proposed approach is validated with the ORL database. Experimental results demonstrate the effectiveness of this method in the performance of face recognition.
Research State and Development of Sprinkler Irrigation Equipments in China

The researching, production, and application of 8 sprinkler irrigation systems widely used inthe world are analyzed, including sprinkler, pump and the main equipments of sprinkler irrigation systems.The research advances, existing problems and gaps between developed countries during the Tenth Five-YearPlan in China are discussed. The developing trends, aim, emphases and developing pattern during the EleventhFive-year Plan in china are put forward, and four pieces of advice on the development policy of the water-saving irrigation engineering and equipments are put forward.
Offloading in Mobile Edge Computing Based on Federated Reinforcement Learning

Mobile edge computing (MEC) has become a more and more popular technology, which plays a very important role in various fields. In view of the task of offloading of multiple users, most of the existing studies do not take into account data sharing and cooperation among users, which can easily lead to less generalization of the model trained by a single user, and some data sharing may also cause privacy leakage. Then, this paper uses the method of federated reinforcement learning to solve this problem in order to insure privacy. Besides, considering the poor quality of local models, which leads to the poor versatility of the overall parameters, this paper proposes a federated reinforcement learning method based on Attention mechanism to aggregate the parameter weights, which makes the new model more generalized. The experimental results show that the federated reinforcement learning task offloading model with Attention mechanism can reduce the processing delay of the task.
Wireless positioning technology based on UWB

In order to satisfy the requirement of highly positioning accuracy, ultra wide band(UWB)positioning technology in wireless communication is studied. According to the research of Federal Communications Commission, research situation of wireless positioning technology is analyzed. Definition of ultra wide band signal and commonly used in wireless location technology are introduced. Finally, Combined with analysis of several wireless positioning technology, positioning technologies that fit ultra-wideband networks are given. The analysis result show that ultra wide band(UWB)positioning technology have high positioning accuracy than the tradition positioning technology.
Automatic dispatch system of power grid urgent repair

The design of automatic dispatch system for grid urgent repair is introduced,which is composed of the information collection and data communication channel monitoring module,the database generation and message sending module and the communication processing module. It extracts, classifies and processes the failure signals from the supervisory control and data acquisition system,energy management system and online communication channel monitoring system. The key design technologies of this system are described in detail. It can be seamlessly integrated with MIS to reduce the fault treatment time.