Miracle-dz/UniFAR-FTUs huggingface dataset:
TECHNICAL ASPECTS OF ILLUSTRIS- A COSMOLOGICAL SIMULATION

THE BIG QUESTION Where did we come from and where are we going? Humans have been trying to figure out the origin of the known universe since the beginning of time and Since the early part of the 1900s, the Big Bang theory is the most accepted explanation and has dominated the discussion of the origin and fate of the universe. And the future of the universe can only be hypothesized based on our knowledge but the question does not seem to get irrelevant anytime in the near future. With the advancement technology and the available research, data and techniques like data mining and machine learning the problems can be visualised through accurate digital representations and simulations which are being used extensively to facilitate further developments in all fields of science.
Progress on IOF's Process and Production Planning Reference Ontology

Modern manufacturing enterprises are characterized by applications of information and automation at all levels in product life cycle (design, manufacturing, usage, recycling). Seamless flow of the data between various stake holders in such supply chain is expected to deliver concepts such as Industry 4.0 and IIoT. However, in order to achieve such semantic integration it is necessary to capture and share knowledge from various product development stages. This paper reports on efforts to develop a reference ontology for Process and Production Planning (PPS) and current progress of the corresponding working group within Industrial Ontology Foundry (IOF). The development process is described together with the current draft of the PPS ontology. Discussion at the end also addresses remaining challenges.
Early Detection of Alzheimer Disease using Brain Connectome: A Brief Survey

Alzheimer disease is one of the most common neurodegenerative disorder/disease. People are now aware about this disease, due to different technologies available to detect it at an early stage. Around 7.15 million people are predicted to be affected by Alzheimer’s by the end of 2030 globally [1]. It is observed that elderly people are more prone to suffer from Alzheimer’s or any other neurodegenerative disorder. Alzheimer’s is incurable; once a person is affected he/she has to live with it lifelong as it is generally detected during the later stages. Early detection of Alzheimer’s primarily helps in delaying its progression, improvising the living of people suffering from the disease. Secondarily, it gives a better view and in-depth knowledge to doctors and researchers in understanding and treating the disease. Hence, an overview of some of the recent techniques for early detection of Alzheimer’s is presented in this paper. Some of the factors that help in diagnosing the disease in its early stages are: Brain connectomes, Cerebrospinal fluids (CSF) and amyloid levels (p-tau or t-tau), age of the patient, etc. In one of the methods, CSF levels, p-tau levels and age are the prime factors used for detecting Alzheimer’s. Second method detects the disease using structural and functional connectomes. Brain morphometry and structural connectomes are used with different machine learning algorithms in the third technique. In the next method, prion-like mechanism is simulated for better understanding of the disease. Structural and functional connectomes of the subjects are evaluated using graphical methods in the last technique.
Soot Formation from the Combustion of Biomass Pyrolysis Products and a Hydrocarbon Fuel, n-Decane: An Aerosol Time Of Flight Mass Spectrometer (ATOFMS) Study

This paper is concerned with an aerosol time-of-flight mass spectrometer (ATOFMS) study of soot formation from the combustion of proxies of biomass (eugenol, furfural) and a hydrocarbon fuel (n-decane). The objective of this work was to gain insight into the soot growth mechanism in the combustion of biomass by studying the combustion of single components of wood (eugenol–lignin model and furfural–cellulose model), and by comparison with soot composition from combustion of a hydrocarbon fuel whose soot-forming mechanism is better known. Liquid fuels were burned using a wick burner, and the products in the aerosol phase were examined using an ATOFMS. The reaction process for n-decane combustion was examined using an opposed flame simulation with Chemkin-Pro modeling. A comparison of the model output with experimental results for n-decane give information on the soot growth mechanism. The same main routes for soot formation were operative both in biomass proxies and in n-decane. The principal differences in.
Attribute based Data Management in Crypt-Cloud

Digital file computing and backup services are valuable to businesses and institutions of all kinds. Data management in the cloud is rising as an alternative to data management using traditional on premises software systems. However like different cloud computing technologies, cloud data management can introduce challenges like information security associated with storing sensitive business information outside the company’s firewall. In this paper, we tend to propose a system that involves attribute based data management in crypt cloud. At the site end the individual has an initial level authentication procedure that is processed inside the database of the website. Now the accountable Semi-Trusted Authority produces decryption keys dependent on their collection of characteristics for the members of the organization. The encryption of the files uploaded into the general public cloud is completed by the data owner using RSA encryption algorithmic program which generates a unique file access permission key for the users to access the information within the cloud. The outsourced details may be accessed by registered data users (e.g., read, compose, print, erase, and decrypt). Based on their expertise and role entered in their registered records, file permission keys are given here to the users. Senior staff have any right to access the data (read, write, remove, and download). Fresher's have just the authorization to search the files. If any senior worker leaks or shares their secret permission keys to their junior workers, the system will generate an attribute set for their role in the background confirming that the user has every right to access the information when entering the password for re-encryption. Unless the collection of attributes is not aligned to the regulation files of the data owners they would be charged as guilty. The proposed scheme achieves confidentiality and user access privileges.
A Mixed approach of Deep Learning method and Rule-Based method to improve Aspect Level Sentiment Analysis

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users opinion. Hence, the organizations would benefit through the development of a platform, which can analyze public sentiments in the social media about their products and services to provide a value addition in their business process. Over the last few years, deep learning is very popular in the areas of image classification, speech recognition, etc. However, research on the use of deep learning method in sentiment analysis is limited. It has been observed that in some cases the existingmachine learningmethods for sentiment analysis fail to extract some implicit aspects andmight not be very useful. Therefore, we propose a deep learning approach for aspect extraction from text and analysis of users sentiment corresponding to the aspect. A seven layer deep convolutional neural network (CNN) is used to tag each aspect in the opinionated sentences. We have combined deep learning approach with a set of rulebased approach to improve the performance of aspect extraction method as well as sentiment scoring method. We have also tried to improve the existing rule-based approach of aspect extraction by aspect categorization with a predefined set of aspect categories using clustering method and compared our proposed method with some of the state-of-the-art methods. It has been observed that the overall accuracy of our proposed method is 0.87 while that of the other state-of-the-art methods like modified rule-basedmethod and CNN are 0.75 and 0.80 respectively. The overall accuracy of our proposedmethod shows an increment of 7–12% from that of the stateof-the-art methods.
Effectiveness of Principals Interpersonal Communication: A Literature Review

The purpose of this review is to determine the effectiveness of interpersonal communication of the principal In context of the world. This research uses compare journals related to the effectiveness of interpersonal communication in the sphere of education. Based on the results of a literature review from various countries in the world, the authors found that interpersonal communication can help the school principal in carrying out their duties by communicating in interpersonal with anyone. Therefore, the principal is expected to communicate well in interpersonal to create relationships, openness and trust within the scope of the organization Communication that can be done by the principal is interpersonal communication to create the relationship and trust are invited to communicate. Interpersonal communication can be effective if communication is conducted face-to-front and two-way with openness, clarity, transparency, brief, kindness, concrete, consideration. The importance of the effectiveness of interpersonal communication in education attracts researcher to examine, and this article is to test how the effectiveness of interpersonal communication of the principal in the organization. With the expectation of the principal can develop continuously interpersonal communication to build relationships and trust to anyone.
Effects of climate variables on the incidence of scorpion stings in Iran for five years

Abstract Background: Although scorpionism is recorded worldwide, some regions such as Iran present a higher incidence. Due to the great prevalence of scorpion stings in Khuzestan province, southwestern Iran, the present study examined the relationship between different climate parameters and the scorpion sting rate in this area from April 2010 to March 2015. Methods: In this cross-sectional descriptive-analytical study, we considered all scorpion sting cases recorded in the Department of Infectious Diseases, Ahvaz Jundishapur University of Medical Sciences. Data were analyzed using statistics, frequency distribution and Pearson’s correlation coefficient. Results: A total of 104,197 cases of scorpion stings was recorded from 2010 to 2015. The cumulative incidence of scorpion sting was 2.23%. The spatial distribution of scorpion stings showed that most cases occurred in the Dehdez district (4,504 scorpion stings/100,000 inhabitants) and the Masjed Soleyman county (4,069 scorpion stings/100,000 inhabitants). A significant association was found between climate factors (temperature, evaporation rate, sunshine duration, humidity, and precipitation) and the scorpion sting rate. An increase in rainfall and humidity coincided with a reduction in scorpion stings whereas an increase in temperature, evaporation, and sunshine duration was accompanied by a growth of scorpion stings. No significant correlation was found between wind velocity/direction and the incidence rate of stings. Moreover, the seasonal peak incidence of scorpion stings was recorded in summer (an average of 8,838 cases) and the lowest incidence was recorded during winter (an average of 1,286 cases). The annual trend of scorpion sting cases decreased during the period from 2010 to 2015. Conclusion: Climate variables can be a good index for predicting the incidence of scorpion stings in endemic regions. Since they occur mostly in the hot season, designing preventive measures in the counties and districts with a high incidence of scorpion stings such as Dehdez and Masjed Soleyman can minimize mortality and other burdens.
Pectoralis Major Ruptures in the National Football League: Incidence, RTP, and Performance Analysis

Background: While pectoralis major (PM) tears are rare injuries in National Football League (NFL) athletes (previous study reported only 10 PM ruptures between 2000 and 2010), the incidence of these injuries has increased over the past decade. The impact these injuries have on a player’s performance after return has not been measured. Purpose/Hypothesis: To identify player characteristics that may predispose to PM tears and to determine the impact of this injury on return to play and performance. We hypothesized that there would be no difference in performance between the year before and after their injury. Study Design: Descriptive epidemiology study. Methods: NFL players who experienced PM tears between the years 2010 and 2018 were identified using publicly available reports. Several individual player characteristics were identified and recorded, and the return-to-play rates after injury were determined for each position. The pre- and postinjury Pro Football Focus grades of players who met inclusion criteria were compared. A paired t test analysis of the change in player performance was used for analysis. Results: In this study, 63 ruptures were identified between 2010 and 2018. Linebackers had the highest incidence of PM tear compared with any other position. Of all injuries, 79.3% were sustained by defensive players. The majority of PM tears occurred during games. Only 6.9% of players who sustained the injury were suspended for performance-enhancing drug use during their professional career. A total of 85.7% of players returned to play in the NFL after injury. Among those who returned to play there were no significant changes in player performance from pre- to post-injury. Conclusion: NFL players demonstrated 85.7% return-to-play rates and no significant drop-off in performance after PM ruptures. During the time period studied, there was an increase in incidence of PM ruptures compared with the previous decade. Further investigation is needed to determine potential causes for the increased incidence of PM ruptures in NFL players.
Posttraumatic growth in women with breast cancer: emotional regulation mediates satisfaction with basic needs and maladaptive schemas

ABSTRACT Background: Despite the negative consequences of breast cancer, many women experience positive changes after diagnosis. Objective: The aim of this study was to examine the mediating role of emotion regulation between post-traumatic growth (PTG), satisfaction of basic needs and maladaptive schemas. Method: A total of 210 female patients diagnosed with breast cancer for at least six months were assessed using measures of the PTG Inventory, Basic Psychological Needs Satisfaction Scale, Young Schema Questionnaire–Short Form, and the Emotion Regulation Questionnaire. The collected data was analysed using structural equation modelling by SPSS and Amos 23.0. Results: Basic needs and maladaptive schema paths to emotion regulation and PTG, and emotion regulation path to PTG were significant. In addition, maladaptive schemas path to emotion regulation was insignificant. Conclusion: The current results show that focusing on satisfaction of basic needs and using positive emotion regulation strategies positively affect PTG. Additionally, activating maladaptive schemas and using negative emotion regulation strategies have a negative effect on PTG. HIGHLIGHTS The current study’s model showed that the emotion regulation played a mediatory role in the relationship between basic needs satisfaction and PTG but not between maladaptive schemas and PTG.
Characterization of the complete chloroplast genome of an annual herb, Chenopodium album (Amaranthaceae)

Abstract Chenopodium album is an annual herb from Amaranthaceae with worldwide distribution. It is a leafy vegetable as well as an important subsidiary grain crop with high nutritional value and medicinal value. In this study, we reported the complete chloroplast genome of C. album. The total chloroplast genome was 152,167 bp in length, containing a large single-copy region (LSC, 83,676 bp), a small single-copy region (SSC, 18,105 bp), and a pair of inverted repeat regions (IRs, 25,193 bp). The complete chloroplast genome contains 110 genes, including 78 protein-coding genes, 28 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes with an overall GC content of 37.3%. Phylogenetic analysis showed that C. album was sister to C. acuminatum within Chenopodioideae. The complete chloroplast genome of C. album will provide useful resources for the development and utilization of this species and the phylogenetic study of Amaranthaceae.
Effect of Capsular Closure After Hip Arthroscopy for Femoroacetabular Impingement Syndrome on Achieving Clinically Meaningful Outcomes: A Meta-analysis of Prospective and Comparative Studies

Background: Recent literature has demonstrated conflicting evidence as to whether capsular closure after hip arthroscopy for femoroacetabular impingement syndrome (FAIS) results in superior outcomes compared with capsulotomy without repair. Additionally, these studies have not explored the effect of capsular management on clinically significant outcome improvement. Purpose: To perform a meta-analysis of prospective and comparative studies to determine whether capsular management influences the rate of clinically significant outcome improvement after hip arthroscopy for FAIS. Study Design: Systematic review; Level of evidence, 3. Methods: PubMed, OVID/Medline, EMBASE, and Cochrane databases were queried in September 2020 for studies with evidence levels 1 to 3 that directly compared capsular management cohorts and reported rates of achieving the minimal clinically important difference (MCID) at a minimum follow-up of 2 years. Studies of level 4 evidence, those not describing or directly comparing capsular management techniques as well as those not reporting the MCID were excluded. Methodological quality was assessed using the methodological index for nonrandomized studies tool. Mantel-Haenszel fixed-effects models were constructed to quantitatively evaluate the association between capsular management and achievement of the MCID by generating effect estimates in the form of relative risk (RR) with 95% CIs. Results: A total of 6 studies with 1611 patients were included. The overall pooled rate of MCID achievement for the modified Harris Hip Score (mHHS), Hip Outcome Score Activities of Daily Living (HOS-ADL), and HOS Sports Subscale (HOS-SS) were 84.4%, 80.3%, and 82.5%, respectively, at a mean follow-up of 40.8 months (range, 24-87.6 months). Capsular closure was associated with a significantly higher rate of MCID achievement for the mHHS (RR, 1.06; 95% CI, 1.01-1.10; P = .001) and trended toward statistical significance for the HOS-ADL (RR, 1.11; 95% CI, 1.0-1.24; P = .055) and the HOS-SS (RR, 1.09; 95% CI, 0.99-1.21; P = .094). Conclusion: Although capsular closure appeared to result in higher rates of clinically significant outcome improvement in hip function, there was no definitively increased likelihood of achieving clinically significant improvement in relevant hip outcome scores with capsular closure.
Disabling the Nuclear Translocalization of RelA/NF-κB by a Small Molecule Inhibits Triple-Negative Breast Cancer Growth

Introduction Constitutive activation of NF-κB has been implicated as being contributive to cancer cell growth, drug resistance, and tumor recurrence in many cancers including breast cancer. Activation of NF-κB leads to nuclear translocation of RelA, a critical component of the NF-κB transcription factor complex, which subsequently binds to specific DNA sites and activates a multitude of genes involved in diverse cell functions. Studies show that triple-negative breast cancer (TNBC) cells possess constitutively active NF-κB and concomitantly have higher levels of nuclear localization of RelA than cytoplasmic RelA. This feature is considered to be associated with the response to chemotherapy. However, currently, there is no specific inhibitor to block nuclear translocation of RelA. Methods A structure-based approach was used to develop a small-molecule inhibitor of RelA nuclear translocation. The interaction between this molecule and RelA was verified biophysically through isothermal titration calorimetry and microscale thermophoresis. TNBC cell lines MDA-MB-231 and MDA-MB-468 and a human TNBC xenograft model were used to verify in vitro and in vivo efficacy of the small molecule, respectively. Results We found that the small molecule, CRL1101, bound specifically to RelA as indicated by the biophysical assays. Further, CRL1101 blocked RelA nuclear translocation in breast cancer cells in vitro, and markedly reduced breast tumor growth in a triple-negative breast cancer xenograft model. Conclusion Our study demonstrates that CRL1101 may lead to new NF-κB-targeted therapeutics for TNBC. Further, blocking of nuclear translocation of shuttling transcription factors may be a useful general strategy in cancer drug development.
Artificial intelligence for identification and characterization of colonic polyps

Colonoscopy remains the gold standard exam for colorectal cancer screening due to its ability to detect and resect pre-cancerous lesions in the colon. However, its performance is greatly operator dependent. Studies have shown that up to one-quarter of colorectal polyps can be missed on a single colonoscopy, leading to high rates of interval colorectal cancer. In addition, the American Society for Gastrointestinal Endoscopy has proposed the “resect-and-discard” and “diagnose-and-leave” strategies for diminutive colorectal polyps to reduce the costs of unnecessary polyp resection and pathology evaluation. However, the performance of optical biopsy has been suboptimal in community practice. With recent improvements in machine-learning techniques, artificial intelligence–assisted computer-aided detection and diagnosis have been increasingly utilized by endoscopists. The application of computer-aided design on real-time colonoscopy has been shown to increase the adenoma detection rate while decreasing the withdrawal time and improve endoscopists’ optical biopsy accuracy, while reducing the time to make the diagnosis. These are promising steps toward standardization and improvement of colonoscopy quality, and implementation of “resect-and-discard” and “diagnose-and-leave” strategies. Yet, issues such as real-world applications and regulatory approval need to be addressed before artificial intelligence models can be successfully implemented in clinical practice. In this review, we summarize the recent literature on the application of artificial intelligence for detection and characterization of colorectal polyps and review the limitation of existing artificial intelligence technologies and future directions for this field.
The complete mitochondrial genome of Traulia minuta Huang & Xia, 1985 (Orthoptera: Catantopinae)

Abstract In the present study, we obtained and annotated the complete mitochondrial genome (mitogenome) of Traulia minuta. The length of the whole mitogenome was 15,636 bp and the AT content of the complete mitogenome was 74.5%. All protein-coding genes (PCGs) started with typical ATN codon and ended with complete TAA/TAG codons except Nad5, which ended with incomplete T codon. The phylogenetic tree indicated that T. minuta was clustered together with T. szetschuanensis.