Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Status of Experimental Animal Skin Flap Models: Ischemic Preconditioning and Molecular Factors

Skin flaps are necessary in plastic and reconstructive surgery for the removal of skin cancer, wounds, and ulcers. A skin flap is a portion of skin with its own blood supply that is partially separated from its original position and moved from one place to another. The use of skin flaps is often accompanied by cell necrosis or apoptosis due to ischemia–reperfusion (I/R) injury. Proinflammatory cytokines, such as nuclear factor kappa B (NF-κB), inhibitor of kappa B (IκB), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and oxygen free radicals are known causative agents of cell necrosis and apoptosis. To prevent I/R injury, many investigators have suggested the inhibition of proinflammatory cytokines, stem-cell therapies, and drug-based therapies. Ischemic preconditioning (IPC) is a strategy used to prevent I/R injury. IPC is an experimental technique that uses short-term repetition of occlusion and reperfusion to adapt the area to the loss of blood supply. IPC can prevent I/R injury by inhibiting proinflammatory cytokine activity. Various stem cell applications have been studied to facilitate flap survival and promote angiogenesis and vascularization in animal models. The possibility of constructing tissue engineered flaps has also been investigated. Although numerous animal studies have been published, clinical data with regard to IPC in flap reconstruction have never been reported. In this study, we present various experimental skin flap methods, IPC methods, and methods utilizing molecular factors associated with IPC.
Network Security in a Mixed Environment with Cdrom

From the Publisher: Computing in a mixed environment can be risky business. Dont take any unnecessary chances. Protect your network with the help of Network Security in a Mixed Environment. Industry expert Dan Blacharski combines technical insight and real-world experience to produce a solid how-to manual designed to reduce the dangers inherent in mixed environment computing. Network Security in a Mixed Environment covers all the basics in establishing a protected network, from determining security needs to acquiring the right hardware and software. Youll get detailed information on NetWare®, Windows NT®, and UNIX security features, safeguarding your network against various threats, hardware and software, security monitors, and more. The CD-ROM comes with Internet Explorer 4.0 and two cutting-edge programs designed to bolster your networks security -- CA-InocuLAN and WebStalker Pro.
Analysis of Artillery Autoloader Faults by Current Recognition Method

A large number of electric current data of the oil source supply battery were anal sized to get the fault reasons of the automatic reloading system of artillery.The instant current signal was picked with Hall current sensor while the reloading system was working,and the time domain figure was drawn with MATLAB tools.By the comparison of the current response signal with and without faults,the fault reason was judged preliminarily.Then by decomposing the signal of the autoloader's 6 actions to 12 layers with the method of wavelet,the fault reason was determined ultimately.The test result demonstrates that the method to recognize faults through the current signal can realize the rapid fault recognition of the automatic reloading system of artillery.
Blood biomarkers in early bacterial infection and sepsis diagnostics in feverish young children

Background and objectives: While most feverish children have self-limiting diseases, 5-10% develop a serious and potentially life-threatening bacterial infection (BI). Due to potential risk, prompt recognition of BI and sepsis in the pediatric emergency department (PED) remains a clinical priority. The aim of the study was to evaluate the role of certain cytokines and chemokines separately and in combination with routine blood tests in early BI and sepsis diagnostics at PED. Materials and methods: We prospectively studied children younger than 5 presenting to the PED with fever lasting for under 12 hours with high risk for serious illness. Clinical data, routine blood analysis, and inflammatory cytokine and chemokine panels were evaluated for their diagnostic abilities. Two separate analyses were carried out on the patients' data: one contrasting BI and viral infection (VI) groups, the other comparing septic and non-septic patients. Results: The sample comprised 70 patients (40% with BI). IL-2 was found to be the most specific biomarker to identify BI with specificity of 100%. The best discriminative ability was demonstrated by combining IL-2, IL-6, CRP, WBC, and neutrophil count: AUC 0.942 (95% Cl 0.859-0.984). IL-10 exhibited a greater AUC (0.837. 95% CI: 0.730-0.915 p<0.05) than CRP (0.807. 95% CI: 0.695-0.895 p<0.05) when predicting sepsis and showed high specificity (98%) and moderate sensitivity (75%). Conclusions: IL-6 and IL-2 could increase the diagnostic ability of routine blood tests for predicting BI, as IL-10 raises specificity for recognizing sepsis in the early hours of disease onset.
Leadership Traits’ Impact on Employees’ Performance in the Banking Sector (A Field Study on Bank Misr)

This study is investigating the effect of different leadership styles and traits (autocratic, democratic, and participative style) on employees’ performance within the public sector in Egypt. They are aiming to analyze the effect of diverse leadership styles on employees’ performance and productivity in ‘Bank Misr’ as it is the primary public bank in Egypt which has more than 500 branches all-over the country; employing 12,500 people who serve more than seven million clients in Egypt. Researchers used primary and secondary research tools to be able to come up with adequate results, conclusions and recommendations which might help in revealing and explaining facts about this important issue especially in the public sector. To validate the research objectives, different scholarly views are presented of the effect of independent variables on dependent variables. Finally, the researchers came up with a main finding which is that the participative understanding leader is the main contributor in boosting employees’ performance and productivity, although ironically the dictator and autocratic leader is useful if the organization is going through a severe crises and highly turbulent circumstances.
Deep Learning Approach for Spoken Digit Recognition in Gujarati Language

— Speech Recognition is an emerging field in the area of Natural Language Processing which provides ease for human machine interaction with speech. Speech recognition for digits is useful for numbers oriented communication such as mobile number, scores, account number, registration code, social security code etc. This research paper seeks to achieve recognition of ten Gujarati digits from zero to nine ( ૦ to ૯ ) by using a deep learning approach. Dataset is generated with total 8 native speakers 4 male 4 female with the age group of 20 to 40. The dataset includes 2400 labeled audio clips of both genders. To implement a deep learning approach, Convolutional Neural Network (CNN) with MFCC is used to analyze audio clips to generate spectrograms. For the proposed approach three different experiments were performed with different dataset sizes as 1200, 1800 and 2400. With this approach maximum 98.7% accuracy is achieved for spoken digits in Gujarati language with 98% Precision and 98% Recall. It is analyzed from various experiments that increase in dataset size improves the accuracy rate for spoken digit recognition. No of epochs in CNN also improves accuracy to some extent.
Fourier Ptychographic Microscopy via Alternating Direction Method of Multipliers

Fourier ptychographic microscopy (FPM) has risen as a promising computational imaging technique that breaks the trade-off between high resolution and large field of view (FOV). Its reconstruction is normally formulated as a blind phase retrieval problem, where both the object and probe have to be recovered from phaseless measured data. However, the stability and reconstruction quality may dramatically deteriorate in the presence of noise interference. Herein, we utilized the concept of alternating direction method of multipliers (ADMM) to solve this problem (termed ADMM-FPM) by breaking it into multiple subproblems, each of which may be easier to deal with. We compared its performance against existing algorithms in both simulated and practical FPM platform. It is found that ADMM-FPM method belongs to a global optimization algorithm with a high degree of parallelism and thus results in a more stable and robust phase recovery under noisy conditions. We anticipate that ADMM will rekindle interest in FPM as more modifications and innovations are implemented in the future.
Commentary: Experimental Mouse Models of Invasive Candidiasis Caused by Candida auris and Other Medically Important Candida Species

The study ““Experimental Mouse Models of Disseminated Candida auris Infection” provides the first insight into the critical role of C5 in the host antimicrobial defense to disseminated candidiasis caused by C. auris. This study also establishes an inbred A/J mouse model of systemic C. auris infection without drug-induced immunosuppression. C. auris has become the first fungal pathogen causing global public health threat due to its multidrug resistance (MDR) and persistence in hospital and nursing home settings. Currently, as compared to C. albicans, very limited animal models are available to study the progression of non-albicans Candida (NAC) species including C. auris. We have successfully established immunosuppressed C57BL/6, BALB/c and A/J murine models of disseminated candidiasis caused by five clinically significant Candida species: C. albicans, C. glabrata, C. tropicalis, C. parapsilosis and C. auris. Here we also report updated progress of some important mouse models for C. auris infection in the field. These valuable mouse models can be used for the assessment of antifungal drugs, evaluation of potential vaccines and monoclonal antibodies (mAbs) to protect before and after candidiasis, and comparison of pathogenicity of different Candida species.
Stochastic input-to-state stability for nonlinear impulsive switched systems with random impulses coupled by multiple jump maps

This article focuses on a class of nonlinear random impulsive and switched systems for stochastic input-to-state stability. The impulse is divided into two types: single jump map and multiple jump maps. When the impulse is chosen as single jump map, it means that the impulse between the two adjacent switching times is single as well as impulse and switching occur simultaneously, in which the impulsive moments are fixed. When the impulse is chosen as multiple jump maps, in this model, the impulse is not only limited by multiple maps, but also the impulse instants are assumed to be random. Therefore, this model is an extension of the traditional impulsive and switched system. In view of admissible edge-dependent average dwell time switching signal and the impulse dynamic satisfying Poisson’s process, sufficient conditions for the stochastic input-to-state stability are introduced into nonlinear impulsive switched system with random impulses. Three significant distinctions from the existing results rest with that (1) a new multiple Lyapunov functions are first created; the novelty contains discontinuity at the discrete points including switching moments and the impulse jump instants of Lyapunov-like functional; (2) the coefficient of derivative of a Lyapunov-like functions is permitted to be either positive or negative, which is less conservative; (3) the adopted admissible edge-dependent average dwell time switching scheme delves into less conservative stochastic input-to-state stability condition than mode-dependent average dwell time switching, nonlinear impulsive switched system with various jump maps. Numerical examples are simulated to manifest the validity of the main results.
Structural Concrete Systems

Scott W. McConnell, P.E. * 10.1 Overview 10-2 Introduction • Durability • Constructability • Appearance 10.2 Building Loads 10-3 Introduction • Gravity Live Loads • Lateral Live Loads 10.3 Composite Steel–Concrete Construction 10-7 Introduction • Advantages and Disadvantages • Other Considerations • Composite Action • Unshored vs. Shored Construction • Composite Columns 10.4 Foundations 10-10 Shallow Foundations • Deep Foundations 10.5 Structural Frames 10-14 Rigid Frames • Braced and Unbraced Frames • Column Proportioning • Beam Proportioning • Beam–Column Joints • Construction Considerations 10.6 Concrete Slab and Plate Systems 10-17 One-Way Beam–Slab Systems • Flat Plates and Flat Slabs 10.7 Liquid-Containing Structures 10-23 Introduction • Circular Tanks • Rectangular Tanks 10.8 Mass Concrete 10-26 Introduction • Materials for Mass Concrete • Concrete Mixture Design • Quality Control 10.9 On-Site Precasting and Tilt-Up Construction 10-28 10.10 Lift-Slab Construction 10-30 Introduction • Foundations • Columns • Supported Slabs • Lifting Collars • Lifting Jacks • Critical Component Design • Applications 10.11 Slip-Form Construction 10-33 Introduction • Materials and Methods • Advantages and Disadvantages • Economy 10.12 Prestressed Concrete 10-37 Introduction • Pretensioned (Precast) Concrete • Post-Tensioned Concrete Acknowledgments 10-40 References 10-40
A Competent, Humble Cost Catalyst from Biowaste: High Performance and Combustion Characteristics of Alternative Diesel Fuel

This current work displays experimental results obtained from assessing the methyl esters from the local waste cooking oil as an alternative fuel for diesel engines using a heterogeneous catalyst based on agricultural waste. The performance of the diesel engines and their exhaust emissions have been experimentally investigated using the produced biodiesel from waste cooking oil as a blend with fossil fuel (B10, B15, and B20) compared to the diesel. The reusability of the catalyst confirmed a high conversion efficiency after 8 cycles of the production. The highest conversion efficiency of the converting waste cooking oil extended to 90.38% with 92.5% maximum mass yield and methyl ester content of 97.7% wt. at the optimized conditions. According to the results, the effective blend for thermal efficiency and specific fuel usage is B15. Also, all emission concentrations decrease with increasing the engine load, especially for B15 fuels compared to diesel oil.
Predicting the distribution of Australian frogs and their overlap with Batrachochytrium dendrobatidis under climate change

Amphibians, with over 40% of assessed species listed as threatened, are disproportionately at risk in the global extinction crisis. Among the many factors implicated in the ongoing loss of amphibian biodiversity are climate change and the disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd). These threats are of particular concern in Australia, where Bd has been implicated in the declines of at least 43 frog species, and climate change is emerging as an additional threat. We explore how climate change is likely to affect the distributions of Australian frog species and Bd to the year 2100, and how the spatial and climatic niche overlap between chytridiomycosis‐declined frogs and Bd could shift.
Quantum Magnetic Resonance Analyzer (QMRA) As A Method For Assessment of Copper and Zinc Serum Levels in Autistic Children

Introduction: Autism is a long- term developmental disorder demonstrating an association with low serum levels of zinc and high copper. Aim: To determine Zn and Cu levels in ASD children using a new technology Quantum Magnetic Resonance Analysis (QMRA) method compared to a reference method to determine the sensitivity and specificity of the new method. Method: This study is a comparative cross- sectional study. It was carried out in The Children with Special Needs Center, Faculty of Postgraduate Childhood Studies; ASU and a Private Clinic from Jan 2019 to Sep 2021. The study groups included children with ASD (n= 30; M= 19; F= 11; age range= 3- 15) and an equal control group of typically developing children matched in sex and age. Zn and Cu were measured by a QMRA- 998 8th Generation device and the reference direct colorimetric method. Statistical Analysis: Results were analyzed using descriptive statistics, Pearson’s correlation, Chi- square, analysis of variance (ANOVA) and linear regression and a sensitivity and specificity cross- tabulation test to evaluate the QMRA in measuring Zn and Cu levels. Results: Both methods showed lower means for Zn levels in the ASD group than in the control group with a significant correlation on measuring Zn but not Cu. By reference method, but not with QMRA, serum Cu was higher in ASD than in control group. Sensitivity of QMRA was 84% when measuring Zn levels but only 60% for Cu and specificity was 87% for Zn but only 60% for Cu. Conclusion: Non- invasive measurement devices such as QMRA can be used as a screening or adjunct tool for measurement of Zn levels but not Cu. It is recommended to test blood levels of Zn and Cu in all autistic children and give them a Zn supplement if needed.
Implications of a Carbon Tax Mechanism in Remanufacturing Outsourcing on Carbon Neutrality

Many governments have imposed methods such as a carbon tax that aim to even out the negative effects of carbon emissions. The taxes levied on different agents lead to different make–buy decisions for production structures and different environmental outcomes. Some original equipment manufacturers (OEMs) outsource remanufacturing to independent remanufacturers (IRs). Thus, a question arises: What are the implications of carbon taxes levied on different agents on remanufacturing outsourcing decisions? To answer this question, we developed two models: (1) acting as common brand owners, OEMs can be taxed for both new and remanufactured products, or (2) acting as different emitters for production and remanufacturing, OEMs are taxed for new products; however, all carbon taxes related to remanufacturing are levied on IRs. Our analysis reveals that, regarding economic performance, firms should undertake a carbon emission tax on their own initiative because this allows the taxpayer to choose more units for its preferred products and leaves its rivals at a huge disadvantage. Moreover, regarding environmental sustainability, carbon emission taxes indeed lead to mitigating the effects of carbon emissions per unit; however, environmental agencies should also pay attention to reducing the total carbon emissions by limiting the volume effects.
Using career learning theory to inform the design and evaluation of ICT based CEIG services

Careers professionals are increasingly making decisions about whether and how to use the volume of new technologies available in the services they offer. This article is derived from a project which asks how theories about how people learn about careers, can be used to provide a theoretical underpinning to the design and evaluation of ICT based careers interventions. A critical comparison of career learning theories is used to propose a framework for careers professionals designing ICT-based careers interventions. With such a range of ICT-based services already on offer, an approach to evaluating the effectiveness of these interventions using learning outcomes is also proposed.
Development, Implementation and Acceptance of an AI-based Tutoring System: A Research-Led Methodology

: This Design-Based Research (DBR) project aims to develop an intelligent tutoring system (ITS) for higher education. The system will collect teaching and learning materials in audio and video formats (e.g., podcasts, lecture recordings, screencasts, and explainer videos), and store them on a learning experience platform (LXP). Then, the ITS will process them with the help of speech recognition to gain data which, in turn, will be used to power further applications: Using artificial intelligence (AI), the platform will allow users to search the materials, automatically compiling them according to criteria like lesson subject, language, medium, or required prior knowledge. By the end of the last DBR cycle, the ITS will also provide a more active form of support: It will automatically generate exercises based on predefined patterns and teaching materials, thus allowing learners to check up on their learning progress autonomously. In order to closely match the ITS’s features to the needs and learning habits of students in higher education, the development of this AI-based tutoring system is accompanied by an interdisciplinary team which will continuously re-evaluate and adapt the concept over the course of several DBR cycles. Our goal is to derive implications for the system’s technical development by collecting and evaluating educational research data (mixed methods design; primary and secondary research methods).
β-Cyclodextrin as the Key Issue in Production of Acceptable Low-Cholesterol Dairy Products

The application of cyclodextrins in food technology is extensive due to their unique ability to form complexes with many bioactive substances. Consumption of dairy products is associated with an increased risk of cardiovascular diseases (CVD) due to its high content of saturated fatty acids and cholesterol, so the production of low-cholesterol content products would be one of the critical steps in CVD prevention with regards to lowered total daily cholesterol intake. To maintain consumer acceptance, organoleptic profiles of such products should be, in the optimal case, the same with comparison to original ones. So, this study deals with the development of set low cholesterol foods (milk, cream, butter, soft cheese, cottage cheese) by β-cyclodextrin treatment and the characterization of their organoleptic profiles such as color and textural characteristics. During the experiments, high effectivity of cholesterol removal was reached as follows: milk–97.3%, cream–95.6%, butter–95.6%, cottage cheese–97.9%, soft cheese–97.7%, while color differences varied from 0.25 to 1.13 and textural characteristics were not influenced by cholesterol removal as well. So, it can be concluded that the proposed procedure is enabled to be substantial for the production of a new assortment of low-cholesterol dairy products with considerable health benefits toward the incidence of CVD.