Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of the Optimum Preparation of Peach Gum Polysaccharides and the In Vivo and In Vitro Therapeutic Effects on Acute Pyelonephritis

Background Acute pyelonephritis (APN), known as stranguria in traditional Chinese medicine, is commonly treated with antibiotics. However, the rise in antibiotic resistance and the high rates of recurrence of APN make its treatment complicated, thus the development of alternative therapies is critical. Peach gum has long been recognized by traditional Chinese medicine as a food with medicinal value of relieving stranguria, but whether and how its primary constituent peach gum polysaccharides (PGPs) contribute to the diuretic function is still not clear. Purpose The aim of this study was to investigate the optimum extraction process of PGPs and to evaluate its therapeutic effect on APN rats and to discover the underlying mechanism. Methods In this study, surface design optimization was adopted to optimize the preparation of PGPs and HPLC and FT-IR spectra were used to evaluate the quality of PGPs; APN model rat was established by the Escherichia coli urinary tract infection method; the therapeutic effect and mechanism of PGPs on APN were determined by the visceral index, biochemical indicators, pathological section of the APN rat, and diuretic activity on mice and antibacterial activity in vitro. Results Compared with an untreated APN group, the results showed that treatment with PGPs increased the APN-induced attenuation of secretory immunoglobulin A (sIgA) and creatinine clearance and decreased the APN-induced enhancement of the number of white blood cell (WBC), neutrophil counts (NC), bacteria load of the kidneys, kidney index, serum creatinine, urine volume, blood urea nitrogen (BUN), and interleukin-2 (IL-2) levels. The mechanism underlying these effects was further elucidated through in vitro experiments of the antibacterial and antiadhesion effects of PGPs. Conclusion Due to the good therapeutic effects and advantages of PGPs, it could be considered as an alternative medicine to treat APN.
Academic Values & Student Identity in the Marketized Higher Education Sector

The competition among higher education institutions is rising on a national and international level. As knowledge represents the main driving force for economic growth in today’s globalized world, universities have not only taken up internationalization efforts, but they are also actively marketing themselves around the globe. While some scholars see the benefits of the marketing approach for the higher education sector, others perceive the adoption of business practices as highly problematic: a growing fear of dwindling ethical academic standards along with a decrease of true student-knowledge engagement can be noted. Given this context, this thesis aims to explore how German master students at Aalborg University Denmark (AAU) perceive their personal and academic development within a transforming higher education landscape. Further, and from the perspective of AAU’s i ter atio al recruit e t tea , it tries to find out how AAU could market itself successfully to potential German students. This is of interest since higher education marketing is fairly new in Germany and it is not clear how German students respond to a university conducting promotional activities. By shedding light on the students’ study experiences in Germany in comparison to Denmark, insight for addressing the sketched issues is provided. The classical way of teaching in Germany opposed to the Problem Based Learning (PBL) method (based on group and project work) practiced at AAU also constitutes an integral part of this
Dynamic Scene Creation from Text

iv DEDICATION . v ACKNOWLEDGEMENTS . vi LIST OF TABLES . ix LIST OF FIGURES . x LIST OF ACRONYMS . xi CHAPTER 1: INTRODUCTION . 1 1.1 Applications . 2 1.1.1 Entertainment. 2 1.1.2 Scientific . 4 1.1.3 Other Industries . 5 1.2 Motivation . 7 1.3 Problem Statement . 8 1.4 Thesis Contribution . 9 1.5 Thesis Organization. 9 CHAPTER 2: 3D ANIMATION PIPELINE . 10 2.1 Preproduction . 11 2.2 Production . 15 2.3 Postproduction . 19 CHAPTER 3: LITERATURE REVIEW . 21 3.1 Text to Scene . 21 3.2 Text to animation . 27 CHAPTER 4: AUTODESK MAYA . 33
WORKPLACE CHARACTERISTICS, JOB SATISFACTION AND ORGANIZATIONAL COMMITMENT OF EXTENSION PERSONNEL IN THE NEW VALLEY GOVERNORATE

This study aimed at: (1) knowing about the profile of workplace characteristics, job satisfaction and organizational commitment of extension personnel in the New Valley Governorate; (2) identifying and testing the mediating effect of job satisfaction between workplace characteristics and organizational commitment. Data were collected by using a questionnaire during the period from March to May 2013 from 103 personnel representing about 85.1 % of the total number of extension personnel in this Governorate (121 Personnel). Data were described by the arithmetic mean. The results revealed the moderate presence of the workplace characteristics inside the agricultural extension workplace of the New Valley Governorate. Low levels of job satisfaction and commitment were found among the respondents toward their organization. The mediation analysis confirmed that job satisfaction is significantly mediating the relationship between workplace characteristics and organizational commitment. This indicates that workplace characteristics predict job satisfaction, which in turn is an antecedent to organizational commitment.
DEVELOPING AN IPM PROGRAM FOR CONTROLLING POCKET GOPHERS AND VOLES IN ALFALFA

Pocket gophers (Thomomys spp.) and voles (also known as meadow mice; Microtus spp.) are often the most damaging vertebrate pests in alfalfa. The amount and form of damage they cause can be quite varied but includes a loss in vigor and/or mortality of plants, damage to subsurface drip lines, and loss of irrigation water down burrow systems. Many control options are available including the use of toxic baits, burrow fumigation, and trapping. An Integrated Pest Management (IPM) program that incorporates several of these approaches, and potentially other techniques, can have many positive attributes for controlling pocket gophers and voles, not the least of which is greater control than is typically observed by focusing on any single method. The best IPM plan for alfalfa growers will vary depending on numerous aspects including the time of year when control is needed or implemented; the cost of control measures; the presence of non-target, threatened, or endangered species; and existent laws and regulations for potential control methods. Nonetheless, an effective IPM program can be developed by adhering to the following four-step process: 1) identify the species that is causing the damage, 2) assess your control options, 3) develop and implement the management plan, and 4) monitor to determine the effectiveness of the management plan. Adhering to these four steps should allow alfalfa growers to effectively control pocket gophers and voles, while reducing control costs.
From Art to Industry : Development of Biomedical Simulators

The authors’ methodology of creating e-learning content for the students of physiology, pathophysiology and biomedicine at the Faculty of Medicine is presented here. The design process from a formalized description of physiological reality to interactive educational software is described. Various tools are used during the design – starting with the numerical simulation software Matlab/Simulink, through Macromedia Flash for interactive animations, Control Web or MS Visual Studio for user interface design to web publishing tools including the Macromedia Breeze learning management system. Also, various professions are involved – teachers, physicians, simulation/modeling experts, graphic designers and programmers. The aim is to provide students with software that helps them understand the complex dynamics of physiological systems. Index Terms — Computer aided learning, elearning, medicine, physiology, simulation models
OPTIMAL SERVOMOTOR SELECTION ALGORITHM FOR INDUSTRI AL ROBOTS AND MACHINE TOOLS NC AXIS

This paper presents a complete calculus algorithm f or selecting the optimal servomotors of the kinematic chains included in the numerically contro lled axes (NCA) of machine tools (NCMT) and industrial robots (IR). The algorithm can be applied for both type controlled axes, i.e. industrial robots, and machine tools, as well as either rotation axis or t ranslation axis, regardless of their mechanical str uc ure. The presented calculus algorithm includes six major steps: defining the working cycle motion diagram f or the operated mechanical system and complementary in put data; identifying the static and dynamic forces applied to the driven system during operation and t he specific mechanical structure on NCA (i.e. speci fic transfer ratio of each included mechanism); prelimi nary selection of the driving servomotor by checkin g the kinematic criterion; determining of the total r esistant equivalent load applied on the driven elem nt; secondary selection of the driving servomotor by ch ecking the static and dynamic criterion; and tertia ry selection of the driving servomotor by checking the performance parameters related to full kinematic chain driving (acceleration time, braking time, ser vomotor's thermal behavior). The motor finally chos en represents the optimum solution for driving the NCA in terms of satisfying all imposed criteria (kinem atic criterion, static criterion, dynamic criterion) and complying as well the necessary performance requir ments for NCA's electro-mechanic driving system. ¶
Perceptions of Desirable Employability Skills for Commerce Students

South Africa is currently experiencing serious challenges relating to youth and graduate unemployment. Some of the reasons cited for this problem are the inability of Higher Education to produce graduates that meet employer needs. As a result there is a great need for higher education institutions (HEIs) to develop approaches to address the issue of graduate employability skills. The main aim of this study is to investigate the perceptions of desirable graduate workplace skills for commerce graduates. A crosssectional research design was followed with data collected by means of surveys. A sample of 244 final year students, 94 postgraduates and 21 academics participated in this study. The results showed that the higher education institution contributed mostly to the graduate skills of independence, ability/willingness to learn, decision making, problem solving and achievement orientation. The most important graduate skills identified included professionalism, time management, ability/willingness to learn, communication and independence. Keywords— Employability, Graduates, Soft skills, Talent Management.
An extended transfer matrix model for the sound insulation of dual leaf structures with corrugated panels and structural connections

The transfer matrix method (TMM) was implemented both as a standalone approach and as a method of obtaining cavity infill layer effective properties in a periodic double plate model. These approaches were studied for their potential in predicting the sound insulation characteristics of corrugated dual leaf roofs, with applicability to multi-layered building elements more generally. Corrugated panels were modelled as equivalent orthotropic plates. Infill materials were modelled using both effective fluid representations and a Biot model. Available corrections were introduced to simulate diffuse laboratory conditions and enable comparisons to available laboratory sound transmission loss data. A number of diffuse TL measurements of dual leaf partitions and full roof systems were compared to the TMM. The inclusion of point-to-point connections reduces overestimation of such systems at high frequency, showing a strong influence of connector stiffness and panel damping factor on high frequency performance of systems, particularly with absorbent infill. The equivalent orthotropic plate model predicts a stronger effect of profile depth on low-mid frequency performance than in practice. The predicted TL is compared with laboratory measurements for several systems.
A Simulation Study of Sustainable Agri-Food Supply Chain

Agri-food supply chain (ASC) topic has attracted a lot of academics and practitioners in the last decade due to the globally increasing concern of public health and food safety and quality. Fresh produce has special characteristics, which includes perishability, uncertainty of supply and demand, and carbon dioxide equivalent emissions produced throughout the supply chain due to cooling, transportation, and disposal of fresh produce. These factors impose an additional complexity while managing this type of supply chains. This work concentrates on developing a simulation model of a two-echelon real life supply chain. The objective is to study the effect of changing order quantity under uncertain demand and lead time on a set of economic, social and environmental performance measures. Although, in a business environment economic dimension continues to be a top priority, simulation results showed that there is no contradiction between all three dimensions of sustainability. It minimized food wastage, offering higher quality fresh produce, lower emissions; while maintaining highest profit and an acceptable service level.
ASSESSMENT RISK OF FRACTURE IN THIN-WALLED FIBER REINFORCED AND REGULAR HIGH PERFORMANCE CONCRETES SANDWICH ELEMENTS

High Performance Concrete Sandwich Elements (HPCSE) are an interesting option for future low or plus energy building construction. Recent research and development work, however, indicate that such elements are prone to structural cracking due to the combined effect of shrinkage and high temperature load. Due to structural restraints, autogenous shrinkage may lead to high self-induced stresses. Therefore autogenous shrinkage plays important role in design of HPCSE. The present paper assesses risk of fracture due to autogenous shrinkage-induced stresses in three fiber reinforced and regular High Performance Concretes (HPC). The research work described in this paper contains a description of experimental setup that allows measurement of effective shrinkage in HPC, which develops on an elastic inhomogeneity embedded in HPC matrix undergoing shrinkage during hydration (autogenous shrinkage). The test setup is based on direct measurement of the hydrostatic pressure developed in a simple pressure sensor embedded in the same matrix and a subsequent analysis based on Eshelby's solution for an ellipsoidal inhomogeneity embedded in an infinite matrix. The paper also presents the analysis necessary to perform an interpretation of the experimental results and to determine effective shrinkage in the HPC matrix. Furthermore, the mechanical properties of all the mixes – static elastic modulus, compression strength, tensile strength as well as fracture energy were investigated in detail as function of time. Finally the paper describes the modeling work with HPCSE predicting structural cracking provoked by autogenous shrinkage. It was observed that risk of cracking due to autogenous shrinkage rapidly rises after 3 days in case of regular HPC and after 7 days in case of fiber reinforced HPC.
Algorithmic Implementation of Load Balancing –in Wireless LAN

Intra domain traffic engineering (TE) has become an indispensable tool for Internet Service Providers (ISPs) to optimize network performance and utilize network resources efficiently. Various explicit routing TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires Large Ternary Content Addressable Memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this project, we present an approach, called Generalized Destination-Based Multipath Routing (GDMR), to achieve the high performance as explicit routing. The main contribution of this project is to enhance an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR.
Sentence embedding with contrastive multi-views learning

In this work, we propose a self-supervised method to learn sentence representations with an injection of linguistic knowledge. Multiple linguistic frameworks propose diverse sentence structures from which semantic meaning might be expressed out of compositional words operations. We aim to take advantage of this linguist diversity and learn to represent sentences by contrasting these diverse views. Formally, multiple views of the same sentence are mapped to close representations. On the contrary, views from other sentences are mapped further. By contrasting different linguistic views, we aim at building embeddings which better capture semantic and are less sensitive to the sentence outward form.
Improved Modeling of Complex Systems Using Hybrid Physics/Machine Learning/Stochastic Models

Combining domain knowledge models with neural models has been challenging. End-to-end trained neural models often perform better (lower Mean Square Error) than domain knowledge models or domain/neural combinations, and the combination is inefficient to train. In this paper, we demonstrate that by composing domain models with machine learning models, by using extrapolative testing sets, and invoking decorrelation objective functions, we create models which can predict more complex systems. The models are interpretable, extrapolative, dataefficient, and capture predictable but complex non-stochastic behavior such as unmodeled degrees of freedom and systemic measurement noise. We apply this improved modeling paradigm to several simulated systems and an actual physical system in the context of system identification. Several ways of composing domain models with neural models are examined for time series, boosting, bagging, and auto-encoding on various systems of varying complexity and non-linearity. Although this work is preliminary, we show that the ability to combine models is a very promising direction for neural modeling.
Using application knowledge to reduce cold starts in FaaS services

In Function-as-a-Service platforms (FaaS), which have become very popular lately, code is deployed in the unit of single functions and the cloud provider handles resource management. There, a key problem is the so-called cold start problem: when a request comes in and no idle container can be found for the execution of the target function, then a new container needs to provisioned. In that case, the request incurs an extra latency - the cold start latency. Recent work has largely focused on reducing the duration of cold starts. In this paper, we present three approaches, complementary to related work, that reduce the number of cold starts while treating the FaaS service as a black box. In the approaches, implemented as part of a lightweight choreography middleware, we use knowledge on the composition of functions to trigger cold starts and, thus, the provisioning of new containers before the application process invokes the respective function. In experiments on AWS Lambda and OpenWhisk, we could show that our approaches remove an average of about 40% (in some cases up to 80%) of all cold starts while causing only a small cost overhead.
Liquid biopsy: expanding the frontier of circulating biomarker discovery and validation in breast cancer

Liquid biopsies represent an attractive, minimally-invasive alternative to surgical sampling or complex imaging of breast cancer and breast cancer metastasis. Here we present a summary of the major biomarker components often evaluated in liquid biopsy samples from patients with breast cancer, including circulating tumor cells, circulating cell-free tumor DNA, and cancer-associated plasma proteins. We discuss recent advancements in methods of detection and use of these biomarkers in breast cancer. Finally, we highlight some of our own recent contributions to breast cancer liquid biopsy, including the identification and characterization of circulating Cancer Associated Fibroblasts.
CMAR_A_196614 2471..2483

1Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming 650118, People’s Republic ofChina; 2Department of Radiology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou 510655, People’s Republic of China; 3Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, People’s Republic of China; 4School of Medicine, South China University of Technology, Guangzhou 510641, People’s Republic of China; 5Department of Pathology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming 650118, People’sRepublic of China; 6Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming 650118, People’sRepublic of China; 7Department of Medical Oncology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou 510655, People’s Republic of China
Leakage Detection with Kolmogorov-Smirnov Test

Leakage detection seeking the evidence of sensitive data dependencies in the side-channel traces instead of trying to recover the sensitive data directly under the enormous efforts with numerous leakage models and state-of-the-art distinguishers can provide a fast preliminary security assessment on the cryptographic devices for designers and evaluators. Therefore, it is a popular topic in recent side-channel research of which the Welch’s t-test-based Test Vector Leakage Assessment (TVLA) methodology is the most widely used one. However, the TVLA is not always the best option under all kinds of conditions (as we can see in the latter section of this paper). Kolmogorov-Smirnov test is a well-known nonparametric method for statistical analysis to determine whether the samples are from the same distribution by analyzing the cumulative distribution. It has been proposed into side-channel analysis as a successful distinguisher. This paper proposes—to our knowledge, for the first time—Kolmogorov-Smirnov test as a new method for leakage detection. Besides, we propose two implementations to speed up the KS leakage detection procedure. Experimental results on simulated leakage with various parameters and the practical traces verify that KS is an effective and robust leakage detection tool and the comprehensive comparison with TVLA shows that KS-based leakage detection can be a right-hand supplement to TVLA when performing the side-channel assessment.