Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering Latent Representations of Relations for Interacting Systems

Systems whose entities interact with each other are common. In recent years, there has been increasing interest in discovering the relationships between entities in interacting systems using graph neural networks. However, existing approaches are difficult to apply if the number of relations is unknown or if the relations are complex. We propose the DiScovering Latent Relation (DSLR) model, which is flexibly applicable even if the number of relations is unknown or many types of relations exist. The flexibility of our DSLR model comes from an encoder that represents the relation between two entities in a latent space and a decoder that can handle all types of relations. Experiments conducted on graph data with various relationships between entities show that the proposed method is suitable for analyzing dynamic graphs with an unknown number of complex relations.
Vein-first Lobectomy for Lung Cancer Assessed According to the Status of Clustered Circulating Tumour Cells.

Background/Aim Vein-first lobectomy (VFL) in lung cancer might reduce shedding of circulating tumour cells (CTCs). This study assessed the clinical significance of VFL. Patients and Methods Lung cancer patients undergoing lobectomy and CTC testing were evaluated. The primary evaluation item was postoperative clustered CTC detection, and the secondary outcome measures were the 2-year overall survival and recurrence-free survival rates according to the status of VFL and postoperative clustered CTC. Results Eighty-six patients with similar backgrounds, except for lobe resection and pulmonary vein dissection time, showed postoperative clustered CTC identification rates of 43.8% and 37.9% in the VFL group (n=57) and no-VFL group (n=29), respectively. However, prognosis was not significantly different, although the presence of clustered CTC after surgery was a predictor of recurrence. Conclusion The status of postoperative clustered CTC was similar regardless of VFL or not, although the detection of clustered CTC was a predictor of recurrence.
Effects of Agricultural Use on Endangered Plant Taxa in Spain

Agriculture is one of the most widespread human activities and has the greatest impact on terrestrial ecosystems, as it transforms natural ecosystems into artificial landscapes using, in many cases, large amounts of pesticides as well as overexploiting natural resources. Therefore, for effective biodiversity conservation, it is necessary to include agricultural systems in conservation programs. In this work, the 50 plant taxa described for Spain as threatened by agricultural use were selected. These were divided according to the type of threat into those affected by crop extension, intensification, or abandonment. In addition, information was obtained concerning their conservation status, level of protection and functional traits (life form, pollination, and dispersal). Finally, the evolution of land use, in the areas near the populations of the selected species, was identified. The selected taxa belong to 21 families and present different life forms and modes of dispersal or pollination. Forty-six percent are endangered (EN) and most are included in legal protection lists. Nearly three-quarters are threatened by crop expansion and land use dynamics, reflecting an expansion of cultivated areas, which adds further pressure to these species. In addition to agricultural expansion, taxa are also at risk, due to important rates of agricultural land abandonment, and mention agricultural intensification. Nevertheless, conservation measures do exist to promote biodiversity in agricultural landscapes that may help to reverse the negative effect of land use dynamics on selected species, but few are specific to threatened flora. Therefore, if threatened plants are to be conserved in agricultural areas, it is necessary to promote a profound transformation of our socioecological systems. One of these transformative changes could come from the human-nature reconnection.
CryoEM of endogenous mammalian V-ATPase interacting with the TLDc protein mEAK-7

The structure of mammalian V-ATPase with mEAK-7 shows how a TLDc domain-containing protein can bind the proton pump to form an activity-sensitive interaction. V-ATPases are rotary proton pumps that serve as signaling hubs with numerous protein binding partners. CryoEM with exhaustive focused classification allowed detection of endogenous proteins associated with porcine kidney V-ATPase. An extra C subunit was found in ∼3% of complexes, whereas ∼1.6% of complexes bound mEAK-7, a protein with proposed roles in dauer formation in nematodes and mTOR signaling in mammals. High-resolution cryoEM of porcine kidney V-ATPase with recombinant mEAK-7 showed that mEAK-7’s TLDc domain interacts with V-ATPase’s stator, whereas its C-terminal α helix binds V-ATPase’s rotor. This crosslink would be expected to inhibit rotary catalysis. However, unlike the yeast TLDc protein Oxr1p, exogenous mEAK-7 does not inhibit V-ATPase and mEAK-7 overexpression in cells does not alter lysosomal or phagosomal pH. Instead, cryoEM suggests that the mEAK-7:V-ATPase interaction is disrupted by ATP-induced rotation of the rotor. Comparison of Oxr1p and mEAK-7 binding explains this difference. These results show that V-ATPase binding by TLDc domain proteins can lead to effects ranging from strong inhibition to formation of labile interactions that are sensitive to the enzyme’s activity.
Prediction of rubber vulcanization using an artificial neural network

Determination of rubber rheological properties is indispensable in order to conduct efficient vulcanization process in rubber industry. The main goal of this study was development of an advanced artificial neural network (ANN) for quick and accurate vulcanization data prediction of commercially available rubber gum for tire production. The ANN was developed by using the platform for large-scale machine learning TensorFlow with the Sequential Keras-Dense layer model, in a Python framework. The ANN was trained and validated on previously determined experimental data of torque on time at five different temperatures, in the range from 140 to 180 oC, with a step of 10 oC. The activation functions, ReLU, Sigmoid and Softplus, were used to minimize error, where the ANN model with Softplus showed the most accurate predictions. Numbers of neurons and layers were varied, where the ANN with two layers and 20 neurons in each layer showed the most valid results. The proposed ANN was trained at temperatures of 140, 160 and 180 oC and used to predict the torque dependence on time for two test temperatures (150 and 170 oC). The obtained solutions were confirmed as accurate predictions, showing the mean absolute percentage error (MAPE) and mean squared error (MSE) values were less than 1.99 % and 0.032 dN2 m2, respectively.
Development of Inactivated FAKHRAVAC® Vaccine against SARS-CoV-2 Virus: Preclinical Study in Animal Models

The recent viral infection disease pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global public health crisis. Iran, as one of the countries that reported over five million infected cases by September 2021, has been concerned with the urgent development of effective vaccines against SARS-CoV-2. In this paper, we report the results of a study on potency and safety of an inactivated SARS-CoV-2 vaccine candidate (FAKHRAVAC) in a preclinical study so as to confirm its potential for further clinical evaluation. Here, we developed a pilot-scale production of FAKHRAVAC, a purified inactivated SARS-CoV-2 virus vaccine candidate that induces neutralizing antibodies in Balb/c mice, guinea pigs, rabbits, and non-human primates (Rhesus macaques—RM). After obtaining ethical code of IR.IUMS. REC.1399. 566, immunizations of animals were conducted by using either of three different vaccine dilutions; High (H): 10 μg/dose, Medium (M): 5 μg/dose, and Low (L): 1 μg/dose, respectively. In the process of screening for viral seeds, viral strains that resulted in the most severe clinical manifestation in patients have been isolated for vaccine development. The viral seed produced the optimal immunity against SARS-CoV-2 virus, which suggests a possible broader neutralizing ability against SARS-CoV-2 strains. The seroconversion rate at the H-, M-, and L-dose groups of all tested animals reached 100% by 28 days after immunization. These data support the eligibility of FAKHRAVAC vaccine candidate for further evaluation in a clinical trial.
Foundations of Human Resource Development

In Foundations of Human Resource Development, the leading scholars in the field present the essential guidebook for the human resource development (HRD) profession. Drawing on an extensive, rigorous knowledge base, Swanson and Holton update their classic single volume compilation of the foundational materials of the profession. Their work is supplemented with contributions from Richard W. Herling, Sharon S. Naquin, Wendy E. A. Ruona, Richard J. Torraco, and Karen E. Watkins. Written to be useful for both experts and novices, this new book provides a much-needed, up-to-date overview of the state of the profession as well as the terminology and processes required for sound HRD practice and study. Foundations of Human Resource Development establishes the contribution of HRD to contemporary organizations
Intelligent Multiparameter Fiber-Optic Sensing for Ocean Observation

With the increasing needs for the protection of marine and fresh water environment, there is surging demand for effective technologies to monitor different environmental parameters. Among different new technologies, fiber-optic sensing technology has found its unique roles in the measurement of different environmental parameters with advantages such as immunity to electromagnetic interference, compact size, low cost, and the possibility of distributed measurement over a long distance. In this study, we demonstrate a novel approach to realize intelligent multiparameter fiber-optic sensing to achieve simultaneous measurement of temperature and other parameters for marine observation, including salinity, flow rate, and chemical sensing. The temperature sensitivities of the acrylate and polyimide-coated fiber sensors are 0.0102 and 0.0094 nm/°C, respectively. The salinity sensitivity of the fiber sensor on potassium chloride concentration is 0.0126 nm/M.
Research Progress of Microtransfer Printing Technology for Flexible Electronic Integrated Manufacturing

In recent years, with the rapid development of the flexible electronics industry, there is an urgent need for a large-area, multilayer, and high-production integrated manufacturing technology for scalable and flexible electronic products. To solve this technical demand, researchers have proposed and developed microtransfer printing technology, which picks up and prints inks in various material forms from the donor substrate to the target substrate, successfully realizing the integrated manufacturing of flexible electronic products. This review retrospects the representative research progress of microtransfer printing technology for the production of flexible electronic products and emphasizes the summary of seal materials, the basic principles of various transfer technology and fracture mechanics models, and the influence of different factors on the transfer effect. In the end, the unique functions, technical features, and related printing examples of each technology are concluded and compared, and the prospects of further research work on microtransfer printing technology is finally presented.
SOURCE BOOK FOR AUSTRALIAN ROADS

The book attempts to cover the entire range of road topics from a technical viewpoint, with a strong Australian bias and using a source book approach. This last aspect means that the book refers readers to other sources of information in many areas, rather than repeating the data given in these key references. To aid this task, the title and contents pages of the key references are included as exhibits at the end of each chapter. The book includes chapters on definitions and terms, history of roads, organisation of roads, road needs, road location, residential streets, materials, moisture effects, stabilisation, pavement design, surfacings, drainage, pavement performance, bridges, driver behaviour, traffic flow and capacity, speeds, road geometry, intersections, signs, pavement markings, traffic signals, lighting, construction, maintenance, vehicles, safety, road user costs and charges, transport, environment, economics, transport planning, acronyms, symbols and information sources. It also has a glossary of terms and is well referenced and indexed (a). The ISBN of the microfiche is 0 86910 046 7. (TRRL)
The effect of gender agreement mismatches on intersentential anaphoric pronouns

This article focuses on the effect of gender agreement mismatches between personal pronouns and their antecedents across sentences. In two acceptability experiments, we test whether acceptability of gender agreement violations on animated nouns may be modulated by grammatical and contextual features of the antecedents of personal pronouns. In the first experiment, we manipulated the “specificity” feature of the antecedent in order to make the antecedent refer either to the class of individuals or to a specific referent. In the second experiment, we used stereotypically male or female proper names to test whether grammatical gender mismatches between personal pronouns and bigender nouns could be attenuated. Although the first experiment showed an effect explainable purely by grammatical factors, against many theories of “semantic” agreement, the results of the second experiment suggest that both the grammatical and the contextual features of the antecedent are computed when speakers evaluate agreement relations between personal pronouns and their antecedents.
Green Scheduling of Control Systems

Electricity usage under peak load conditions can cause issues such as reduced power quality and power outages. For this reason, commercial electricity customers are often subject to demand-based pricing, which charges very high prices for peak electricity demand. Consequently, reducing peaks in electricity demand is desirable for both economic and reliability reasons. In this thesis, we investigate the peak demand reduction problem from the perspective of safe scheduling of control systems under resource constraint. To this end, we propose Green Scheduling as an approach to schedule multiple interacting control systems within a constrained peak demand envelope while ensuring that safety and operational conditions are facilitated. The peak demand envelope is formulated as a constraint on the number of binary control inputs that can be activated simultaneously. Using two different approaches, we establish a range of sufficient and necessary schedulability conditions for various classes of affine dynamical systems. The schedulability analysis methods are shown to be scalable for large-scale systems consisting of up to 1000 subsystems. We then develop several scheduling algorithms for the Green Scheduling problem. First, we develop a periodic scheduling synthesis method, which is simple and scalable in computation but does not take into account the influence of disturbances. We then improve the method to be robust to small disturbances while preserving the simplicity and scalability of periodic scheduling. However the improved algorithm usually result in fast switching of the control inputs. Therefore, event-triggered and self-triggered techniques are used to alleviate this issue. Next, using a feedback control approach based on attracting sets and robust control Lyapunov functions, we develop event-triggered and self-triggered scheduling algorithms that can handle large disturbances affecting the system. These algorithms can also exploit prediction of the disturbances to improve their performance. Finally, a scheduling method for discrete-time systems is developed based on backward reachability analysis. The effectiveness of the proposed approach is demonstrated by an application to scheduling of radiant heating and cooling systems in buildings. Green Scheduling is able to significantly reduce the peak electricity demand and the total electricity consumption of the radiant systems, while maintaining thermal comfort for occupants. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Electrical & Systems Engineering First Advisor George J. Pappas Second Advisor Rahul Mangharam This dissertation is available at ScholarlyCommons: http://repository.upenn. edu/edissertations/678
Communicating in business : a short course for business English students : cultural diversity and socializing, using the telephone, presentations, meetings and negotiations

MODULE 1 CULTURAL DIVERSITY AND SOCIALISING Unit 1 Building a relationship Unit 2 Culture and entertainment MODULE 2 TELEPHONING Unit 3 Could I leave a message? Unit 4 Good to hear from you again! Unit 5 Unfortunately there's a problem. MODULE 3 PRESENTATIONS Unit 6 Planning and getting started Unit 7 Image, impact and making an impression Unit 8 The middle of the presentation Unit 9 The end if near . this is the end MODULE 10 Making meetings effective Unit 11 Sorry to interrupt, but . Unit 12 What do you mean by . MODULE 5 NEGOTIATIONS Unit 13 Know what you want Unit 14 Getting what you can Unit 15 Not getting what you don't want.
Suburban Residential Traffic Calming

In the Washington, D.C./Baltimore, Maryland, suburban areas, postwar residential development frequently featured long curving residential streets with numerous cul-de-sacs. Despite the 25 mph speed limits on the main residential corridors, a more common speed was 38 to 40 mph. This residential speeding led to public outcry, resulting in the development of traffic calming measures. Traffic engineers in the counties surrounding Baltimore and Washington formed the Maryland Traffic Engineers Council to share information on ways to reduce speed in suburban residential communities. This article presents the results of this information sharing, detailing vertical and horizontal alignment measures, such as speed humps (as opposed to bumps), traffic circles, and roundabouts. Other roadway restrictions are described as well.
A Deep Transfer Learning Method for Estimating Fractional Vegetation Cover of Sentinel-2 Multispectral Images

Fractional vegetation cover (FVC) is an important indicator for exploring hydrosphere, pedosphere, atmosphere, biosphere, and their interactions. Deep learning (DL) is a potential tool to handle large-scale data and approximate the complex nonlinear relationship between variables. It is, therefore, suitable for FVC estimation. However, few DL-based algorithms have been developed to estimate FVC as it is difficult to obtain a large amount of training data. This letter presents a novel method by means of deep transfer learning to address this issue. The proposed technique consists of two steps. In the first step, a large amount of simulated training samples were generated by a physical model (PROSPECT + SAIL radiative transfer model, PROSAIL). In the second step, a long short-term memory (LSTM) network was pretrained with the simulated training dataset obtained in the first step. Then limited real samples from satellite images were used to fine-tune the pretrained network. Experiments were conducted for the Sentinel-2 multispectral satellite images of two areas and the results were compared with those obtained by the traditional the Normalized Difference Vegetation Index (NDVI)-based method and two machine learning approaches. The results demonstrate that the performance of our method outperforms other advanced FVC estimation methods.
Clearance criteria for civil aircraft

In this report we describe the clearance criteria which are intended to serve for robustness analysis purposes within the COFCLUO project. Several criteria related to the assessment of stability, handling quality, turbulence caused loads, non-exceedance of protection limits and actuator damages due to fatigue are de¯ned. For each criterion, we describe the necessary evaluation model, the employed indicators, and the criterion de¯nition and evaluation procedure. A selected set of criteria will form the basis for the implementation of a criteria library to serve for the optimization based clearance.
The Effects of Women’s Self-Help Group Participation on Domestic Violence in Andhra Pradesh, India

This article explores the impact of Self-Help Group (SHG) participation on the frequency of domestic violence in rural India. The study hypothesizes that SHG participation can raise tensions between married men and women because husbands may perceive some aspects of women’s empowerment as a challenge to patriarchal cultural norms. Using household panel data collected in rural Andhra Pradesh in 2004, 2006, and 2007, this article employs double difference methodology with an instrumental variables approach for impact evaluation. The estimation results show that, while SHG participation reduced domestic violence in the short-term, medium-term participation increased the frequency of domestic violence, particularly after women’s credit access through SHG participation had improved. This article furthermore reveals that the impact of SHG participation on domestic violence was more pronounced among couples who married with dowry. Spouses who practiced dowry appear to be more susceptible to financial inflow through the wife. HIGHLIGHTS Self-Help Group (SHG) participation impacts the frequency of domestic violence in conflicting ways. Women’s SHG participation initially reduces tensions with their husbands. In the medium term, women’s access to credit creates conflicts with their husbands. SHG participation alone is not enough to overcome patriarchal practices and structures. Effective gender-advocacy programs should include training to change both women’s and men’s attitudes.
Mobile services for truck drivers

The thesis has been done at Volvo Technology Corp in Gothenburg and the goal was to discover interesting truck driver services that can be used in the truck driver profession. The services should be executed on a Personal Digital Assistant (PDA), related to the work done by the drivers when they are outside of the truck. A lot of theories have been used as a base for our study. All work has been carried out in correspondence with methods for the following areas; literature studies, field studies, analysis of problem areas, and design, implementation, and test of a software prototype on a PDA. When all literature studies, own conducted field studies, and some part of the analysis phase were completed, we had come up with a large number of ideas. All ideas were further analysed and of them were five services selected. These services are named: Load Indicator, Consignment Note, Drivers Manual, Friend Finder, Keyless entry and Alarm. Load Indicator is a service that helps the driver to keep track that the maximum cargo weight for the truck is not exceeded. Our Consignment Note, involves all handling of the notes in a digital form, i.e. no paper is needed. Drivers Manual is the digital version of the manual shown on the PDA. Friend Finder is a service that keeps track of a driver’s colleagues and friends. Keyless entry includes services that handle automatic locking/unlocking of the truck door and automatic handling of the trucks spot and load lights. Finally, if the burglary attempt is made on the truck and an alarm is raised this alarm will also be shown on the PDA in the Alarm service. In the design of the above services, the end-users were in focus. The end-users are truck drivers usually not that familiar with computers (especially PDAs). Their work is also conducted, to a large extent, outside of the truck. Thus, our design is characterized with “usability” for that particular end-user group, with for example the use of large designed “Buttons” and the use of keystrokes on the PDA