Miracle-dz/UniFAR-FTUs huggingface dataset:
Age as a Predictor of Burnout in Russian Public Librarians

Objective – Increasing life expectancy leads to an increase in the mean age of the workforce. The aging workforce implies new challenges for management and human resources. Existing findings on relations between age and burnout are controversial and scarce. Also, the problem of burnout amongst library workers in Russia has received little attention from researchers. Methods – The studied sample consisted of 620 public librarians from 166 public libraries of different regions (the Moscow region, Yaroslavl, Chelyabinsk, Novosibirsk, Astrakhan, and Republic of Buryatia) of the Russian Federation, who completed a self-reported online survey. For measuring burnout, a new Burnout Assessment Tool was implemented. To examine the associations of interest, we used structural equation modeling with a group correction approach. In addition, library location, general self-efficacy, and length of employment at the current workplace were utilized as predictors. All statistical analysis was performed in R. Results – Findings confirmed the hypotheses partially and revealed negative links between exhaustion, mental distance, and cognitive control and age, while reduced emotional control did not relate to age. Urban librarians tended to demonstrate higher levels of mental distance and had more significant problems with emotional regulation than their rural counterparts. Also, the non-Moscow region librarians did not demonstrate correlations between age and reduced cognitive control. Moreover, they showed a positive link between age and reduced emotional control. Conclusion – The current paper confirmed some previous results on the negative relations between burnout symptoms and chronological age. The results suggest the existence of higher risks of burnout for younger library workers. Potential mechanisms underlying the resilience of older workers are discussed.
Seleksi Fitur Relieff Pada Klasifikasi Malware Android Menggunakan Support Vector Machine(SVM)

Seiring berkembangnya jaman perkembangan malware android terus mengalami peningkatan setiap tahunnya.Machine Learning adalah salah satu teknik yang bisa kita gunakan dalam melakukan analisa malware android dengan 2 model pendekatan statis dan dinamis.Penulis menggunakan Support Vector Machine(SVM) untuk proses klasifikasiannya dan menggunakan kernel RBF. Fitur yang digunakan dalam penelitian ini adalah Permission dan Broadcast Receiver. Untuk menambah hasil akurasinya digunakan metode Seleksi Fitur Relieff. Dan Seleksi Fitur pembandingnya adalah Chi-Square(CHI),Correlation-based Feature Selection(CFS), dan Gain Ratio(GR). Hasil dari Seleksi Fitur Relieff akan di evaluasi dengan Seleksi Fitur pembandingnya serta juga dengan hasil klasifikasi tanpa menggunakan Seleksi Fitur. Akurasi klasifikasi Seleksi Fitur Relieff menghasilkan 33.33333%, hasil akurasi Seleksi Fitur pembanding lainnya juga memberikan hasil sama dengan Seleksi Fitur Relieff. Sedangkan hasil klasifikasi tanpa Seleksi Fitur memberikan hasil yang cukup tinggi yaitu 95%. Hasil pengujian menunjukkan bahwa Seleksi Fitur tidak cocok digunakan dengan data yang sedikit karna memberikan hasil yang jauh lebih rendah dari tanpa menggunakan Seleksi Fitur.
Model predictive position tracking control for motion system with random communication delay

: This study focuses on position tracking control for the networked predictive motion control system with random communication delay. First, the output feedback controller is designed by networked predictive control law to actively compensate the time delay induced by the random channels of the motion control system. A closed-loop model is established for the networked predictive motion control system with random bounded communication delay, modelled by a Markov chain. Then
Development of Livelihood Skills through School-Based, Agripreneurship Projects
Integrating Youth-Adult Partnerships: The Experiences of Youth Partners in Uganda

quipping young people with livelihood skills is essential for positive youth development and empowerment as they transition into adulthood to become productive and engaged members of their communities. In Uganda, which may be the case in other nations of Sub-Saharan Africa, and elsewhere, even though many youth are becoming better educated and graduating from high schools and colleges, a majority of these graduates remain either unemployed or underemployed. Many have not acquired the necessary skills to transition from school to becoming employable and self-reliant. This phenomenon has been attributed to an outdated curriculum that does not meet the needs of contemporary times. Further, the mode of instruction in most of Uganda’s schools is teacher-centered and provides little room for student engagement and creativity to generate new knowledge, to have authentic learning experiences, or to reflect. Such challenges may be overcome through student-centered learning approaches involving School-Based, Agripreneurship Projects (SAPs) that integrate Youth-Adult Partnerships (YAPs), as were explored in this study. Evaluation of the students’ experiences through deductive and inductive thematic analysis indicated that they acquired knowledge in poultry science, business, agripreneurship, and life skills, including better communication, leadership, and conflict resolution practices. Longitudinal studies should be conducted to determine the longterm effectiveness and impact of SAPs facilitated by Y-APs on improving youth livelihoods, especially that prepare them with the life skills necessary to be productive citizens. Such research could involve cohort or panel investigations. Keywords: entrepreneurship; positive youth development (PYD); project-based learning (PjBL)
Adaptive Asymptotic Tracking Control of Uncertain Nonlinear Systems Based on Taylor Decoupling and Event-Trigger

This article studies the robust adaptive asymptotic tracking control problem for uncertain nonlinear systems with event-triggered inputs. Contrary to the existing results, a novel nonaffine nonlinear control input separated design scheme is developed based on the Taylor decoupling technique instead of the previous approximation ways. Correspondingly, the augmented dimension parameter updated laws and the unknown bound estimation of the compounded disturbance with a positive continuous integrable function are skillfully introduced. Also, by introducing a suitable decreasing function of tracking error variables, an improved adaptive event-triggered mechanism is constructed to achieve the asymptotic tracking and the communication load can be effectively alleviated. Moreover, it is shown that all the signals in the closed-loop system are uniformly bounded and the tracking errors converge to zero in a preset compact set. Finally, the validity of the proposed method is illustrated by simulation on an inverted pendulum model.
Estimation of Clearance Rate of Iodine-131 From Thyroid Cancer Patients Based on Individual Patient’s Characteristic.

Differentiated thyroid carcinomas (DTC) are the most frequent malignancies of the endocrine system in 2015 in Japan. The purpose of this study is to estimate clearance rate of Iodine-131 from thyroid cancer patients based on individual patient’s characteristics. Materials and methods: We conducted retrospective study including 87 cases with DTC who had received RAI from June 2016 till July 2018. Patients who had complete information on primary tumor size (PTS) as mentioned in their histopathology reports, TNM staging, serum TSH (uIU/ml), free-T3 (pg/mL), free-T4 (ng/dL), thyroglobulin level (Tg) (ng/ml) (one month before, on the day of the treatment, and one month after receiving RAI), anti-Tg antibodies (IU/mL), dose of Levothyroxine (before and after RAI), as well as renal function (creatinine, BUN, eGFR), exposure rate (µSv/h) and taken dose (mCi) were included in our study. Results: Univariate analysis showed significant associations of effective half-life with several factors (gender, body height, body weight, eGFR, size of tumor, dose of Levothyroxine, free-T3 one month after receiving RAI). Conclusion: Effective management of these factors could help the doctors to optimize the occupancy of isolated rooms with higher output, but also reduce the operational cost of the hospital and improving the comfort to patients.
Chiral Discrimination and Enantiomeric Cytotoxicity on Triple Negative Breast Cancer Cells

The negative health impact of chiral environmental pollutants (CEPs), including mutagenicity, teratogenicity, and developmental problems, highlight the importance of chirality to the biomedical research community and the need for new techniques for accurate analysis of CEPs in humans to promote the development of biomedical protocols for CEPs poisoning therapy. This study examined the effects of chirality on 1-(9-anthryl)-2,2,2-triflouroethanol (TFE) and 1,1′binaphthyl-2,2′-diamine (BNA) enantiomers interactions with human serum albumin (HSA), the dominant serum protein and a transporter of hormones, drugs and metabolites in human. Specifically, the emission, the binding constants, stoichiometry, and thermodynamic properties of enantiomers of TFE-HSA and BNA-HSA complexes were investigated using analytical spectroscopy (Fourier transform infrared, UV-visible and fluorescence). The influence of experimental conditions such as the temperature and the concentration of TFE and BNA enantiomers on TFE-HSA and BNA-HSA complexations were also investigated. In addition, the effect of TFE and BNA enantiomers on the mobility of HSA in solution was explored by the use of steady state fluorescence anisotropy measurement. Furthermore, enantiomeric cytotoxicity and cell viability of TFE and BNA enantiomers on triple negative breast cancer cells was investigated. The results of this study showed considerable differences in the emission property, the binding constants, and thermodynamic properties of the enantiomers TFE-HSA and BNAHSA complexes, indicating diastereomeric complex formations and chiral discrimination. The result of the study also showed differences in the TFE and BNA enantiomeric cell cytotoxicity and cell viability on triple negative breast cancer cells.
PERAN INTELLECTUAL CAPITAL DAN INNOVATIVE BEHAVIOR UNTUK MENINGKATKAN OPPORTUNITY CAPTURE PADA INDUSTRI PERHOTELAN

The tourism business in the city of Surabaya, especially the hotel industry, has been hit badly by the Covid-19 pandemic where hotel occupancy rates fell to their lowest level. However, efforts must be made to keep the wheels of the organization running in the face of this difficult situation. Therefore, hotel business actors must make something innovative so that hotels can continue to operate and have a competitive edge. This study attempts to analyze the factors that can generate the ability to opportunity capture through the implementation of innovative behavior which in turn is also driven by various types of intellectual capital at each organizational level such as human capital, organizational capital and social capital. This research is a quantitative study and uses the Generalized Structured Component Analysis (GSCA) method to process research data that has been collected from 74 hotels in the city of Surabaya. Of the four hypotheses developed in this study, only three hypotheses can be accepted, namely human capital has a positive effect on innovative behavior, social capital has a positive effect on innovative behavior, and innovative behavior has a positive effect on opportunity capture. While the hypothesis which states that organizational capital has a positive effect on innovative behavior is not proven.
From the Whisper Network to #MeToo—Framing Gender, Gossip and Sexual Harassment

There is a long-standing connection between gender and gossip in Western culture as the communication amongst women has been stigmatized as gossip. Long before #MeToo, women who had become victims of sexual abuse and who spoke out against sexual violence were pillorized through gossip and stigmatized as gossips in the public sphere. As a consequence, women have resorted to private forms of communication―so-called “whisper networks”―to warn each other about abuse and harassment. However, the #MeToo-movement has shifted this network from the private sector into that strange hybrid of private and public communication that is social media. The “mainstreaming” of feminist activism achieved through hashtag feminism has had repercussions for the representation of rape survivors and feminist activists in traditional, analog media. The particulars of these repercussions are what this essay seeks to analyze. The traditional public forum of the printed press started to represent these women as trustworthy witnesses―in a dramatic deviation from previous patterns of representation. While the connection between femininity and gossip thus seems to have been severed, this does not, however, mean that the representation of women in the media has been fundamentally altered. Through a semiotic analysis of the visual representations of women in print media around and after #MeToo, this essay will critically call into question the extent of the perceived paradigm shift in the context of #MeToo and the trial of Bill Cosby in 2017.
Voronoi Partition to Support Data Search in Uncertain Database with k-Bound Filtering

With the development of mobile technology, one of its main functions is to have mobile navigation capabilities, this is one of the Location-Based Services (LBS). Mobile navigation is designed as a mobile device to be able to monitor access objects from users. Because of the mobile characteristic, the impact on the points of objects to be found always occur a not certain change. Efficient query processing is needed on a set of mobile data due to the movement of users. This movement has an impact on searching in an uncertain database. For this uncertain database, the important query method is Probabilistic k-Nearest Neighbor query (PkNN), which calculates the probability of the set of k objects to be closest to the given query point. Several studies have been conducted at this time in order to contribute to the search results in a mobile database and uncertain with the support of certain algorithms to produce better performance. In this study, we propose a method called voronoi partitioning to support searching in uncertain database (Partition threshold k Aggregate Nearest Neighbor query method-Partition_PANN). In designing the partition of the voronoi region, it starts by using voronoi local networks to calculate query answers for small areas around the request point. A query point that meets the threshold used as a value as a set of threshold queries. So, all of the query points that meet the thresholds are the basis for forming local network voronoi partitions. Thus, this method does not require preliminary calculations also evaluation of distances at each intersection. The purpose of this research is to improve the performance of queries in an uncertain database by making the aggregate process and trimming the probability value as one phase of the search algorithm. In the first stage, objects which not able to form the answers are filtered by calculating the minimum closed circle from the dataset of query which prepared for the trimming phase. The second step called probabilistic candidate selection, its cut significant set of candidates for inspected as the aggregate function of the nearest neighbor’s demand. The remaining set is sent for verification which obtains possible answers at the lower and upper limits so that candidates whose probabilities are not less than the user-specified threshold are saved in the result set and returned to the user. We also examine the efficient data structures spatially which support this method. Our solution can be applied to uncertain data with an ever-changing probability density function.
DenseNet-ResNet-LSTM model for modulation recognition of communication signal

The traditional artificial neural network provides a low recognition rate in the modulation recognition of communication signals, suffering from the difficulty of feature extraction. Also, it requires a high signal-to-noise ratio (SNR). In order to solve these problems, this paper proposes the combined model: DenseNet-ResNet-LSTM. In the proposed model, DenseNet and ResNet extract different spatial features of samples, and then LSTM extracts the sequence of samples. Also, the attention mechanism is employed to improve the learning efficiency and ability to learn important features. Experimental results show that the proposed model achieves higher accuracy and better generalization ability over the CNN-LSTM network.
Fatty acids in rumen and meat of lambs fed with different condensed and hydrolysable tannin extracts

Five groups of lambs (n = 9 each) were used to test the effect of plant extracts rich in hydrolysable (HT) or condensed tannin (CT) on animal performance, fatty acid composition of rumen content and meat. The control group (CO) received a concentrate-based diet without tannins supplementation. The other groups received the same diet as the control lambs plus 4% chestnut (CH) and tara (TA) extracts as a source of HT and mimosa (MI) and gambier (GA) extracts as a source of CT. Dietary CH negatively affected animal performance. The rumen content of the different groups showed comparable levels of 18:3 c9c12c15, 18:2 c9c12, 18:2 c9t11, 18:1 t11 and 18:0, whereas 18:1 t10 was greater in CO. Also, 18:1 t10 tended to be lower in the rumen of HT than CT-fed lambs. These data were partially confirmed in meat, where CO showed a greater percentage of individual trans 18:1 fatty acids in comparison with tannins-fed groups. Our findings challenge some accepted generalizations on the use of tannins in ruminant diets as they were ineffective to favour the accumulation of dietary PUFA or healthy fatty acids of biohydrogenation origin in the rumen content and lamb meat, but suggest a general action of tannins on the whole biohydrogenation process.
Surface cross-linked thermoplastic starch with different UV wavelengths: mechanical, wettability, hygroscopic and degradation properties

Here, we report a method to improve the properties of thermoplastic starch (TPS) by surface ultraviolet (UV) cross-linking. TPS sheets were prepared by injection molding and coated with an ethanol solution of photo-initiator TPO (2,4,6-trimethyl benzoyl diphenyl phosphine oxide), then, irradiated by UV with different wavelengths for 15 min. Untreated and irradiated TPS sheets were characterized using tensile and bending tests, impact tests, dynamic mechanical thermal analysis (DMTA) and infrared spectroscopy (FTIR). FTIR spectra showed that UV irradiation can effectively trigger surface cross-linking of TPS sheets. The mechanical and dynamic mechanical properties of the TPS were improved and the optimized properties were obtained by 308 nm UV irradiation. A tensile strength of 4.1 MPa, a bending strength of 2.7 MPa, an impact strength of 96.8 kJ m−2, and the corresponding activation energy of 251.22 kJ mol−1 were obtained. The water contact angle and moisture absorption of the samples were also investigated and the 308 nm UV irradiated sheets have a contact angle of 74°. Moisture absorption rate as a function of the square root of time showed a sigmoid curve including a linear stage which conforms to Fick's second law. The samples irradiated by 308 nm UV had the lowest equilibrium moisture absorption rate M∞ and the longest time T0 to enter into the Fick's diffusion stage and the lowest slope K and diffusion coefficient D. All samples displayed biodegradable properties when buried in soil. This method has potential applications for agricultural mulch films, packing and medical film products.
Strontium arsenate doped conducting polyaniline matrix as gas sensor

Electrical response of strontium arsenate (Sr3(AsO4)2) doped conducting Polyaniline (PANI) composites matrix in liquid petroleum gas (LPG) environment is studied. One step in situ chemical polymerization technique was used to synthesis conducting PANI and PANI / Sr3(AsO4)2 composites. Characterization confirmed the formation conducting polymer by FTIR, presence of Sr3(AsO4)2 in PANI matrix and its crystallinity by X-RD, Surface morphology and porosity by ESEM. Conductivity increases by with temperature, due to ion transfer within the composites by curling behavior of polymer. Absorption of charges by analyte gas from polymer matrix due to electron affinity, increases electrical resistance with increase in concentration of LPG. The absorption of the charges depends on the surface area of interaction between analyte gas and polymer matrix.
Decoupling Economic Growth from Fossil Fuel Use—Evidence from 141 Countries in the 25-Year Perspective

This study offers an in-depth analysis of the decoupling of economic growth from fossil fuel use in 141 countries over the last 25 years. The study is based on the Tapio decoupling approach, and two methods of measuring fossil fuel use, i.e., domestic material consumption (DMC) and material footprint (MF), are applied. Groups of countries with similar decoupling patterns are identified through the k-medoids method. Next, the relationship between these patterns and the level of countries’ development is examined. The results reveal that using different measures of fossil fuel use yields different processes of decoupling economic growth from fossil fuel use. In particular, when the DMC indicator is considered, relative decoupling is observed in most analysed cases. When the MF indicator is applied, the decoupling states of individual countries change more frequently. Finally, in highly developed countries, absolute decoupling is frequently observed, although only when the DMC indicator is used.
The Research of Single Image Super-Resolution Based on the Generative Adversary Networks

In order to enhance the visual effects of the reconstructed images in the single image super-resolution, and solve the problem of instability of the training phase of super-resolution with generative adversary network (SRGAN), a new super-resolution model is built with more depth and width, and the corresponding super-resolution algorithm is proposed. The network structure of the original SRGAN is modified, so that deeper and wider convolutional networks can be used with high efficiency. Furthermore, the loss function is employed to balance the training of the generative network and the discriminator network, and solve the instability problem in the training phase. The training images for the network are obtained from the database of ImageNet on the web as other researchers. Experimental results show that images reconstructed by the proposed algorithm has better visual effects than those by the original SRGAN. In addition, the objective measures of PSNR and SSIM of the reconstructed images have also been improved.
Exfoliation of Graphene in Ionic Liquids: Pyridinium versus Pyrrolidinium

Exfoliation is an elegant physical technique to directly obtain graphene from graphite. A search for high-performance exfoliation solvents is actively pursued nowadays. We report potentials of mean force and free energies, characterizing steered separation of graphene sheets and their subsequent solvation by room-temperature ionic liquids (RTILs). The exfoliation performance of N-butylpyridinium bis(trifluoromethanesulfonyl)imide [BPY][TFSI] is compared to that of 1-butyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide [PYR][TFSI]. Both RTILs are shown to exhibit comparable exfoliation performance, which is superior to the performance of 1-ethyl-3-methylimidazolium tetrafluoroborate by ∼20 kJ mol–1 nm–1. The sulfur atom of TFSI– contributes an essential portion of the solvation enthalpy due to its dispersive attraction to carbon atoms of graphene. Both RTILs maintain a single, moderately defined shell around the graphene surface. [BPY][TFSI] and [PYR][TFSI] are suitable starting compounds to engi.