Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of the starting performance of damper coiled salient pole synchronous generator with different slot design

Starting performance of synchronous generators and the time in which the machine comes into steady state are important. Hence, there is much research carried out on the starting performance of synchronous generators. The more the power of the synchronous generator is, the more important its starting performance becomes. In the present study, through Ansoft Maxwell program, the design of 2.2 MW and 6600v synchronous generators was made, and then two-dimensional static magnetic analyses and two-dimensional transient analyses were performed. In this way, we were able to investigate starting losses, period of coming to steady state, phase currents and instantaneous torque values of the synchronous generators.
Second order statistics of the SIR for cellular mobile networks in the presence of correlated co-channel interferers

In this paper second order statistics of the SIR (signal-to-interference ratio) are derived in the presence of cross correlated shadowing components. An analytical approach is proposed that extends to second order statistics the Wilkinson's approximation method for the power sum of log-normal components. The method is used to evaluate the outage occurrence rate for various propagation scenarios, characterized by different shadowing correlation decay distances and cross-correlations among shadowing components. Simulation results are then used to validate the analysis.
Radiowave propagation in industrial environments

This paper presents results from wireless local area network field tests executed in indoor industrial environments. The tests have been conducted at a chemical pulp factory, a cable production hall and a nuclear power plant. All tests have focused on IEEE 802.11 compliant equipment and the ISM frequency bands. The objectives of the tests were to investigate standard off the shelf communication equipment for utilisation in industrial environments. This equipment is designed for use in offices and storage facilities. Wireless networks in an industrial environment may have large impact on maintenance and service routines and seems to be greatly welcomed by the industry. The channel sounding showed heavy multipath fading with good coverage behind obstacles and slow power attenuation. There were no problems with signal quality in covered areas. The overall performance of the equipment was far better than expected.
Solar combisystem with seasonal thermal storage

The performance of a solar combisystem with a long-term thermal storage capacity is investigated for a typical one-storey detached house in Montreal. Simulation results from the TRNSYS program show that, starting with the second year, the system is able to cover fully the heating and domestic hot water thermal loads using the solar energy exclusively. The solar combisystem with seasonal storage capacity is technically feasible, can be built with equipment currently available, and can lead to significant energy savings in the residential sector in Montreal. The Energy Payback Time index shows that the embodied energy initially invested in the equipment is recovered in less than 6 years through the thermal energy savings. The current barriers to the deployment of such a system at large scale are the low electricity rates in Quebec, the high initial costs and the absence of substantial financial incentives.
Development and Quality Evaluation of Coconut Milk Chocolate By Incorporation of Fat and Corn Flour

The demand of milk product is increasing. Among all the milk products, chocolate is mostly preferred con- fectionary product. Coconut (Cocus nucifera) is the stone of the drupes borne by the coconut palm, a member of the monocotyledonous family Palmae. It is known as the "wonder food" and is regarded as perfect diet because it contains almost all essential nutrients needed by the human body. Milk is one of the most important ingredients in chocolate production. Coconut milk may be considered as a substitute for cow milk. Soymilk/Coconut milk can be added in chocolate to improve the texture and to increase the binding capacity of chocolate. The texture, flavor and level of mouth feel are unique characteristics. It may be used by the people who cannot tolerate cow milk. For formulation coconut milk, cocoa powder, GMS, coconut shreds, sugar, corn flour and vegeta- ble shortening was selected. The six samples was prepared. These six samples were analyzed for sensory and chemical and microbial analysis. In sensory evaluation the sample which is having (coconut milk: 130ml, sugar: 100g, cocoa powder: 15g, corn flour: 4g, veg. fat shortening: 6g, and coconut shreds: 32g) was having good flavor, taste, color, texture and mouth feel and overall acceptability.
Search for the 
α
 
+
 core structure in the ground state bands of 
22≤Z≤42
 even-even nuclei

A systematic analysis of the α + core structure is performed in the ground state bands of even-even nuclei of the 22 ≤ Z ≤ 42 region in terms of the Local Potential Model. The α + core interaction is described by the nuclear potential of (1 + Gaussian)×(W.S. + W.S.) shape with 2 free parameters. Properties such as energy levels, reduced α-widths, B(E2) transition rates and rms charge radii are calculated and compared with experimental data. A good agreement with the experimental data is obtained in general, even for the nuclei without the α + {doubly closed shell core} configuration. The analysis of the selected nuclei in the 22 ≤ Z ≤ 42 region indicates that Ti and Mo have a greater α-clustering degree in comparison with their respective neighboring nuclei of this set. In addition, the model points to the existence of nuclei without the α + {doubly closed shell core} configuration with a significant α-clustering degree compared to Ti, Zn, and Mo. The study shows that the α + core approach is satisfactorily applicable to nuclei other than those with αclustering above double-shell closures.
Efficiency of Jet Pumps

A theoretical analysis and an experimental study on the efficiency of water jet pumps, where water is used for both the primary and secondary flows, are presented in this paper. The theoretical efficiency equations for such jet pumps were first derived based on one-dimensional formulation, and the theoretical maximum ideal efficiency of 100% was obtained. An experimental rig was designed and constructed to conduct the experimental study in which a commercial water jet pump was used. The effects of different area ratios of nozzle to mixing throat as well as different nozzle cross sections, which include square and triangular nozzles, on the jet pump performance were then investigated. The best nozzle cross section for the jet pump was found to be circular, and for high efficiency, the area ratio was found to be around 0.30.
Micro-RNA Analysis of Pancreatic Cyst Fluid for Diagnosing Malignant Transformation of Intraductal Papillary Mucinous Neoplasm by Comparing Intraductal Papillary Mucinous Adenoma and Carcinoma

Although intraductal papillary mucinous neoplasm (IPMN) is thought to be a precursor lesion of pancreatic cancer, diagnosing malignant transformation of IPMN using non-invasive diagnostic methods is difficult and complicated. Micro-RNAs (miRNAs) are currently recognized as biomarkers and molecular targets of various diseases, including malignancy. In this study, we investigated a potential diagnostic approach using miRNA in pancreatic cyst fluid as a marker for evaluating malignant alternation of IPMN. Cystic fluid was sampled mainly during surgical resection. The collected samples were evaluated by performing comprehensive analysis of miRNA using a highly sensitive DNA chip. miRNA expression was compared between IPM adenoma (IPMA) and IPM carcinoma (IPMC) to evaluate the related biomarkers for malignant transformation of IPMN. miRNA analysis revealed that six miRNAs (miR-711, miR-3679-5p, miR-6126, miR-6780b-5p, miR-6798-5p, and miR-6879-5p) in IPMC were significantly enriched compared to those in IPMA. The difference was validated using quantitative real-time PCR. Cyst fluid miRNA analysis might be useful for diagnosing malignant alteration of IPMN. Further evaluations of diagnostic capability as well as functional analysis using the identified miRNAs are required with larger cohorts to confirm its efficacy.
Imprint of chiral symmetry restoration on the Polyakov loop and the heavy quark free energy

The Polyakov loop expectation value $\langle P\rangle$ is an order parameter of the deconfinement transition in the heavy quark mass regime, whereas its sensitivity to the deconfinement of light, dynamical quarks is not apparent. From the perspective of an effective Lagrangian in the vicinity of the chiral transition, the Polyakov loop, $P$, is an energy-like observable, and $\langle P\rangle$ should hence scale like the energy density. Using $N_f=2+1$ HISQ configurations at finite lattice spacing, we show that near the chiral transition temperature, the scaling behavior of $\langle P\rangle$ and the heavy quark free energy $F_q$ is consistent with energy-like observables in the 3-$d$, O($N$) universality class. We extend this analysis to other Polyakov loop observables, including the response of the heavy quark free energy, $F_q$, to the baryon chemical potential, which is expected to scale like a specific heat.
Lyman-α constraints on freeze-in and superWIMPs

Dark matter (DM) from freeze-in or superWIMP production is well known to imprint non-cold DM signatures on cosmological observables. We derive constraints from Lyman-α forest observations for both cases, basing ourselves on a reinterpretation of the existing Lyman-α limits on thermal warm DM. We exclude DM masses below 15 keV for freeze-in, in good agreement with previous literature, and provide a generic lower mass bound for superWIMPs that depends on the mother particle decay width. Special emphasis is placed on the mixed scenario, where contributions from both freeze-in and superWIMP are similarly important. In this case, the imprint on cosmological observables can deviate significantly from thermal warm DM. Furthermore, we provide a modified version of the Boltzmann code class, analytic expressions for the DM distributions, and fits to the DM transfer functions that account for both mechanisms of production. Moreover, we also derive generic constraints from ΔN eff measurements and show that they cannot compete with those arising from Lyman-α observations. For illustration, we apply the above generic limits to a coloured t-channel mediator DM model, in which case contributions from both freeze-in through scatterings and decays, as well as superWIMP production can be important. We map out the entire cosmologically viable parameter space, cornered by bounds from Lyman-α observations, the LHC, and Big Bang Nucleosynthesis.
A Supervised Learning Framework for Joint Angle-of-Arrival and Source Number Estimation

Machine learning is a promising technique for angle-of-arrival (AOA) estimation of waves impinging a sensor array. However, the majority of the methods proposed so far only consider a known, fixed number of impinging waves, i.e., a fixed source number. This paper proposes a machine-learning-based estimator designed for the case when the source number is variable and hence unknown a priori. The proposed estimator comprises a framework of single-label classifiers. Each classifier predicts if waves are present within certain randomly selected segments of the array's field of view (FOV), resulting from discretising the FOV with a certain (FOV) resolution. The classifiers' predictions are combined into a probabilistic angle spectrum, whereupon the source number and the AOAs are estimated jointly by applying a probability threshold whose optimal level is learned from data. The estimator's performance is assessed using a new performance metric: the joint AOA estimation success rate. Numerical simulations show that for low SNR (-10 dB), a low FOV resolution (2$^\circ$) yields a higher success rate than a high resolution (1$^\circ$), whereas the opposite applies for mid (0 dB) and high (10 dB) SNRs. In nearly all simulations, except one at low SNR and a high FOV resolution, the proposed estimator outperforms the MUSIC algorithm if the maximum allowed AOA estimation error is approximately equal to (or larger than) the FOV resolution.
AntagomiR-19a Induced Better Responsiveness to Bortezomib in Myeloma Cell Lines

Objective Multiple myeloma (MM) is the clonal proliferation of neoplastic plasma cells in the bone marrow. Although bortezomib (BTZ) is a crucial drug for the treatment of MM, drug resistance is a major problem. OncomiR-19a plays an oncogenic role in many cancers, including MM; however, the function of miR-19a in the pathogenesis of MM and drug resistance has not been completely identified. The present research aims to investigate the inhibition of miR-19a by an antagomir to determine BTZ responsiveness, and determine if miR-19a can be a prognostic biomarker for MM. Materials and Methods In this experimental study, viability and apoptosis of myeloma cells were analysed by the colorimetric 3-(4, 5-Dimethylthiazol-2-yl)-2, 5-Diphenyltetrazolium Bromide (MTT) and Annexin V/propidium iodide (PI) flow cytometry assays. Quantitative real-time polymerase chain reaction (qRT-PCR) was implemented to evaluate the expression levels of miR-19a, its targets SOCS3, STAT3, B-cell lymphoma 2 (BCL-2), PTEN and CDKN1A (anti- apoptotic and cell cycle related genes) at the mRNA level. Results miR-19a was downregulated and exacerbated in transfected cells treated with BTZ. The rate of apoptosis in the myeloma cells after BTZ treatment considerably increased, which indicated an increase in the mRNA of SOCS3, PTEN, BCL-2, and CDKN1. A decrease in STAT3 was also observed. Conclusion OncomiR-19a, as a biomarker, may induce better responsiveness to BTZ in myeloma cell lines through its targets SOCS3, STAT3 and PTEN. In the future, this biomarker may provide new therapeutic targets for MM.
Risk Factors Associated With Birth Asphyxia in Term Newborns at a Tertiary Care Hospital of Multan, Pakistan

Background Perinatal asphyxia is one of the main causes of death in term newborns. During the past two decades, no significant progress has been made in reducing neonatal deaths in developing countries. This study was aimed to determine various factors associated with birth asphyxia in term newborns at a tertiary care hospital of Multan, Pakistan. Methods This case-control study was conducted at the Neonatal pediatrics Department, The Children’s Hospital, Multan in collaboration with the labor room of Nishtar Hospital Multan from April 2020 to September 2020. Newborns delivered in the labor room with a low Apgar score of five or less at the first minute were recruited as cases and newborns with an Apgar score of more than five in the first minute were recruited as controls. The demographic information of neonates and mothers was noted. A Performa was used to collect all information. All data were analyzed through SPSS 26.0 (IBM SPSS Inc., Chicago, IL, USA). Results A total of 426 newborns (213 cases and 213 controls) were enrolled. In cases, there were 132 males and 81 females whereas there were 115 males and 98 females in the control group (P=0.09). Majority 132 (62%) mothers of cases were primiparous compared with 110 (52%) mothers of control. The difference in parity of mothers of cases and control (P=0.03) was significant. Prolonged labour was noted in cases 123 (58%) vs. controls 55 (26%) (P=0.001) while fetal distress was found in 120 (56%) cases and 45 (21%) controls (P=0.001). Meconium was found in the amniotic fluid in 171 (80%) cases and 86 (40%) controls (P=0.001). All other risk factors turned out to be insignificant between cases and controls (P>0.05). Conclusion Meconium stained liquor is a major risk factor for birth asphyxia. Prolonged labor of more than 24-hour period, as well as fetal distress, is also a major risk factor of perinatal asphyxia. Involving obstetricians in the present research give more reliability and reproducibility of the data collected.
One-Shot Generative Domain Adaptation

This work aims to transfer a Generative Adversarial Network (GAN) pre-trained on one image domain to another domain referred to as few as just one reference image. The challenge is that, under limited supervision, it is extremely difficult to synthesize photo-realistic and highly diverse images while retaining the representative characters of the target domain. Different from existing approaches that adopt the vanilla fine-tuning strategy, we design two lightweight modules in the generator and the discriminator respectively. We first introduce an attribute adaptor in the generator and freeze the generator’s original parameters, which can reuse the prior knowledge to the most extent and maintain the synthesis quality and diversity. We then equip the well-learned discriminator with an attribute classifier to ensure that the generator with the attribute adaptor captures the appropriate characters of the reference image. Furthermore, considering the very limited diversity of the training data (i.e., as few as only one image), we propose to constrain the diversity of the latent space through truncation in the training process, alleviating the optimization difficulty. Our approach brings appealing results under various settings, substantially surpassing state-of-the-art alternatives, especially in terms of synthesis diversity. Noticeably, our method works well even with large domain gaps and robustly converges within a few minutes for each experiment. Code and models are available at https://genforce.github. io/genda/.
Dynamic-TinyBERT: Boost TinyBERT's Inference Efficiency by Dynamic Sequence Length

Limited computational budgets often prevent transformers from being used in production and from having their high accuracy utilized. TinyBERT addresses the computational efficiency by self-distilling BERT into a smaller transformer representation having fewer layers and smaller internal embedding. However, TinyBERT's performance drops when we reduce the number of layers by 50%, and drops even more abruptly when we reduce the number of layers by 75% for advanced NLP tasks such as span question answering. Additionally, a separate model must be trained for each inference scenario with its distinct computational budget. In this work we present Dynamic-TinyBERT, a TinyBERT model that utilizes sequence-length reduction and Hyperparameter Optimization for enhanced inference efficiency per any computational budget. Dynamic-TinyBERT is trained only once, performing on-par with BERT and achieving an accuracy-speedup trade-off superior to any other efficient approaches (up to 3.3x with<1% loss-drop). Upon publication, the code to reproduce our work will be open-sourced.
Improving Transferability of Representations via Augmentation-Aware Self-Supervision

Recent unsupervised representation learning methods have shown to be effective in a range of vision tasks by learning representations invariant to data augmentations such as random cropping and color jittering. However, such invariance could be harmful to downstream tasks if they rely on the characteristics of the data augmentations, e.g., location- or color-sensitive. This is not an issue just for unsupervised learning; we found that this occurs even in supervised learning because it also learns to predict the same label for all augmented samples of an instance. To avoid such failures and obtain more generalizable representations, we suggest to optimize an auxiliary self-supervised loss, coined AugSelf, that learns the difference of augmentation parameters (e.g., cropping positions, color adjustment intensities) between two randomly augmented samples. Our intuition is that AugSelf encourages to preserve augmentation-aware information in learned representations, which could be beneficial for their transferability. Furthermore, AugSelf can easily be incorporated into recent state-of-the-art representation learning methods with a negligible additional training cost. Extensive experiments demonstrate that our simple idea consistently improves the transferability of representations learned by supervised and unsupervised methods in various transfer learning scenarios. The code is available at https://github.com/hankook/AugSelf.
Closed ray nil-affine manifolds and parabolic geometries

Ray nil-affine geometries are defined on nilpotent spaces. They occur in every parabolic geometry and in those cases, the nilpotent space is an open dense subset of the corresponding flag manifold. We are interested in closed manifolds having a ray nil-affine structure. We show that under a rank one condition on the isotropy, closed manifolds are either complete or their developing map is a cover onto the complement of a nilaffine subspace. We prove that if additionally there is a parallel volume or if the automorphism group acts non properly then closed manifolds are always complete. This paper is a sequel to a previous work on ray manifolds in affine geometry.
Factors associated with the appropriate use of asthma medications among adult asthmatic patients attending asthma clinic in a teaching hospital

Introduction asthma tends to be more severe with worse symptoms in Africa due to late diagnosis and delayed initiation of treatment. To identify patient and treatment-related factors which influence the appropriate use of asthma medications. Methods the study was institution based cross-sectional design. Patients were invited to provide information regarding the use of their asthma medications and factors potentially associated with appropriate use of these medications. A stepwise multivariate logistic regression analysis was used to evaluate the most important factor at a 0.05 level of significance. Results respondents with better knowledge of their asthma medications were more likely to use them appropriately (OR 5.82 [CI 95% 2.25-15.04]) as were those with positive attitudes and beliefs towards asthma and asthma medications (OR 3.88 [CI 95% 1.44-10.44]). Conclusion patients need to understand the importance of adhering to the prescribed regimen for their asthma medications even in the absence of overt symptoms in order to optimize clinical outcome.