Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Gender Make a Difference? Undergraduate Students' Use of Smart CVs for Career Planning

In the contemporary society, gender equality in accessing the job market is advocated, and often protected by law in developed countries. In reality, however, gender differences exist in different aspects and stages of recruitment processes and career development, say from career planning, job search, application, recruitment and promotion. Such differences are usually exemplified by different interesting findings in the literature. Some research findings had shown that male candidates spend less time than female candidates to secure a post-displacement job, male candidates in overall are more "linear" in job seeking than female candidates. One proposed explanation on the phenomenon is on how male and female candidates use online CVs for job hunting. This research aims to investigate the undergraduate students' perceived effects of three facets: Portfolio, Presentation and Presence in career planning, job search and application processes by using online CVs. Initial results indicate that gender differences exist on the perceptions of 3P's in career planning. Notably, female candidates see their Presence has direct relationship with Career Planning but male candidates do not. While male candidates perceive a direct relationship between Portfolio and Career Planning, but their female counterparts do not.
Designing a Transcription Game

In this thesis, we develop a method to generate audio file transcripts with the high accuracy of professional transcription and the low costs of computerized transcription. We apply the principles of “Games With A Purpose” to this problem, creating a solution in the form of a game. In designing the Transcription Game, we overcome the obstacle of being unable to determine which transcripts are accurate, creating an incentive structure that results in a Perfect Bayesian Equilibrium in which all players enter the most accurate transcripts possible. We test our hypothesis that an iterative implementation of this game, in which players improve upon others’ entries, performs better than a parallel implementation, in which players enter transcripts without seeing others’ entries. Empirical results comparing the accuracy, efficiency, and enjoyability of the two versions support our initial hypothesis. Ultimately, while this game was not an instant hit, it provides solid groundwork for future development. The 96.6% accuracy of the transcripts obtained through the iterative process clearly demonstrates the potential of the methods implemented herein and hints at the possibility of someday being able to use a similar system on a larger scale for audio file transcription.
Residual Neural Networks for Speech Recognition Hari

Recent developments in deep learning methods have greatly influenced the performances of speech recognition systems. In a Hidden Markov model-Deep neural network (HMMDNN) based speech recognition system, DNNs have been employed to model senones (context dependent states of HMM), where HMMs capture the temporal relations among senones. Due to the use of more deeper networks significant improvement in the performances has been observed and developing deep learning methods to train more deeper architectures has gained a lot of scientific interest. Optimizing a deeper network is more complex task than to optimize a less deeper network, but recently residual network have exhibited a capability to train a very deep neural network architectures and are not prone to vanishing/exploding gradient problems. In this work, the effectiveness of residual networks have been explored for of speech recognition. Along with the depth of the residual network, the criticality of width of the residual network has also been studied. It has been observed that at higher depth, width of the networks is also a crucial parameter for attaining significant improvements. A 14-hour subset of WSJ corpus is used for training the speech recognition systems, it has been observed that the residual networks have shown much ease in convergence even with a depth much higher than the deep neural network. In this work, using residual networks an absolute reduction of 0.4 in WER error rates (8% reduction in the relative error) is attained compared to the best performing deep neural network.
Comparative Evaluation of Bivalent Malaria Rapid Diagnostic Tests versus Traditional Methods in Field with Special Reference to Heat Stability Testing in Central India

Background Malaria presents a diagnostic challenge in areas where both Plasmodium falciparum and P.vivax are co-endemic. Bivalent Rapid Diagnostic tests (RDTs) showed promise as diagnostic tools for P.falciparum and P.vivax. To assist national malaria control programme in the selection of RDTs, commercially available seven malaria RDTs were evaluated in terms of their performance with special reference to heat stability. Methodology/Principal Findings This study was undertaken in four forested districts of central India (July, 2011– March, 2012). All RDTs were tested simultaneously in field along with microscopy as gold standard. These RDTs were stored in their original packing at 25°C before transport to the field or they were stored at 35°C and 45°C upto 100 days for testing the performance of RDTs at high temperature. In all 2841 patients with fever were screened for malaria of which 26% were positive for P.falciparum, and 17% for P.vivax. The highest sensitivity of any RDT for P.falciparum was 98% (95% CI; 95.9–98.8) and lowest sensitivity was 76% (95% CI; 71.7–79.6). For P.vivax highest and lowest sensitivity for any RDT was 80% (95% CI; 94.9 - 83.9) and 20% (95% CI; 15.6–24.5) respectively. Heat stability experiments showed that most RDTs for P.falciparum showed high sensitivity at 45°C upto 90 days. While for P.vivax only two RDTs maintained good sensitivity upto day 90 when compared with RDTs kept at room temperature. Agreement between observers was excellent for positive and negative readings for both P.falciparum and P.vivax (Kappa >0.6–0.9). Conclusion This is first field evaluation of RDTs regarding their temperature stability. Although RDTs are useful as diagnostic tool for P.falciparum and P.vivax even at high temperature, the quality of RDTs should be regulated and monitored more closely.
Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS

In this work we introduce a method for visualization of fuzzy label information obtained from prototype based fuzzy labeled self- organizing map (FLSOM) for fuzzy classification. FLSOM returns vectors of fuzyy class labels for the prototypes containing class simlarity informa- tion. This information is used for apropriate visualization by an adequate, similarity preserving color space embedding realized by an advanced MDS- approach. Using this embedding, classification results can be visualized by the similarity-based color representation of the data. The method is ap- plied for image segmentation with uncertain (fuzzy) class membership. 1I ntroduction Real world data are often characterized by uncertain and possibly inconsistent information. In particular in medical and biological applications this problem plays an important role. If data are processed by machine learning approaches, this uncertainty has to be taken into account. Prototype based fuzzy classifica- tion offers a possible solution for learning of labeled data in the context of clas- sification tasks. Respective algorithms are the fuzzy labeled neural gas (FLNG - (1)) or its self-organizing map (SOM) based counterparts FuzzySOM (2) and fuzzy labeled self-organizing map (FLSOM - (3)), which offer better data visual- ization possibilities due to its underlying regular grid structure of self-organizing maps (SOM - (4)). This advantage is caused by the topology preserving mapping realized by unsupervised SOMs under certain conditions. Usually, the supervised variants return a probability vector assigned to each prototype, which reflects the class probabilities for each possible data class. Yet, FuzzySOM does not minimize a predefined cost function because both parts of the adaptation, the SOM learning and the subsequent learning vector quantization are not based on a gradient descent approach. FLSOM, however, is based on the Heskes' variant of SOMs, for which a cost function is given. The SOM adaptation scheme is imposed by a gradient descent on classification accuracy. Further, the topology preservation may be lost by the subsequent learning in FuzzySOM, whereas it is not in FLSOM. Yet, the visualization of fuzzy classification information is difficult. One method is to consider the barplots of the probability vectors as demonstrated for FLSOM (5). However, we can use a special feature of FLSOM. In contrast to FuzzySOM, FLSOM inherently contains the neighborhood cooperativeness also in label adaptation. Therefore, in case of adequate conditions, topological ordering is obtained for both prototype distribution and label vectors. From the
3,5,6,7,8,3′,4′-Heptamethoxyflavone, a Citrus Flavonoid, Inhibits Collagenase Activity and Induces Type I Procollagen Synthesis in HDFn Cells

Citrus fruits contain various types of flavonoids with powerful anti-aging and photoprotective effects on the skin, and have thus been attracting attention as potential, efficacious skincare agents. Here, we aimed to investigate the chemical composition of Citrus unshiu and its protective effects on photoaging. We isolated and identified a bioactive compound, 3,5,6,7,8,3′,4′-heptamethoxyflavone (HMF), from C. unshiu peels using ethanol extraction and hexane fractionation. HMF inhibited collagenase activity and increased type I procollagen content in UV-induced human dermal fibroblast neonatal (HDFn) cells. HMF also suppressed the expression of matrix metalloproteinases 1 (MMP-1) and induced the expression of type I procollagen protein in UV-induced HDFn cells. Additionally, HMF inhibited ultraviolet B (UVB)-induced phosphorylation of the mitogen-activated protein kinases (MAPK) cascade signaling components—ERK, JNK, and c-Jun—which are involved in the induction of MMP-1 expression. Furthermore, HMF affected the TGF-β/Smad signaling pathway, which is involved in the regulation of type I procollagen expression. In particular, HMF induced Smad3 protein expression and suppressed Smad7 protein expression in UV-induced HDFn cells in a dose-dependent manner. These findings suggest a role for Citrus unshiu in the preparation of skincare products in future.
Regulation of podocalyxin trafficking by Rab small GTPases in 2D and 3D epithelial cell cultures

Epithelial polarity establishment involves transcytosis of podocalyxin to the apical domain, but its route and regulation are unclear. Here, Mrozowska and Fukuda demonstrate that different Rabs and Rab effectors coordinate podocalyxin transport during polarization in 2D and 3D structures.
Nanocomposite polyacrylonitrile filaments with electrostatic dissipative and antibacterial properties

In this study, silver nitrate was added to polyacrylonitrile filament structure and chemical reduction was applied to composite filaments in order to develop multifunctional polyacrylonitrile filaments with electrostatic dissipative and antibacterial properties. Composite filaments of polyacrylonitrile and silver nitrate were characterized and evaluated in terms of morphology, chemical structure, tensile properties, crystallinity, conductivity, thermal properties, silver ion release behaviour and antibacterial activity. Additionally, ultraviolet-visible spectroscopy was used to confirm the formation of nanoparticles and the variation in the concentration of the nanoparticles with the application of the chemical reduction process. Scanning electron microscope images and ultraviolet-visible spectroscopy results confirmed the formation of nanoparticles in the filament structure. Breaking strength and breaking elongation increased at silver nitrate content of 1%. Composite filaments displayed improved thermal stability and their conductivities were in the semiconductive range. Atomic absorption spectroscopy confirmed that necessary amounts of silver release for antibacterial activity occurred, while the antibacterial activity analysis showed that the composite filaments have excellent antibacterial activity. The results obtained were promising and showed that the composite filaments could be used in electrostatic dissipative and antibacterial applications.
Triggercast: Enabling Wireless Collisions Constructive

It is generally considered that concurrent transmissions should be avoided in order to reduce collisions in wireless sensor networks. Constructive interference (CI) envisions concurrent transmissions to positively interfere at the receiver. CI potentially allows orders of magnitude reductions in energy consumptions and improvements on link quality. In this paper, we theoretically introduce a sufficient condition to construct CI with IEEE 802.15. 4 radio for the first time. Moreover, we propose Triggercast, a distributed middleware, and show it is feasible to generate CI in TMote Sky sensor nodes. To synchronize transmissions of multiple senders at the chip level, Triggercast effectively compensates propagation and radio processing delays, and has $95^{th}$ percentile synchronization errors of at most 250ns. Triggercast also intelligently decides which co-senders to participate in simultaneous transmissions, and aligns their transmission time to maximize the overall link PRR, under the condition of maximal system robustness. Extensive experiments in real testbeds reveal that Triggercast significantly improves PRR from 5% to 70% with 7 concurrent senders. We also demonstrate that Triggercast provides on average $1.3\times$ PRR performance gains, when integrated with existing data forwarding protocols.
Sources of interferon-gamma (IFN-gamma) in early immune response to Listeria monocytogenes.

Early, innate production of interferon-gamma (IFN-gamma) is a critical step in immunological defense against certain pathogens such as intracellular bacteria (e.g. Listeria monocytogenes), viruses and fungi. While activated T cells and activated natural killer (NK) cells were initially thought to be the only relevant source of IFN-gamma, macrophages (Mphi) and dendritic cells can also be stimulated to produce IFN-gamma in vitro under certain conditions. However, a convincing analysis at single cell level of the source(s) of IFN-gamma in the early immune response to an acute bacterial infection is still missing. In the light of controversial literature, the work presented here aimed to clarify the role of NK cells and other components of the innate cellular immune system in the early IFN-gamma production, thereby avoiding in vitro artifacts whenever possible. Immunocompetent C57BL/6 (wild type (WT)) and T and B cell-deficient C57BL/6 rag-1(-/-) (RAG) mice were infected intravenously with a pathogenic strain of L. monocytogenes. Leukocyte populations of spleen and liver were discriminated by characteristic surface markers and analyzed for intracellular interleukin (IL)-12 and IFN-gamma using flow cytometry. These cells have not been restimulated in vitro nor sorted before analysis. In RAG mice, at least, a large NK1.1+ cell population produced IFN-gamma 19 h p.i. No MHC class II+ population co-expressed intracellular IFN-gamma at this time point. For comparison with the immunocompetent situation, syngeneic WT mice were also infected and sacrificed 9, 19, and 29 h later. At 9 h p.i. , the situation resembled that of uninfected mice. At 19 and 29 h p.i. it was again the NK1.1+ population that contained most of the IFN-gamma-positive events. MHC II + CD 19- Mphi/dendritic cells and MHC II+ CD19+ B cells did not co-express intracellular IFN-gamma at these time points. CD3+ T cells were also found to contain intracellular IFN-gamma; most were also CD8+ and some CD4+. These results indicate that after infection of C57BL/6 mice with L. monocytogenes, NK1.1+ cells and, to a lesser extent, CD3+ cells are the prominent sources of innate IFN-gamma. MHC II+ cells do not play a significant role in the early IFN-gamma production following an acute primary bacterial infection.
Dilution of rice with other gluten free grains to lower inorganic arsenic in foods for young children in response to European Union regulations provides impetus to setting stricter standards

There has been an increasing realisation that young infants are exposed to elevated concentrations of the carcinogen inorganic arsenic, relative to adults. This is because many infant food products are rice based, and rice is ~10-fold elevated in inorganic arsenic compared to most other foods. The European Commission (EC) has acted on this concern setting stricter standards for infants, 100 μg of inorganic arsenic per kg of food (100 μg/kg), as compared to adults (200 μg/kg), for rice based foods, a law that was brought into place in 1st January 2016. Here we investigate how this law has impacted on inorganic arsenic in baby food products in the UK market, and compare the findings to previous baby food surveys taken before and just after the law came into place. We find that for a wide range of UK infant products that the new regulations are being adhered to, with all samples surveyed, being under 100 μg/kg inorganic arsenic. The prevalence of pure rice products had decreased in the UK, and there appears to be careful sourcing of the rice used in these products to ensure conformity with regulations. There has been an increased presence of mixed cereal products, with rice and maize as the main ingredient, appearing on the UK market, with varying rice contents for infant porridges, cakes and mueslis, with the latter being a relatively innovative product for infant foods. There was a highly significant correlation (P<0.0001) between rice content and inorganic arsenic concentration across all infant foods. When UK infant rice cakes, breakfast cereals and porridges were compare to their general, i.e. not labelled specifically for being for infant consumption, equivalent it was found that the adult foods generally exceeded the 100 μg/kg inorganic arsenic standard for infant foods. Thus, infants should not be given rice products not specifically labelled as being for them if a lower inorganic arsenic diet is to be maintained.
Plasma membrane repairs by small GTPase Rab3a

Lysosomes fuse with the plasma membrane to help repair membrane lesions, but how they are positioned close to these lesions is not fully understood. Now, Encarnação et al. (2016. J. Cell Biol. http://dx.doi.org/10.1083/jcb.201511093) demonstrate that the lysosomal GTPase Rab3a and its effectors orchestrate lysosome positioning and plasma membrane repair.
New Potential Pharmacological Functions of Chinese Herbal Medicines via Regulation of Autophagy

Autophagy is a universal catabolic cellular process for quality control of cytoplasm and maintenance of cellular homeostasis upon nutrient deprivation and environmental stimulus. It involves the lysosomal degradation of cellular components such as misfolded proteins or damaged organelles. Defects in autophagy are implicated in the pathogenesis of diseases including cancers, myopathy, neurodegenerations, infections and cardiovascular diseases. In the recent decade, traditional drugs with new clinical applications are not only commonly found in Western medicines, but also highlighted in Chinese herbal medicines (CHM). For instance, pharmacological studies have revealed that active components or fractions from Chaihu (Radix bupleuri), Hu Zhang (Rhizoma polygoni cuspidati), Donglingcao (Rabdosia rubesens), Hou po (Cortex magnoliae officinalis) and Chuan xiong (Rhizoma chuanxiong) modulate cancers, neurodegeneration and cardiovascular disease via autophagy. These findings shed light on the potential new applications and formulation of CHM decoctions via regulation of autophagy. This article reviews the roles of autophagy in the pharmacological actions of CHM and discusses their new potential clinical applications in various human diseases.
Current perspectives in coronary microvascular dysfunction

The coronary arterial system consists of large epicardial coronary arteries, pre‐arterioles, and arterioles, which together closely regulate CBF. Structural, functional, and extravascular abnormalities of the microcirculation lead to CMD. CMD can present with symptoms suggestive of CAD, often in the absence of significant obstructive epicardial CAD. Conventional invasive angiography does not allow direct visualization of the microcirculation. Invasive indices, such as CBF and CFR, and non‐invasive imaging modalities, such as CMR and PET, can be used to quantify absolute MBF and enable a direct and accurate assessment of coronary microvascular function. CMD appears to be more prevalent in women, typically presenting with symptoms of ischemia with unobstructed coronary arteries, and has a relatively unfavorable prognosis. CMD is classified clinically depending on the presence or absence of epicardial CAD, myocardial disease, or iatrogenic causes. Although invasive intracoronary techniques can be used to detect CMD, these cannot provide insight into the mechanisms involved in its pathogenesis. Imaging modalities such as CMR and cardiac PET are becoming indispensable tools in the evaluation of suspected CMD.
Downscaling GRACE Remote Sensing Datasets to High-Resolution Groundwater Storage Change Maps of California's Central Valley

NASA’s Gravity Recovery and Climate Experiment (GRACE) has already proven to be a powerful data source for regional groundwater assessments in many areas around the world. However, the applicability of GRACE data products to more localized studies and their utility to water management authorities have been constrained by their limited spatial resolution (~200,000 km2). Researchers have begun to address these shortcomings with data assimilation approaches that integrate GRACE-derived total water storage estimates into complex regional models, producing higher-resolution estimates of hydrologic variables (~2500 km2). Here we take those approaches one step further by developing an empirically based model capable of downscaling GRACE data to a high-resolution (~16 km2) dataset of groundwater storage changes over a portion of California’s Central Valley. The model utilizes an artificial neural network to generate a series of high-resolution maps of groundwater storage change from 2002 to 2010 using GRACE estimates of variations in total water storage and a series of widely available hydrologic variables (PRISM precipitation and temperature data, digital elevation model (DEM)-derived slope, and Natural Resources Conservation Service (NRCS) soil type). The neural network downscaling model is able to accurately reproduce local groundwater behavior, with acceptable Nash-Sutcliffe efficiency (NSE) values for calibration and validation (ranging from 0.2445 to 0.9577 and 0.0391 to 0.7511, respectively). Ultimately, the model generates maps of local groundwater storage change at a 100-fold higher resolution than GRACE gridded data products without the use of computationally intensive physical models. The model’s simulated maps have the potential for application to local groundwater management initiatives in the region.