Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-Agnostic Metric for Zero-Shot Learning

Zero-shot Learning (ZSL) aims to learn a classifier to recognize unseen categories without training samples. Most ZSL works based on embedding models handle the visual space and the semantic space through a common metric space and then apply a simple nearest neighbor search which directly leads to the hubness problem, one of the main challenges of ZSL. Contrary to recent works, whose conclusions about hubs are drawn based on Euclidean and specific models like ridge regression, we adopt cosine metric and for the first time prove cosine is model-agnostic to alleviate the hubness problem in ZSL. Assuming that the normalized mapped semantic vectors follow a uniform distribution, we provide theoretical analysis which demonstrates that hubs can be better reduced with a higher-dimensional cosine metric space. Moreover, we introduce a diversity-based regularizer with the cosine metric which underpins the assumption about the uniform distribution and further improves the model’s discriminative ability. Extensive experiments on five benchmarks and large-scale Imagenet dataset show that our method can improve the performance, surpassing previous embedding methods by large margins.
Development Needs of Middle Managers In Higher Education Institutions: A Case Study of A Post 1992 New University in UK

Development of staff by Human Resources (HR) department in any organisation is crucial to implement its strategy, operations, goals and for eventual success. Similarly, in Higher Education Institutions (HEIs) the Middle Managers (MM) are drivers who execute organisation vision, mission and contribute towards its desired attainment. MM job titles at faculty level include Deans, Head of Departments, Subject leaders and Principle lecturers/Programme leaders. However, evidenced from contemporary literature, changes and challenges transpiring in HEIs sector is influencing and generating tremendous pressures and workloads for MM to work effectively and efficiently in their respective roles. Therefore, the fortitude of this study is to explore this phenomenon and capture true MM Development Needs (DN) and propose a conceptual model. In stage one (qualitative stage), a semi structured interview protocol was derived from 2 pilot semi structured interviews and literature review theoretical model. A meso case study (sub cases and individual embedded cases) of a UK Post 1992 university was conducted with 23 semi-structured interviews lasting an hour each. 14 interviews were analysed in rich detail. The major findings depict 251 themes from the qualitative data analysis categorised under 6 main categories. To validated and cross compare the themes, 9 collected interviews were audio listened to verify and validate the findings. In summary, based on stage 1 results, there is a gap in the development programmes provided by HR in HEIs, and MM requirements. Future study in Stage two (quantitative stage), will further explore MM development needs via pilot testing a survey questionnaire in the same post 1992 HEI before disseminating it externally to 141 UK HEIs providers (Gov. UK, 2017) for validation prior to proposing the final development model.
What Mediators Want: A Qualitative Needs Analysis on the Training and Formation of Future Intercultural Mediators

This article presents the results of a sample survey on the training of intercultural mediators working in rescue, primary, and second phases of migrant reception in the Sicilian province of Ragusa. Adopting ethnomethodological and phenomenological approaches (Moustakas 1994 Creswell 2013: 81), the survey focuses on the intercultural mediators’ (henceforth ICMs) perception of the qualifications, experience, and skills they believe are necessary to carry out their work efficiently. A sample of 10 ICMs with different experiential and educational backgrounds responded to open ended questionnaires shedding light on the ways in which they experienced the shared phenomenon of mediating in contexts of emergency arrivals in Italy and their preparedness for such work. Informants included graduates in “Scienze per la mediazione interculturale” from the University of Catania’s School of Modern Languages in Ragusa and ICMs who had attended a vocational course at the Il Centro Mediterraneo di Studi e Formazione Giorgio La Pira in Pozzallo. To gain further insights, in-depth semi-structured interviews were then carried out with six of the ICMs who had responded to the questionnaires, and with the course directors at the above-mentioned institutions. The study aims to contribute to the ongoing debate on the status of the intercultural mediator in Italy, both legally and ontologically. Most crucially, however, the research attempts to understand what intercultural mediators feel they need in terms of training and education, particularly for those who work in the field of the reception and integration of migrants coming from the African continent. 1. Positionality and Paradigms – the research rationale This pilot study addresses two research aims: firstly, to investigate the status quo on intercultural mediator (ICM) training in and around the
Transcriptomic analysis of effects of 1-methylcyclopropene (1-MCP) and ethylene treatment on kiwifruit (Actinidia chinensis) ripening

Ethylene (ET) is a gaseous phytohormone with a crucial role in the ripening of many fruits, including kiwifruit (Actinidia spp.). Meanwhile, treatment with 1-methylcyclopropene (1-MCP), an artificial ET inhibitor delays the ripening of kiwifruit. The objective of this study was to determine the effect of ET and 1-MCP application during time-course storage of kiwifruit. In addition, we aimed to elucidate the molecular details underlying ET-mediated ripening process in kiwifruit. For this purpose, we conducted a time-course transcriptomic analysis to determine target genes of the ET-mediated maturation process in kiwifruit during storage. Thousands of genes were identified to be dynamically changed during storage and clustered into 20 groups based on the similarity of their expression patterns. Gene ontology analysis using the list of differentially expressed genes (DEGs) in 1-MCP-treated kiwifruit revealed that the identified DEGs were significantly enriched in the processes of photosynthesis metabolism and cell wall composition throughout the ripening process. Meanwhile, ET treatment rapidly triggered secondary metabolisms related to the ripening process, phenylpropanoid (e.g. lignin) metabolism, and the biosynthesis of amino acids (e.g. Phe, Cys) in kiwifruit. It was demonstrated that ET biosynthesis and signaling genes were oppositely affected by ET and 1-MCP treatment during ripening. Furthermore, we identified a ET transcription factor, AcEIL (Acc32482) which is oppositely responsive by ET and 1-MCP treatment during early ripening, potentially one of key signaling factor of ET- or 1-MCP-mediated physiological changes. Therefore, this transcriptomic study unveiled the molecular targets of ET and its antagonist, 1-MCP, in kiwifruit during ripening. Our results provide a useful foundation for understanding the molecular details underlying the ripening process in kiwifruit.
Word Distinctivity – Quantifying Improvement of Topic Modeling Results from N-Gramming ∗

: • Text data cleaning is an important but often overlooked step in text mining because it is difﬁcult to quantify the contribution. Therefore, we propose the word distinctivity to measure the improvement of topic modeling results from n-gramming, which preserves special phrases in a corpus. The word distinctivity evaluates the signal strength of a word’s topic assignments, and a high distinctivity means a high posterior probability for the word to come from a certain topic. We implemented the latent Dirichlet allocation for topic modeling, and discovered that some special phrases show an increase in word distinctivity, reducing uncertainty in topic identiﬁcation.
Egalitarian redistribution in the era of hyper-globalization

Two traditional theorems of welfare economics posit a trade-off between a government redistribution targets and efficiency. We propose a third ‘claim’ of welfare economics, stating that in closed economies the actual efficiency costs associated with redistribution are small. We then examine the claim in the current phase of ‘hyper-globalization’. On the one hand, a race-to-the-bottom in taxation restricts the capacity to tax high-earners and the associated brain drain may affect a country’s long-run growth. On the other hand, demand for social insurance should be particularly high in an open economy, especially with advancing digitalization. Xenophobic sentiments may, however, offset this demand. We also discuss the impact of globalization on wage equalization and productive efficiency. We conclude against the idea that the welfare state is intrinsically unable to carry out its redistributive function in an era of globalization. However, its strategies and tools of intervention must be rethought.
Wasserstein Measure Coresets.

The proliferation of large data sets and Bayesian inference techniques motivates demand for better data sparsification. Coresets provide a principled way of summarizing a large dataset via a smaller one that is guaranteed to match the performance of the full data set on specific problems. Classical coresets, however, neglect the underlying data distribution, which is often continuous. We address this oversight by introducing Wasserstein measure coresets, an extension of coresets which by definition takes into account generalization. Our formulation of the problem, which essentially consists in minimizing the Wasserstein distance, is solvable via stochastic gradient descent. This yields an algorithm which simply requires sample access to the data distribution and is able to handle large data streams in an online manner. We validate our construction for inference and clustering.
Nonlinear optics in a high-index of refraction material

Nonlinear response in a material increases with its index of refraction as $n^4$. Commonly, $n \sim$ 1 so that diffraction, dispersion, and chromatic walk-off limit nonlinear scattering. Ferroelectric crystals with a periodic 3D polarization structure overcome some of these constraints through versatile Cherenkov and quasi-phase-matching mechanisms. Three-dimensional self-structuring can also lead to a giant broadband refraction \cite{DiMei2018}. We here perform second-harmonic-generation experiments in KTN:Li with $n>26$. Enhanced response causes wavelength conversion to occur in the form of bulk Cherenkov radiation without diffraction and chromatic walk-off, even in the presence of strong wave-vector mismatch and highly focused beams. The process occurs with an arbitrarily wide spectral acceptance, more than 100 nm in the near infrared spectrum, an ultra-wide angular acceptance, up to $\pm 40^{\circ}$, with no polarization selectivity, and can be tuned to allow bulk supercontinuum generation. Results pave the way to highly efficient versatile and adaptable nonlinear optical devices with the promise of single-photon-to-single-photon nonlinear optics.
Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space

To analyze high-dimensional and complex data in the real world, generative model approach of machine learning aims to reduce the dimension and acquire a probabilistic model of the data. For this purpose, deep-autoencoder based generative models such as variational autoencoder (VAE) have been proposed. However, in previous works, the scale of metrics between the real and the reduced-dimensional space(latent space) is not well-controlled. Therefore, the quantitative impact of the latent variable on real data is unclear. In the end, the probability distribution function (PDF) in the real space cannot be estimated from that of the latent space accurately. To overcome this problem, we propose Rate-Distortion Optimization guided autoencoder. We show our method has the following properties theoretically and experimentally: (i) the columns of Jacobian matrix between two spaces is constantly-scaled orthonormal system and data can be embedded in a Euclidean space isometrically; (ii) the PDF of the latent space is proportional to that of the real space. Furthermore, to verify the usefulness in the practical application, we evaluate its performance in unsupervised anomaly detection and it outperforms current state-of-the-art methods.
Regulations of Regenerative Medicine Including Clinical Application of iPS Cells in Japan

Clinical studies of regenerative medicine using induced pluripotent stem (iPS) cells have recently been performed, especially in Japan. To promote regenerative medicine research using iPS cells, the related laws have been enacted in Japan, leading to the use of other bioresources. Here, we overview the legislation of regenerative medicine. In parallel with this legislation, Kyoto University Hospital and the Center for iPS Cell Research and Application (CiRA) at Kyoto University, Japan, have rapidly established a bioresource stocking system for the purpose of clinical study and therapy using iPS cells. Kyoto University Hospital and CiRA are now preparing for the use of stocked iPS cells and other bioresources based on joint research contracts between Kyoto University and external institutions.
Progress and challenges in directing the differentiation of human iPSCs into spinal motor neurons

Motor neuron (MN) diseases, including amyotrophic lateral sclerosis, progressive bulbar palsy, primary lateral sclerosis and spinal muscular atrophy, cause progressive paralysis and, in many cases, death. A better understanding of the molecular mechanisms of pathogenesis is urgently needed to identify more effective therapies. However, studying MNs has been extremely difficult because they are inaccessible in the spinal cord. Induced pluripotent stem cells (iPSCs) can generate a theoretically limitless number of MNs from a specific patient, making them powerful tools for studying MN diseases. However, to reach their potential, iPSCs need to be directed to efficiently differentiate into functional MNs. Here, we review the reported differentiation protocols for spinal MNs, including induction with small molecules, expression of lineage-specific transcription factors, 2-dimensional and 3-dimensional cultures, as well as the implementation of microfluidics devices and co-cultures with other cell types, including skeletal muscle. We will summarize the advantages and disadvantages of each strategy. In addition, we will provide insights into how to address some of the remaining challenges, including reproducibly obtaining mature and aged MNs.
Remote sensing inversion of the Zabuye Salt Lake in Tibet, China using LightGBM algorithm

The Zabuye Salt Lake in Tibet, China is the only salt lake in the world that contains natural crystalline lithium carbonate. The grade and spatial distribution of mineral resources are of great importance to the development and utilization of salt lake mineral resources. The use of remote sensing technology for salt lakes observations can overcome the disadvantages of traditional station observations, such as spatial discontinuity, high time consumption, and high labor costs. In addition, machine learning algorithms can efficiently analyze the information from remote sensing data. In this study, Landsat-8 remote sensing image data and the Light Gradient Boosting Machine (LightGBM) algorithm were used to perform inversions of the depth, salinity, and lithium concentration of the Zabuye Salt Lake. Moreover, the water volume, total salinity, and total lithium content of Zabuye Salt Lake in 2000 and 2017 were estimated, and the distribution of mineral resources and changes during the study period were analyzed. The results show that the water depth and volume of the entire lake increased sharply in 2017, resulting in a decrease in salinity and lithium concentration in the lake. Due to the inflow from the surrounding dry salterns, the South Lake experienced a relatively small change. Furthermore, the amount of lithium resources in North Lake decreased significantly in 2017 compared to 2000, possibly due to higher temperatures during the month of observation, which led to precipitation of lithium carbonate. Our study proves the feasibility and accuracy of the LightGBM machine learning algorithm for rapid inversion of salt lakes, which provides technical insight into remote sensing inversion of other mineral resources in salt lakes. Thus, the development of remote sensing technology in recent years can provide increasingly detailed assessments of salt lake resources in the future.
First cross-border outbreak of foodborne botulism in the European Union associated with the consumption of commercial dried roach (Rutilus rutilus)

Botulism outbreaks due to commercial products are extremely rare in the European Union. Here we report on the first international outbreak of foodborne botulism caused by commercial salt-cured, dried roach (Rutilus rutilus). Between November and December 2016, an outbreak of six foodborne botulism type E cases from five unrelated households was documented in Germany and Spain. The outbreak involved persons of Russian and Kazakh backgrounds, all consumed unheated salt-cured, dried roach—a snack particularly favored in Easter-European countries. The implicated food batches had been distributed by an international wholesaler and were recalled from Europe-wide outlets of a supermarket chain and other independent retailers. Of interest, and very unlike to other foodborne disease outbreaks which usually involves a single strain or virus variant, different Clostridium botulinum strains and toxin variants could be identified even from a single patient's sample. Foodborne botulism is a rare but potentially life-threatening disease and almost exclusively involves home-made or artisan products and thus, outbreaks are limited to individual or few cases. As a consequence, international outbreaks are the absolute exception and this is the first one within the European Union. Additional cases were likely prevented by a broad product recall, underscoring the importance of timely public health action. Challenges and difficulties on the diagnostic and epidemiological level encountered in the outbreak are highlighted.
Relationship between changes in microbiota induced by resveratrol and its anti-diabetic effect on type 2 diabetes

Although a general healthy gut microbiota cannot be defined due to numerous internal and external individual factors, such as sex, age, ethnicity, genetics, environment, diet and drugs affect its composition, certain microbial species and gut microbiota compositions seem to be related to the progression of insulin resistance to type 2 diabetes, as well as the development of microvascular and macrovascular complications of diabetes. The present review aimed at gathering the reported information describing how resveratrol induced changes in microbiota composition can mediate the positive effects of this polyphenol on glucose homeostasis under type 2 diabetic conditions, both in animals and humans. Based on the fact that some changes observed in the gut microbiota of type 2 diabetic animals and patients are reversed by resveratrol treatment, and taking into account that some resveratrol mediated changes in gut microbiota composition are similar to those induced by anti-diabetic drugs such as metformin, it can be proposed that four genera, Alistipes, Allobaculum, Desulfovibrio and Blautia could be involved in the benefits of resveratrol on glycameic control. Nevertheless some limitations are observed in this research field: (a) the number of studies analyzing both the effects of resveratrol on glucose homeostasis and microbiota composition in the same cohort of animals, in order to know the potential involvement of microbiota in the anti-diabetic effects of this phenolic compound, are very scarce and practically inexistent in the case of humans. , (b) the studies present inconsistencies concerning the effects of resveratrol on gut microbiota changes, (c) the experimental design used do not allow the researchers to establish a causal relationship between the changes in microbiota and the anti-diabetic effect, in the vast majority of the studies, (d) the knowledge about the role of each type of bacteria on glycaemic control is not sufficient so far.
Full-length transcriptome sequencing reveals the molecular mechanism of monoterpene and sesquiterpene biosynthesis in Cinnamomum burmannii

Essential oil of Cinnamomum burmannii is rich in monoterpenes and sesquiterpenes and is widely used in cosmetics and medicines. Knowledge about the enzymes that catalyze the formation of monoterpenes and sesquiterpenes in C. burmannii is insufficient. Therefore, anatomy observation of C. burmannii at the four developmental stages (7 days, CBS1; 14 days, CBS2; 21 days, CBS3, and 28 days, CBS4) were conducted to elucidate the origins of essential oil production. Twelve full-length transcriptomes of C. burmannii leaves at the four stages were generated using Oxford Nanopore Technologies. GC-MS analysis revealed 15 monoterpene and sesquiterpenes dramatically increased from CBS1 to CBS4. A weighted correlation network analysis (WGCNA) in association and differentially expressed genes across four developmental stages were performed. A total of 44 differentially expressed genes (DEGs) were involved in terpenoid syntheses during leaf development. Among them, the DEGs of the mevalonate acid (MVA) pathway were predominantly expressed at CBS1, while those of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway showed increased expression from CBS2 to CBS4. Besides, fourteen genes were associated with monoterpene synthesis and nine with sesquiterpene synthesis. Functions of these DEGs were further predicted with regard to gene expression profile and phylogenetic relationship with those characterized in previous studies. In addition, 922 long noncoding RNAs (lncRNAs) were detected, of which twelve were predicted to regulate monoterpene and sesquiterpene biosynthesis. The present study provided new insights the molecular mechanisms of monoterpenoid and sesquiterpenoid syntheses of C. burmannii.
Supply Chain Network Analytics Guiding Food Regulatory Operational Policy

Food adulteration poses a serious threat to public health. The U.S. Food and Drug Administration (FDA) has a major role in maintaining food safety in the U.S. through various activities including sampling of imported shipments and site inspections. However, resource constraints limit the number of these interventions, making risk-based allocation essential to ensure effectiveness. This paper aims to develops a data-driven, risk analytics approach to identify high-risk firms importing food (consignees). Leveraging supply chain analytics, based on shipment history and other data sources, network features are constructed to model risk, specifically predicting which consignees are likely to fail FDA site inspections. The approach is applied to consignees of shrimp, a product with frequent food safety problems. The main findings are that supply chain network complexity, and website network engagement, are predictive of risk. For instance, firms that import a more unusual portfolio of products, as measured through subgraph modularity on a product network graph, are more likely to fail site inspections. The results suggest that network-based risk analytics could significantly improve the effectiveness of regulatory activities related to food supply chains, and increase the "hit rate'' for failed site inspections by up to 42.1%.