Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual Infection of an Open Fracture Caused by Mycobacterium setense and Clostridium celerecrescens

Infections caused by Mycobacterium setense or Clostridium celerecrescens are extremely rare. In this report, for the first time a dual infection with these two pathogens is described. An 18-year-old female suffered multiple injuries, including an open comminuted fracture of the right humeral diaphysis after falling from a fifth-floor balcony in January 2019. Five months after the accident, a fistula appeared in the scar, reaching the bone tissue. M. setense and C. celerecrescens were cultured from sinus swabs and subsequently from perioperative samples. The patient was initially treated with a combination of intravenous antibiotics (ATBs): imipenem, amikacin, and ciprofloxacin. One month after the fracture fixation with a titanium nail, C. celerecrescens was again detected; therefore, metronidazole was added to the therapy. A triple combination of oral (PO) ATBs (trimethoprim–sulfamethoxazole, moxifloxacin, and metronidazole) followed, 8 weeks after the initial intravenous therapy. C. celerecrescens was cultured again two times, most recently in November 2019, when surgical debridement was supplemented by the topical administration of cancellous bone impregnated with vancomycin. Signs of bone healing were found at follow-ups and ATB treatment was finished in March 2020 after a total of 9 months of therapy. To this day, there have been no signs of reinfection. This case thus illustrates the need for a combination of systemic and individualized local therapy in the treatment of complicated cases of dual infections with rare pathogens.
Seaweeds in the Oncology Arena: Anti-Cancer Potential of Fucoidan as a Drug—A Review

Marine natural products are a discerning arena to search for the future generation of medications to treat a spectrum of ailments. Meanwhile, cancer is becoming more ubiquitous over the world, and the likelihood of dying from it is rising. Surgery, radiation, and chemotherapy are the mainstays of cancer treatment worldwide, but their extensive side effects limit their curative effect. The quest for low-toxicity marine drugs to prevent and treat cancer is one of the current research priorities of researchers. Fucoidan, an algal sulfated polysaccharide, is a potent therapeutic lead candidate against cancer, signifying that far more research is needed. Fucoidan is a versatile, nontoxic marine-origin heteropolysaccharide that has received much attention due to its beneficial biological properties and safety. Fucoidan has been demonstrated to exhibit a variety of conventional bioactivities, such as antiviral, antioxidant, and immune-modulatory characteristics, and anticancer activity against a wide range of malignancies has also recently been discovered. Fucoidan inhibits tumorigenesis by prompting cell cycle arrest and apoptosis, blocking metastasis and angiogenesis, and modulating physiological signaling molecules. This review compiles the molecular and cellular aspects, immunomodulatory and anticancer actions of fucoidan as a natural marine anticancer agent. Specific fucoidan and membranaceous polysaccharides from Ecklonia cava, Laminaria japonica, Fucus vesiculosus, Astragalus, Ascophyllum nodosum, Codium fragile serving as potential anticancer marine drugs are discussed in this review.
Aislamiento y caracterización bioquímica de la α-glucosidasa II del hongo patógeno Candida albicans

La a-glucosidasa II participa en la ruta de la N-glicosilacion de proteinas. En Candida albi­cans se ha aislado un polipeptido soluble de 47 kDa con actividad de a-glucosidasa II; sin embargo, analisis bioinformaticos indican que la enzima nativa pudiera tener un peso mo­lecular de 100 kDa. En este trabajo se estudio el efecto de inhibidores de proteasas sobre la distribucion intracelular de la a-glucosidasa II. Se demostro que la distribucion intracelular no fue afectada significativamente, pero la actividad de la a-glucosidasa II estuvo asociada a una proteina de 83 o 47 kDa en ausencia o presencia de inhibidores de proteasas, res­pectivamente. La enzima soluble de 83 kDa se purifico por metodos convencionales y se demostro que presenta caracteristicas bioquimicas similares a la enzima de 47 kDa. Estos datos confirmaron que la proteina de 83 kDa es una a-glucosidasa II y sugieren que es precursora de la enzima de 47 kDa previamente descrita.
Extract and Abstract with BART for Clinical Notes from Doctor-Patient Conversations

Reducing the burden of documentation physicians are required to do with speech understanding is a challenging and worthwhile goal with the potential to improve care. When transcripts of doctor-patient conversations are available, automatic summarization with deep neural networks is one promising so-lution to reducing documentation workload. We develop an “extract-and-abstract” approach to automatic generation of the History of Present Illness (HPI) section in clinical notes with BART: we train a classifier on annotated data to predict a clinical section each utterance is most relevant to; we then utilize the trained classifier to select only utterances from conversations relevant to HPI to be considered as input to BART for summarization; we experiment with additional filtering methods on selected utterances to further reduce input truncation due to the token limit of BART model. Results show that the generated summaries from our approach improve in both ROUGE scores and extracted medical concepts over previously published re-sults. Considering the improvement is achieved with a relatively small set of doctor-patient conversations, we expect further improvement with more labeled data in the future.
Therapeutic Effects and Uses of Ozone in Dentistry: A Systematic Review

ABSTRACT As antibiotic resistance is increasing daily, the desire to treat an infection without causing any harmful effects assumes increasing importance. Ozone gas is a reactive antioxidant. Its role in blood circulation and uplifting immunity is an ideal complement to achieving curative care treatments. Aside from treatments, the therapeutic and biological effects of ozone may have positive results by reducing tooth demineralization, its antimicrobial capabilities rely upon its ability to oxidize, which produces free radicals, and has immediate action on microbes. The usage of ozone in dentistry is recommended for a variety of purposes, which comprises carious lesion treatments, root canal disinfection, post-surgical treatment, tooth bleaching, periodontal problems, prosthodontics, and orthodontics. Ozone has the potential to be a promising alternative therapy in dentistry. However, well-designed research is needed to analyze ozone’s utilization in the field of dentistry to determine its importance from a clinical perspective so that the general public can benefit from it. This systematic review aims to describe the technique in which ozone can be advantageous as well as the many ways of applications of ozone therapy in dentistry.
Analysis of Stiction Effect on the Dynamics of Compressor Suction Valve

A new type compression mechanism named ' Helical Blade Compressor' was presented at Purdue conference in 1992. There showed the design, performance of prototype , and theoretical analysis. Since then, fundamental experiment and theoretical analysis have clarified the phenomenon of the compression process. The gas is compressed in accordance with design theory of Helical Blade Compressor. This paper shows its potential by testing result of compression process against those of the other compression mechanism, rotary, screw, and scroll.
Competency Standardization for Indonesian Tourism Human Resources: Implementation in Education, Training and Competency Certification

The increasing trend of Indonesia's tourism competitiveness has placed it as one of the priority industrial sectors in Indonesia. However, this achievement is not in line with increasing the competitiveness of human resources (HR). The national work competency standardization system (SKKN), which the Indonesian Government has implemented since 2012, has not been effective, and human resources' competitiveness has even shown a negative trend. It is feared that this situation will hamper the growth rate of Indonesia's tourism competitiveness in the future. The purpose of this study is to critically analyze the application of the SKKNI system, which is focused on education, training, and competency certification of Indonesian tourism human resources, to uncover the inhibiting factors for its implementation. This education, training, and competency certification are the main components in the performance of the SKKNI system in Indonesia. The research was carried out by reviewing the relevant literature, analyzing the processes and elements in applying the SKKNI system. Research data is secondary data collected from data sources of Government and non-government institutions and scientific and non-scientific literature available on official government websites and the internet. The research results are then triangulated to get a comprehensive picture and understanding of the application of the SKKNI system. The results showed that the implementation of the SKKN system was effective in increasing the capacity of Indonesian tourism human resources but has a tiny growth Quantitatively. The main obstacle is limited trainer, assessor, facilities, and educational, training, and certification institutions to produce trained and certified human resources of tourism.
Characterization of Three-Dimensional Trophoblast Spheroids: An Alternative Model to Study the Physiological Properties of the Placental Unit

It was postulated that 3D cell culture models more accurately reflect the complex tissue physiology and morphology in comparison to 2D cell monolayers. Currently, there is a shortage of well-characterized and easily maintainable high-throughput experimental models of the human placenta. Here, we characterized three different 3D cultures (e.g., spheroids) derived from trophoblast cell lines and studied their functionality in comparison to primary fetal trophoblasts and placental tissue. The spheroid growth rates of JEG3, BeWo and HTR8/SVneo cell lines were similar among each other and were significantly larger in comparison to primary trophoblast spheroids. All spheroids exhibited migratory properties and shortest distances were registered for JEG3 spheroids. Even though all spheroids displayed invasive capabilities, only the invasive features of HTR8/SVneo spheroids resulted in specific branching. This was in agreement with the invasive properties of the spheroids obtained from primary trophoblasts. Human chorionic gonadotropin production was highest in JEG3 spheroids and only increased when stimulated with cAMP and forskolin in BeWo, but not HTR8/SVneo spheroids. The gene expression analysis confirmed that 3D trophoblast cell cultures and especially HTR8/SVneo spheroids showed considerable similarities with the gene expression profile of primary placental tissue. This study offers a broad characterization of 3D trophoblast spheroids that, in turn, can help in selecting the best model depending on the scientific question that needs to be answered.
A Pilot Analysis on the Efficacy of Multiple Trigger-Point Saline Injections in Chronic Tension-Type Headache: A Retrospective Observational Study

This study aimed to investigate the efficacy of new targeted trigger-point injections (TPIs) using isotonic saline in patients with chronic tension-type headache (CTTH). Of 121 patients with headache who were retrospectively reviewed, 19 were included in this study and were categorized into two groups: those who received TPIs more than four times (group 1); and those who received TPIs less than, or equal to, four times (group 2). The patients received ultrasound-guided isotonic saline injections into the active trigger points once weekly. The primary outcome was an effect on headache intensity, determined using the visual analog scale (VAS), whereas the secondary outcome was an effect on quality of life, evaluated using the Henry Ford Hospital Headache Disability Inventory (HDI). The mean symptom duration of the 19 patients (11 men and 8 women; mean age, 52.5 years; and range, 23–81 years) was 16 months. The most frequently injected muscle was the splenius capitis. Patient demographics were similar between the two groups (p > 0.05). Simple linear regression revealed that symptom duration (p = 0.001) and baseline VAS score (p = 0.009) were significantly associated with the number of injections. At one month after the first injection, the mean VAS and HDI scores in group 2 were significantly lower than those in group 1 (p < 0.05), whereas the scores significantly decreased immediately after the last injection in both groups (p < 0.05). No adverse effects were reported in any patient. Our results indicate that the administration of new targeted TPIs using isotonic saline into the head and neck muscles of patients with CTTH can effectively relieve headache intensity and safely improve their quality of life.
Accent Conversion using Pre-trained Model and Synthesized Data from Voice Conversion

Accent conversion (AC) aims to generate synthetic audios by changing the pronunciation pattern and prosody of source speakers (in source audios) while preserving voice quality and linguistic content. There has not been a parallel corpus that contains pairs of audios having the same contents yet coming from the same speakers in different accents, the authors hence work on a solution to synthesize one as training input. The training pipeline is conducted via two steps. First, a voice conversion (VC) model is constructed to synthesize a training data set, con-taining pairs of audios in the same voice but two different accents. Second, an AC model is trained with the synthesized data to convert a source accented speech to a target accented speech. Given the recognized success of self-supervised learning speech representation (wav2vec 2.0) on certain speech problems such as VC, speech recognition, speech translation, and speech-to-speech translation, we adopt this architecture with some cus-tomization to train the AC model in the second step. With just 9-hour synthesized training data, the encoder initialized by the weight of the pre-trained wav2vec 2.0 model outperforms the LSTM-based encoder.
Cellulose in Foliage and Changes during Seasonal Leaf Development of Broadleaf and Conifer Species

Stable isotope approaches are widely applied in plant science and many improvements made in the field focus on the analysis of specific components of plant tissues. Although technical developments have been very beneficial, sample collection and preparation are still very time and labor-consuming. The main objective of this study was to create a qualitative dataset of alpha-cellulose content of leaf tissues of arboreal species. We extracted alpha-cellulose from twelve species: Abies alba Mill. , Acer pseudoplatanus L. , Fagus sylvatica L. , Larix decidua Mill. , Picea abies (L.) Karst. , Pinus sylvestris L. , Quercus cerris L. , Quercus petrea (Matt.) Liebl. , Quercus pubescens Wild. , Quercus robur L. , Tilia platyphyllos Scop. and Ulmus glabra Huds. While these species show an increase in cellulose yield from bud break to full leaf development, the rates of increase in cellulose content and the duration of the juvenile phase vary greatly. Moreover, the veins display significantly higher alpha-cellulose content (4 to 11%) compared to blade tissues, which reflects their different structural and biochemical functions. A guide for the mass of sample material required to yield sufficient alpha-cellulose for a standard stable isotope analysis is presented. The additional benefits of the assessment of the mass of required sample material are reduced sample preparation time and its usefulness in preparing samples of limited availability (e.g., herbarium material, fossil samples).
Silver Nanoparticle Effects on Antioxidant Response in Tobacco Are Modulated by Surface Coating

The antimicrobial properties of silver and enhanced reactivity when applied in a nanoparticle form (AgNPs) led to their growing utilization in industry and various consumer products, which raises concerns about their environmental impact. Since AgNPs are prone to transformation, surface coatings are added to enhance their stability. AgNP phytotoxicity has been mainly attributed to the excess generation of reactive oxygen species (ROS), leading to the induction of oxidative stress. Herein, in vitro-grown tobacco (Nicotiana tabacum) plants were exposed to AgNPs stabilized with either polyvinylpyrrolidone (PVP) or cetyltrimethylammonium bromide (CTAB) as well as to ionic silver (AgNO3), applied in the same concentrations, either alone or in combination with cysteine, a strong silver ligand. The results show a higher accumulation of Ag in roots and leaves after exposure to AgNPs compared to AgNO3. This was correlated with a predominantly higher impact of nanoparticle than ionic silver form on parameters of oxidative stress, although no severe damage to important biomolecules was observed. Nevertheless, all types of treatments caused mobilization of antioxidant machinery, especially in leaves, although surface coatings modulated the activation of its specific components. Most effects induced by AgNPs or AgNO3 were alleviated with addition of cysteine.
Dynamic Reliability-Aware Virtual Network Embedding for Airborne Tactical Networks

Airborne tactical networks (ATNs) built on network virtualization (NV) can enable efficient information sharing for network-centric warfare by breaking the tight coupling between applications and network infrastructure and thus solving the network ossification problem. With dynamic changes during military missions, the application of virtualization is challenged by the changing demands on network resources when instantiating multiple virtual networks (VNs) on a shared substrate network (SN), known as virtual network embedding (VNE). However, existing dynamic VNE algorithms, mostly designed for wired networks, focus on the dynamic changes of single VN and do not consider the dynamic changes of different VNs. The proper processing of changes of different VNs is beneficial to improve the embedding profits of VNs. On these backgrounds, we investigate the dynamic wireless VNE that processes the dynamic changes of different VNs in the wireless environment of ATNs. A relationship matrix-based dynamic wireless VNE (DWVNE-RM) algorithm is proposed in order to maximize the acceptance ratio of VN requests. The dynamic changes of different VNs are classified into negative changes (requiring resource) and positive changes (releasing resource). Then, the relationship matrix between negative and positive changes is constructed to properly process the resource relationship among different changes in order to improve the acceptance ratio. In addition, the complex interference of ATNs is considered in the mapping or remapping of virtual nodes and links to improve the reliability. Through extensive simulation, DWVNE-RM is compared with multiple existing dynamic algorithms and outperforms over others.
Cohomological methods in transformation groups

Preface 1. Equivalent cohomology of G-CW-complexes and the Borel construction 2. Summary of some aspects of rational homotopy theory 3. Localisation 4. General results on torus and p-torus actions 5. Actions on Poincare duality spaces Appendices References Indexes.
Laser-induced Spin Dynamics in Metallic Multilayers

Electronic excitations in a ferromagnet can trigger ultrafast spin dynamics with potential applications in a speed increase in magnetic recording. The project investigates ultrafast magnetization dynamics, which is driven in metallic layers by ballistic hot electrons. In a ferromagnet these electrons induce a change in the absolute value of the magnetization M through spin-dependent scattering. If the electrons are spin-polarized, scattering at the interface of a noble metal and a ferromagnet results in spin-transfer torque and hence modifies the direction of M. To reveal the underlying mechanisms, we study model systems, which are realized by layers of Au with its large ballistic mean free path and Fe as an itinerant ferromagnet. We aim at understanding ultrafast demagnetization and femtosecond all-optical generation of spin transfer torque effects (excitation of hot electrons with a femtosecond laser). The launched dynamics are probed by magneto-optics in a time-resolved experiment.
Optimal Control of Inverted Pendulum

This report investigates two methods of finding the optimal control of aninverted pendulum with a quadratic cost functional.In the first method a discretisation of a Hamiltonian system is taken as a symplectic Euler-scheme for Newton’s method which is used to find theoptimal control from an initial guess. According to the Pontryagin principle this gives the optimal control, since the solution to a Hamiltonian system gives the optimum to a control problem. The second method uses the matrix Riccati differential equation to find the optimal control for a linearised model of the pendulum.The result was two programs that find the optimal control. The first method’s program demands clever initial guesses in order to converge. The linearised model’s solutions are only valid for a limited area, which turned out to be surprisingly large.
Hierarchical Tagger with Multi-task Learning for Cross-domain Slot Filling

In task-oriented dialog systems, slot filling aims to identify the semantic slot type of each token in utterances. Due to the lack of sufficient supervised data in many scenarios, it is necessary to transfer knowledge by using cross-domain slot filling. Previous studies focus on building the relationships among similar slots across domains by providing additional descriptions, yet not fully utilizing prior information. In this study, we mainly make two novel improvements. First, we improve the hierarchical frameworks based on pre-trained models. For instance, we add domain descriptions to auxiliary information in the similarity layer to enhance the relationships. Second, we improve the independent fine-tuning with multi-task learning by using an auxiliary network, where the domain detection task is deliberately set up corresponding to the domain descriptions. Additionally, we also adopt an adversarial regularization to avoid over-fitting. Experimental results on SNIPS dataset show that our model significantly outperforms the best baseline by 16.11%, 11.06% and 8.77%, respectively in settings of 0-shot, 20-shot and 50-shot in terms of micro F1, which demonstrates our model has better generalization ability, especially for domain-specific slots.