Miracle-dz/UniFAR-FTUs huggingface dataset:
Harvesting of Arthrospira platensis with helicoidal and straight trichomes using filtration and centrifugation

ABSTRACT Arthrospira is the most widely cultivated strain of all microalgae and cyanobacteria. Arthrospira forms helical trichomes that, under certain circumstances, can switch to a straight morphology. This study compared harvesting using filtration and centrifugation between helical and straight Arthrospira strains. Filtration using woven nylon membranes is the most commonly used harvesting method in the industry. Gravity filtration using nylon membranes resulted in a high retention efficiency for both strains, but the filtration flux was very low for the straight strain. Pumped filtration resulted in an increase in the filtration flux for both strains (12 to 20 m3 m−2 h−1) but in a strong decline in the retention efficiency for the straight Arthrospira strain. The nominal pore size of the woven nylon membranes had only a minor influence on the harvesting efficiency. Centrifugation yielded a high harvesting efficiency and a solid pellet at relatively low g forces (4000 g) for the straight strain, but efficiency was low even at high g forces for the helical strain. These results illustrate the importance of selecting the most appropriated harvesting methodology depending on Arthrospira strains’ morphology. While the helical strain could be easily harvested using filtration, it is preferably to use centrifugation at low g force for the straight strain.
Estimation of body weight of Sparus aurata with artificial neural network (MLP) and M5P (nonlinear regression)-LR algorithms.

In this study, morphometric features such as total length, standard length, and fork length obtained from a total of 321 Sparus aurata species, including 164 females and 157 males, captured between 2012-2013 from Iskenderun Bay were used as input value, while weight was used as an output value. The Artificial Neural Network (MLP-Multi Layer Perceptron) as well as the M5P algorithm and Linear Regression (LR) algorithm from version 3.7. 11 of the WEKA Program were applied. When coefficients of correlation were assessed, the MLP algorithm for males, females and the total were calculated as 0.9686, 0.9605 and 0.9663, respectively; the M5P algorithm for males, females and the total were calculated as 0.9722, 0.9596 and 0.9735, respectively; and the LR Model for males, females and the total were calculated as 0.9777, 0.9498 and 0.9473, respectively. With respect to the Mean Absolute Error (MAE) calculations, the MLP algorithm MAE values for males, females and the total were calculated as 2.94, 2.57 and 2.7074, respectively; the M5P algorithm MAE values for males, females and the total were calculated as 2.400, 2.641 and 2.157, respectively; and the LR Model MAE values for males, females and the total were calculated as 3.217, 2.811 and 3.11, respectively. It can also be concluded from the study that, in order to predict ANN interactions Nonlinear Regression model is more effective and access a better performance than the conventional models.
Highly reliable, targeted photothermal cancer therapy combined with thermal dosimetry using indocyanine green lactosome

Indocyanine green (ICG) is a near-infrared light-absorbing substance. Thus, when a tumor in which ICG has accumulated is irradiated with a near-infrared (NIR) laser, only the tumor can be heated by a photothermal reaction. We developed ICG lactosome, a novel drug delivery system (DDS) composed of polymeric micelles and ICG that shows selective accumulation in tumor based on an enhanced permeability and retention (EPR) effect. We showed that ICG lactosome accumulated in a tumor by using an intradermal tumor mouse model of a murine colon cancer cell line (Colon26) transfected with Nano lantern luminescent protein (NLC26). Two days after the administration of ICG lactosome, the tumor was irradiated with an 808-nm diode-laser while monitoring tumor temperature. The results showed that the treated tumors were cured when the peak of tumor temperature during NIR irradiation reached 43°C or higher. To verify these results, photothermal therapy (PTT) using ICG lactosome was carried out using a newly developed system that can control the temperature at the NIR irradiation site at a constant level. All of the tumors that had been kept at 43°C during irradiation were cured, while 2 of 5 tumors that had been kept at 42°C were not cured, and none of tumors that had been kept at a temperature below 41°C were cured. ICG lactosome-assisted PTT combined with thermal dosimetry is a highly reliable method for cancer treatment and may afford further clinical opportunities for PTT.
Respiratory complications and 30-day unplanned hospital readmissions in patients with epilepsy.

Background To help mitigate the burden of health care on US economy, public policymakers and health care legislation have been focusing on reducing hospital readmissions. Respiratory complications have been identified among the commonest of adverse events in neurologic patients. The goal of our study was to better understand respiratory complications and their contribution to rehospitalizations in patients with seizures. Methods We used the 2013 Nationwide Readmission Database to analyze unplanned 30-day readmission rate (30RR). The study population comprised of patients with index hospital discharge diagnosis of generalized convulsive epilepsy and status epilepticus. Patients under 18 years of age, who died during hospitalization or who had missing demographic data, were excluded. Patients hospitalized in December were also excluded due to lack of 30-day follow-up. The primary outcome of interest was 30-day readmission. The causes of readmission were determined by corresponding International Classification of Diseases, Ninth Revision, Clinical Modification codes. Results The 30RR was highest in patients with index hospitalization discharge diagnosis of status epilepticus, followed by generalized convulsive epilepsy (intractable), followed by generalized convulsive epilepsy (nonintractable). While seizure was the most common reason for readmission, contribution of respiratory complications to readmissions was 7.85%, 12.39%, and 6.93%, respectively. Pneumonia/aspiration pneumonitis and respiratory insufficiency accounted for the majority of the readmissions in all subgroups. Conclusions Respiratory complications are the leading nonseizure cause of 30-day unplanned readmissions in patients with generalized convulsive epilepsy and status epilepticus. Further research on identifying appropriate interventions to reduce readmissions from respiratory causes may improve outcomes for patients in these epilepsy subgroups.
Biological and Biochemical profiling of commercially available fish species along Mandapam coast, Tamil Nadu, India

This study was conducted to determine the biological and biochemical profiling of selected marine fishes along the Mandapam coast of India. The crude protein content of Penaeus indicus, Tylosurus crocodilus and Lethrinus harak was reported to have 61.33 ± 0.28%, 60.16 ± 0.28% and 59.30 ± 0.26% respectively. The total lipid content was comparatively low, ranging from 9.83 ± 0.76% in T. crocodilus to 13.20 ± 0.20% in P.indicus. Among the fatty acid (C15:1) cis-10-pentadecenoic acid ranging from 21.45% in L.harak to 24.4% in T.crocodiles. Although these fish contained reasonable amounts of essential PUFA such as docosahexaenoic, eicosapentaenoic and arachidonic acids. The eicosapentaenoic acid and docosahexaenoic acid as the fraction of the total fatty acids was high (EPA) 0.75% 7.09% and (DHA) 0.37% 4.9%. The polyunsaturated fatty acid/highly unsaturated fatty acid content ranged from 38.9% in P.indicus to 43.8% in T.crocodilus. The trace metal concentrations among the fishes were generally low. These fishes contained appreciable levels of Omega-3 & 6 PUFA fatty acids and beneficial minerals suggesting that these fishes could be used as a source of healthy diet for humans. These findings might be useful for nutritionists and fish consumers to choose their choice of fishes for their betterment.
Improvement of Motor and Sensory Neuron Survival with N-acetyl cysteine after Peripheral Nerve Injury

Background : Nerve transfers require for the donor nerve to be injured, either partially or completely, in order to guide regenerating axons into new targets. Axon regeneration and recovery after nerve grafting and transfer may be limited by retrograde neuronal death after injury. N-acetyl cysteine (NAC) and acetyl-L-carnitine (ALC) improve survival of neurons after adult nerve injury but it is unknown whether they improve survival after paediatric or neonatal injury when neurons are most susceptible to retrograde neuronal death. Our objective is to examine whether NAC or ALC treatment improves survival of neonatal motor or sensory neurons in a rat model of neonatal nerve injury. Methods : Rat pups received either a sciatic nerve crush or transection injury at postnatal day 3 and were then randomized to receive either intraperitoneal vehicle (5% dextrose), NAC (750 mg/kg) or ALC (300 mg/kg) once or twice daily. Four weeks after injury, surviving neurons were retrograde-labeled with 4% Fluorogold. The lumbar spinal cord and L4/L5 dorsal root ganglia were then harvested and sectioned to count surviving motor and sensory neurons. Results : Transection and crush injuries resulted in significant motor and sensory neuron loss, with transection injury resulting in significantly more retrograde neuron death. High-dose NAC (750 mg/kg twice daily) significantly increased motor neuron survival after neonatal sciatic nerve crush and transection injury. Neither NAC nor ALC treatment improved sensory neuron survival. Conclusions : Proximal neonatal nerve injuries produce significant retrograde neuronal death after injury. Treatments improving motor and sensory neuron survival after nerve injury may improve recovery after nerve transfers or nerve grafting.
Control of Septoria tritici blotch by winter wheat cultivar mixtures: Meta-analysis of 19 years of cultivar trials

Wheat is the most commonly grown cereal crop in Europe and in major parts the most yield limiting disease is Septoria tritici blotch (STB). Currently, the control of the disease depends on cultivar resistance and significant input of fungicides. The impact of using mixtures of elite cultivars as an alternative was investigated through a meta-analysis based on trial data from the Danish national cultivar testing. The cultivar testing includes a four-way cultivar mixture every year and in these trials STB severity and yield have been monitored at multiple locations between 1995 and 2017. Results from 19 years of cultivar testing trials provided a data set for 406 trials from which the effect of mixtures was evaluated. The meta-analysis revealed that cultivar mixtures reduced STB severity with 10.6% and increased yields with 1.4% across all trials. The effects were greatest in untreated trials where STB severity was reduced with 17% and yields increased with 2.4%. The mixtures did not only perform better than the average of their component cultivars grown as pure stand, they also performed better than the average of the four most grown cultivars in a given year. No relationship was found between disease pressure or location and the performance of the mixtures. The mixtures included in the cultivar testing were not designed to control STB and the results are therefore perceived as a baseline to the attainable disease control from mixtures. The use of cultivar mixtures is relevant for low input farming systems, but can also contribute to disease control in intensive farming systems. Cultivar mixtures have the potential to minimise dependency on fungicides as an important element in integrated pest management.
Robust Neural Networks are More Interpretable for Genomics

Deep neural networks (DNNs) have been applied to a variety of regulatory genomics tasks. For interpretability, attribution methods are employed to provide importance scores for each nucleotide in a given sequence. However, even with state-of-the-art DNNs, there is no guarantee that these methods can recover interpretable, biological representations. Here we perform systematic experiments on synthetic genomic data to raise awareness of this issue. We find that deeper networks have better generalization performance, but attribution methods recover less interpretable representations. Then, we show training methods promoting robustness – including regularization, injecting random noise into the data, and adversarial training – significantly improve interpretability of DNNs, especially for smaller datasets.
A Review on Strategies to Manage Physician Burnout

Physician burnout is an emerging condition that can adversely affect the performance of modern-day medicine. Its three domains are emotional exhaustion, depersonalization, and a sense of reduced accomplishment among physicians, with the Maslach Burnout Inventory (MBI) being the gold standard questionnaire used to scale physician burnout. This concern not only impacts physicians but the entire healthcare system in general. There is growing awareness regarding the mental health of physicians and the consequences faced by the healthcare system as a result of burnout. According to a recent study, more than 50% of physicians reported suffering from at least one burnout symptom. In this review article, we aim to identify the causes leading to burnout, its impact on physicians, and hospital management as well as interventions to reduce this work-related syndrome. Some contributing factors leading to burnout are poor working conditions with long work shifts, stressful on-call duties, lack of appreciation, and poor social interactions. Burnout can lead to adverse consequences, such as depression, substance use, and suicidal ideation in physicians and residents. This can result in poor patient care increasing total length of stay, re-admissions, and major medical errors. Due to increased scrutiny of patient and healthcare costs, along with increased lawsuits as a result of major medical errors, it is crucial for both the hospital management and physicians to recognize and address burnout among physicians. Comprehensive professional training such as Cognitive behavioral therapy (CBT), stress-reducing activities such as mindfulness and group activities, and strict implementation of work-hour limitations recommended by Accreditation Council for Graduate Medical Education (ACGME) for residents are a few methods that may help to manage burnout and increase productivity in hospitals.
Changing the Curriculum to Problem-Based and Project-Based Learning

Problem based and project based learning (PBL) models are implemented all over the world in various versions at curriculum or course level. Due to this development, the conceptual understanding of PBL has become more diverse and sometimes confusing. This chapter summarizes the conceptual work done by the UNESCO Chair in PBL in engineering education in order to define PBL as a set of core learning principles that can be applied in practice. The PBL learning principles are formulated within three aspects: learning, social, and content of study. Furthermore, the chapter contains a PBL curriculum model, which can be used for analysis and development of the curriculum or single courses. Seven elements are identified as important for the planning and implementation of PBL learning principles, and for each of the elements there are several choices to be made. Finally, the chapter presents concrete advice for utilization of PBL learning principles in the curriculum or in the single course. DOI: 10.4018/978-1-4666-1809-1.ch003
A novel approach to the integration of simulation and implementation to digital signal processing systems

Integrating the simulation and implementation of complex digital signal processing systems based on block diagram oriented simulation and code generation is described. The basic concept consists of a generic, i.e., reusable, block diagram with different underlying semantics. This allows the generation of software adapted to the special needs of both simulation and implementation. In order to achieve application-specific implementations, the code generator supports tradeoffs between implementation constraints such as code size, throughput, or latency. Therefore, a wide spectrum of different optimization strategies has been incorporated in the code generator. <<ETX>>
Performance management in SONET-based multi-service networks

A performance management scheme is introduced to satisfy end-to-end performance requirements of multiclass services, using a nested control scheme. The network-level controller periodically computes an optimal bandwidth allocation policy for the entire network, and downloads parameters to the call- and packet-level controllers to regulate network traffic accordingly. The call-level controller limits SONET (synchronous optical network) pipe fills, exercises access-control fairly across source destination pairs, and is based on profitability across call classes. The packet-level controller provides congestion-free high-speed data transmission within the SONET pipes designated and realized by the network and call controllers, respectively. <<ETX>>
Veterinary Microbiology and Microbial Disease.

Knowing what and how much to teach the modern veterinary student about pathogenic bacteriology and virology is a challenging topic. I would give this book a “B+” or “A-”. It has many similarities to Hirsh and Zee's Veterinary Microbiology (2nd edition), to which it is a more up-to-date superior. It seems extraordinary, however, that the same publisher (Blackwell Scientific) should publish 2 very similar books. This book is an introductory text in veterinary microbiology and microbial disease for veterinary undergraduates, written by faculty members at University College, Dublin. It is divided into 6 sections, an introduction to bacteriology, a large section of systematic pathogenic bacteriology, mycology, an introduction to virology, a large section on systematic pathogenic virology, and a final section on microbial agents and disease production (which has some slightly quirky choice chapters). The book is well laid out and well illustrated with line drawings. It has excellent tables. Students will find it useful for its clear organization and introductory overview nature, as well as its currentness of nomenclature. It is a little heavy on biochemical and related differentiating characteristics of important bacteria and too superficial about some of the important infections it describes. However, reasonably good thumbnail sketches are given of the essential features of the infections discussed, which a student encountering them for the first time will find generally helpful. This text is a bit weak on Helicobacter, Campylobacter, and nonsporeforming anaerobes. With a view to help today's veterinary student who is struggling with being overwhelmed by information, the book uses “boxes” of key concepts relating to different groups of bacteria or viruses. Some of these miss key points, while emphasizing what seems trivial. For example, is it really a key point about Brucella that they are urease-positive and mostly oxidase-positive? How memorable is this for veterinary students as an encapsulated feature of this genus? Each chapter has a list of references cited and a list of suggested supplemental reading. This is probably wasted space, since abstracts of the primary literature are available to anyone with Internet access to PubMed within days of it being published. A particular strength of the book is its introductory or overview chapters; the chapters on disinfection and on other aspects of disease control, and on infection and immunity, show great teachers at work. There are excellent illustrative figures and tables explaining some of the fundamental concepts of infectious disease and its outcomes, which will be of use to teachers and students alike. Overall, this is a book that can be recommended with confidence to veterinary students and teachers as a good introductory overview of veterinary microbiology. I will particularly value it on my bookshelf for some of the overview figures and for some of the summary tables.
Examining Legibility of the Letter "e" and Number "0" Using Classification Tree Analysis

Summary. This study investigated the legibility of onscreen typefaces and the influence of individual character features on correct identification. Specific attributes of alphanumeric characters and symbols shown to be the least legible were measured and analyzed using a statistical method called classification tree analysis. Results from this analysis for the letter "e" and the number zero are discussed.
Psychovisual correlations with multifractal measures for wavelet and wavelet packet progressive image transmission

In an effort to develop a quantitative measure for image quality, this paper looks for psychovisual correlations of image quality to multifractal measures. Image metrics such as peak signal-to-noise ratio are not well suited as perceptual indicators and other techniques are primarily limited to just noticeable differences which limit their use in general. It is desirable to have image quality metrics for progressive image transmission that are more general and can evaluate images produced during a progressive image transmission, from the worst image reconstruction step all the way to the final perfect image. We focus on how the Renyi (1955) dimension spectrum changes as more wavelet and wavelet packet coefficients are included in a progressive image transmission. Mean opinion score (MOS) results serve as an additional basis for analyzing how the progressive image transmission affect the Renyi dimension spectrum. While this paper does not give a final answer to what the best metric would be for image quality in a progressive image transmission, it does attempt to link perceptual quality with multifractal measures.
Temporal sequence classification by memory neuron networks

A recurrent connectionist architecture, called memory neuron network (MNN), is applied for classification of temporal sequences. The network architecture allows a learnable parametric representation of the activation history of the units. It has been shown that the network is generalized version of network with time-delays. The learning protocol has been developed to train a collection of such networks as discriminant models for classes of temoral sequences. The design is tested in classification of voiced plosives /B/,/D/,/G/. Due to continuous movement of the articulators, the spectral characteristics of the speech signal change during transitions from one phoneme to the other. MNN has been used to model this dynamic behavior during the transitions from plosive sounds to vowels. <<ETX>>
A Skip-mode Coding for Distributed Compressive Video Sensing

분산 압축 비디오 센싱 (DCVS) 기술은 압축센싱 및 분산 비디오 부호화 기술의 결합을 통해 저 비용의 샘플링을 실현하는 새로운 패러다임이다. 본 논문에서는 프레임 간 높은 시간 상관성을 활용한 DCVS에서의 스킵모드 부호화 방법을 제안한다. 제안하는 방법은 일정조건을 만족하는 비 키-프레임에 대한 측정값을 복호화기에 전송하지 않아도 시간적 보간법을 통해 해당 비 키-프레임의 복원이 가능하도록 하여 율-왜곡 측면에서 좋은 압축 성능을 보장한다. 이와 더불어, 더 나은 시간적 보간을 위하여 계층적 구조를 사용하는 방법을 제안한다. 실험 결과, 제안하는 스킵모드 부호화 방법은 약간의 PSNR 감소에 비해 매우 높은 측정율 절약이 되는 것을 확인하였다. 또한, 제안하는 방법을 높은 시간 연관성을 갖는 비디오 영상에 적용할 경우, 복호화기의 연산 복잡도가 평균 43.75% 감소하는 것을 확인하였다.