Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Natural Killer Cell and T Cell Responses to Influenza Infection

Influenza viruses have perplexed scientists for over a hundred years. Yearly vaccines limit their spread, but they do not prevent all infections. Therapeutic treatments for those experiencing severe infection are limited; further advances are held back by insufficient understanding of the fundamental immune mechanisms responsible for immunopathology. NK cells and T cells are essential in host responses to influenza infection. They produce immunomodulatory cytokines and mediate the cytotoxic response to infection. An imbalance in NK and T cell responses can lead to two outcomes: excessive inflammation and tissue damage or insufficient anti-viral functions and uncontrolled infection. The main cause of death in influenza patients is the former, mediated by hyperinflammatory responses termed “cytokine storm. ” NK cells and T cells contribute to cytokine storm, but they are also required for viral clearance. Many studies have attempted to distinguish protective and pathogenic components of the NK cell and T cell influenza response, but it has become clear that they are dynamic and integrated processes. This review will analyze how NK cell and T cell effector functions during influenza infection affect the host response and correlate with morbidity and mortality outcomes.
Fertilización con boro y su relación con la producción de frutos sin semilla en mango 'Ataulfo'* Boron fertilization and its relation to the production of seedless fruit in mango 'Ataulfo'

Mexico is the fourth largest producer of mango (Mangifera indica L.) in the world. The Ataulfo cultivar has commercial importance because of its larger shelf life compared to other cultivars; but it has the disadvantage of producing seedless fruits that have no value for export. In order to determine whether the application of boron to soil can reduce the formation of seedless fruit and, improve the nutritional status of the tree, soil applications of boron were made (Solubor) 25, 50 and 100 g of B per tree, after three months after harvest in an orchard eight years old in Tepic, Nayarit. The percentage of seedless fruit, the nutrient concentration in leaves, inflorescences and fruits were evaluated. The nutritional analysis foliar before application of said treatments trees presented nitrogen deficiency. Doses of 50 and 100 g of B decreased by 45 and 35%, respectively, the number of seedless fruit and improved concentration of Ca and B on the plant, and that of B in shoots with inflorescences and leaves at the end of fruit development. The inflorescences concentrated N, P, K and Mg. Ca and B were concentrated in the leaves. The seeds accumulated more N, P, K, Ca and Mg than the
Accuracy Improvement on Learning Vector Quantization (LVQ) Using Exponential Smoothing for Driving Activity Classification

Identification of driving activities is important to find out abnormal driving conditions such as accidents. In this work, identifying driving activities is carried out using the LVQ (Learning Vector Quantization) algorithm. This algorithm creates a prototype that is easily interpreted for experts in each application domain. The dataset for each driving activity is obtained from the accelerometer sensor and the android smart gyroscope. The exponential smoothing method is used in the sensor dataset to improve the accuracy of classification results. The best accuracy is obtained from the classification of the gyroscope sensor dataset after smoothing with an accuracy of 90.429%.
Narrowing Diurnal Temperature Amplitude Alters Carbon Tradeoff and Reduces Growth in C4 Crop Sorghum

Effect of diurnal temperature amplitude on carbon tradeoff (photosynthesis vs. respiration) and growth are not well documented in C4 crops, especially under changing temperatures of light (daytime) and dark (nighttime) phases in 24 h of a day. Fluctuations in daytime and nighttime temperatures due to climate change narrows diurnal temperature amplitude which can alter circadian rhythms in plant, thus influence the ability of plants to cope with temperature changes and cause contradictory responses in carbon tradeoff, particularly in night respiration during dark phase, and growth. Sorghum [Sorghum bicolor (L.) Moench] is a key C4 cereal crop grown in high temperature challenging agro-climatic regions. Hence, it is important to understand its response to diurnal temperature amplitude. This is the first systematic investigation using controlled environmental facility to monitor the response of sorghum to different diurnal temperature amplitudes with same mean temperature. Two sorghum hybrids (DK 53 and DK 28E) were grown under optimum (27°C) and high (35°C) mean temperatures with three different diurnal temperature amplitudes (2, 10, and 18°C) accomplished by modulating daytime and nighttime temperatures [optimum daytime and nighttime temperatures (ODNT): 28/26, 32/22, and 36/18°C and high daytime and nighttime temperatures (HDNT): 36/34, 40/30, and 44/26°C]. After exposure to different temperature conditions, total soluble sugars, starch, total leaf area and biomass were reduced, while night respiration and specific leaf area were increased with narrowing of diurnal temperature amplitude (18 to 2°C) of HDNT followed by ODNT. However, there was no influence on photosynthesis across different ODNT and HDNT. Contradiction in response of foliar gas exchange and growth suggests higher contribution of night respiration for maintenance rather than growth with narrowing of diurnal temperature amplitude of ODNT and HDNT. Results imply that diurnal temperature amplitude has immense impact on the carbon tradeoff and growth, regardless of hybrid variation. Hence, diurnal temperature amplitude and night respiration should be considered while quantifying response and screening for high temperature tolerance in sorghum genotypes and comprehensive understanding of dark phase mechanisms which are coupled with stress response can further strengthen screening procedures.
An Improved Approximation Algorithm for Scheduling Under Arborescence Precedence Constraints

We consider a scheduling problem on unrelated machines with precedence constraints. There are m unrelated machines and n jobs and every job has to be processed non-preemptively in some machine. Moreover, jobs have precedence constraints; specifically, a precedence constraint j ≺ j' requires that job j' can only be started whenever job j has been completed. The objective is to minimize the total completion time. The problem has been widely studied in more restricted machine environments such as identical or related machines. However, for unrelated machines, much less is known. In the paper, we study the problem where the precedence constraints form a forest of arborescences. We present a O((log n)2/(log log n)3)-approximation algorithm - that improves the best-known guarantee of O((log n)2/log log n) due to Kumar et al. [12] a decade ago. The analysis relies on a dual-fitting method in analyzing the Lagrangian function of non-convex programs.
Unsupervised Knowledge Transfer for Object Detection in Marine Environmental Monitoring and Exploration

The volume of digital image data collected in the field of marine environmental monitoring and exploration has been growing in rapidly increasing rates in recent years. Computational support is essential for the timely evaluation of the high volume of marine imaging data, but often modern techniques such as deep learning cannot be applied due to the lack of training data. In this article, we present Unsupervised Knowledge Transfer (UnKnoT), a new method to use the limited amount of training data more efficiently. In order to avoid time-consuming annotation, it employs a technique we call “scale transfer” and enhanced data augmentation to reuse existing training data for object detection of the same object classes in new image datasets. We introduce four fully annotated marine image datasets acquired in the same geographical area but with different gear and distance to the sea floor. We evaluate the new method on the four datasets and show that it can greatly improve the object detection performance in the relevant cases compared to object detection without knowledge transfer. We conclude with a recommendation for an image acquisition and annotation scheme that ensures a good applicability of modern machine learning methods in the field of marine environmental monitoring and exploration.
Information Value of the Segment Reporting in the Polish Energy Sector

Abstract Conventional energy sources dominate in the Polish energy sector, which is a huge risk to meeting environmental protection requirements. Polish energy companies are facing challenges related to meeting the requirements of the European Union and the National Energy Policy. The paper attempts to answer the question whether the ongoing discussion on the future of the energy sector, dealing with such issues as development of renewable energy sources is reflected in the annual financial reports of companies listed on the Warsaw Stock Exchange and covered by the WIG_ENERGY index. This study contributes to the extant literature on financial disclosures in several ways. First, the examination of compliance of segment reporting of selected companies listed on the Polish stock exchange with International Reporting Standards (IFRS) was carried out (particularly IFRS 8 – Operating Segments). Second, the information value of disclosures for investors in the energy industry was assessed. The empirical part was preceded by a description of segment reporting principles in accordance with IFRS 8 and the summary of challenges facing the energy sector in Poland.
A passive user‐side solution for evil twin access point detection at public hotspots

This paper proposes a passive user‐side solution, called Wi‐Fi legal access point (AP) finder (LAF), to the notorious evil twin access point problem, which in turn can result in diverse security problems, such as fraud, identity theft, and man‐in‐the‐middle attacks. Due to the severe security threats created by evil twins, many promising solutions have been proposed. However, the majority of these solutions are designed for the administrators of wireless networks, not for Wi‐Fi users. Hence, they are either too expensive or need some data that are usually not accessible to normal users. LAF utilizes the TCP three‐way handshake‐related packets and packet forwarding property created by evil twins to find legal APs, called good twins, at public hotspots or unencrypted WLANs; thus, it does not need any data or assistance from wireless network administrators. LAF does not send exploring packets actively; hence, evil twins cannot sense its existence. No matter when and where a user needs to utilize an AP to connect to the Internet at a hotspot, he can just use LAF to find out a legal AP to connect to. Experimental results show that LAF can quickly and accurately find legal APs after observing only a few packets.
Thyroid Ultrasound Image Segmentation: A Review

The incidence of thyroid nodule has increased enormously in recent years. Nowadays, computer-aided diagnosis (CAD) systems using ultrasound images have been widely developed in assisting radiologists to improve diagnosis accuracy. Image segmentation is the crucial key to the subsequent processing and determines the quality of final analysis in C AD. However ultrasound segmentation remains a challenging problem due to various disorders including inhomogeneity, artifact, speckle and weak boundary. A number of thyroid ultrasound segmentation techniques have been utilized in the last decades and reported to be accurate on private datasets. The improvement of the performance is still increasingly challenging. In this paper, we discuss the basic ideas, pros/cons of the approaches and group them into categories in which easier to understand. With more detail techniques presented, this review will be useful for one’s involved in CAD systems development on thyroid ultrasound imaging.
Temperate Eurasian Origins of Hawaiian Chenopodium (Amaranthaceae), Plus Description of a New Subspecies Endemic to Moloka‘i

Abstract Hawaiian taxa of Chenopodium are tetraploids and are distinguished from other members of the circumglobally distributed genus by minute morphological characters. Because of these reasons, the geographic origin of Hawaiian Chenopodium has remained unclear. Across the Hawaiian Archipelago, taxa of Chenopodium are morphologically variable and grow in highly disparate xeric habitats, especially in terms of precipitation, temperature, wind, salt spray, and solar irradiation. Habitats include dry subalpine shrublands, sandy beach strands on atolls in the Northwest Hawaiian Islands, dry to mesic forests, and precipitously tall sea cliffs of northwestern Moloka‘i. From the Moloka‘i sea cliffs, which are battered by high energy winds, salt spray, and strong seasonal precipitation, we describe C. oahuense subspecies ilioensis as segregated from the widespread Hawaiian C. oahuense sensu lato. Morphometric analyses distinguish C. oahuense subsp. ilioensis by its strongly prostrate to scandent habit, thick succulent leaves, smaller average leaf size, limited lobing of the laminar margins, and smaller seeds. Phylogenetic analyses using two DNA regions (the plastid gene rpl32-trnL and nuclear ITS) of newly sequenced individuals of C. oahuense s. l. and C. oahuense subsp. ilioensis plus outgroup taxa support the monophyly of Hawaiian Chenopodium and reveal a geographic origin of temperate Eurasia. Two equivocal hypothetical scenarios are discussed regarding the likely sequence of events leading to the arrival of Chenopodium in Hawaiian Islands followed by possible in situ speciation of the Moloka‘i endemic C. oahuense subsp. ilioensis.
Effect of plant growth regulators on growth, yield and essential oil production of henna (Lawsonia inermis L.)

Summary A field experiment was conducted during 1994–95 and 1995–96 at Udaipur, India to study the effect of cycocel (1000, 2000, 4000 ppm), thiourea (500, 1000, 2000 ppm) and kinetin (25, 50, 100 ppm) on vegetative growth, essential oil content, yield and quality of henna. A spray of 2000 ppm cycocel was found to be most effective, resulting in reduced plant height and an increased number of in¯orescences. Maximum yield of foliage, as well as henna powder per plant were recorded with cycocel 2000 ppm which was, statistically, as effective as thiourea at 2000 ppm. The maximum weight of flowers, essential oil content in flowers and yield of essential oil per plant were recorded with thiourea 2000 ppm. The colour intensity of henna powder was shown to be maximal with kinetin 100 ppm followed by thiourea 2000 ppm.
Medication Overuse Withdrawal in Children and Adolescents Does Not Always Improve Headache: A Cross-Sectional Study

Background: MOH can be diagnosed in subjects with headache occurring 15 days/month in association with a regular medication overuse, but its existence is not universally accepted. ICHD-3 redefined criteria for MOH, removing the criterion associating drug suspension with headache course. The aim of our study was to compare the rate of patients diagnosed with medication overuse headache (MOH) according to ICHD-2 and ICHD-3 criteria, to verify the degree of concordance. The secondary aim was to verify if drug withdrawal was really associated with pain relief. Methods: In this cross-sectional study, we retrospectively analyzed a sample of 400 patients followed for primary chronic headache at the Headache Center of Bambino Gesù Children's Hospital. We then selected those presenting with a history of medication overuse, and we applied both ICHD-2 and ICHD-3 criteria to verify in which patients the criteria would identify a clinical diagnosis of MOH. Results: We identified 42 subjects (10.5%) with MOH; 23 of them (55%) presented a relief of headache withdrawing drug overuse. Regarding the applicability of the ICHD-2 criteria, 43% of patients (18/42) fulfilled all criteria, while all ICHD-3 diagnostic criteria were satisfied in 76% of patients (32/42). Eighteen patients (43%) satisfied both ICHD-2 and ICHD-3 criteria, while 10 patients (24%) did not satisfy either diagnostic criterion. Conclusions: Our study suggests that in children and adolescents, withdrawing medication overuse is not always associated with a clinical benefit. Therefore, though allowing a MOH diagnosis in a higher rate of patients as compared to ICHD-2, the application of ICHD-3 criteria does not guarantee a true a causal relationship between medication overuse and headache worsening.
Effects of intermittent starvation on preservation characteristics of ANAMMOX bacteria

The effects of intermittent starvation on preservation characteristics of anammox bacteria were studied using three different preservation methods,which contained 4 ℃,4 ℃ with addition of substrate(NO-2-N/NH+4-N ratio of 1.32) every ten days and 4 ℃ with addition of substrate(NO-2-N/NH+4-N ratio of 1.63) every ten days.Results indicated that intermittent starvation was more harmful to anammox bacteria than that of the long-term continuous starvation under anaerobic conditions.Besides,it could be found that the higher concentration of nitrite would have stronger inhibiting effects on the preservation of anammox bacteria.In addition,the anammox bacterial activities were directly correlated with the content of heme c.The color of anammox bacteria could reflect the relative bacterial activities as well as heme c content under the conditions without deliberate color interference.Further,results also showed that the particle structure and the extracellular polymers of anammox bacteria would help to increase the resistance of bacteria to adverse factors.During the 5-month preservations,all the activity decaying rates of the three methods decreased fast initially,and then slowed down to relatively stable values with survival activity percentages of 75.3%,70.8% and 62.7%,respectively.
Platform and Genre Identification for Designing Serious Games

Psychological misconceptions are widespread among the general public and scientific community so it requires an effort to reduce these phenomena. This preliminary study aims to identify the platform and genre of games and also find out what popular games are played by students in order to create a Serious Game that contains critical thinking instruction to reduce misconception in psychology. The method used was a survey involving 357 student respondents, consisting of 86 students who had designed games and 271 students who had never designed any game. Questionnaires concerning the most preferred platform, genre, and the most played game were given, and the results were then processed and analyzed using frequency and chi-square calculations. The results showed that the platform preference of students who had experience in designing games was Personal Computer Games, while the platform preference of students who had never designed game was Mobile Games. For the genre, the most preferred genre of game among students was Adventure game. The findings obtained from this research study will be used as the basis for determining the platform and genre to design an effective, entertaining and educational Serious Game. Implications for game design and future research are subsequently discussed.
EEG-based BMI using Multi-Class Motor Imagery for Bionic Arm

One of the rehabilitation methods developed to help people with physical disabilities, especially patients with disabilities of the upper-limb arm, to do Activities of Daily Living (ADL) is the Bionic arm. The commonly used bionic arm control method is utilizing residual muscle motor neurons. However, the problem arises in patients with upper elbow amputation, limited residual muscle, muscle cells damaged or not growing again which causes the arm to not be able to give enough signals. The electrical activity of the brain recorded using electroencephalography (EEG) can be utilized for bionic arm control. The movement of grasping an object to fulfill ADL is a complex movement, so a system that is able to overcome these needs is needed. The Brain-Machine Interface (BMI) with Motor Imagery (MI) on a bionic arm multiclass control system based on Fast Fourier Transform (FFT) and Support Vector Machine (SVM) is described and discussed in this article. The system built can handle complex movements grasping various objects and evaluated for use with long pauses. The experiment results show good SVM-FFT performance when implemented on a real bionic arm. The use of Additional Movement (AM) increases classification success by up to 20%. On the other hand, this system is able to handle usage even though it has been rested in a few minutes.
Comparisons of the Thermal Stability of Poly(3,4-Ethylenedioxythiophene) (PEDOT) and ITO on Flexible Substrates

Organic materials have been widely used in photovoltaic solar applications because of their flexibility and low cost. Poly(3,4-ethylenedioxythiophene) (PEDOT) has been known to have good mechanical stability under stretching and bending and also has good electrical and optical properties. Unlike inorganic materials, PEDOT can withstand high strains. In flexible solar cells, modules are usually exposed to heating–cooling cycles during day and night. When the structure of a thin film on a flexible substrate is exposed to high temperatures, the film and the substrate will expand at different rates; this will produce a residual strain caused by the thermal mismatch between the two layers. In contrast, indium–tin oxide (ITO) is brittle, and its conductivity decreases significantly as the ITO films are exposed to stretching or bending strains, especially in flexible/foldable solar cell applications. Cracks in ITO appear at very low strains that might cause failure in the conductive layer because of the combination of a very thin film of brittle ceramic material applied to a polymer substrate. In this work, a comparison of the thermal stability was conducted between PEDOT and ITO on flexible polyethylene terephthalate (PET) substrate. The performances of the two candidates were assessed during thermal bending fatigue and accelerated thermal cycling experiments. This work was designed to study the behavior of ITO and PEDOT under thermal cycling and thermal bending fatigue.
kNN-guided Adversarial Attacks

In the last decade, we have witnessed a renaissance of Deep Learning models. Nowadays, they are widely used in industrial as well as scientiﬁc ﬁelds, and noticeably, these models reached super-human performances on speciﬁc tasks such as image classiﬁcation. Unfortunately, despite their great success, it has been shown that they are vulnerable to adversarial attacks - images to which a speciﬁc amount of noise imper-ceptible to human eyes have been added to lead the model to a wrong decision. Typically, these malicious images are forged, pursuing a misclas-siﬁcation goal. However, when considering the task of Face Recognition (FR), this principle might not be enough to fool the system. Indeed, in the context FR, the deep models are generally used merely as features ex-tractors while the ﬁnal task of recognition is accomplished, for example, by similarity measurements. Thus, by crafting adversarials to fool the classiﬁer, it might not be suﬃcient to fool the overall FR pipeline. Starting from this observation, we proposed to use a k-Nearest Neighbour algorithm as guidance to craft adversarial attacks against an FR system. In our study, we showed how this kind of attack could be more threatening for an FR system than misclassiﬁcation-based ones considering both the targeted and untargeted attack strategies.