Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal effects on neurons during stimulation of the brain

All electric and magnetic stimulation of the brain deposits thermal energy in the brain. This occurs through either Joule heating of the conductors carrying current through electrodes and magnetic coils, or through dissipation of energy in the conductive brain. Objective. Although electrical interaction with brain tissue is inseparable from thermal effects when electrodes are used, magnetic induction enables us to separate Joule heating from induction effects by contrasting AC and DC driving of magnetic coils using the same energy deposition within the conductors. Since mammalian cortical neurons have no known sensitivity to static magnetic fields, and if there is no evidence of effect on spike timing to oscillating magnetic fields, we can presume that the induced electrical currents within the brain are below the molecular shot noise where any interaction with tissue is purely thermal. Approach. In this study, we examined a range of frequencies produced from micromagnetic coils operating below the molecular shot noise threshold for electrical interaction with single neurons. Main results. We found that small temperature increases and decreases of 1 ∘C caused consistent transient suppression and excitation of neurons during temperature change. Numerical modeling of the biophysics demonstrated that the Na-K pump, and to a lesser extent the Nernst potential, could account for these transient effects. Such effects are dependent upon compartmental ion fluxes and the rate of temperature change. Significance. A new bifurcation is described in the model dynamics that accounts for the transient suppression and excitation; in addition, we note the remarkable similarity of this bifurcation’s rate dependency with other thermal rate-dependent tipping points in planetary warming dynamics. These experimental and theoretical findings demonstrate that stimulation of the brain must take into account small thermal effects that are ubiquitously present in electrical and magnetic stimulation. More sophisticated models of electrical current interaction with neurons combined with thermal effects will lead to more accurate modulation of neuronal activity.
Delayed dynamics of migratory response to CTLA-4 blockade reveals a mechanistic view on potential T cells reinvigoration following immune checkpoint blockade

Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) receptors, two clinically relevant targets for immunotherapy of cancer, are negative regulators of in immune cell activation and migration. However, optimizing therapeutic outcomes still requires fundamental research to reach a comprehensive insight into the coherent function of immune regulators. Here, we investigated the statistical dynamics of T cells migration as a measure of the functional response to these pathways in an experimental setup of immune checkpoint blockade. For this purpose, we used a previously developed 3-dimensional organotypic culture of patient-derived tumor spheroids. Experiment-based dynamical modeling remarked distinct characteristics of the receptors regulation followed through with the modification of their proportions in the immune modulation. We demonstrated that time-delayed kinetics of PD-1 activation just overrides its relatively more efficient cell-level function which potentially makes an operative contribution to the functional dominance of CTLA-4 in the tumor microenvironment. Simulation results showed good agreement with data for tumor cells reduction and active immune cells count observed in each experiment. These analyses propose a new mechanistic view on relative immunogenicity of PD-1 and CTLA-4 inhibitors manifested in literature and point the possible inherent obstacles in checkpoint inhibition-based immunotherapy of cancer to address in the future. Significance Ex vivo monitoring of temporal response to PD-1 and CTLA-4 in the closure of T cell movement dynamics and elucidating their feasible commitment to the kinetic constraints at cell-level resolution. Delayed dynamics of migratory response to CTLA-4 inhibition revealed a mechanistic view on potential T cell reinvigoration following immune checkpoint blockade.
Creating culture from scratch : a multiple case study into creating culture in English free schools

This thesis considers the introduction of the free school, questioning whether the culture of such start-up schools differs to that of existing schools. The research focuses on the extent to which the founding headteacher controls the formation and continuation of culture, and by what methods. The research builds on existing theories of organisational culture to establish a current understanding of leadership of school culture within English schools and compares this it five secondary free schools. Within each case study a range of stake holders were interviewed, and documents analysed to investigate how the intended culture was planned for the schools, and what emergent culture has resulted. The findings presented show an explicit need to plan and embed a new culture and give some practical suggestions as to how to achieve this. Free schools studied demonstrated some distinctive cultural elements, unique in the consistency with which they were embedded. It is postulated these cultural facets are as a direct result of the political turmoil surrounding the free school, and largely result from the external opposition to such schools. The importance and power of the founding generation of staff and students in creating new culture has also emerged as a critical theme.
Preliminary evidence for one-trial social learning of vervet monkey alarm calling

How do non-human primates learn to use their alarm calls? Social learning is a promising candidate, but its role in the acquisition of meaning and call usage has not been studied systematically, neither during ontogeny nor in adulthood. To investigate the role of social learning in alarm call comprehension and use, we exposed groups of wild vervet monkeys to two unfamiliar animal models in the presence or absence of conspecific alarm calls. To assess the learning outcome of these experiences, we then presented the models for a second time to the same monkeys, but now without additional alarm call information. In subjects previously exposed in conjunction with alarm calls, we found heightened predator inspection compared to control subjects exposed without alarm calls, indicating one-trial social learning of ‘meaning’. Moreover, some juveniles (but not adults) produced the same alarm calls they heard during the initial exposure whereas the authenticity of the models had an additional effect. We concluded that, in non-human primates, call meaning can be acquired by one-trail social learning but that subject age and core knowledge about predators additionally moderate the acquisition of novel call-referent associations.
Genomic legacies of ancient adaptation illuminate the GC-content evolution in bacterial genomes

In conventional views, the bacterial adaptation is characterized by strong purifying selection as well as rapid evolution in changing environments. However, the genomic GC content varies greatly but has some degree of phylogenetic stability. Using 11,083 representative genomes, we report a phylogenetically constrained bimodal distribution of the genomic GC. Results suggest that such divergence of the genomic GC can be well explained by the DNA replication and repair (DRR) system, in which multiple pathways are observed correlated to the genomic GC. The biased conservations of various stress-related genes especially the DRR-related ones imply distinct adaptive evolution of the ancestral lineages of high or low GC clades which may be induced by major environmental changes in early evolution. Furthermore, our findings support that the mutational biases resulted from these legacies of adaptation have changed the course of adaptive evolution in bacteria thus causing great variation in the genomic GC. This study demonstrates the importance of indirect effects from natural selection which may be easily misinterpreted as neutral processes.
Two pathways drive meiotic chromosome axis assembly in Saccharomyces cerevisiae

Successful meiotic recombination, and thus fertility, depends on conserved axis proteins that organize chromosomes into arrays of anchored chromatin loops and provide a protected environment for DNA exchange. Here, we show that the stereotypic chromosomal distribution of axis proteins in S. cerevisiae is the additive result of two independent pathways: a cohesin-dependent pathway, which was previously identified and mediates focal enrichment of axis proteins at gene ends, and a parallel cohesin-independent pathway that recruits axis proteins to broad genomic islands with high gene density. These islands exhibit elevated markers of crossover recombination as well as increased nucleosome density, which we show is a direct consequence of the underlying DNA sequence. A predicted PHD domain in the center of the axis factor Hop1 specifically mediates cohesin-independent axis recruitment. Intriguingly, other chromosome organizers, including cohesin, condensin, and topoisomerases, are differentially depleted from the same regions even in non-meiotic cells, indicating that these DNA sequence-defined chromatin islands exert a general influence on the patterning of chromosome structure.
Deep Learning Approaches on Multimodal Sentiment Analysis

Sentiment analysis aims to uncover people's sentiment based on some information about them, often using machine learning or deep learning algorithm to determine. The importance of such a technique heavily grows because it can help companies better understand users' attitudes toward things and decide future plans. Considering the maturity of sentiment analysis on a single modal such as text and image and the advancement of social media, which allow users to post with text and image simultaneously, novel methods are designed for multimodal sentiment analysis. Because of the infancy of this field, new methods are sometimes inefficient, unstable and lack robustness and still need further study. One big challenge on the multimodal sentiment analysis is to find a proper way that can overcome heterogeneous gap between different modalities, which implies that researchers should develop a method of combining various modalities properly to get higher efficiency and accuracy. Although much research has been performed and many new models are implemented, related summary is still lacking. This paper mainly introduces four interesting and relatively novel methods of solving the links among diverse modalities. First it briefly introduces some basic definitions and terminologies in sentiment analysis, followed by several popular and common datasets on multimodal sentiment analysis. After that it gives some evaluation index to assess one model's competence. Then it shows four models and compares pros and cons among them, showing the potential trend of future study in multimodal sentiment analysis. Finally, it proposes future challenges and opportunities.
Underwater attached organisms intelligent detection based on an enhanced YOLO

In today's shipping, various organisms attached to the bottom of the ship do great harm to the ship, including increasing fuel loss, hindering the operation of electronic instruments and accelerating bottom corrosion. In the process of removing the organisms attached to the bottom of the ship plays a vital role in the operation. The underwater image recognition system will carry out the visual detection of underwater attachments based on the underwater robot and assist the robot in cleaning. In this paper, we propose a underwater attached organism detection method based on an Enhanced YOLOv4. We apply the Retinex theory to enhance the underwater images to overcome the influence from turbidity and illumination. We deploy our proposed method and do experiments in the underwater attachments, e.g., starfish, barnacle, shell, sea urchin, sea rainbow, coral, etc. The experiment results show that our enhanced YOLO method achieve much better performance than the original YOLOv4 method.
Revitalising safety practices in construction projects: The case of Nigeria and United Kingdom

The construction industry plays a vital role in boosting the global economy. From the reviewed literature, studies indicate that the industry is also hazardous and frequently accident prone. This study examined safety practices of construction industry in Nigeria and the United Kingdom with a view to revitalise current practice. To achieve this, semi-structured interviews were conducted among fifteen senior managers in Nigeria and the United Kingdom. The emerging key issues indicated that knowledge and skills, national legislations and policies, influx of migrant workers, the fragmented nature of the construction were among the major challenges and barriers for safety in the construction industry. Based on the findings, it was further suggested that strategies such as the use of informal trainings which provide additional learning options for construction workers and lean construction techniques which support safety should be adopted by the construction industry to revitalise future safety practices.
Real-time scheduling for optimal energy optimization in smart grid integrated with renewable energy sources

Load scheduling, battery energy storage control, and improving user comfort are critical energy optimization problems in smart grid. However, system inputs like renewable energy generation process, conventional grid generation process, battery charging/discharging process, dynamic price signals, and load arrival process comprise controller performance to accurately optimize real-time battery energy storage scheduling, load scheduling, energy generation, and user comfort. Thus, in this work, the virtual queue stability based Lyapunov optimization technique (LOT) is adopted to investigate real-time energy optimization in a grid-connected sustainable smart home with a heating, ventilation, and air conditioning (HVAC) load considering unknown system inputs dynamics. The main goal is to minimize overall time average energy cost and thermal discomfort cost in a long time horizon for sustainable smart home accounting for changes in home occupancy state, the most comfortable temperature setting, electrical consumption, renewable generation output, outdoor temperature, and the electricity costs. The employed algorithm creates and regulates four queues for indoor temperature, electric vehicle (EV) charging, and ESS. Extensive simulations are conducted to validate the employed algorithm. Simulation results illustrate that the proposed algorithm performs real-time energy optimization and reduces the time average energy cost of 20.15% while meeting the user’s energy and comfort requirement.
Big Data Analyzing Techniques in Mathematical House Price Prediction Model

The Chinese house market has been flourishing in the past three decades as an increasingly bigger population moves into cities. To keep the rise of house price within a proper range and acceptable to the public, the government has adopted various approaches to bring the price under control. After intermittent fluctuations, house purchasing has become a hot topic for both the media and the public. It is of great significance to study the change of house price considering all the related factors. Some scientists prefer machine learning. Machine learning is a subject which involves many subjects such as probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. In this paper, we will discuss the details of the machine learning algorithms, three typical models (i.e., AdaBoost, Linear Regression and KNN) and their strengths and weaknesses. In the future, the growing complexity of all the factors that influence house price will cause more and more trouble for scientists pursuing more precise results. Also, based on its own specialty that computer is still not able to think like a man, machine learning cannot achieve 100% right, which often results in some silly outcomes.
Karakteristik Biodiesel Kemiri Sunan [Reutealis trisperma ( Blanco ) Airy Shaw] Menggunakan Proses Transesterifikasi Dua Tahap

Biodiesel merupakan alternatif terbaik pengganti bahan bakar diesel yang bersumber dari fosil. Selain dapat digunakan secara langsung pada mesin tanpa modifikasi, biodiesel juga ramah lingkungan. Pengembangan biodiesel kedepan lebih diarahkan ke bahan nonpangan. Salah satu bahan nonpangan yang berpotensi sebagai bahan biodiesel adalah kemiri sunan [ Reutealis trisperma (Blanco) Airy Shaw]. Proses produksi biodiesel minyak kemiri sunan saat ini masih menghasilkan biodiesel yang belum memenuhi Standar Nasional Indonesia (SNI). Penelitian ini dilakukan di Lembaga Minyak dan Gas serta di Balai Penelitian Tanaman Industri dan Penyegar bulan November 2011, bertujuan mengevaluasi karakteristik biodiesel kemiri sunan dan membandingkannya dengan SNI (SNI-04-7182-2006) dan standar USA (ASTM D6751). Metode pembuatan biodiesel menggunakan proses transesterifikasi dua tahap. Hasil yang diperoleh menunjukkan bahwa rendemen biodiesel kemiri sunan mencapai 88% dari volume minyak. Dari 18 kriteria yang diamati, hanya residu karbon yang belum memenui kriteria SNI. Sedangkan untuk standar USA, yang belum memenuhi kriteria adalah residu karbon dan titik nyala. The Characteristic Of The Philippine Tung [Reutealis Trisperma (Blanco) Airy Shaw ] Biodiesel Processed Through Two Step Transesterification Process ABSTRACT Biodiesel is likely to be the best alternative to replace diesel derived fuel from fossil. It may be used directly onto machines without any necessary modification and be environmental friendly. Biodiesel development in the future will focus on non-edible vegetable oils of many potential sources. Philippine tung [ Reutealis trisperma (Blanco) Airy Shaw] might be considered. However, biodiesel production at present has not been sta n darized by Indonesian National Standard ( SNI ). A study was conducted at the Research and Development Center for Oil and Gas Technology and Indonesian Research Institute for Industrial and Beverages Crops on November 2011. The objective of this study was to evaluate the characteristics of Philippine Tung biodiesel and compared with SNI ( SNI -04-7182-2006) and USA standart (ASTM D6751). The method used was a two-stage transesterification process. The result showed that the ratio of biodiesel to total oil volume (v/v) was 88% . From 18 parameters on SNI based there was only carbon residue which is not meet SNI. While based on US standard, flash point and carbon residue didn’t meet with the criteria.
The Role of MIF and IL-10 as Molecular Yin-Yang in the Modulation of the Host Immune Microenvironment During Infections: African Trypanosome Infections as a Paradigm

African trypanosomes are extracellular flagellated unicellular protozoan parasites transmitted by tsetse flies and causing Sleeping Sickness disease in humans and Nagana disease in cattle and other livestock. These diseases are usually characterized by the development of a fatal chronic inflammatory disease if left untreated. During African trypanosome infection and many other infectious diseases, the immune response is mediating a see-saw balance between effective/protective immunity and excessive infection-induced inflammation that can cause collateral tissue damage. African trypanosomes are known to trigger a strong type I pro-inflammatory response, which contributes to peak parasitaemia control, but this can culminate into the development of immunopathologies, such as anaemia and liver injury, if not tightly controlled. In this context, the macrophage migration inhibitory factor (MIF) and the interleukin-10 (IL-10) cytokines may operate as a molecular “Yin-Yang” in the modulation of the host immune microenvironment during African trypanosome infection, and possibly other infectious diseases. MIF is a pleiotropic pro-inflammatory cytokine and critical upstream mediator of immune and inflammatory responses, associated with exaggerated inflammation and immunopathology. For example, it plays a crucial role in the pro-inflammatory response against African trypanosomes and other pathogens, thereby promoting the development of immunopathologies. On the other hand, IL-10 is an anti-inflammatory cytokine, acting as a master regulator of inflammation during both African trypanosomiasis and other diseases. IL-10 is crucial to counteract the strong MIF-induced pro-inflammatory response, leading to pathology control. Hence, novel strategies capable of blocking MIF and/or promoting IL-10 receptor signaling pathways, could potentially be used as therapy to counteract immunopathology development during African trypanosome infection, as well as during other infectious conditions. Together, this review aims at summarizing the current knowledge on the opposite immunopathological molecular “Yin-Yang” switch roles of MIF and IL-10 in the modulation of the host immune microenvironment during infection, and more particularly during African trypanosomiasis as a paradigm.
Theoretical Analysis on the Stability of Single Bulk Nanobubble

As predicted by classical macroscopic theory, the lifetime for nanoscale gas bubbles is extremely short, which causes conflict when detecting stable bulk nanobubbles experimentally in recent years. In fact, the stability of bulk nanobubbles depends on the surrounding liquid environment. Also, the dynamic process of gas in water involves the dissolution, diffusion, release, and transportation of gas as well as the properties of nanobubbles inside. Here, based on previous reports, we introduce the gas transport parameter ℓ in the classical diffusion equation by considering the gas diffusion near the bulk nanobubble at different locations in a container and consider the MacLeod-Sugden relationship between the surface tension and densities of liquid and gas for computing the lifetime of single bulk nanobubbles in an open system. The results show that the single nanobubble lifetime depends on the inner density and gas transport length. It could reach the order of 10–100 s for a single nanobubble with an initial radius of 200 nm, and provides a new idea to prolong the lifetime of the single bulk nanobubble. Meanwhile, compared with the continuous influence of the inner density on the gas diffusion flux near the nanobubble, the range of the gas transport near the nanobubble on the gas diffusion flux is limited, which is affected by the dissolution time of the nanobubble. Our findings would be helpful to explore the storage conditions of nanobubbles and the mechanism of mass transfer at the gas-liquid interface at the micro-scale.