Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances of immune checkpoint blockade in the treatment of advanced gastric cancer

The treatment of advanced gastric cancer has been a worldwide problem, chemotherapy can only improve the median survival and overall survival of advanced gastric cancer to a certain extent, and its treatment effect is very limited. Although targeted therapy brings new hope to some patients, there are still some limitations. Trastuzumab is mainly used in the HER-2-expressed gastric cancer, while Ramucirumab is only limited to second-line treatment[1]. With the proposing of new classification of gastric cancer, immunotherapy is considered to be a major breakthrough in the treatment of gastric carcinoma in recent years, and the immune checkpoint blockade[2] that uses programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1) antibody has become a focus in the study of immunotherapy. The Cancer Genome Atlas (TCGA) suggests dividing the gastric cancer into four subgroups, among which the microsatellite instability (MSI) subgroup and EB virus infection (EBV) subgroup account for 22% and 9% respectively. The former is characterized by MLH1 promoter supermethylation, including the elevated incidence of gene mutation that encodes cancer-causing signaling transduction protein, etc.; the latter is characterized by DNA hypermethylation, especially the CDKN2A promoter hypermethylation, the PIK3CA gene mutation and PD-L1/2 overexpression[3]. The tumor immune response plays an important role in the two subgroups, and the immunotherapy that blocking tumor antigenic escape is the effective method for the treatment of patients with these subgroups of gastric cancer.
On angled bounce-off impact of a drop impinging on a flowing soap film

Small drops impinging obliquely on thin flowing soap films frequently demonstrate the rare emergence of bulk elastic effects working in-tandem with the more commonplace hydrodynamic interactions. Three collision regimes are observable: (a) drop piercing through the film, (b) it coalescing with the flow, and (c) it bouncing off the film surface. During impact, the drop deforms along with a bulk elastic deformation of the film. For impacts that are close-to-tangential, the bounce-off regime predominates. We outline a reduced order analytical framework assuming a deformable drop and a deformable three-dimensional film, and the idealization invokes a phase-based parametric study. Angular inclination of the film and the ratio of post and pre-impact drop sizes entail the phase parameters. We also perform experiments with vertically descending droplets (constituted from deionized water) impacting against an inclined soap film, flowing under constant pressure head. Model-predicted phase domain for bounce-off compares well to our experimental findings. Additionally, the experiments exhibit momentum transfer to the film in the form of shed vortex dipoles, along with propagation of free surface waves. On consulting prior published work, we note that for locomotion of water-walking insects using an impulsive action, the momentum distribution to the shed vortices and waves are both significant, taking up respectively 2/3 and 1/3 of the imparted streamwise momentum. Considering the visually similar impulse actions, this theory, despite its assumption of a quiescent liquid bath of infinite depth, is applied to the drop bounce-off experiments, and the resultant shed vortex dipole momenta are compared to the momenta of the coherent vortex structures computed from particle imaging velocimetry data. The magnitudes reveal identical order (10−7 N s), suggesting that notwithstanding the disparities, the bounce-off regime may be tapped as a toy analog for impulse-based interfacial biolocomotion.
Effects of Gold Reserve Policy of Major Central Banks on Gold Prices Changes

Central banks which are responsible for minting and monetary policy implementations are the institutions carry out sensitive policies for the healthy functioning of the economy. Policies implemented by central banks and its existing institutional structures cannot be dissociated from the political and social development of the country they live in, and the whole of economic policy. In recent years, with increasing pace of globalization, the mobility of international financial markets increased and this effect has extended the decisions of the central bank from national markets to international markets. In this study, we studied the possible impacts of changes in the share of gold in central banks? reserves on gold prices proving empirical evidence from the USA, the Euro area, China and Russia. According to Causality and Forecast Error Variance Decomposition analysis deriving from VEC model, reserve polices of central banks of these countries has considerable effects on variations in gold price in the long-term. Empirical findings reveal the importance of the size of balance sheet of central banks, while it is also stressed that growth potential of economies and investment opportunities are crucial issues in terms storing reserves in terms of gold.
Dynamically Determining Neighborhood Parameter for Locally Linear Embedding: Dynamically Determining Neighborhood Parameter for Locally Linear Embedding

Locally linear embedding is a kind of very competitive nonlinear dimensionality reduction with good representational capacity for a broader range of manifolds and high computational efficiency. However, they are based on the assumption that the whole data manifolds are evenly distributed so that they determine the neighborhood for all points with the same neighborhood size. Accordingly, they fail to nicely deal with most real problems that are unevenly distributed. This paper presents a new approach that takes the general conceptual framework of Hessian locally linear embedding so as to guarantee its correctness in the setting of local isometry to an open connected subset but dynamically determines the local neighborhood size for each point. This approach estimates the approximate geodesic distance between any two points by the shortest path in the local neighborhood graph, and then determines the neighborhood size for each point by using the relationship between its local estimated geodesic distance matrix and local Euclidean distance matrix. This approach has clear geometry intuition as well as the better performance and stability to deal with the sparsely sampled or noise contaminated data sets that are often unevenly distributed. The conducted experiments on benchmark data sets validate the proposed approach.
ERIKA - Early Robotics Introduction at Kindergarten Age

In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human–robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents.
HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent

Phenotypic and genotypic predictors forHIV/SIV tropism are available. The genotypic predictors are more rational. However, they are sequence alignment dependent only. Regrettably, non-homologous proteins are found to display common biological functionality. This indicates that sequence-dependent predictors cannot be trusted with appropriate classification of the HIV and SIV isolates, especially if the isolates belong to same tropic group but share divergent sequence alignment. There is therefore need for genotypic predictors that will incorporate embedded intrinsic biological characteristics of the HIV and SIV isolates in the determination of HIV tropism. Secondly, more than 30 positions with at least single mutation outside the V3 domain have been found to influence HIV Tropism. Disappointingly, the available sequence alignment-based HIV genotypic predictors engage only the hyper-variable region (V3) of the HIV gp120. This has resulted in inaccurate classification of HIV and SIV strains. Finally, available HIV genotypic predictors are found to lack the ability to identify and accurately evaluate the sequences of most HIV-1 non B clades, HIV-2 and SIV. Against this background, the ability of the Digital Signal Processing (DSP) Technique called Informational Spectrum Method (ISM), which does not engage sequence similarity but the embedded bio-functionalities of the entire gp120 sequence length to predict HIV and SIV tropism is therefore investigated. 83 isolates of HIV and SIV are subjected to ISM and three other procedures. Results are generated and findings correlated. For isolates, which are analyzable by the four procedures, the results from ISM and three other procedures are found to correlate. Using 50% affinity for the host CD4 as the cut-off, the tropism of the uncategorized isolates are predicted. ISM-based technique is adjudged a better procedure. It analyzes the sequences of all HIV (HIV-1 together with non B, and HIV-2) as well as SIV isolates including those that could not be investigated by other genotypic predictors. It engages the embedded biological characteristics rather than sequence similarity and utilizes the entire HIV gp120 sequence-length instead of V3 domain. This makes ISM-based procedure a better tool for over 180,000 isolates of HIV-1, HIV-2 and SIV in the UNIPROT database. Clinical approaches are unfeasible. This study recommends ISM technique principally for viral tropism prediction as it does not discriminate against HIV/SIVcategories. It suggests that further work be done to determine a suitable cut-off (as in geno2pheno[CORECEPTOR]), and the procedure in combination with other genotypic predictors be engaged in developing an algorithm for determining viral tropism.
The influenza matrix protein 2 as a vaccine target

Matrix protein (M)2 is an Influenza A, type III membrane protein with an extracellular domain (ectodomain of M2 [M2e]) of 23 amino acid residues, which is strongly conserved across virus strains. M2 fulfills an important biological function in the life cycle of the Influenza A virus and has been a target of antiviral drugs. M2e has generated much interest as a potential vaccine target, and a clinical M2e vaccine trial was initiated in 2007. The advantage of M2e compared with hemagglutinin, the prime antigen target in conventional influenza vaccines, is that its sequence is conserved. This means that a stable, efficacious and easily produced M2e-based vaccine would provide protection not only against drifting seasonal influenza epidemic strains, but would also make it possible to vaccinate in anticipation of an emerging pandemic. Furthermore, most reported M2e-based vaccines are produced by economical and safe technologies. IgG subtype antibodies directed against M2e can prevent death from influenza and re.
Biological activity of endophytic fungi associated with palm trees.

Endophytic fungi were isolated from leaves, petioles and roots of palm trees in King Mongkut’s Institute of Technology Ladkrabang (KMITL), Bangkok, Thailand, and tested for biological activity test. A total of 60 isolates were obtained and morphological identification. Phoma exigua. , Fusarium chamydosporum, Phialophola spp. and Nigrospora spp. were examined for bi-culture antagonisict test against Colletotrichum coffeanum causing coffee Anthracnose. The result showed that all of these 4 species of endophytics exptressed the antifungal activity inhibited colony growth and spore production of colletotrichum coffeanum, which were 6.68cm, 5.89cm, 6.25cm, 5.66cm, in colony diadmeter and 0.875×10, 0.375×10, 1.125×10, 1.0625×10 in spore numbers. And, the inhibition percentage of colony growth were 25.75%, 35.28%, 30.55%, 37.02%, respectively, the inhibition percentage of spore production were 76.66%, 89.99%, 69.99%, 71.66% respectively. Nigrospora spp. showed the best inhibition percentage of colony growth, and, Fusarium chamydosporum gived the best inhibition percentage of spore production.
PREDICTION OF UPLIFT CAPACITY OF SUCTION CAISSON IN CLAY USING FUNCTIONAL NETWORK AND MULTIVARIATE ADAPTIVE REGRESSION SPLINE

Suction caissons are extensively used as anchors for offshore foundation structures. The uplift capacity of suction caisson is an important factor from effective design point of view. In this paper, two recently developed AI techniques, functional network (FN) and multivariate adaptive regression spline (MARS), have been used to predict the uplift capacity of suction caisson in clay. The performances of the developed models are compared with other AI techniques; artificial neural network, support vector machine, relevance vector machine, genetic programming, extreme learning machine and group method of data handling with harmony search (GMDH-HS). The model inputs include the aspect ratio of the caisson, undrained shear strength of soil at the depth of the caisson tip, relative depth of the lug at which the caisson force is applied, load inclination angle and load rate parameter. Comparative analyses are made with the results of the above AI techniques, using different statistical performances criteria; correlation coefficient (R), root mean square error, Nash-Sutcliffe coefficient of efficiency, log-normal distribution of ratio of predicted to observed load capacity, with a ranking system to find out the best predictive model. The FN and MARS models are found to be comparably efficient and they outperform other AI techniques.
Termite: a system for tunneling through heterogeneous data

Data-driven analysis is important in virtually every modern organization. Yet, most data is underutilized because it remains locked in silos inside of organizations; large organizations have thousands of databases, and billions of files that are not integrated together in a single, queryable repository. Despite 40+ years of continuous effort by the database community, data integration still remains an open challenge. In this paper, we advocate a different approach: rather than trying to infer a common schema, we aim to find another common representation for diverse, heterogeneous data. Specifically, we argue for an embedding (i.e., a vector space) in which all entities, rows, columns, and paragraphs are represented as points. In the embedding, the distance between points indicates their degree of relatedness. We present Termite, a prototype we have built to learn the best embedding from the data. Because the best representation is learned, this allows Termite to avoid much of the human effort associated with traditional data integration tasks. On top of Termite, we have implemented a Termite-Join operator, which allows people to identify related concepts, even when these are stored in databases with different schemas and in unstructured data such as text files, webpages, etc. Finally, we show preliminary evaluation results of our prototype via a user study, and describe a list of future directions we have identified.
Mature 25 Gb / s Silicon Photonic Platform towards Multi-Layer Circuits for High Integration Level

Silicon photonics is definitely a key technology in next-generation communication systems from Long-Haul networks to short reach data interconnects. To address 25 Gb/s and above applications, we present our R&D platform that uses a CMOS foundry line. The fabrication process is following a modular integration scheme which leads to a flexible platform, allowing various device combinations. Moreover this platform is associated to a device library in a PDK which includes specific photonic features and which is compatible with commercial EDA tools. Based on the maturity of this platform to build high-speed optical transceivers, we present our strategy to anticipate the next integration disruptive level by implementing multi-layer photonic circuits. Such a technology represents a new paradigm for the design of very high integration circuits that we consider first for optical interposer, and finally for optical network on chip with the convergence of photonics and electronics.
Children's Consumption of Wic-Approved Foods

The WIC program offers supplemental foods to low-income women, infants, and children. This study compared consumption patterns of WIC children with those of three different comparison groups: eligible nonparticipating children living in non-WIC households, eligible nonparticipating children living in WIC households, and children living in households whose income is too high to be eligible for WIC. The study provides strong evidence that participation in the WIC program increases consumption of at least some types of WIC-approved foods. Although WIC-participating children consumed significantly more calories from WIC-approved foods than children in the two comparison groups of eligible nonparticipants, there was no significant difference in total calories consumed. The results suggest that WIC foods replace non-WIC foods in the diets of children participating in WIC rather than adding to their food consumption. This is the first study to examine in detail children's consumption of WIC-approved foods by WIC status. Understanding WIC's effect on the consumption of foods contained in the WIC food packages can help inform decisions on possible changes to the packages.
INVESTIGATING THE HEAVY METALS AND PESTICIDES CONCENTRATION IN AGRICULTURAL SOIL AND GROUNDWATER OF MANSA DISTRICT OF PUNJAB , INDIA : INSIGHTS INTO ITS IMPACT ON HUMAN HEALTH

In the present study, we report presence of heavy metals and pesticides from the agricultural soil and groundwater samples of Mansa District of Punjab India. The investigation of the soil and water samples revealed presence of heavy metals Ni (47.7 mgkg -1 ), Hg (23.8 mgkg -1 ), Se (21.1 mgkg -1 ) and Cd (3.1 mgkg -1 ) above the permissible limit, as set by Ministry of Environment (MOE). Conversely, the level of Ba (0.066 mgL -1 ) and Se (0.006 mgL -1 ) detected in the water sample was below the permissible limit as set by MOE. Further analysis of the soil for the presence of cypermethrin a potent insecticide used by the farmers worldwide demonstrated varied presence of different isomer (I and III-0.019ppb, II-0.018ppb, IV-0.017ppb) in the soil. All other pesticides analyzed demonstrated their presence below the detection limit (BDL). In water, all pesticides observed were found below the detection limit. Significantly high level of soil contamination detected in this region indicates a potential risk to its soil as well as groundwater quality.
Factors that Affect Farmland Conversion in China and Indonesia

The first challenge in this century is to maintain or increase the farmland because land is the determinant factor. China and Indonesia have a considerable population, have the same major food crops, and have been facing a problem with farmland conversion. The problem will be focused on the following issue whether factors are affecting farmland conversion in China and Indonesia. This research used the data from The World Bank in 1982 - 2014 and used Auto-Regressive Distributive Lags (ARDL) as the data analysis. In the short-run, investment and urban population are significant variables to affect the farmland conversion in China and Indonesia. The employment merely affects for farmland conversion in China, while the agriculture GDP and railways affect for Indonesia. In the long-run, employment and railways affect farmland conversion in China; however, the agriculture GDP, investment, and urban population are significant for Indonesia. Some policies which needed to prevent farmland conversion began stipulated zoning and spatial planning in central and local government, and incentives for the farmer.
High-cadence spectroscopy of M-dwarfs – II. Searching for stellar pulsations with HARPS

Stellar oscillations appear all across the Hertzsprung–Russell diagram. Recent theoretical studies support their existence also in the atmosphere of M dwarfs. These studies predict for them short periodicities ranging from 20 min to 3 h. Our Cool Tiny Beats (CTB) programme aims at finding these oscillations for the very first time. With this goal, CTB explores the short time domain of M dwarfs using radial velocity data from the High Accuracy Radial velocity Planet Searcher (HARPS)-European Southern Observatory and HARPS-N high-precision spectrographs. Here we present the results for the two most long-term stable targets observed to date with CTB, GJ 588 and GJ 699 (i.e. Barnard's star). In the first part of this work we detail the correction of several instrumental effects. These corrections are especially relevant when searching for subnight signals. Results show no significant signals in the range where M dwarfs pulsations were predicted. However, we estimate that stellar pulsations with amplitudes larger than ∼0.5 m s−1 can be detected with a 90 per cent completeness with our observations. This result, along with the excess of power regions detected in the periodograms, opens the possibility of non-resolved very low amplitude pulsation signals. Next generation more precise instrumentation would be required to detect such oscillations. However, the possibility of detecting pulsating M-dwarf stars with larger amplitudes is feasible due to the short size of the analysed sample. This motivates the need for completeness of the CTB survey.
Structure of quantum stochastic processes with finite Markov order

Non-Markovian quantum processes exhibit different memory effects when measured in different ways; an unambiguous characterization of memory length requires accounting for the sequence of instruments applied to probe the system dynamics. This instrument-specific notion of quantum Markov order displays stark differences to its classical counterpart. Here, we explore the structure of quantum stochastic processes with finite memory length in detail. We begin by examining a generalized collision model with memory, before framing this instance within the general theory. We detail the constraints that are placed on the underlying system-environment dynamics for a process to exhibit finite Markov order with respect to natural classes of probing instruments, including deterministic (unitary) operations and sequences of generalized quantum measurements with informationally complete repreparations. Lastly, we show how processes with vanishing quantum conditional mutual information form a special case of the theory. Throughout, we provide a number of representative, pedagogical examples to display the salient features of memory effects in quantum processes.