Miracle-dz/UniFAR-FTUs huggingface dataset:
Ligand Discovery for the Alanine-Serine-Cysteine Transporter (ASCT2, SLC1A5) from Homology Modeling and Virtual Screening

The Alanine-Serine-Cysteine transporter ASCT2 (SLC1A5) is a membrane protein that transports neutral amino acids into cells in exchange for outward movement of intracellular amino acids. ASCT2 is highly expressed in peripheral tissues such as the lung and intestines where it contributes to the homeostasis of intracellular concentrations of neutral amino acids. ASCT2 also plays an important role in the development of a variety of cancers such as melanoma by transporting amino acid nutrients such as glutamine into the proliferating tumors. Therefore, ASCT2 is a key drug target with potentially great pharmacological importance. Here, we identify seven ASCT2 ligands by computational modeling and experimental testing. In particular, we construct homology models based on crystallographic structures of the aspartate transporter GltPh in two different conformations. Optimization of the models’ binding sites for protein-ligand complementarity reveals new putative pockets that can be targeted via structure-based drug design. Virtual screening of drugs, metabolites, fragments-like, and lead-like molecules from the ZINC database, followed by experimental testing of 14 top hits with functional measurements using electrophysiological methods reveals seven ligands, including five activators and two inhibitors. For example, aminooxetane-3-carboxylate is a more efficient activator than any other known ASCT2 natural or unnatural substrate. Furthermore, two of the hits inhibited ASCT2 mediated glutamine uptake and proliferation of a melanoma cancer cell line. Our results improve our understanding of how substrate specificity is determined in amino acid transporters, as well as provide novel scaffolds for developing chemical tools targeting ASCT2, an emerging therapeutic target for cancer and neurological disorders.
Detail to Attention: Exploiting Visual Tasks for Selective Rendering

The perceived quality of computer graphics imagery depends on the accuracy of the rendered frames, as well as the capabilities of the human visual system. Fully detailed, high fidelity frames still take many minutes even hours to render on today's computers. The human eye is physically incapable of capturing a moving scene in full detail. We sense image detail only in a 2° foveal region, relying on rapid eye movements, or saccades, to jump between points of interest. Our brain then reassembles these glimpses into a coherent, but inevitably imperfect, visual percept of the environment. In the process, we literally lose sight of the unimportant details. In this paper, we demonstrate how properties of the human visual system, in particular inattentional blindness, can be exploited to accelerate the rendering of animated sequences by applying a priori knowledge of a viewer's task focus. We show in a controlled experimental setting how human subjects will consistently fail to notice degradations in the quality of image details unrelated to their assigned task, even when these details fall under the viewers' gaze. We then build on these observations to create a perceptual rendering framework that combines predetermined task maps with spatiotemporal contrast sensitivity to guide a progressive animation system which takes full advantage of image-based rendering techniques. We demonstrate this framework with a Radiance ray-tracing implementation that completes its work in a fraction of the normally required time, with few noticeable artifacts for viewers performing the task.
A Pilot Study of an mHealth Application for Healthcare Workers: Poor Uptake Despite High Reported Acceptability at a Rural South African Community-Based MDR-TB Treatment Program

Introduction As the South African province of KwaZulu-Natal addresses a growing multidrug-resistant tuberculosis (MDR-TB) epidemic by shifting care and treatment from trained specialty centers to community hospitals, delivering and monitoring MDR-TB therapy has presented new challenges. In particular, tracking and reporting adverse clinical events have been difficult for mobile healthcare workers (HCWs), trained health professionals who travel daily to patient homes to administer and monitor therapy. We designed and piloted a mobile phone application (Mobilize) for mobile HCWs that electronically standardized the recording and tracking of MDR-TB patients on low-cost, functional phones. Objective We assess the acceptability and feasibility of using Mobilize to record and submit adverse events forms weekly during the intensive phase of MDR-TB therapy and evaluate mobile HCW perceptions throughout the pilot period. Methods All five mobile HCWs at one site were trained and provided with phones. Utilizing a mixed-methods evaluation, mobile HCWs’ usage patterns were tracked electronically for seven months and analyzed. Qualitative focus groups and questionnaires were designed to understand the impact of mobile phone technology on the work environment. Results Mobile HCWs submitted nine of 33 (27%) expected adverse events forms, conflicting with qualitative results in which mobile HCWs stated that Mobilize improved adverse events communication, helped their daily workflow, and could be successfully expanded to other health interventions. When presented with the conflict between their expressed views and actual practice, mobile HCWs cited forgetfulness and believed patients should take more responsibility for their own care. Discussion This pilot experience demonstrated poor uptake by HCWs despite positive responses to using mHealth. Though our results should be interpreted cautiously because of the small number of mobile HCWs and MDR-TB patients in this study, we recommend carefully exploring the motivations of HCWs and technologic enhancements prior to scaling new mHealth initiatives in resource poor settings.
DNA Barcoding for Efficient Species- and Pathovar-Level Identification of the Quarantine Plant Pathogen Xanthomonas

Genus Xanthomonas comprises many economically important plant pathogens that affect a wide range of hosts. Indeed, fourteen Xanthomonas species/pathovars have been regarded as official quarantine bacteria for imports in China. To date, however, a rapid and accurate method capable of identifying all of the quarantine species/pathovars has yet to be developed. In this study, we therefore evaluated the capacity of DNA barcoding as a digital identification method for discriminating quarantine species/pathovars of Xanthomonas. For these analyses, 327 isolates, representing 45 Xanthomonas species/pathovars, as well as five additional species/pathovars from GenBank (50 species/pathovars total), were utilized to test the efficacy of four DNA barcode candidate genes (16S rRNA gene, cpn60, gyrB, and avrBs2). Of these candidate genes, cpn60 displayed the highest rate of PCR amplification and sequencing success. The tree-building (Neighbor-joining), ‘best close match’, and barcode gap methods were subsequently employed to assess the species- and pathovar-level resolution of each gene. Notably, all isolates of each quarantine species/pathovars formed a monophyletic group in the neighbor-joining tree constructed using the cpn60 sequences. Moreover, cpn60 also demonstrated the most satisfactory results in both barcoding gap analysis and the ‘best close match’ test. Thus, compared with the other markers tested, cpn60 proved to be a powerful DNA barcode, providing a reliable and effective means for the species- and pathovar-level identification of the quarantine plant pathogen Xanthomonas.
Spread spectrum medium access protocol with collision avoidance in mobile ad-hoc wireless network

Spread spectrum techniques and collision avoidance multiple access protocols are combined to form a new set of medium access protocols for mobile wireless ad hoc networks. The request-to-send and clear-to-send message dialogue solves the "hidden terminal" and the "exposed terminal" problems and speeds up the retransmission. The spreading code assignment avoids disruption of any ongoing transmission by an intruder. Simulation results confirm that a higher channel throughput is achieved by the new protocols even in a dense network.
Magnetic resonance tagging or the mouse heart:a feasibility study

The availability of genetically modified mice offers unique opportunities to measure the effects of an increase or a decrease in the expression levels of specific genes, or to investigate the effect of targeted gene mutations. The phenotyping of such models calls for reliable and non-invasive tools for the in-vivo measurement of the consequences of the genetic modification. Magnetic Resonance Imaging (MRI) is rapidly becorning the most important imaging modality for measuring organ and tissue function of these genetically engineered rnice. This graduation report deals with the u se of MRI to measure the mouse heart function. A so-called "tagging MRI" imaging sequence is implemented, which allows for the determination of displacement and strain fields of the mouse heart muscle. This sequence introduces a modulation to the longitudinal spin magnetization, which results in a characteristic stripe pattem as a function of the position in the image. The movements of this stripe pattem can then be foliowed by using a fast readout imaging sequence. The sequence was tested on a rotating phantom. It is concluded that MR tagging experiments in vivo on mouse hearts are within experimental reach with the current MR instrument, provided the heart rate of the mouse can be lowered, by well controlled anaesthesia, to about 300-400 beats/min. In vivo experiments on rnice were not performed yet. Eindhoven University of Technology Magnetic Resonance Laboratories . I Edwin Heijman Graduation report
A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems

This paper proposes a new method for online secondary path modeling in active noise control systems. The existing methods for active noise control systems with online secondary path modeling consist of three adaptive filters. The main feature of the proposed method is that it uses only two adaptive filters. In the proposed method, the modified-FxLMS (MFxLMS) algorithm is used in adapting the noise control filter and a new variable step size (VSS) least mean square (LMS) algorithm is proposed for adaptation of the secondary path modeling filter. This VSS LMS algorithm is different from the normalized-LMS (NLMS) algorithm, where the step size is varied in accordance with the power of the reference signal. Here, on the other hand, the step size is varied in accordance with the power of the disturbance signal in the desired response of the modeling filter. The basic idea of the proposed VSS algorithm stems from the fact that the disturbance signal in the desired response of the modeling filter is decreasing in nature, (ideally) converging to zero. Hence, a small step size is used initially and later its value is increased accordingly. The disturbance signal, however, is not available directly, and we propose an indirect method to track its variations. Computer simulations show that the proposed method gives better performance than the existing methods. This improved performance is achieved at the cost of a slightly increased computational complexity.
Role of ERα in Mediating Female Uterine Transcriptional Responses to IGF1

Estrogen (E2) signaling through its nuclear receptor, E2 receptor α (ERα) increases insulinlike growth factor 1 (IGF1) in the rodent uterus, which then initiates further signals via the IGF1 receptor. Directly administering IGF1 results in similar biological and transcriptional uterine responses. Our studies using global ERα-null mice demonstrated a loss of uterine biological responses of the uterus to E2 or IGF1 treatment, while maintaining transcriptional responses to IGF1. To address this discrepancy in the need for uterine ERα in mediating the IGF1 transcriptional vs growth responses, we assessed the IGF1 transcriptional responses in PgrCre+Esr1f/f (called ERαUtcKO) mice, which selectively lack ERα in progesterone receptor (PGR) expressing cells, including all uterine cells, while maintaining ERα expression in other tissues and cells that do not express Pgr. Additionally, we profiled IGF1-induced ERα binding sites in uterine chromatin using chromatin immunoprecipitation sequencing. Herein, we explore the transcriptional and molecular signaling that underlies our findings to refine our understanding of uterine IGF1 signaling and identify ERα-mediated and ERα-independent uterine transcriptional responses. Defining these mechanisms in vivo in whole tissue and animal contexts provides details of nuclear receptor mediated mechanisms that impact biological systems and have potential applicability to reproductive processes of humans, livestock and wildlife.
Internal Fixation of Femoral Bone Comminuted Fracture - FE Analysis

This paper presents finite element analysis of the mechanical stability of some fixation solution often used in treatment of the femoral bone comminuted fractures. In this study we consider two, most popular, fixation devices: neutralization plate and intramedullary nail. Fixation devices were assumed to be made of stainless steel – modelled as elastic material, and bone tissue is modelled using nonlinear viscoelastic material model proposed by Carter and Hayes [1]. This study reveals advantages and disadvantages of analysed fixation devices regarding the stress distribution within the material and hence mechanical stability.
A compact factored representation of heterogeneous subsurface scattering

Many translucent materials exhibit heterogeneous subsurface scattering, which arises from complex internal structures. The acquisition and representation of these scattering functions is a complex problem that has been only partially addressed in previous techniques. Unlike homogeneous materials, the spatial component of heterogeneous subsurface scattering can vary arbitrarily over surface locations. Storing the spatial component without compression leads to impractically large datasets. In this paper, we address the problem of acquiring and compactly representing the spatial component of heterogeneous subsurface scattering functions. We propose a material model based on matrix factorization that can be mapped onto arbitrary geometry, and, due to its compact form, can be incorporated into most visualization systems with little overhead. We present results of several real-world datasets that are acquired using a projector and a digital camera.
An Intrinsic Graphical Signature Based on Alert Correlation Analysis for Intrusion Detection

We propose a graphical signature for intrusion detection given alert sequences. By correlating alerts with their temporal proximity, we build a probabilistic graph-based model to describe a group of alerts that form an attack or normal behavior. Using the models, we design a pairwise measure based on manifold learning to measure the dissimilarities between different groups of alerts. A large dissimilarity implies different behaviors between the two groups of alerts. Such measure can therefore be combined with regular classification methods for intrusion detection. We evaluate our framework mainly on Acer 2007, a private dataset gathered from a well-known Security Operation Center in Taiwan. The performance on the real data suggests that the proposed method can achieve high detection accuracy. Moreover, the graphical structures and the representation from manifold learning naturally provide the visualized result suitable for further analysis from domain experts.
Counting occurrences for a finite set of words : an inclusion-exclusion approach

In this paper, we give the multivariate generating function counting texts according to their length and to the number of occurrences of words from a finite set. The application of the inclusion-exclusion principle to word counting due to Goulden and Jackson (1979, 1983) is used to derive the result. Unlike some other techniques which suppose that the set of words is reduced (i.e., where no two words are factor of one another), the finite set can be chosen arbitrarily. Noonan and Zeilberger (1999) already provided a MAPLE package treating the non-reduced case, without giving an expression of the generating function or a detailed proof. We give a complete proof validating the use of the inclusion-exclusion principle and compare the complexity of the method proposed here with the one using automata for solving the problem.
Heterogeneity in Macrophage Phagocytosis of Staphylococcus aureus Strains: High-Throughput Scanning Cytometry-Based Analysis

Alveolar macrophages (AMs) can phagocytose unopsonized pathogens such as S. aureus via innate immune receptors, such as scavenger receptors (SRs). Cytoskeletal events and signaling pathways involved in phagocytosis of unopsonized bacteria likely govern the fate of ingested pathogens, but are poorly characterized. We have developed a high-throughput scanning cytometry-based assay to quantify phagocytosis of S. aureus by adherent human blood-derived AM-like macrophages in a 96-well microplate format. Differential fluorescent labeling of internalized vs. bound bacteria or beads allowed automated image analysis of collapsed confocal stack images acquired by scanning cytometry, and quantification of total particles bound and percent of particles internalized. We compared the effects of the classic SR blocker polyinosinic acid, the cytoskeletal inhibitors cytochalasin D and nocodazole, and the signaling inhibitors staurosporine, Gö 6976, JNK Inhibitor I and KN-93, on phagocytosis of a panel of live unopsonized S. aureus strains, (Wood, Seattle 1945 (ATCC 25923), and RN6390), as well as a commercial killed Wood strain, heat-killed Wood strain and latex beads. Our results revealed failure of the SR inhibitor polyinosinic acid to block binding of any live S. aureus strains, suggesting that SR-mediated uptake of a commercial killed fluorescent bacterial particle does not accurately model interaction with viable bacteria. We also observed heterogeneity in the effects of cytoskeletal and signaling inhibitors on internalization of different S. aureus strains. The data suggest that uptake of unopsonized live S. aureus by human macrophages is not mediated by SRs, and that the cellular mechanical and signaling processes that mediate S. aureus phagocytosis vary. The findings also demonstrate the potential utility of high-throughput scanning cytometry techniques to study phagocytosis of S. aureus and other organisms in greater detail.
Trypsin from unicorn leatherjacket (Aluterus monoceros) pyloric caeca: purification and its use for preparation of fish protein hydrolysate with antioxidative activity.

BACKGROUND Fish proteases, especially trypsin, could be used to prepare fish protein hydrolysates with antioxidative activities. In this study, trypsin from the pyloric caeca of unicorn leatherjacket was purified by ammonium sulfate precipitation and soybean trypsin inhibitor (SBTI)-Sepharose 4B affinity chromatography. Hydrolysate from Indian mackerel protein isolate with different degrees of hydrolysis (20, 30 and 40% DH) was prepared using the purified trypsin, and antioxidative activities (1,1-diphenyl-2-picrylhydrazyl and 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) radical-scavenging activities, ferric-reducing antioxidant power and ferrous-chelating activity) of the hydrolysate were determined. RESULTS Trypsin was purified 26.43-fold with a yield of 13.43%. The purified trypsin had a molecular weight (MW) of 23.5 kDa and optimal activity at pH 8.0 and 55 °C. It displayed high stability in the pH range of 6.0-11.0 and was thermally stable up to 50 °C. Both SBTI (0.05 mmol L(-1)) and N-p-tosyl-L-lysine-chloromethylketone (5 mmol L(-1)) completely inhibited trypsin activity. Antioxidative activities of the hydrolysate from Indian mackerel protein isolate increased with increasing DH up to 40% (P < 0.05). Based on sodium dodecyl sulfate polyacrylamide gel electrophoresis, the hydrolysate with 40% DH had a MW lower than 6.5 kDa. CONCLUSION The purified protease from unicorn leatherjacket pyloric caeca was identified as trypsin based on its ability to hydrolyze a specific synthetic substrate and the response to specific trypsin inhibitors. The purified trypsin could hydrolyze Indian mackerel protein isolate, and the resulting hydrolysate exhibited antioxidative activity depending on its DH.
Doped Graphene as Non-Metallic Catalyst for Fuel Cells

Aiming a commercial development of proton exchange membrane fuel cells (PEMFC), a low cost, sustainable and high performance electrocatalyst for oxygen reduction reaction (ORR) with capability to replace/reduce rare metals, are high desirable. In this paper, we present a class of doped graphene, namely iodinated graphene with highly ORR electrochemical performances, synthesized by using the electrophilic substitution method. The prepared samples were characterized by different techniques, including Scanning Electron Microscopy SEM, X-ray photoelectron spectroscopy XPS, Raman spectroscopy, surface area measurement by BET method, that revealed the structure and morphology. The most highly iodinated graphene was tested in a single cell by measuring the cyclic voltammetry. The electrochemical performances were evaluated and compared with a typical PEMFC configuration, when a single cathodic peak at 0.2 V with a current density of – 3.67 mA cm-2 for the Pt/C electrode was obtained. The best electrochemical performances in terms of electrochemical active area, was obtained for a new concept of cathode composed from Pt/C – iodine doped graphene, when a well-defined peak centred at 0.23 V with a current density of approx. – 9.1 mA cm-2 was obtained, indicating a high catalytic activity for ORR.DOI: http://dx.doi. org/10.5755/j01.ms.23.2. 16216
Search for Patterns in Compressed Time Series

We describe a technique for fast compression of time series, indexing of compressed series, and retrieval of series similar to a given pattern. The compression procedure identifies "important" points of a series and discards the other points. We use the important points not only for compression, but also for indexing a database of time series. Experiments show the effectiveness of this technique for indexing of stock prices, weather data and electroencephalograms.
Sustainable innovation journeys: exploring the dynamics of firm practices as part of transitions to more sustainable food and farming

Deep structural and sustained change is necessary to tackle contemporary environmental challenges. How such change emerges and can be governed has been explored through the notion of sustainable innovation journeys. To date research had conceptualised such journeys as transitions to more sustainable socio-technical systems, e.g. mobility, shelter, food and farming. However, there is a paucity of how innovation proceeds in firms as part of sustainable innovation journeys. This paper begins to address this gap in knowledge. A longitudinal case study was completed of a medium-sized food-processing firm in the UK. Qualitative data were collected using ethnographic methods such as participant observation. Drawing on practice theory, a conceptual framework was developed which enabled us to explore and make sense of the firm's sustainable innovation journey conceptualised as practices. Findings show that we can usefully treat a firm as a flow of practices that either resist or otherwise accommodate new practices deemed more sustainable.