Miracle-dz/UniFAR-FTUs huggingface dataset:
Homopiperazine Derivatives as a Novel Class of Proteasome Inhibitors with a Unique Mode of Proteasome Binding

The proteasome is a proteolytic machinery that executes the degradation of polyubiquitinated proteins to maintain cellular homeostasis. Proteasome inhibition is a unique and effective way to kill cancer cells because they are sensitive to proteotoxic stress. Indeed, the proteasome inhibitor bortezomib is now indispensable for the treatment of multiple myeloma and other intractable malignancies, but is associated with patient inconvenience due to intravenous injection and emerging drug resistance. To resolve these problems, we attempted to develop orally bioavailable proteasome inhibitors with distinct mechanisms of action and identified homopiperazine derivatives (HPDs) as promising candidates. Biochemical and crystallographic studies revealed that some HPDs inhibit all three catalytic subunits (ß 1, ß 2 and ß 5) of the proteasome by direct binding, whereas bortezomib and other proteasome inhibitors mainly act on the ß5 subunit. Proteasome-inhibitory HPDs exhibited cytotoxic effects on cell lines from various hematological malignancies including myeloma. Furthermore, K-7174, one of the HPDs, was able to inhibit the growth of bortezomib-resistant myeloma cells carrying a ß5-subunit mutation. Finally, K-7174 had additive effects with bortezomib on proteasome inhibition and apoptosis induction in myeloma cells. Taken together, HPDs could be a new class of proteasome inhibitors, which compensate for the weak points of conventional ones and overcome the resistance to bortezomib.
Graphene nanostructures toward clean energy technology applications

Graphene, a one‐atom‐layer‐thick carbon‐structured material, has attracted global research attention due to its unique two‐dimensional structure, high electrical conductivity, superior electron‐transfer properties and charge‐carrier charge‐carrier mobility, large specific surface area, high transparency, and good mechanical properties. After its successful isolation into the free standing form in 2004, various graphene nanostructures have been developed and incorporated as key components in supercapacitors, lithium‐ion batteries, solar cells, and fuel cells; the energy supporting devices which hold the key role to sustain our energy demand well into the future. Herein, we summarized the recent progress and performance of these graphene–nanostructure‐based devices.
Optical Graphene Gas Sensors Based on Microfibers: A Review

Graphene has become a bridge across optoelectronics, mechanics, and bio-chemical sensing due to its unique photoelectric characteristics. Moreover, benefiting from its two-dimensional nature, this atomically thick film with full flexibility has been widely incorporated with optical waveguides such as fibers, realizing novel photonic devices including polarizers, lasers, and sensors. Among the graphene-based optical devices, sensor is one of the most important branch, especially for gas sensing, as rapid progress has been made in both sensing structures and devices in recent years. This article presents a comprehensive and systematic overview of graphene-based microfiber gas sensors regarding many aspects including sensing principles, properties, fabrication, interrogating and implementations.
Semantic Web technology-driven Geosciences Network

In this white paper, it is argued that the design and architecture of the geosciences network, as envisioned in the EarthCube framework, can be based on the Semantic Web (SW) technology. The SW technology offers the best solutions to enable the required semantic-based integration of data by providing formal (i.e., machine readable) and explicit meaning for geoscience data, thus enhancing their understanding by geoscientists. The Web Ontology Language (OWL) and its underlying RDF and RDFS languages, with the help of the Unique Resource Identifier (URI) and the HTTP protocol, allow geoscientists in different fields to build and deploy ontologies. The main purpose of building ontologies is to represent and manage domain knowledge, and to discover new knowledge, with the help of the semantic rules embedded in these languages, applying the reasoning power of the SW query languages such as SPARQL. The Semantic Web technology enables us to reach the cardinal goal of global integration of geosciences data, advancing knowledge, building effective search and query tools, and achieving interoperability and intercommunication among geoscientists and their resources at all levels in each community. We argue that the self-similarity that characterizes the research of interacting geosciences communities, and that of many geological processes, requires a fractal structuring of resources, such as software, database, ontology, and tools, over a wide range of scales, from individuals to progressively larger communities, on the proposed network.
Hybrid position-position and position-speed command strategy for the bilateral teleoperation of a mobile robot

In this paper a control method for the bilateral teleoperation of a mobile robot was proposed, which is combining position-position and position-speed command strategies. We consider bilateral teleoperation of a wheeled mobile robot. Our main objective is to combine position-speed command strategy, which is usual for mobile robot control, with position-position command strategy. Generally teleoperation scheme has two control modes, which are position-speed mode and position-position mode. In position-speed mode, a master haptic manipulator's position defines the linear velocity and heading angle of the mobile robot. In position-position mode, the position of the robot is controlled based on the position of the master device. In this paper we propose a strategy to adapt a reasonable control mode automatically. Sonar sensors were used to detect obstacle range information, which is the source of force feedback to human operator. Developed scheme was tested with numerical simulations and experiments. The different types of navigation tasks were evaluated. Productivity, accuracy and usability of hybrid control strategy are analyzed. Flexible and intuitive control was achieved.
Automation Bias and Errors: Are Crews Better Than Individuals?

The availability of automated decision aids can sometimes feed into the general human tendency to travel the road of least cognitive effort. Is this tendency toward "automation bias" (the use of automation as a heuristic replacement for vigilant information seeking and processing) ameliorated when more than one decision maker is monitoring system events? This study examined automation bias in two-person crews versus solo performers under varying instruction conditions. Training that focused on automation bias and associated errors successfully reduced commission, but not omission, errors. Teams and solo performers were equally likely to fail to respond to system irregularities or events when automated devices failed to indicate them, and to incorrectly follow automated directives when they contradicted other system information.
Understanding the behavioral differences between american and german users: A data-driven study

Given that the USA and Germany are the most populous countries in North America and Western Europe, understanding the behavioral differences between American and German users of online social networks is essential. In this work, we conduct a data-driven study based on the Yelp Open Dataset. We demonstrate the behavioral characteristics of both American and German users from different aspects, i.e., social connectivity, review styles, and spatiotemporal patterns. In addition, we construct a classification model to accurately recognize American and German users according to the behavioral data. Our model achieves high classification performance with an F1-score of 0.891 and AUC of 0.949.
Medical cannabis – the Canadian perspective

Cannabis has been widely used as a medicinal agent in Eastern medicine with earliest evidence in ancient Chinese practice dating back to 2700 BC. Over time, the use of medical cannabis has been increasingly adopted by Western medicine and is thus a rapidly emerging field that all pain physicians need to be aware of. Several randomized controlled trials have shown a significant and dose-dependent relationship between neuropathic pain relief and tetrahydrocannabinol – the principal psychoactive component of cannabis. Despite this, barriers exist to use from both the patient perspective (cost, addiction, social stigma, lack of understanding regarding safe administration) and the physician perspective (credibility, criminality, clinical evidence, patient addiction, and policy from the governing medical colleges). This review addresses these barriers and draws attention to key concerns in the Canadian medical system, providing updated treatment approaches to help clinicians work with their patients in achieving adequate pain control, reduced narcotic medication use, and enhanced quality of life. This review also includes case studies demonstrating the use of medical marijuana by patients with neuropathic low-back pain, neuropathic pain in fibromyalgia, and neuropathic pain in multiple sclerosis. While significant preclinical data have demonstrated the potential therapeutic benefits of cannabis for treating pain in osteoarthritis, rheumatoid arthritis, fibromyalgia, and cancer, further studies are needed with randomized controlled trials and larger study populations to identify the specific strains and concentrations that will work best with selected cohorts.
Monitoring of change in cantaloupe fruit quality under pre-cooling and storage treatments.

During recent years, global concern for protection of the environment has led researchers to improving postharvest treatments such (precooling, handling, storage, etc.,). The present investigation was also directed to find out the precooling and storage alternatives for the extension of the storage life of cantaloupe fruits (Cucumis melon). Fruits were harvested at the mature stage and precooled by forcing cooling air with velocity of 1-2 m/s at three different air temperatures of 5°C, 10°C and 15°C. The fruits were analyzed for physiological characters such as loss in weight, fruit firmness, change in color surface of fruit and its flesh. Fruit temperature expectedly decreased from initial level of about 36-38°C to the desired storage temperature of 10°C by forcing cooling air at 5°C, for about 45 min. Cooling time increased to 105 and 165 min when cooling air temperature increased to 10°C and 15°C, respectively. During subsequent storage at 15°C with 90-95% relative humidity, precooled fruits were exhibit more desirable characteristics than that of non-precooled fruits (control), where precooling was retard softening. Non precooled fruits “control” turned ripe-soft after 15 days when firmness decreased to less than 10 N from initial value of 90 N at the unripe stage.
Silicon Oil-Based 2-Channel Fiber-Optic Temperature Sensor Using a Subtraction Method

We developed a 2-channel fiber-optic temperature sensor (FOTS) using a temperature sensing probe, a fiber-optic coupler, transmitting optical fiber, and an optical time domain reflectometer (OTDR). The temperature sensing probe is divided into a sensing probe and a reference probe for accurate thermometry. A sensing probe is composed of a silicon oil, a FC terminator, a brass pipe, and a singlemode optical fiber and the structure of a reference probe is identical with that of the sensing probe excluding a silicon oil. In this study, we measured the modified optical powers of the light signals reflected from the temperature sensing probe placed inside of the water with a thermal variation from 5 to 70oC. Although the optical power of the reference probe was constant regardless of the temperature change, the optical power of the sensing probe decreased linearly as the temperature increased. As experimental results, the FOTS using a subtraction method showed a small difference (i.e., hysteresis) in its response due to heating and cooling. The reversibility and reproducibility of the FOTS were also evaluated.
Fabrication of Bioactive Glass Fiber Reinforced Polyamide with High Mechanical Performance by the Function of Apatite Nuclei

We immersed micropores-formed glass fiber reinforced polyamide MXD6 (GFR-MXD6) in SBF and precipitated apatite nuclei in the pores of the substrate by raising both the pH and the temperature of SBF and obtained bioactive GFR-MXD6. By immersing in SBF, hydroxyapatite formation was induced by the apatite nuclei in the pores and grew to the surface of the substrate. High adhesive strength between the formed hydroxyapatite and the substrate was obtained by a mechanical interlocking effect.
Current Science

WITH the publication of its July issue, our Indian contemporary, Current Science, enters upon its fifth year. Founded to supply an obvious need in the scientific renaissance of India, Current Science is almost unique in that its editor is assisted by a board comprising the majority of the best-known Indian men of science. The July issue contains much of interest not only to India but also to the West. The leading article comments on the inauguration, by his Excellency the Viceroy, of a Nutrition Advisory Committee. The outstanding investigations of Sir Robert McCarrison in Coonoor have in recent years focused the attention of Indian public opinion upon the importance of adequate feeding for national efficiency. Inadequate nutrition, combined in many areas with endemic malaria, is known to be the cause of the poor physique of many classes. The Royal Society is now assisting in the investigation of the intricate problems of malaria control, and will doubtless co-operate with this new Advisory Committee. Another article in the July issue, of more than local interest, is the summary of a lecture given by Prof. Birbal Sahni on the Karewas of Kashmir, where the geology, of the Karewas series in the Himalayas is discussed from the point of view of the botanist. We congratulate the editor of Current Science on the high standard of the journal, which, if maintained, ensures its continued success.
An Improvement Program as a Way to Intensify Inter-Professional Collaboration in the Community for People with Mental Disabilities: A Follow-Up

The aim of the study was to follow up inter-professional experiences of improvement work one year after a completed CII improvement program aiming at improve health care and social services for people with mental disabilities living in ordinary housing. This study was performed with a qualitative descriptive approach which employed six focus group interviews followed by a thematic analysis. The results revealed four themes; Self-awareness and insights; Behavior and actions in daily practice; Organizational cultures and subcultures; and Organizational practices, using Ken Wilbers' integral theory of four quadrants of realities as a holistic frame in the discussion.
Oxytocin selectively facilitates learning with social feedback and increases activity and functional connectivity in emotional memory and reward processing regions

In male Caucasian subjects, learning is facilitated by receipt of social compared with non‐social feedback, and the neuropeptide oxytocin (OXT) facilitates this effect. In this study, we have first shown a cultural difference in that male Chinese subjects actually perform significantly worse in the same reinforcement associated learning task with social (emotional faces) compared with non‐social feedback. Nevertheless, in two independent double‐blind placebo (PLC) controlled between‐subject design experiments we found OXT still selectively facilitated learning with social feedback. Similar to Caucasian subjects this OXT effect was strongest with feedback using female rather than male faces. One experiment performed in conjunction with functional magnetic resonance imaging showed that during the response, but not feedback phase of the task, OXT selectively increased activity in the amygdala, hippocampus, parahippocampal gyrus and putamen during the social feedback condition, and functional connectivity between the amygdala and insula and caudate. Therefore, OXT may be increasing the salience and reward value of anticipated social feedback. In the PLC group, response times and state anxiety scores during social feedback were associated with signal changes in these same regions but not in the OXT group. OXT may therefore have also facilitated learning by reducing anxiety in the social feedback condition. Overall our results provide the first evidence for cultural differences in social facilitation of learning per se, but a similar selective enhancement of learning with social feedback under OXT. This effect of OXT may be associated with enhanced responses and functional connectivity in emotional memory and reward processing regions. Hum Brain Mapp 36:2132–2146, 2015. © 2015 Wiley Periodicals, Inc.
Microstructure and Mechanical Properties of WC-Co Reinforced With NbC

Cemented carbides such as tungsten carbide-cobalt WC-Co composites have been widely used as cutting tool materials. Several reports have shown the influence of different factors such as grain size, type and amount of binder phase and the addition of hard particles on the properties of WC-Co. The purpose of this work was to investigate the effect of niobium carbide on the microstructure and mechanical properties of WC-Co. Specimens of WC-Co reinforced with NbC were mixed and subsequently hot-pressed in a inert atmosphere. The WC-Co-NbC composite material exhibited high hardness values (18.9 GPa), flexural strength (2100 MPa) and fracture toughness (11.2 MPa.m1/2 ). TEM analysis has shown a bimodal grain size distribution of WC.
Low Rank Enhanced Matrix Recovery of Hybrid Time and Frequency Data in Fast Magnetic Resonance Spectroscopy

Goal: The two dimensional magnetic resonance spectroscopy (MRS) possesses many important applications in bioengineering but suffers from long acquisition duration. Non-uniform sampling has been applied to the spatiotemporally encoded ultrafast MRS, but results in missing data in the hybrid time and frequency plane. An approach is proposed to recover this missing signal, of which enables high quality spectrum reconstruction. M ethods: The natural exponential characteristic of MRS is exploited to recover the hybrid time and frequency signal. The reconstruction issue is formulated as a low rank enhanced Hankel matrix completion problem and is solved by a fast numerical algorithm. Results: Experiments on synthetic and real MRS data show that the proposed method provides faithful spectrum reconstruction, and outperforms the state-of-the-art compressed sensing approach on recovering low-intensity spectral peaks and robustness to different sampling patterns. C onclusion: The exponential signal property serves as an useful tool to model the time-domain MRS signals and even allows missing data recovery. The proposed method has been shown to reconstruct high quality MRS spectra from non-uniformly sampled data in the hybrid time and frequency plane. Significance: Low-intensity signal reconstruction is generally challenging in biological MRS and we provide a solution to this problem. The proposed method may be extended to recover signals that generally can be modeled as a sum of exponential functions in biomedical engineering applications, e.g., signal enhancement, feature extraction, and fast sampling.
On the statistical distribution of object-oriented system properties

The statistical distributions of different software properties have been thoroughly studied in the past, including software size, complexity and the number of defects. In the case of object-oriented systems, these distributions have been found to obey a power law, a common statistical distribution also found in many other fields. However, we have found that for some statistical properties, the behavior does not entirely follow a power law, but a mixture between a lognormal and a power law distribution. Our study is based on the Qualitas Corpus, a large compendium of diverse Java-based software projects. We have measured the Chidamber and Kemerer metrics suite for every file of every Java project in the corpus. Our results show that the range of high values for the different metrics follows a power law distribution, whereas the rest of the range follows a lognormal distribution. This is a pattern typical of so-called double Pareto distributions, also found in empirical studies for other software properties.
Sub 100 nW Volatile Nano-Metal-Oxide Memristor as Synaptic-Like Encoder of Neuronal Spikes

Advanced neural interfaces mediate a bioelectronic link between the nervous system and microelectronic devices, bearing great potential as innovative therapy for various diseases. Spikes from a large number of neurons are recorded leading to creation of big data that require online processing under most stringent conditions, such as minimal power dissipation and on-chip space occupancy. Here, we present a new concept where the inherent volatile properties of a nano-scale memristive device are used to detect and compress information on neural spikes as recorded by a multielectrode array. Simultaneously, and similarly to a biological synapse, information on spike amplitude and frequency is transduced in metastable resistive state transitions of the device, which is inherently capable of self-resetting and of continuous encoding of spiking activity. Furthermore, operating the memristor in a very high resistive state range reduces its average in-operando power dissipation to less than 100 nW, demonstrating the potential to build highly scalable, yet energy-efficient on-node processors for advanced neural interfaces.
Mechanical Characterization of Boron-Nitride Nanoribbons via Nonlinear Structural Mechanics

In the present paper, the tensile mechanical behavior of different sized, almost squared shaped, boron nitride nanoribbons is numerically investigated and predicted by using a structural mechanics approach based on the use of appropriate nonlinear potential functions concerning both two-body and three-body interatomic interactions appearing within their nanostructure. According to the proposed method, appropriate spring elements are combined in nanoscale in order to simulate the interatomic interactions appearing within boron-nitride nanostructure. The dimensions of boron-nitride nanoribbons as well as the shape of their edges, which may be armchair or zigzag, have influence on the overall behavior of the nanoribbons. Therefore, the study focuses on the prediction of tensile stress-strain behavior of boron-nitride nanoribbons of different sizes and edge shapes as well as on the estimation of significant corresponding material properties such as Young’s modulus, tensile strength, tensile failure strain and tensile toughness. The numerical results, which are compared with corresponding data given in the open literature where possible, demonstrate thoroughly the important influence of size and chirality of a narrow boron nitride monolayer on its mechanical behavior.