Miracle-dz/UniFAR-FTUs huggingface dataset:
outputs SentiCircles : A Platform for Contextual and Conceptual Sentiment Analysis

Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics’ feelings towards policies, brands, business, etc. In this paper we present SentiCircles, a platform that captures feedback from social media conversations and applies contextual and conceptual sentiment analysis models to extract and summarise sentiment from these conversations. It provides a novel sentiment navigation design where contextual sentiment is captured and presented at term/entity level, enabling a better alignment of positive and negative sentiment to the nature of the public debate.
Cryptic proteins translated from deletion-containing viral genomes dramatically expand the influenza virus proteome.

Productive infections by RNA viruses require faithful replication of the entire genome. Yet many RNA viruses also produce deletion-containing viral genomes (DelVGs), aberrant replication products with large internal deletions. DelVGs interfere with the replication of wild-type virus and their presence in patients is associated with better clinical outcomes. The DelVG RNA itself is hypothesized to confer this interfering activity. DelVGs antagonize replication by out-competing the full-length genome and triggering innate immune responses. Here, we identify an additionally inhibitory mechanism mediated by a new class of viral proteins encoded by DelVGs. We identified hundreds of cryptic viral proteins translated from DelVGs. These DelVG-encoded proteins (DPRs) include canonical viral proteins with large internal deletions, as well as proteins with novel C-termini translated from alternative reading frames. Many DPRs retain functional domains shared with their full-length counterparts, suggesting they may have activity during infection. Mechanistic studies of DPRs derived from the influenza virus protein PB2 showed that they poison replication of wild-type virus by acting as dominant-negative inhibitors of the viral polymerase. These findings reveal that DelVGs have a dual inhibitory mechanism, acting at both the RNA and protein level. They further show that DPRs have the potential to dramatically expand the functional proteomes of diverse RNA viruses.
Sketching User Experiences: The Hands-on Course

When designing novel user interfaces, paper-pencil sketches can support the design thinking process and are valuable for communicating design ideas to others. This hands-on course will demonstrate how to integrate sketching into researchers' and interaction designers' everyday practice with a particular focus on the design of novel user experiences. Participants will learn essential sketching strategies, apply these in practice during many hands-on exercises, and learn the various ways of using sketches as a tool during all stages of the HCI research and design process. Our emphasis is on quick, easy to learn, and easy to apply methods for generating and refining ideas.
IL-6 predicts non-suicidal self-injury over 3 months in high-risk adolescents

Background Suicide is the second leading cause of death in 12- to 17-year-old adolescents in the USA. Research on biological mechanisms contributing to self-harm risk that could be targeted in treatment could help to prevent suicide and self-harm episodes. Aims We aimed to evaluate whether markers of inflammation, interleukin-6 (IL-6) and C-reactive protein (CRP), predict self-harm over 3 months within a sample selected for elevated suicide/self-harm risk at project entry. Method Fifty-one adolescents aged 12–19 years selected for elevated suicide/self-harm risk completed three clinical interviews about suicide attempts and non-suicidal self-injury, 3 months apart. At baseline and 3 months, youth also provided blood samples, from which we assayed levels of IL-6 and CRP. Results Using generalised mixed models, we found that greater levels of IL-6 predicted more self-harm episodes (odds ratio [OR] = 3.3, 95% CI: 1.1, 10.0) and specifically, non-suicidal self-injury (OR = 3.5, 95% CI: 1.1, 11.2), over 3 months. Conclusions The study findings increase our understanding of whether and how inflammation may be implicated in risk of self-harm. IL-6 may be a viable biological marker of short-term risk for self-harm.
Influence of hydrodynamic mixing on the distribution of dissolved 
organic carbon in the East China Sea and the northwest Pacific

Abstract. Oceanic dissolved organic carbon (DOC) is one of the largest carbon reservoirs on Earth, and its distribution and behavior play important roles in carbon cycling and biogeochemical processes in the ocean. Here, we report distribution and concentrations of DOC for water samples collected from the shelf-edge and slope regions in East China Sea (ECS) and the Kuroshio Extension (KE) in the northwestern North Pacific (NP) during two cruises in 2014–2015. Concentrations of DOC were 45–88 µM in the ECS and 35–65 µM in the KE. In addition to biological processes, the distribution of DOC is largely controlled by hydrodynamic mixing of different water masses. The intrusion of Kuroshio Current could dilute DOC concentrations at stations in the outer shelf and slope ranges of the ECS. The inverse correlation of DOC with apparent oxygen utilization (AOU) suggests that DOC oxidation only contributes 18 % of the oxygen consumption in the ECS slope waters. In contrast, concentrations of DOC in the KE were significantly lower in surface waters, and a relatively low and stable DOC level (~ 40 µM) was found in deep waters. The observed spatial variations of DOC in the upper 700 m among the stations in the KE were largely influenced by the mixing of the two water masses carried by the two major western boundary currents: Kuroshio and Oyashio that mix and form the KE. The hydrodynamic processes play important roles not only in the distribution of DOC but nutrients as well, thus could have major impact to primary production and ecosystems in the KE region.
The domestic water supply puzzle in Zimbabwean cities: challenges and opportunities for Mtapa residential suburb, Gweru, Zimbabwe

Zimbabweâ€™s economic meltdown decade of 2000-2009 virtually paralyzed all socio-economic sectors including services delivery in urban areas. Economic sanctions imposed by the West, coupled with the climate change threat have only exacerbated the urban services delivery nightmare, especially the water delivery system. Notwithstanding, not all hope is lost. This study sought to assess the urban domestic water supply challenges and opportunities in Gweruâ€™s Mtapa (or Mutapa) suburb using questionnaires, interviews and direct observations. Questionnaires were self-administered to 56 systematically selected residents of Mtapa Sections 5 and 6, while interviews were conducted with 3 purposively sampled key respondents who included Gweru Residents Association Organizing Secretary, Councillor for ward 6 which covers Mtapa suburb, and Chief Water Technician responsible for water supply. Results confirm that Mtapa suburb faces serious water supply challenges. Over 50% of the respondents confirmed that the unreliable water supply situation has affected their use of the toilet and they now live in fear of diarrhoeal diseases due to this unsanitary situation. Over 80% of the respondents have a negative perception in terms of water service delivery. Women have been largely affected by this situation in that they cannot fetch enough water for all domestic purposes mainly due to the distance to the alternative water sources (boreholes). There are, however, a number of feasible opportunities which can be pursued to improve this poor water supply situation in Mtapa and the city of Gweru in general. The study recommends that Gweru City Council avoids politicizing agreements with international organizations to help reduce the water problems because this will block these organizations from financially and technically helping in service delivery. The study also recommends that City Council resume pumping of water into reservoir tanks so that in cases of emergency or breakdown of pumps, water will be available for domestic use by residents. This can be achieved since there is now the involvement of international organizations for financial assistance.
Standard Handbook Oil Spill Environmental Forensics : Fingerprinting and Source Identification Ed. 2

Standard Handbook Oil Spill Environmental Forensics: Fingerprinting and Source Identification, Second Edition, provides users with the latest information on the tools and methods that have become popular over the past ten years. The book presents practitioners with the latest environmental forensics techniques and best practices for quickly identifying the sources of spills, how to form an effective response, and how to determine liability. This second edition represents a complete overhaul of the existing chapters, and includes 13 new chapters on methods and applications, such as emerging application of PAHi isomers in oil spill forensics, development and application of computerized oil spill identification (COSI), and fingerprinting of oil in biological and passive sampling devices.Contains 13 new chapters on methods and applications, including emerging application of PAH isomers in oil drill forensics, the development and application of computerized oil spill identification (COSI), and the fingerprinting of oil in biological and passive sampling devicesPresents the latest technology and methods in biodegradation of oil hydrocarbons and its implications for source identification, surface trajectory modeling of marine oil spills, and identification of hydrocarbons in biological samples for source determinationContains new case studies to illustrate key applications, methods, and techniques
Bulletin of Electrical Engineering and Informatics

Received Mar 14, 2023 Revised May 25, 2023 Accepted Jun 5, 2023 As a result of notable progress in image processing and machine learning algorithms, generating, modifying, and manufacturing superior quality images has become less complicated. Nonetheless, malevolent individuals can exploit these tools to generate counterfeit images that seem genuine. Such fake images can be used to harm others, evade image detection algorithms, or deceive recognition classifiers. In this paper, we propose the implementation of the best-performing convolutional neural network (CNN) based classifier to distinguish between generated fake face images and real images. This paper aims to provide an in-depth discussion about the challenge of generated fake face image detection. We explain the different datasets and the various proposed deep learning models for fake face image detection. The models used were trained on a large dataset of real data from CelebA-HQ and fake data from a trained generative adversarial network (GAN) based generator. All testing models achieved high accuracy in detecting the fake images, especially residual neural network (ResNet50) which performed the best among with an accuracy of 99.43%.
Succession of an Upland Oak/Hickory Forest in the Central Hardwood Region

For the last 9,000-10,000 years the Central Hardwood Region (CHR) has been primarily composed of a mosaic of mesophytic communities in climax and communities of successional forest types dominated by oak (Quercus Linnaeus) and hickory (Carya Nuttall). Shade intolerant oak/hickory dominated forest types have been maintained by natural disturbance processes in synergy with anthropogenic causes, resulting in a large composition of communities which are neither at climatic nor edaphic climax. Reduction in fire events, thinning, forest grazing, and other disturbance processes over the last 80-100 years have coincided with decreased regeneration of shade intolerant species due to lack of adequate light availability and recruitment of shade tolerant species of communities dominated by American beech (Fagus grandifolia L.) and maple (Acer saccharum L.) into the overstory of forests typically dominated by oak/hickory. Forest inventory data at Trail of Tears State Forest was analyzed across two separate time events (1980 and 2014) to determine compositional and structural changes which have occurred. Density, basal area, and community patterns via ordination were compared across six Ecological Land Types (ELTs) to determine topography’s effect on composition. Community trends were analyzed via NMS Ordination and between ELTs by a Mantel Test. A Multi-Response Permutation Procedures (MRRP) was also used as a nonparametric method for assessing differences between ELTs examined in the NMS. Density and basal area between years for species, ELT, and species*ELT interactions were compared. Across all ELTs, between 1980 and 2014, overstory density decreased from 218 trees/ac in 1980 to 180 trees/ac in 2014 and basal area increased from 98 ft2/ac in 1980 to 106 ft2/ac in 2014. Maple basal area increased from 5 ft2/ac to 12 ft2/ac while beech increased from 1 ft2/ac to 8ft2/ac, signifying progression of these species from the understory up into the canopy. The component of soft masting species within the forest has also decreased sharply in the last 34 years. MRPP analysis of overstory compositional gradients reported distinct species compositions between ELTs, however the trend was weak (MRPP: p
Longtime variation of phytoplankton in the South China Sea from the perspective of carbon fixation

The ocean is a huge carbon pool in the earth, and about half of the anthropogenic emissions of carbon dioxide are absorbed by the ocean each year. By converting inorganic carbon into organic carbon, the photosynthesis process of phytoplankton affords an important way for carbon sequestration in the ocean. According to previous researches, primary production (NPP) and the structure of phytoplankton community are important in regulate the efficiency of biological carbon pump. This study examined the spatiotemporal variability of satellite remote sensing derived chlorophyll a concentration (Chla), phytoplankton carbon biomass (Carbon), composition ratio of micro-, nano- and pico- phytoplankton, NPP and integrated particulate organic carbon (IPOC) during 1998-2007 in the South China Sea (SCS). Micro-, nano-phytoplankton and NPP showed similar seasonal variation with highest values in winter (January) (especially in the western ocean of Luzon Strait) and lowest values in summer (July) in SCS. Chla, phytoplankton carbon biomass, and IPOC showed different seasonal trends with one peak values occurred in winter and lowest in spring. Two sampling areas (A, N:17-21°, E:117.5-120° and B, N:12.5-15°, E:112-119°) in SCS were selected based on spatial distribution of the standard deviation of research parameters mentioned above. Compared to Chla, phytoplankton carbon biomass, NPP and IPOC, the interannual changes of phytoplankton community structure were remarkable in the two areas. The fraction of micro- and nano- phytoplankton in SCS tend to rise when La Nina events occur. Our results contribute to an understanding of the response of phytoplankton to climate change in the marginal sea. To quantify the efficiency of biological carbon pump in this area, more attention should be paid to the development of remote sensing algorithms of export NPP (or POC export flux) as well as the regulate mechanism of export NPP.
Detecting Real Earthquakes Using Artificial Earthquakes: On the Use of Synthetic Waveforms in Matched‐Filter Earthquake Detection

Matched‐filters are an increasingly popular tool for earthquake detection, but their reliance on a priori knowledge of the targets of interest limits their application to regions with previously documented seismicity. We explore an extension to the matched‐filter method to detect earthquakes and low‐frequency earthquakes on local to regional scales. We show that it is possible to increase the number of detections compared with standard energy‐based methods, with low false‐detection rates, using suites of synthetic waveforms as templates. We apply this to a microearthquake swarm and an aftershock sequence, and to detect low‐frequency earthquakes. We also explore the sensitivity of detections to the synthetic source's location and focal mechanism. Source‐receiver geometry has a first‐order control on how sensitive matched‐filter detectors are to variations in source location and focal mechanism, and this likely applies to detections made using both synthetic and real templates.
Computer Energy Aware Routing Protocol Based on Adaptive Transmission Range and Fuzzy Threshold Energy

— Energy efficiency is a critical issue for battery-powered mobile devices in ad hoc networks, wherein routing based on energy-related parameters is used to extend the network lifetime. In this paper, a comprehensive energy optimized cross layer routing algorithm is proposed and is implemented with ad hoc on demand distance vector routing (AODV). Transmission power is varied in accordance with the required transmission range ensuring sufficient number of mobile nodes to maintain network connectivity. Further, a power aware routing algorithm based on the adaptive fuzzy threshold energy is used for routing of packets. The results are compared with the traditional AODV routing algorithm and also with power aware routing algorithm based on adaptive fuzzy threshold energy (AFTE). The proposed routing algorithm based on adaptive transmission range with AODV (ATRAODV) is able to extend network lifetime longer as compared to AODV and AFTE routing algorithms.
Principle of Wireless Sensor Networks

Wireless sensor networks are a subset of wireless networking applications, which focus on enabling connectivity without, the need, generally, of wires to connect to the sensors and actuators (Gutierrez et al. 2004). Due to the length of the name ‘‘wireless sensor and actuator networks’’ or ‘‘wireless sensor and control networks’’, most people have adopted the shorter ‘‘wireless sensor networks’’ instead. In any case, it is important to remember that the design of this type of network is meant to collect information from wireless sensors and send control commands to actuators attached to the wireless network. Sensor and actuator networks have existed for decades. Computer based control systems are a typical hardwired sensor and actuator network. As shown in Fig. 2.1, sensors and actuators are connected with a central computer or control terminal via a data bus system or other networks and implement control and monitoring functions. This type of hardwired sensor network is simple and reliable, and often seen in industrial control such as process control and manufacturing production control. Because of the involvement of large amount of cabling in the installation, wired sensor networks are hard to extend. The installation cost of hardwired sensor networks is high, which takes in the form of cabling, labor, material, testing, and verification. Furthermore, cables require connectors that can become loose, lost, misconnected, or even break. This problem is commonly known as the last meter connectivity problem and is called this due to the analogous problem in a wide area network. The use of large number of hardwired sensors networked to a system brings considerable complexity to the system, including cabling deployment, power supply, and configuration, making it impossible in many cases such as forest monitoring and battlefield surveillance. Recent Integrated Circuit (IC) and Micro
On the second eigenvalue of random regular graphs

Expanders have many applications in Computer Science. It is known that random d-regular graphs are very efficient expanders, almost surely. However, checking whether a particular graph is a good expander is co-NP-complete. We show that the second eigenvalue of d-regular graphs, λ2, is concentrated in an interval of width O(√d) around its mean, and that its mean is O(d3/4). The result holds under various models for random d-regular graphs. As a consequence a random d-regular graph on n vertices, is, with high probability a certifiable efficient expander for n sufficiently large. The bound on the width of the interval is derived from martingale theory and the bound on E(λ2) is obtained by exploring the properties of random walks in random graphs.
Computers & Graphics

We present a novel approach for 3D shape synthesis from a collection of existing models. The main idea of our approach is to synthesize shapes by recombining ﬁne-grained parts extracted from the existing models based purely on the objects’ geometry. Thus, unlike most previous works, a key advantage of our method is that it does not require a semantic segmentation, nor part correspondences between the shapes of the input set. Our method uses a template shape to guide the synthesis. After extracting a set of ﬁne-grained segments from the input dataset, we compute the similarity among the segments in the collection and segments of the template using shape descriptors. Next, we use the similarity estimates to select, from the set of ﬁne-grained segments, compatible replacements for each part of the template. By sampling di ﬀ erent segments for each part of the template, and by using di ﬀ erent templates, our method can synthesize many distinct shapes that have a variety of local ﬁne details. Additionally, we maintain the plausibility of the objects by preserving the general structure of the template. We show with several experiments performed on di ﬀ erent datasets that our algorithm can be used for synthesizing a wide variety of man-made objects.
A 1-Tap 40-Gb/s Look-Ahead Decision Feedback Equalizer in 0.18-$muhbox m$SiGe BiCMOS Technology

This paper describes a fully differential 1-tap decision feedback equalizer in 0.18-mum SiGe BiCMOS technology. The circuit is capable of equalizing NRZ data up to 40 Gb/s. A look-ahead architecture is employed with modifications to reduce complexity in the high-speed clock distribution. An analog differential voltage controls the tap weights. The design is fabricated in 0.18-mum SiGe BiCMOS technology with a 160-GHz fT. It occupies an area of 1.5 mmtimes1 mm and operates from a 3.3-V supply with 230-mA current. It is the first feedback equalizer at 40 Gb/s
Low-Power Near-Threshold Design: Techniques to Improve Energy Efficiency Energy-efficient near-threshold design has been proposed to increase energy efficiency across a wid

i»? Energy-efficient near-threshold design has been proposed to increase energy efficiency across a wide range of applications. This article first provides a background motivating near-threshold and how it differs from super-threshold and subthreshold operation. Next, state-of-the-art near-threshold techniques are summarized that help overcome barriers to near-threshold adoption, namely high variation at low voltage. Last, example industrial and academic wide-voltage scaling systems are discussed.