Miracle-dz/UniFAR-FTUs huggingface dataset:
‘This Helps You See Life Differently’: Evaluating Youth Development and Capability Expansion in Remote Communities of Honduras

Youth in rural Honduras experience barriers to accessing education, vocational training, and social supports for their formative development. This study evaluated over 18 years of youth-specific development interventions implemented by a Honduran organization in two rural municipalities. The study draws on 94 semi-structured interviews and demographic data from 1596 program participants. Three impact pathways were identified through which respondents experienced positive outcomes from program involvement: transformative participation; meaningful collaboration; and low-risk experimentation. The findings parallel known development theories and empowerment frameworks, including the Human Development and Capabilities Approach and Positive Youth Development, thus supporting the effectiveness of these approaches in facilitating youth development and capability expansion in remote Honduran communities.
Capillary flow of evaporating liquid solutions in open rectangular microchannels

Abstract Capillary flow of liquids plays a key role in many applications including lab-on-a-chip devices, heat pipes and printed electronics manufacturing. Open rectangular microchannels often appear in these applications, with the lack of a top resulting in a complex free-surface morphology and evaporation. In this work we develop a theoretical model based on lubrication theory and kinetically limited evaporation to examine capillary flow of evaporating liquid solutions in open rectangular microchannels connected to circular reservoirs. The model accounts for the complex free-surface morphology, solvent evaporation, Marangoni flows due to gradients in solute concentration and temperature and finite-size reservoir effects. Significant differences are predicted in flow behaviour between pure liquids and liquid solutions due to solvent evaporation and solute transport. Marangoni flows are found to promote more uniform solute deposition patterns after solvent evaporation. Model predictions of meniscus position evolution are in good agreement with prior capillary-flow experiments of aqueous poly(vinyl alcohol) solutions in the presence of evaporation. The model reveals that the principal mechanism through which evaporation influences the meniscus position in the experiments is the increase in viscosity with solute concentration.
A deep learning-based approach to extraction of filler morphology in SEM images with the application of automated quality inspection

Abstract Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system can simultaneously classify, detect, and segment fillers in SEM images, making it suitable for morphology analysis of fillers and automatic quality inspection. We also propose a novel SEM image simulation procedure to overcome the data scarcity for training a deep CNN architecture. The proposed filler detection system is trained on the simulated images. It is shown that the trained network can detect and segment fillers with higher accuracy even in the overlapping and obscure situations. The performance and robustness of the proposed system are evaluated using both simulated and real microscopic images.
The effect of policy incoherence on the emergence of groundwater-related subsidence phenomena: a case study from Iran

ABSTRACT Land subsidence due to overexploitation of aquifers is often attributed to incoherent public policies. Taking the case of the Mahyar valley in Iran as an example, and based on a mixed-method research design, this study analyses the effects of policy incoherence on well use for agricultural irrigation and the resulting groundwater levels. Results show how an accumulation of policy incoherence over time results in an increased construction of wells, ultimately leading to a groundwater table drawdown, with a significant decrease of 7.61 m in the last 16 years.
Report on women in IR (WIR 2021) at SIGIR 2021

The SIGIR'21 Women in IR event 1, co-organized by SIGIR WIR co-chairs, Nazli Goharian (US East Coast) and Hannah Bast (Central Europe), took place on July 13-14 and was attended by ~70 participants. Due to Covid-19, SIGIR'21 was held online. To accommodate all the time zones, we organized two sessions (A and B) on the same topics. Session A, which was scheduled at a good time for the US and Europe, was well attended by around 52 participants. Session B, which was aimed for Asia-Pacific, had only around 15 participants, where several already attended the earlier session. The low attendance of Session B caused a significant delay in the start of the session which impacted negatively the session due to the very late / middle of night of the organizers physical location. This year's theme was "Community Engagement & Influence" covering two topics: 1. Gender pay disparity and the community feedback and input which were captured via a survey and presented during the session, and 2. A presentation and discussion on the notion of hero culture. Date: 13--14 July, 2021.
CAdViSE or how to find the sweet spots of ABR systems

With the recent surge in Internet multimedia traffic, the enhancement and improvement of media players, specifically Dynamic Adaptive Streaming over HTTP (DASH) media players happened at an incredible rate. DASH Media players take advantage of adapting a media stream to the network fluctuations by continuously monitoring the network and making decisions in near real-time. The performance of algorithms that are in charge of making such decisions was often difficult to be evaluated and objectively assessed from an End-to-end or holistic perspective [1]. CAdViSE provides a Cloud-based Adaptive Video Streaming Evaluation framework for the automated testing of adaptive media players [4]. We will introduce the CAdViSE framework, its application, and propose the benefits and advantages that it can bring to every web-based media player development pipeline. To demonstrate the power of CAdViSE in evaluating Adaptive Bitrate (ABR) algorithms we will exhibit its capabilities when combined with objective Quality of Experience (QoE) models. Our team at Bitmovin Inc. and ATHENA laboratory has selected the ITU-T P.1203 (mode 1) quality evaluation model in order to assess the experiments and calculate the Mean Opinion Score (MOS), and better understand the behavior of a set of well-known ABR algorithms in a real-life setting [2]. We will display how we tested and deployed our framework using a modular architecture into a cloud infrastructure. This method yields a massive growth to the number of concurrent experiments and the number of media players that can be evaluated and compared at the same time, thus enabling maximum potential scalability. In our team's most recent experiments, we used Amazon Web Services (AWS) for demonstration purposes. Another awesome feature of CAdViSE that will be discussed here is the ability to shape the test network with endless network profiles. To do so, we used a fluctuation network profile and a real LTE network trace based on the recorded internet usage of a bicycle commuter in Belgium. CAdViSE produces comprehensive logs for each experimental session. These logs can then be applied against different goals, such as objective evaluation or to stitch back media segments and conduct subjective evaluations. In addition, startup delays, stall events, and other media streaming defects can be imitated exactly as they happened during the experimental streaming sessions [3].
Bugs in Security Onion

Once the development of information technology and network, the problem of information security is becoming increasingly prominent. The scope and content of network security threats continue to expand and evolve, and the network security situation and challenges are becoming increasingly severe and complex. It is becoming more and more important to perceive the network security situation, monitor the network operation status, and ensure the security of information assets. Security Onion (SO) is a free and opensource Linux distribution for threat hunting, enterprise security monitoring, and log management. Security Onion is used to monitor specific network traffic, detect intrusion actions, and stop the attacker from taking further actions. Bugs in other Linux versions of operating systems may also exist in SO. This paper presents some existing security bugs in Ubuntu and the Linux kernel and tests whether these exist and lead to security vulnerabilities that can be exploited in Security Onion as well. Kali Linux with Nmap and Metasploit-Framework is used to implement exploits.
Multimedia streaming analytics: quo vadis?

In today's complex OTT multimedia streaming ecosystem, the task of ensuring the best streaming experience to end-users requires extensive monitoring, and such monitoring information is relevant to various stakeholders including content providers, CDN providers, network operators, device vendors, developers, and researchers. Streaming analytics solutions address this need by aggregating performance information across streaming sessions, to be presented in ways that help improve the end-to-end delivery. In this paper, we provide an analysis of the state of the art in commercial streaming analytics solutions. We consider five products as representatives, and identify potential improvements with respect to terminology, QoE representation, standardization and interoperability, and collaboration with academia and the developer community.
Highly Accurate Tomato Maturity Recognition: Combining Deep Instance Segmentation, Data Synthesis and Color Analysis

Automatic maturity recognition and counting of tomatoes during different growth stages from images is of great significance for optimal management in tomato farming, long-term yield prediction and robotic harvesting. In this study, we present a novel method that combines deep instance segmentation, data synthesis and color analysis to accurately recognize and count tomatoes during different growth stages. In our approach, we trained the Mask R-CNN instance segmentation neural network with synthetically generated dataset to accurately segment all tomato instances in an image, then color-based thresholding was applied to identify their growth stage and count the tomato number accordingly. The synthetic data generation algorithm preserved the physical structure of the data objects, thus produced photorealistic synthesized cultivation scenes. The trained model demonstrated substantial performance with maximum 92.1% average precision and 91.4% recall against the real-world test datasets for tomato segmentation. The tomato maturity recognition accuracy of the color-analysis method was evaluated by comparing estimated count with ground-truth manual counts. Our experimental results demonstrated high accuracy of tomato counting during three different growth stages: green, half ripened and fully ripened.
WildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns

Software-defined networking (SDN) enables fast service innovations through network programmability. In SDN, a logically centralized controller compiles a set of policies into the network-level rules. These rules are inserted in the TCAM memory of SDN-enabled switches enabling high-speed matching and forwarding of packets. Unfortunately, TCAMs are available in limited capacities and fall short of accommodating all intended rules, especially in networks with large distinct flows like datacenters. Rule compression is a technique that reduces the number of rules by aggregating them with some similarity factors. This paper introduces WildMinnie, a new rule compression method that aggregates rules based on their common address non-prefix wildcards derived from a group of rules with the same output port number. We explore rule conflict issues and provide solutions to resolve them. We demonstrate the capability of WildMinnie in various datacenter topologies with traffics having different diversity of source-destination addresses and show that WildMinnie outperforms the best-known compression method by 20%, on average.
Systemic Deficiency of PTEN Accelerates Breast Cancer Growth and Metastasis

Mutation or loss of the tumor suppressor gene PTEN or its functional status in tumor stromal cells may affect tumor occurrence, development, invasion, and metastasis, in which, however, the role of overall low PTEN expression, mutation, or deletion in the tumor-bearing host has rarely been reported. Breast cancer is a common highly invasive metastatic tumor. We therefore treated mouse breast cancer 4T1 cells with the specific PTEN inhibitor VO-OHpic to study the effects of PTEN suppression or deletion on malignant behavior in vivo and in vitro. VO-OHpic effectively inhibited PTEN gene/protein expression in 4T1 cells, accelerated cell proliferation, and enhanced cell migration and invasion. We also transplanted 4T1 cells with VO-OHpic-inhibited PTEN into mice to create orthotopic and metastatic breast cancer models. The proliferation of 4T1 cells in mouse mammary gland was increased and distant metastasis was enhanced, with metastatic foci in the lung, liver, and intestinal tract. In addition, injection of mice with VO-OHpic to inhibit PTEN in the overall microenvironment accelerated the proliferation of transplanted 4T1 cells and enhanced distant metastasis and the formation of metastatic tumors. Metastatic foci formed in the lung, liver, intestine, thymus, and brain, and PTEN levels in the organ/tissues were negatively associated with the formation of metastatic foci. Similarly, inoculation of PTEN-deficient 4T1 cells into systemic PTEN-inhibited mice further enhanced the orthotopic growth and distant metastasis of 4T1 breast cancer. VO-OHpic inhibition of PTEN in 4T1 cells was also associated with significantly increased phosphorylation of Akt and phosphoinositide 3-kinase (PI3K), suggesting that inhibition of PTEN could activate the PI3K-Akt pathway, as a key signaling pathway regulating cell proliferation and death. These results confirmed that functional loss or deletion of the tumor suppressor gene PTEN significantly enhanced the proliferation, invasion, and metastasis of 4T1 cells. Systemic decrease or deletion of PTEN in the organism or organ/tissue microenvironment was conducive to the proliferation of breast cancer cells in situ and distant metastasis. These results suggest that, as well the PTEN in cancer cells the systemic microenvironment PTEN intensely mediates the proliferation, invasion and metastasis of mouse breast cancer cells via regulating the PI3K-Akt signaling pathway.
Characterization of Microsatellites in the Akebia trifoliata Genome and Their Transferability and Development of a Whole Set of Effective, Polymorphic, and Physically Mapped Simple Sequence Repeat Markers

Akebia trifoliata is a perennial climbing woody liana plant with a high potential for commercial exploitation and theoretical research. Similarly, microsatellites (simple sequence repeats, SSRs) also have dual roles: as critical markers and as essential elements of the eukaryotic genome. To characterize the profile of SSRs and develop molecular markers, the high-quality assembled genome of A. trifoliata was used. Additionally, to determine the potential transferability of SSR loci, the genomes of Amborella trichopoda, Oryza sativa, Vitis vinifera, Arabidopsis thaliana, Papaver somniferum, and Aquilegia coerulea were also used. We identified 434,293 SSRs with abundant short repeats, such as 290,868 (66.98%) single-nucleotide repeats (SNRs) and 113,299 (26.09%) dinucleotide repeats (DNRs) in the A. trifoliata genome. 398,728 (91.81%) SSRs on 344,283 loci were physically mapped on the chromosomes, and a positive correlation (r = 0.98) was found between the number of SSRs and chromosomal length. Additionally, 342,916 (99.60%) potential SSR markers could be designed from the 344,283 physically mapped loci, while only 36,160 could be viewed as high-polymorphism-potential (HPP) markers, findings that were validated by PCR. Finally, SSR loci exhibited broad potential transferability, particularly DNRs such as the “AT/AT” and “AG/CT” loci, among all angiosperms, a finding that was not related to the genetic divergence distance. Practically, we developed a whole set of effective, polymorphic, and physically anchored molecular markers and found that, evolutionarily, DNRs could be responsible for microsatellite origin and protecting gene function.
Perspective Taking and Avatar-Self Merging

Today, avatars often represent users in digital worlds such as in video games or workplace applications. Avatars embody the user and perform their actions in these artificial environments. As a result, users sometimes develop the feeling that their self merges with their avatar. The user realizes that they are the avatar, but the avatar is also the user—meaning that avatar’s appearance, character, and actions also affect their self. In the present paper, we first introduce the event-coding approach of the self and then argue based on the reviewed literature on human-avatar interaction that a self-controlled avatar can lead to avatar-self merging: the user sets their own goals in the virtual environment, plans and executes the avatar’s actions, and compares the predicted with the actual motion outcomes of the avatar. This makes the user feel body ownership and agency over the avatar’s action. Following the event-coding account, avatar-self merging should not be seen as an all-or-nothing process, but rather as a continuous process to which various factors contribute, including successfully taking the perspective of the avatar. Against this background, we discuss affective, cognitive, and visuo-spatial perspective taking of the avatar. As evidence for avatar-self merging, we present findings showing that when users take the avatar’s perspective, they can show spontaneous behavioral tendencies that run counter to their own.
Increased Drug Resistance and Biofilm Formation Ability in ST34-Type Salmonella Typhimurium Exhibiting Multicellular Behavior in China

Salmonella Typhimurium is an important food-borne pathogen. In this paper, multicellular behavior and associated characteristics of S. Typhimurium isolated from human and animal source food were studied. All the S. Typhimurium strains exhibiting multicellular behavior (100%) belonged to the ST34 type. In addition, most of the ST34-type multicellular behavior S. Typhimurium strains had a human origin (69.11%) and 98% of the ST34-type multicellular behavior strains exhibited strong biofilm formation capacity, which was much higher than that of non-multicellular behavior strains (7%, P < 0.01). Antibiotic resistance in ST34-type multicellular behavior strains was significantly higher than in strains with non-multicellular behavior for most conventional drugs (P < 0.05); notably, Polymyxin B (8%) and Imipenem (1%) resistances were also observed in the ST34-type strains. Furthermore, all the ST34-type multicellular behavior strains (100%) exhibited Multiple Drug Resistance (resistance to ≥3antibiotics), which was much higher than that of the non-multicellular behavior strains (P < 0.05). Consistent with the drug-resistant phenotype, the carrying rates of most drug-resistant genes in ST34-type multicellular behavior strains were higher than that those in non-multicellular behavior strains (P < 0.05). Therefore, this study revealed the emergence of a prevalent ST34-type multicellular behavior S. Typhimurium strains with increased biofilm formation ability and drug resistance rate, which poses a threat to public health safety, and highlights the need for comprehensive monitoring of the strains.
Alcohol Consumption and Risk of Liver Fibrosis in People Living With HIV: A Systematic Review and Meta-Analysis

Objectives It is unclear if a high level of alcohol consumption is a risk factor for liver fibrosis for people living with HIV (PLWH). This study systematically summarizes the risk relationship between different alcohol consumption and the incidence of liver fibrosis among PLWH. Methods We identified potential studies by searching the PubMed, Embase, Web of Science Library, and CNKI databases up to September 26th, 2021. Observation studies in PLWH that evaluated the relationship between alcohol consumption and the risk of liver fibrosis and estimated the effect of alcohol with pooled odds ratios (pooled ORs) and 95% confidence intervals (CIs) were included. Results There were total 15 studies included in data analysis. Three studies were set up as cohort studies and the other twelve were cross-sectional studies. Our study was based on 22,676 individuals and 2,729 liver fibrosis cases from 15 studies. Alcohol abuse is a significant risk factor of liver fibrosis (pooled OR = 2.25, 95% CI: 1.59-3.17, p < 0.05) among PLWH. Daily alcohol consumption > 50 g can elevate the risk of liver fibrosis (pooled OR = 3.10, 95% CI: 2.02-4.73, p < 0.05) among PLWH. However, high-risk alcohol consumption determined by AUDIT-C (AUDIT-C ≥ 4) had little or no effect on subsequent liver fibrosis risk. Further, alcohol consumption > 50 g is also a risk factor to liver fibrosis in PLWH co-infected with HCV (pooled OR = 2.48, 95% CI: 1.62-3.80, p < 0.05) and in HIV mono-infected (pooled OR = 1.85, 95% CI: 1.00-3.43, p < 0.05). Conclusion Alcohol consumption is associated with an increased risk of liver fibrosis in PLWH. HCV co-infection with alcohol abuse could possibly induce a higher risk of liver fibrosis than HIV mono-infected patients. Systematic Review Registration PROSPERO, identifier (CRD42021272604).
Influence of CYP2D6, CYP3A4 and CYP2C19 Genotypes on Recurrence of Plasmodium vivax

Background The influence of the CYPs (cytochrome P-450) in the success of antimalarial therapy remains uncertain. In this study, the association of CYP2D6, CYP2C19 and CYP3A4 polymorphisms and predicted phenotypes with malaria recurrence was investigated. Methods After diagnosis of vivax malaria, individuals treated at a reference center in Manaus were followed up for 180 days. Patients were separated into two groups: a recurrence group and a non-recurrence group. Genotyping of CYP2D6, CYP2C19 and CYP3A4 was performed using a TaqMan™ assay and real-time PCR. Findings The frequencies of decreased-function and normal-function alleles and phenotypes for all CYPs were similar between the groups, except for the CYP2D6*2xN allele (p=0.047) and the CYP2D6 gUM phenotype (p=0.057), which were more frequent in individuals without recurrence. Despite this, the CYP2D6, CYP2C19 and CYP3A4 genotypes had no association with an increased risk of recurrence. CYPs polymorphisms also had no influence in parasite clearance, neither in the time nor the number of recurrence episodes. MAIN Conclusion This prospective cohort study demonstrated that CYP2D6, CYP2C19 and CYP3A4 polymorphisms have no influence on malaria recurrence. Nonetheless, our findings suggest that the CYP2D6 predicted ultrarapid phenotype was less susceptible to recurrence, and that patients with the CYP2D6 gUM phenotype are less susceptible to primaquine failure. Additional investigation of pharmacogenetics and pharmacokinetics are needed before implementing CYP analysis to better orientate individualized radical treatment of vivax malaria in reference centers that treat patients with multiple recurrences.