Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the Effectiveness of Protection Jamming Devices in Mitigating Smart Speaker Eavesdropping Attacks Using Gaussian White Noise

Protection Jamming Devices (PJD) are specialized tools designed to sit on top of virtual assistant (VA) smart speakers and hinder them from “hearing” nearby user speech. PJDs aim to protect you from eavesdropping attacks by injecting a jamming signal directly into the microphones of the smart speaker. However, current signal processing routines can be used to reduce noise and enhance speech contained in noisy audio samples. Therefore, we identify a potential vulnerability for speech eavesdropping via smart speaker recordings, even when a PJD is being used. If an attacker can gain access to or facilitate smart speaker recordings they may be able to compromise a user’s speech with successful noise cancellation. Specifically, we are interested in the potential for Gaussian white noise (GWN) to be an effective jamming signal for a PJD. To our knowledge, the effectiveness of white noise and PJDs to protect against eavesdropping attacks has yet to receive a systematic evaluation that includes physical experiments with an actual PJD implementation. In this work we construct our own PJD, specialized for consistent experimentation, to simulate an attack scenario where recordings from a smart speaker, in the presence of normal speech and the PJDs jamming signal, are recovered. We perform substantial data collection under different settings to build a repository of 1500 recovered audio samples. We applied post-processing on our dataset and conducted an extensive signal/speech quality analysis including both time and frequency domain inspection, and evaluation of metrics including cross-correlation, SNR, and PESQ. Lastly, we performed feature extraction (MFCC) and built machine learning classifiers for tasks including speech (digit) recognition, speaker identification, and gender recognition. We also attempted song recognition using the Shazam app. For all speech recognition tasks that we attempted, we were able to achieve classification accuracies above that of random guessing (46% for digit recognition, 51% for speaker identification, 80% for gender identification), as well as demonstrate successful song recognition. These results highlight the real potential for attackers to compromise user speech, to some extent, using smart speaker recordings; even if the smart speaker is protected by a PJD.
Health Educator Participation in Virtual Micro-Credentialing Increases Physical Activity in Public Health Competencies

Background: Physical activity is an important component of leading a healthy life. Public health is one of the nine major sectors for disseminating information about physical activity and increasing the physical activity of the general public. Purpose: Increase competency among Cooperative Extension agents (i.e., public health workers) on selecting, delivering, and evaluating physical activity programs through a theory-based online training program. Methods: Cooperative Extension agents from two states were invited to participate via statewide listservs. Participants were invited to attend sessions, complete competency checks, and between-session assignments each week. The study was conducted using a video conferencing platform. The intervention was 9 weeks from June to July 2020 and had 130 participants. Pre- and post-program surveys included physical activity competencies and validated scales for flourishing and physical activity status. Data for competencies pre and post were analyzed using the Wilcoxon signed rank test, p < 0.01. Physical activity and flourishing pre and post were compared using t-tests, p < 0.05. Results: Physical activity in public health competency increased significantly (p < 0.00) as did agents' personal physical activity levels (p < 0.05). Changes in flourishing were not significant (p < 0.09) but trended in the hypothesized direction. Conclusions: The online competency-based training program significantly improved Cooperative Extension agents' knowledge of physical activity guidelines and physical activity program implementation. Future work is needed related to the scalability of the training program.
Mixture Compound Fertilizer and Super Absorbent Polymer Application Significantly Promoted Growth and Increased Nutrient Levels in Pinus massoniana Seedlings and Soil in Seriously Eroded Degradation Region of Southern China

Pinus massoniana is the pioneer tree species in the red soil regions of southern China, however, the serious understory soil erosion and nutrient deficiency in that region are the main factors restricting the growth of P. massoniana. This field study examined the effects of compound fertilizer and super absorbent polymer (SAP) on the physiology, growth characteristics, biomass, soil nutrient, plant nutrient content, and nutrient uptake efficiency of 1-year-old P. massoniana seedlings for 2 years at Changting, Fujian in South China. One control (no fertilizer, CK) and fertilization treatments were established, namely, single compound fertilizer application (0.94, 1.89, and 3.56 g⋅plant–1) and mixture compound fertilizer and SAP application (0.94 + 1.01, 1.89 + 1.01, and 3.56 + 1.01 g⋅plant–1). Fertilization significantly improved the physiological performance, root collar diameter growth, height growth, biomass, and nutrient uptake of the seedlings. Compared with other fertilization treatments, the mixture compound fertilizer and SAP application significantly improved the seedling photosynthesis, which meant that the SAP had a significant effect on promoting photosynthesis. Under the mixture compound fertilizer and SAP application, the whole biomass of the seedlings was higher than that of all other treatments. Fertilization significantly increased the nitrogen (N), phosphorus (P), and potassium (K) content in the soils, leaves, stems, and roots of the seedlings, respectively. The P content was the main factor affecting growth characteristics and contributed to 58.03% of the total variation in seedling growth characteristics (P < 0.01). The N:P ratio of CK in the soils, leaves, and stems were higher than that of all the fertilization treatments, indicating that the severely eroded and degraded region had little P and required much of P. The principal component analysis indicated that the F2S (1.89 + 1.01 g) was the optimum fertilization amount and method in this experiment. These results provide a theoretical basis for the fertilization management of P. massoniana forests with severely eroded and degraded red soil regions.
SMap: Internet-wide Scanning for Spoofing

To protect themselves from attacks, networks need to enforce ingress filtering, i.e., block inbound packets sent from spoofed IP addresses. Although this is a widely known best practice, it is still not clear how many networks do not block spoofed packets. Inferring the extent of spoofability at Internet scale is challenging and despite multiple efforts the existing studies currently cover only a limited set of the Internet networks: they can either measure networks that operate servers with faulty network-stack implementations, or require installation of the measurement software on volunteer networks, or assume specific properties, like traceroute loops. Improving coverage of the spoofing measurements is critical. In this work we present the Spoofing Mapper (SMap): the first scanner for performing Internet-wide studies of ingress filtering. SMap evaluates spoofability of networks utilising standard protocols that are present in almost any Internet network. We applied SMap for Internet-wide measurements of ingress filtering: we found that 69.8% of all the Autonomous Systems (ASes) in the Internet do not filter spoofed packets and found 46880 new spoofable ASes which were not identified in prior studies. Our measurements with SMap provide the first comprehensive view of ingress filtering deployment in the Internet as well as remediation in filtering spoofed packets over a period of two years until May 2021. We set up a web service at https://smap.cad. sit.fraunhofer. de to perform continual Internet-wide data collection with SMap and display statistics from spoofing evaluation. We make our datasets as well as the SMap (implementation and the source code) publicly available to enable researchers to reproduce and validate our results, as well as to continually keep track of changes in filtering spoofed packets in the Internet.
A Cross-role and Bi-national Analysis on Security Efforts and Constraints of Software Development Projects

Software security, which is often regarded as a non-functional requirement, tends to be less prioritized than other explicit requirements in development projects. For designing security measures that can be used in software development, we must understand the obstacles that prevent the adoption of secure software development practices. In this study, we quantitatively analyzed security efforts and constraints of software development projects through an online survey of software development professionals in the US and Japan (N=664). We revealed how certain characteristics of a development project, such as the project’s contractual relationships or the software’s target users, influence security efforts and constraints. In addition, by comparing the survey results of two groups (developers and managers), we revealed how the gap in their security efforts and constraints influences software security. We believe the results provide insights toward designing usable measures to assist security-related decision-making in software development and conducting appropriate surveys targeting software development professionals.
MineHunter: A Practical Cryptomining Traffic Detection Algorithm Based on Time Series Tracking

With the development of cryptocurrencies’ market, the problem of cryptojacking, which is an unauthorized control of someone else’s computer to mine cryptocurrency, has been more and more serious. Existing cryptojacking detection methods require to install anti-virus software on the host or load plug-in in the browser, which are difficult to deploy on enterprise or campus networks with a large number of hosts and servers. To bridge the gap, we propose MineHunter, a practical cryptomining traffic detection algorithm based on time series tracking. Instead of being deployed at the hosts, MineHunter detects the cryptomining traffic at the entrance of enterprise or campus networks. Minehunter has taken into account the challenges faced by the actual deployment environment, including extremely unbalanced datasets, controllable alarms, traffic confusion, and efficiency. The accurate network-level detection is achieved by analyzing the network traffic characteristics of cryptomining and investigating the association between the network flow sequence of cryptomining and the block creation sequence of cryptocurrency. We evaluate our algorithm at the entrance of a large office building in a campus network for a month. The total volumes exceed 28 TeraBytes. Our experimental results show that MineHunter can achieve precision of 97.0% and recall of 99.7%.
Don’t hand it Over: Vulnerabilities in the Handover Procedure of Cellular Telecommunications

Mobility management in the cellular networks plays a significant role in preserving mobile services with minimal latency while a user is moving. To support this essential functionality the cellular networks rely on the handover procedure. Most often, the User Equipment (UE) provides signal measurements to the network via reports to facilitate the handover decision when it discovers a more suitable base station. These measurement reports are cryptographically protected. In this paper, we examine the cellular specification and illustrate that this crucial functionality has critical security implications. To the best of our knowledge, this is the first work on cellular Man-In-The-Middle attacks based on the handover procedure. In particular, we demonstrate a new type of fake base station attacks in which the handover procedures, based on the encrypted measurement reports and signal power thresholds, are vulnerable. An attacker who sets up a false base station mimicking a legitimate one can utilize the vulnerabilities in the handover procedure to cause Denial-Of-Service attacks, Man-In-The-Middle attacks, and information disclosure affecting the user as well as the operator. Therefore, users’ privacy and service availability are jeopardized. Through rigorous experimentation, we uncover the vulnerable parts of the handover procedure, a comprehensive attacker methodology, and attack requirements. We largely focus on the 5G network showing that handover vulnerabilities remain unmitigated to date. Finally, we assess the impact of the handover attacks, and carefully present potential countermeasures that can be used against them.
Identification and Validation of CYBB, CD86, and C3AR1 as the Key Genes Related to Macrophage Infiltration of Gastric Cancer

Gastric cancer (GC) is rampant around the world. Most of the GC cases are detected in advanced stages with poor prognosis. The identification of marker genes for early diagnosis is of great significance. Studying the tumor environment is helpful to acknowledge the process of tumorigenesis, development, and metastasis. Twenty-two kinds of immune cells were calculated by CIBERSORT from Gene Expression Omnibus (GEO) database. Subsequently, higher infiltration of macrophages M0 was discovered in GC compared with normal tissues. WGCNA was utilized to construct the network and then identify key modules and genes related to macrophages in TCGA. Finally, 18 hub genes were verified. In the PPI bar chart, the top 3 genes were chosen as hub genes involved in most pathways. On the TIMER and THPA websites, it is verified that the expression levels of CYBB, CD86, and C3AR1 genes in tumor tissues were higher than those in normal tissues. These genes may work as biomarkers or targets for accurate diagnosis and treatment of GC in the future. Our findings may be a new strategy for the treatment of GC.
Estrogen Receptor α Signaling in Osteoblasts is Required for Mechanotransduction in Bone Fracture Healing

Biomechanical stimulation by whole-body low-magnitude high-frequency vibration (LMHFV) has demonstrated to provoke anabolic effects on bone metabolism in both non-osteoporotic and osteoporotic animals and humans. However, preclinical studies reported that vibration improved fracture healing and bone formation in osteoporotic, ovariectomized (OVX) mice representing an estrogen-deficient hormonal status, but impaired bone regeneration in skeletally healthy non-OVX mice. These effects were abolished in general estrogen receptor α (ERα)-knockout (KO) mice. However, it remains to be elucidated which cell types in the fracture callus are targeted by LMHFV during bone healing. To answer this question, we generated osteoblast lineage-specific ERα-KO mice that were subjected to ovariectomy, femur osteotomy and subsequent vibration. We found that the ERα specifically on osteoblastic lineage cells facilitated the vibration-induced effects on fracture healing, because in osteoblast lineage-specific ERα-KO (ERαfl/fl; Runx2Cre) mice the negative effects in non-OVX mice were abolished, whereas the positive effects of vibration in OVX mice were reversed. To gain greater mechanistic insights, the influence of vibration on murine and human osteogenic cells was investigated in vitro by whole genome array analysis and qPCR. The results suggested that particularly canonical WNT and Cox2/PGE2 signaling is involved in the mechanotransduction of LMHFV under estrogen-deficient conditions. In conclusion, our study demonstrates a critical role of the osteoblast lineage-specific ERα in LMHFV-induced effects on fracture healing and provides further insights into the molecular mechanism behind these effects.
Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis

Student performance prediction (SPP) aims to evaluate the grade that a student will reach before enrolling in a course or taking an exam. This prediction problem is a kernel task toward personalized education and has attracted increasing attention in the field of artificial intelligence and educational data mining (EDM). This paper provides a systematic review of the SPP study from the perspective of machine learning and data mining. This review partitions SPP into five stages, i.e., data collection, problem formalization, model, prediction, and application. To have an intuition on these involved methods, we conducted experiments on a data set from our institute and a public data set. Our educational dataset composed of 1,325 students, and 832 courses was collected from the information system, which represents a typical higher education in China. With the experimental results, discussions on current shortcomings and interesting future works are finally summarized from data collections to practices. This work provides developments and challenges in the study task of SPP and facilitates the progress of personalized education.
A new driving waveform to improve dark room contrast ratio in ac plasma display panel

A high dark room contrast ratio is necessary for realizing good image quality in ac plasma display panels (PDP). However, the conventional PDPs have low dark room contrast ratio because the background light mainly results from the reset discharges between the address, scan, and sustain electrodes in every subfield. In this study, a new driving method [improved waveform of contrast ratio (ICR)] is suggested to enhance the dark room contrast ratio. The principle of ICR is that the facing discharges during the reset period occur between the scan and address electrodes instead of surface discharges by applying almost the same voltage waveform as the scan voltage to the sustain electrode after the conventional first subfield. Moreover, the reset discharge occurs only for the cells that experienced sustain discharge in the preceding subfield after the first subfield. The dark room contrast ratio of ICR is improved more than 7/spl times/ as compared to the conventional method.
S0954579421001103jra 1864..1881

Conduct problems are associated with numerous negative long-term psychosocial sequelae and are among the most frequent referrals for children’s mental health services. Youth residing in low-income, urban communities are at increased risk for conduct problems, but not all youth in these environments develop conduct problems, suggesting heterogeneity in risk and resilience processes and developmental pathways. The present study used a developmental psychopathologyand Research Domain Criteria (RDoC)-informed approach for conceptualizing risk and resilience for conduct problems among children from low-income, urban neighborhoods. Participants were 104 children (M = 9.93 ± 1.22 years; 50% male; 96% African American, 4% Latinx). We assessed four constructs reflecting cognitive and neurobiological processes associated with conduct problems using multiple levels of analysis and informants: autonomic nervous system reactivity, limbic system/orbitofrontal cortical functioning, dorsolateral prefrontal cortical functioning, and conduct problems. Latent profile analysis identified four profiles: typically developing (TD, n = 34); teacher-reported conduct problems (TCP, n = 14); emotion processing (EP, n = 27); and emotion expression recognition (EER, n = 29). External validation analyses demonstrated that profiles differed on various indices of conduct problems in expected ways. The EP profile exhibited lower levels of emotional lability and callous–unemotional behaviors, and higher levels of prosocial behavior. The TD profile demonstrated elevated emotional lability. Implications for etiological and intervention models are presented.
Comparing formal and informal social protection: a case study exploring the usefulness of informal social protection in Pakistan

Abstract In most global south countries, various informal institutions provide welfare to a large segment of the neglected, poor and vulnerable populations through informal social protection. Despite being a major source of welfare in the global south, the usefulness of informal social protection at the household level remains an under-researched area. In this exploratory study, we have determined the usefulness of informal social protection provided through religious institutions, such as madrassas and compared it with formal social protection at the household level utilising the case study of a lower-income country such as Pakistan. A mixed methodology of data collection comprising a survey and semi-structured interviews in 14 different cities of Pakistan of the poor and eligible households for receiving formal social protection was conducted for the research. The results suggest the coverage of informal social protection provided by madrassas is greater than formal social protection. The poor and vulnerable population value and considers it more useful than formal social protection. We conclude that integrating informal and formal social protection would help improve the effectiveness of social policies in developing and less developed countries.
Trace Element and Isotope Systematics in Vent Fluids and Sulphides From Maka Volcano, North Eastern Lau Spreading Centre: Insights Into Three-Component Fluid Mixing

Back-arc spreading centres and related volcanic structures are known for their intense hydrothermal activity. The axial volcanic edifice of Maka at the North Eastern Lau Spreading Centre is such an example, where fluids of distinct composition are emitted at the Maka hydrothermal field (HF) and at Maka South in 1,525–1,543 m water depth. At Maka HF black smoker-type fluids are actively discharged at temperatures of 329°C and are characterized by low pH values (2.79–3.03) and a depletion in Mg (5.5 mmol/kg) and SO4 (0.5 mmol/L) relative to seawater. High metal (e.g., Fe up to ∼6 mmol/kg) and rare Earth element (REE) contents in the fluids, are indicative for a rock-buffered hydrothermal system at low water/rock ratios (2–3). At Maka South, venting of white smoke with temperatures up to 301°C occurs at chimneys and flanges. Measured pH values range from 4.53 to 5.42 and Mg (31.0 mmol/kg), SO4 (8.2 mmol/L), Cl (309 mmol/kg), Br (0.50 mmol/kg) and Na (230 mmol/kg) are depleted compared to seawater, whereas metals like Li and Mn are typically enriched together with H2S. We propose a three-component mixing model with respect to the fluid composition at Maka South including seawater, a boiling-induced low-Cl vapour and a black smoker-type fluid similar to that of Maka HF, which is also preserved by the trace element signature of hydrothermal pyrite. At Maka South, high As/Co (>10–100) and Sb/Pb (>0.1) in pyrite are suggested to be related to a boiling-induced element fractionation between vapour (As, Sb) and liquid (Co, Pb). By contrast, lower As/Co (<100) and a tendency to higher Co/Ni values in pyrite from Maka HF likely reflect the black smoker-type fluid. The Se/Ge ratio in pyrite provides evidence for fluid-seawater mixing, where lower values (<10) are the result of a seawater contribution at the seafloor or during fluid upflow. Sulphur and Pb isotopes in hydrothermal sulphides indicate a common metal (loid) source at the two vent sites by host rock leaching in the reaction zone, as also reflected by the REE patterns in the vent fluids.