Frequent Target Research Articles

Trends and Patterns of Systemic Glucocorticoid Prescription in Primary Care Institutions in Southwest China, from 2018 to 2021.

The purpose of this study was to investigate the prescribing patterns and usage trends of systemic glucocorticoids in primary care institutions located in Southwest China from 2018 to 2021. A retrospective cross-sectional analysis of systemic glucocorticoids prescriptions was conducted in 32 primary care institutions located in Southwest China between 2018 and 2021. Prescriptions of systemic glucocorticoids were classified as appropriate or inappropriate use. Inappropriate use was further classified into (1) inappropriate indications and (2) inappropriate selection of glucocorticoids. Generalized estimation equations were employed to investigate the factors associated with inappropriate utilization of systemic glucocorticoids. The seasonal autoregressive integrated moving average (SARIMA) model was employed to predict the rate of inappropriate glucocorticoids prescriptions. A total of 203,846 (92.89%) prescriptions were included, both the number of systemic glucocorticoids prescriptions and inappropriate prescriptions increased in winter. Diseases of the respiratory system (68.90%) were the most frequent targets of systemic glucocorticoids use. Of all prescriptions, 73.18% exhibited inappropriate indications, while 0.05% demonstrated inappropriate selection. The utilization of systemic glucocorticoids was deemed inappropriate for diseases of the respiratory system (94.19%), followed by diseases of the digestive system (87.75%). Physicians, who were female or younger than 33 years old, possess lower levels of education and professional titles and exhibit a higher likelihood of inappropriately prescribing systemic glucocorticoids. The phenomenon of inappropriate glucocorticoids use was commoner among male patients aged 65 years and older. After conducting model verification, it was determined that the SARIMA model could be used to predict the monthly rate of inappropriate systemic glucocorticoids prescriptions in primary care institutions in southwest China. The inappropriate use of systemic glucocorticoids remains a significant concern in primary care institutions. In this regard, continuing education and professional knowledge training of physicians should be strengthened in the future.

Memory and Traumatic Brain Injury: Assessment and Management Practices of Speech-Language Pathologists.

Memory impairments are among the most commonly reported deficits and among the most frequent rehabilitation targets for individuals with traumatic brain injury (TBI). Memory and learning are also critical for rehabilitation success and broader long-term outcomes. Speech-language pathologists (SLPs) play a central role in memory management for individuals with TBI across the continuum of care. Yet, little is known about the current practice patterns of SLPs for post-TBI memory disorders. This study aims to examine the clinical management of memory disorders in adults with TBI by SLPs and identify opportunities to improve post-TBI memory outcomes. SLPs from across the continuum of care were recruited to complete an online survey. The survey assessed key practice areas specific to memory and memory disorders post-TBI, including education and training, knowledge and confidence, and assessment and treatment patterns. Surveys from 155 SLPs were analyzed. Results revealed that TBI-specific training remains low in the field. Respondents varied in their practice patterns in assessing and treating memory disorders. Most SLPs do not appear to have access to appropriate standardized assessments to measure unique forms of memory. Respondents also reported a range of barriers and opportunities to advance memory outcomes following TBI and provided suggestions of areas in which they would like to see more basic and clinical research. These findings establish a baseline of the current practices for clinical management of memory impairment in adults with TBI by SLPs. Improved opportunities for clinician training, the development of a single tool to assess multiple forms of memory, better access to existing memory assessments, and implementation of evidence-based interventions promise to lead to improved memory outcomes for individuals with TBI.

High target prevalence may reduce the spread of attention during search tasks.

Target prevalence influences many cognitive processes during visual search, including target detection, search efficiency, and item processing. The present research investigated whether target prevalence may also impact the spread of attention during search. Relative to low-prevalence searches, high-prevalence searches typically yield higher fixation counts, particularly during target-absent trials. This may emerge because the attention spread around each fixation may be smaller for high than low prevalence searches. To test this, observers searched for targets within object arrays in Experiments 1 (free-viewing) and 2 (gaze-contingent viewing). In Experiment 3, observers searched for targets in a Rapid Serial Visual Presentation (RSVP) stream at the center of the display while simultaneously processing occasional peripheral objects. Experiment 1 used fixation patterns to estimate attentional spread, and revealed that attention was narrowed during high, relative to low, prevalence searches. This effect was weakened during gaze-contingent search (Experiment 2) but emerged again when eye movements were unnecessary in RSVP search (Experiment 3). These results suggest that, although task demands impact how attention is allocated across displays, attention may also narrow when searching for frequent targets.

Chimeric Antigen Receptor T Cell Therapies Clinical Trials in Pediatric Oncology: A Retrospective Analysis from Clinicaltrials.Gov

Background: Chimeric Antigen Receptor (CAR) T-cell clinical trials are growing exponentially. Database analysis can help identify scientific trends and generate projections regarding potential approvals before the results of the studies are completed or published. This is particularly interesting in pediatric oncology, where available analyses from repository databases are scarce or not available. Because of that reason, we sought to analyze the clinical trial public records from entries related to CAR T-cell clinical studies in pediatric patients (18 years or younger) uploaded to the clinicaltrials.gov database. Methods: We query the available data from clinicaltrials.gov using the following keywords: “CAR T cell in pediatrics”, “CAR T cell and cancer”, “chimeric antigen receptor”, “CAR T AND tumor antigen”, 'CAR T cell antigens“, ”Tumor antigens targeted by CAR T cells“, ”engineered T cells“, ”modified T cell“, ”CAR T cells in Cancer“, ”CAR T cell therapy“, ”CAR T cell therapy AND Cancer“ (data cut off July-2023). The data were tabulated, and the trials that did not meet the search criteria were excluded manually. Data cleansing was performed using published scientific data, web search-based information, and patent databases. Results: We found 4297 results in the Clinicaltrials.gov platform; we excluded 3978 clinical trials that did not involve the pediatric population (<18 years) or CAR T-cell intervention. The final analysis included 319 clinical trials posted on the clinicaltrials.gov website by the cut-off date. 207 (64.9%) were conducted in China, 74 (23.2%) in the US, and 21 (6.5%) in Europe. Most CAR T-cell trials focused on hematological cancer (89%), followed by non-CNS solid tumors 8%, and CNS tumors 3%. The most frequent targets were CD19 (46%), CD7 (7%), followed by GD2, CD22, CD123, CD19 + CD22 and CD30. Most clinical trials did not report the construct generation used in their CAR T cell product (58%). Among the trials with that information, second-generation constructs (2G) were used in 32% of the studies, followed by 3G and 4G constructs (5% of studies each). Most clinical trials were in early stages of development, Phase 1 or 2 (75%). We observed a continuous increase in the number of clinical trials registered yearly, except for a small reduction in 2022 and 2021, probably related to COVID restrictions and challenges. Overall, the general trend predicts at least a 50% yearly increase in registered studies ( Figure 1). Similarly, to what is observed in adult clinical trials, the most common signaling domains are 2G CAR constructs expressing either CD28 or 4-1BB as costimulatory domains. Among those, 4-1BB being is the most popular choice. Conclusion: Our findings indicate a growing interest in the clinical development of CAR T-cell therapies applied to pediatric oncology. Most of these studies are in early phase I and II and focus primarily on hematological cancers using second-generation constructs targeting CD19. The is a steady increase in the number of studies registered each year that predicts future FDA approvals using CAR T-cell products.

559. Results of the implementation of a molecular pneumonia panel at a hospital in the Dominican Republic: expanding the scope of detection and management

Abstract Background Lower respiratory tract infections (LRTIs) have been associated to significant morbidity and mortality. Conventional microbiology methods often fail to identify the etiological agent due to lack of sensitivity or viral or fastidious pathogens. Pneumonia molecular diagnostics is able to expand the scope of pathogens detected, therefore, we describe our experience in the incorporation of this method, the difference in etiological identification and clinical decision making. Methods We performed a retrospective cohort study of 75 patients with Filmarray pneumonia panel from November 2020 to September 2022. We described demographics, co-morbid conditions, outcomes and correlation with standard cultures in patients who were admitted with LRTI at the Hospital General de la Plaza de la Salud, a 289-bed tertiary teaching hospital in the Dominican Republic. Results Amongst the 75 patients, 56.6% were male and the average age was 51 years old. The most common comorbidities were diabetes mellitus (81.6%), hypertension (40.8%) and nephropathy (10.5%). The panels had a positivity rate of 74.6% (56/75) versus a 35% (14/40) seen in cultures. The most frequent microbial targets detected were S. aureus (18%), P. aeruginosa (14,3%) and K. pneumoniae group (10%) and at least one antimicrobial resistance gene was detected in 50% (28/56), distributed as MecA/C and MREJ (35%), CTX-M (38%), KPC (10%), NDM (10%), VIM (8%), IMP (8%) and OXA-48 like (3%). A positive culture was most likely to occur when the number of copies/mL in the panel was ≥ 10˄5 (p-value < 0.001). A viral target was detected in 21 patients (28%) alone or coinfecting with a bacterial agent. Conclusion Not only did the pneumonia panels allow an earlier detection of the etiological agent, but they also identified more pathogens compared to cultures. This enabled targeted management by reducing the unnecessary use of antimicrobials as well as activating infection control measures when necessary (i.e Influenza). The results seen in this study, along with the expanded scope of pathogens detected, will definitely serve as an update into our current LRTI hospital guidelines. Disclosures All Authors: No reported disclosures

Antibody Investigations in 2,750 Children With Suspected Autoimmune Encephalitis.

To assess the frequency and types of neuronal and glial (neural) antibodies in children with suspected autoimmune encephalitis (AE). Patients younger than 18 years with suspected AE other than acute disseminated encephalomyelitis, whose serum or CSF samples were examined in our center between January 1, 2011, and April 30, 2022, were included in this study. Samples were systematically examined using brain immunohistochemistry; positive immunostaining was further investigated with cell-based assays (CBA), immunoblot, or live neuronal immunofluorescence. Of 2,750 children, serum or CSF samples of 542 (20%) showed brain immunoreactivity, mostly (>90%) against neural cell surface antigens, and 19 had antibodies only identified by CBA. The most frequent targets were N-methyl-d-aspartate receptor (NMDAR, 76%) and myelin oligodendrocyte glycoprotein (MOG, 5%), followed by glutamic acid decarboxylase 65 (2%) and γ-aminobutyric acid A receptor (2%). Antibodies against other known cell surface or intracellular neural antigens (altogether 6% of positive cases) and unknown antigens (9%) were very infrequent. The repertoire of antibodies in children with AE is different from that of the adults. Except for NMDAR and MOG antibodies, many of the antibodies included in diagnostic panels are rarely positive and their up-front testing in children seems unneeded.

Sustainability in the scope of civil construction: recycling of solid waste in concrete manufacturing

Concrete production has become a frequent target of studies focusing on sustainability in its production chain, given the successive environmental degradation it causes. That said, the present work aims to investigate sustainability in the context of civil construction through the recycling of solid waste in the manufacture of concrete. The methodology used in the present work encompasses a narrative literature review of scientific articles published in journals from 2019 to 2023 relating to the survey of the types of recyclable waste that contribute to the manufacture of concrete. Glass, pneumatic and construction and demolition waste was explained, which had potential in partially replacing some components of the concrete mix, as well as adding them together with minerals to optimize mechanical results. Therefore, the manufacture of concrete from waste recycling boosts sustainability in the context of civil construction, the saving of natural resources and the sustainable disposal of waste, contributing to the field of study with new technologies related to sustainable development.

Multi-Pedestrian Tracking Based on KC-YOLO Detection and Identity Validity Discrimination Module

Multiple-object tracking (MOT) is a fundamental task in computer vision and is widely applied across various domains. However, its algorithms remain somewhat immature in practical applications. To address the challenges presented by complex scenarios featuring instances of missed detections, false alarms, and frequent target switching leading to tracking failures, we propose an approach to multi-object tracking utilizing KC-YOLO detection and an identity validity discrimination module. We have constructed the KC-YOLO detection model as the detector for the tracking task, optimized the selection of detection frames, and implemented adaptive feature refinement to effectively address issues such as incomplete pedestrian features caused by occlusion. Furthermore, we have introduced an identity validity discrimination module in the data association component of the tracker. This module leverages the occlusion ratio coefficient, denoted by “k”, to assess the validity of pedestrian identities in low-scoring detection frames following cascade matching. This approach not only enhances pedestrian tracking accuracy but also ensures the integrity of pedestrian identities. In experiments on the MOT16, MOT17, and MOT20 datasets, MOTA reached 75.9%, 78.5%, and 70.1%, and IDF1 reached 74.8%, 77.8%, and 72.4%. The experimental results demonstrate the superiority of the methodology. This research outcome has potential applications in security monitoring, including public safety and fire prevention, for tracking critical targets.

Prevalence of Collateral Typology in Coronary Chronic Total Occlusion and Its Impact on Percutaneous Intervention Performance

The presence of collateral channels providing distal blood supply is a distinctive characteristic of chronic total occlusion (CTO) lesions. However, data about the distinct baseline and procedural characteristics of each collateral subset are scarce. Accordingly, we sought to explore the procedural aspects specific for each collateral typology (ipsilateral collaterals [ICs], contralateral collaterals [CCs] or mixed) in CTO-percutaneous coronary intervention (PCI). A retrospective analysis of our CTO-PCI registry was performed to investigate the prevalence, procedural characteristics, and outcomes specific for each CTO-PCI subset, defined according to the inter-arterial connection anatomy. A total of 209 cases were included. Of the included cases, 45 (22%) and 92 (44%) patients displayed solely IC or CC, respectively, whereas in 72 (34%) both IC and CC were present (mixed). The procedural success rate was high (91.1%) and comparable among the different groups, despite greater lesion complexity in the CC group. The most frequent target vessel was the left circumflex in the IC group (51% of cases) and the right coronary artery in the CC (63%) and mixed (57%) groups. Among the IC cases, 42% showed a poor collateral connection function (2% and 10% for the CC and mixed group, respectively), and 46% showed a suboptimal collateral recipient artery filling (21% and 20% for the CC and mixed group, respectively). Most of the IC cases were performed using a single access (96%). In conclusion, the success and complication rates were comparable among the collateral typology groups, irrespective of the differences in the baseline and procedural characteristics. Phenotyping CTO as hereby proposed might be helpful for targeted procedural considerations.

Current Techniques for Fruit Juice and Wine Adulterant Detection and Authentication

Fruit juice and wine are important beverages that are consumed all over the world. Due to their constantly increasing demand and high value, fruit juice and wine are one of the most frequent targets of adulteration. Since adulterated foods are proven to have harmful effects on health, several approaches have been utilized for the detection of fruit juice and wine adulteration. Based on the requirement for sample destruction, analytical techniques to assess food authenticity can be classified into 2 main categories, i.e., destructive and non-destructive techniques. This paper provides an overview on the principle of adulteration detection, its application and performance, and the advantages and limitations of various analytical techniques. Destructive approaches, such as physicochemical methods, isotope analysis, elemental analysis, chromatographic techniques, and DNA-based techniques, are reviewed. Furthermore, non-destructive approaches, including spectroscopic-based techniques, nuclear magnetic resonance spectroscopic technique, electronic techniques, and imaging-based techniques, are discussed.

Computer Games as a Pedagogical Tool for Creating Cyber Security Awareness

Cyberattacks are increasing world-wide, both on corporate networks and public institutions network. During 2022 hackers were widening their aim to target business collaboration tools such as Slack, Teams, OneDrive, and Google Drive with phishing exploits, making for a rich harvest of sensitive data given that most organizations’ employees continued to work remotely. In the later years we have also seen academic institutions becoming more frequent targets for both cybercriminals and state sponsored hackers. In 2022 the education/research sector was most attacked industry globally, seeing a 43% increase compared to 2021, with an average of 2,314 attacks per organisation every week. Schools and universities have the unique challenge of dealing with children or young adults, many of which use their own devices, work from shared locations, and often connect to public Wi-Fi without thinking of the security concerns. Additionally, Russia’s war on Ukraine has led to an increase in spear-phishing activity targeting educational institutions in NATO countries. This situation calls attention to the need for awareness raising about personal cyber security. In Norway, Nord University is one of a few universities with specific focus on security and preparedness, including cyber security awareness. The university has two information security courses: one belonging to furthering education and one within the MBA-study program in Security and Preparedness Management. This paper examines the question whether serious games and online quizzes can create heighten cyber security awareness and motivate individual students to change their cyber security behaviour. The paper reports on the findings based on written reflection notes from students belonging to both courses. The technique of examination and interpretation applied to the data was qualitative thematic content analysis supported by computer-assisted qualitative data analysis software NVivo. Theoretical analysis was guided by social constructionist perspective on knowledge creation. While many advantages of the use of online quizzes and computer games were specified by students, challenges were identified as well. However, the findings show that the use of serious games and online quizzes can be an efficient approach to raising security awareness among participating students.

'Don't Fall for This': Communications about Cybersafety from the AARP

Older adults face unique risks in trying to secure their online activities. They are not only the frequent targets of scams and fraud; they are the targets of a barrage of cybersafety communiqués whose impact is unclear. AARP, the United States advocacy group focusing on issues facing older adults over the age of 50, is among those educators whose strategies remain underexplored, yet their reach makes it imperative that we understand what they are saying, to whom, and to what effect. Drawing on an analysis of AARP publications about cybersafety and privacy, we sought to better understand their discourse on the topic. We report on findings that AARP's language may have the effect of portraying bad actors ("fraudsters") as individuals, rather than enterprises, which at the target end, personalizes interactions, placing too much onus on individual users to assess and deflect threats. AARP's positioning of, and guidance about, threats may sometimes prompt a thought process that puts users at the center of the narrative and may encourage engagement. Instructing older Americans, or anyone, on the forensics of cyber-sleuthing is enormously difficult. We conclude with a discussion of different approaches to cybersafety, one that involves educating older adults about the rudiments of surveillance capitalism.

Entitlement Racism on YouTube: White injury—the licence to Humiliate Roma migrants in the UK

Hate speech monitoring has become a challenging task for social media platforms. While efforts have been made to combat racism and other forms of hate speech, marginalised communities, such as the Roma are frequent targets of intense discrimination and online racist abuse. This article examines manifestations of Romaphobia, also known as anti-Roma racism, on YouTube in the context of 2016 UK Referendum on EU membership, when Roma along with other Eastern European migrants became demonized in the right-wing narratives of Brexit supporters. Drawing on Thematic Analysis and Critical Discourse Analysis, the article provides an in-depth account of how Romaphobia is discursively constructed in the commentaries of those watching YouTube documentaries about Eastern European migrants. In addition to drawing attention to various forms of overt and covert racism that fly under the radar in the content moderation process, the analysis shows that ‘entitlement racism’ is gradually becoming normalised in social media, with anti-Roma racism acquiring alarming levels of verbal violence which needs immediate attention.

Trends and Patterns of Antibiotic Prescriptions in Primary Care Institutions in Southwest China, 2017-2022.

To explore the prescription patterns and usage trends of antibiotics within primary care institutions located in underdeveloped regions of China from 2017 to 2022. A retrospective analysis of antibiotic prescriptions was conducted from 25 primary care institutions in Guizhou Province during the period of 2017-2022. Antibiotic prescriptions were categorized into appropriate and inappropriate use. Appropriate use is further categorized into preferred medication, and antibiotics can be used or substituted. Inappropriate use is further categorized into unnecessary use, incorrect spectrum of antibiotics and combined use of antibiotics. Factors associated with inappropriate use were investigated using generalized estimation equations. Holt-Winters and SARIMA models were employed to predict the number of inappropriate antibiotic prescriptions as the alternative model. A total of 941,924 prescriptions were included, revealing a decreasing trend in both the number and inappropriate rates of antibiotic prescriptions from 2017 to 2022. Diseases of the respiratory system (70.66%) was the most frequent target of antibiotic use, with acute upper respiratory infections of multiple and unspecified sites representing 52.04% of these cases. The most commonly used antibiotics were penicillins (64.44%). Among all prescriptions, inappropriate antibiotic prescriptions reached 66.19%. Physicians aged over 35, holding the title of associate chief physician and possessing more than 11 years of experience were more likely to prescribe antibiotics inappropriately. The phenomenon of inappropriate antibiotic use was commoner among children aged five or younger. By comparing model parameters, it was determined that the SARIMA model outperforms the Holt-Winters model in predicting the number of inappropriate antibiotic prescriptions among primary care institutions. The number and inappropriate rates of antibiotic prescriptions in southwest China exhibited a downward trend from 2017 to 2022, but inappropriate prescription remains a serious problem in primary care institutions. Therefore, future efforts should focus on strengthening physician education, training, and clinical practice. Additionally, physicians' awareness of common misconceptions about inappropriate antibiotic use must be improved, and the prescribing behavior of physicians who fulfill patients' expectations by prescribing antibiotics needs to be modified.

Rapid and strain-specific resistance evolution of Staphylococcus aureus against inhibitory molecules secreted by Pseudomonas aeruginosa.

Polymicrobial infections are common. In chronic infections, the different pathogens may repeatedly interact, which could spur evolutionary dynamics with pathogens adapting to one another. Here, we explore the potential of Staphylococcus aureus to adapt to its competitor Pseudomonas aeruginosa. These two pathogens frequently co-occur, and P. aeruginosa is seen as the dominant species being able to displace S. aureus. We studied three different S. aureus strains and found that all became quickly resistant to inhibitory compounds secreted by P. aeruginosa. Our experimental evolution revealed strains-specific adaptations with three main factors contributing to resistance evolution: (i) overproduction of staphyloxanthin, a molecule protecting from oxidative stress; (ii) the formation of small colony variants also protecting from oxidative stress; and (iii) alterations of membrane transporters possibly reducing toxin uptake. Our results show that species interactions can change over time potentially favoring species co-existence, which in turn could affect disease progression and treatment options.

Technology and older adults in British loneliness policy and political discourse.

This article provides an analysis of recent loneliness policy and political discourses from the United Kingdom pertaining to older adults. Although government asserts that several groups in society are "at risk" of loneliness, older adults remain the most frequent targets of policy interventions. Technology is positioned as playing a role in the causation and alleviation of loneliness. Little research has examined loneliness in political discourses. With a focus on how loneliness intersects with themes of technology and aging, this article presents an analysis of discourses guided by Bacchi's What is the Problem Represented to Be (WPR) framework. It endeavors to answer the following questions: What is the problem of loneliness among older adults represented to be, and what is the role of technology in this context - problem or solution? In the discourses, assertions are made that issues of loneliness, societal change and digital exclusion are intertwined. Lonely older adults are problematized as hard to find and thus connect with interventions, warranting surveillance measures like loneliness heatmaps. Technological interventions to assist older adults in maintaining independence and connections to social networks are often proposed as solutions. The findings indicate dominant discourses position older adults primarily as subjects in need of care and as non-users of technology. Technology is positioned as a cost-effective tool to fill gaps in an overburdened and under-funded social care system that compounds issues of loneliness. The author argues the neoliberal and stigmatizing undertones within the corpus may undermine efforts to combat loneliness. Further, austerity is silent in the dominant problematizations of loneliness, foreclosing upon alternatives that problematize loneliness as resulting from neoliberal policies that continue to dismantle public infrastructure and social care.

Practice patterns of adjuvant radiotherapy in women with stage I to II endometrial carcinoma: a real-world multi-institutional analysis in China

BackgroundThis study aimed to report clinical practice patterns of postoperative radiotherapy for stage I to II endometrial carcinoma (EC) patients treated in 13 Chinese medical centers.MethodsWe included early stage EC patients treated by hysterectomy and adjuvant RT between 2003 and 2017 from 13 institutions. Patients were classified into 4 risk groups based on ESMO-ESGO-ESTRO recommendations (2014).ResultsA total of 1,227 cases were analyzed. Along the 15 years of the study, an increasing tendency was found towards administration for vaginal brachytherapy (VBT) alone, while the proportion of external beam pelvic radiotherapy (EBRT) alone remained stable in the corresponding period. When radiation modalities were stratified by risk groups, proportion of VBT alone significantly increased in all risk groups. The higher the risk, the later VBT became the main adjuvant treatment modality. However, EBRT alone or with VBT remained the main adjuvant method for high-risk patients.There were 13 dose-fractionation schemes for VBT alone with the scheme of 30 Gy in 6 fractions prescribed at 0.5cm under the vaginal mucosa accounting for most. There were 17 schemes for VBT boost and the most common schedule was 10 Gy in 2 fractions. The upper 3–5cm part of vagina was the most frequent target. 89.6% of the practitioners performed two-dimensional VBT technique. The median dose for EBRT was 50 Gy. From 2003 to 2017, conventional radiotherapy was gradually replaced by three-dimensional conformal radiotherapy modality and intensity modulated radiotherapy.ConclusionWe report a significant shift from EBRT to VBT alone for high-intermediate-risk, intermediate-risk and low-risk EC patients from 2003 to 2017 while EBRT remained the main radiation modality for high-risk early stage patients. There has been remarkable heterogeneity among VBT dose fractionation schedules across China.Trial registrationThe clinical trial ID was ChiCTR-PRC-17010712. It was authorized by the Institutional Review Board of Peking Union Medical College Hospital (N0. S-K139).

The contribution of corporate initiatives to global renewable electricity deployment

Climate change is gaining importance on the agenda of senior decision makers in the private sector. Hence, corporate renewable electricity (RE) procurement may become more relevant to the energy transition. RE100 is the largest corporate initiative to foster RE procurement with 315 corporate members as of 2021. Yet, the contribution of such initiatives to the energy transition remains unclear, because public reporting is aggregated on the global level. Here, we develop an approach to map the electricity procured by RE100 companies to jurisdictions worldwide, which allows estimating whether and where RE100 can have a transformative impact. We find that these companies source electricity in 129 jurisdictions, accounting for <1% of total electricity generation (RE and non-RE), thus dampening the hopes about the impact of RE100 on the global energy transition. RE100 companies procure 1.4% of available RE, exceeding 20% in nine jurisdictions. To increase its impact, RE100 should focus on interim targets and expansion. By 2030, stringent and frequent interim targets could lead to a cumulated additional 361 TWh of RE procured by RE100 companies, and a realistic membership expansion could lead to procurement of 7.7% of globally available RE by RE100 companies.

Defending Root DNS Servers against DDoS Using Layered Defenses (Extended)

Distributed Denial-of-Service (DDoS) attacks exhaust resources, leaving a server unavailable to legitimate clients. The Domain Name System (DNS) is a frequent target of DDoS attacks. Since DNS is a critical infrastructure service, protecting it from DoS is imperative. Many prior approaches have focused on specific filters or anti-spoofing techniques to protect generic services. DNS root nameservers are more challenging to protect, since they use fixed IP addresses, serve very diverse clients and requests, receive predominantly UDP traffic that can be spoofed, and must guarantee high quality of service. In this paper we propose a layered DDoS defense for DNS root nameservers. Our defense uses a library of defensive filters, which can be optimized for different attack types, with different levels of selectivity. We further propose a method that automatically and continuously evaluates and selects the best combination of filters throughout the attack. We show that this layered defense approach provides exceptional protection against all attack types using traces of ten real attacks from a DNS root nameserver. Our automated system can select the best defense within seconds and quickly reduces traffic to the server within a manageable range, while keeping collateral damage lower than 2%. We show our system can successfully mitigate resource exhaustion using replay of a real-world attack. We can handle millions of filtering rules without noticeable operational overhead.

Machine learning-based target prediction for terrorist attacks

To address the problem that terrorist attacks are frequent and attack targets are widely difficult to predict, we use multidimensional features of terrorist attacks to predict terrorist targets based on a quantitative statistical analysis of data in the global terrorism database (GTD) from 1970 to 2019. In this paper, a machine learning-based prediction model (i.e., a classifier framework) is proposed. The model pre-processes GTD data and uses the OneHotEncoder and KBinsDiscretizer methods for data category transformation, classifies terrorist targets by four algorithms—SVM, decision trees, KNN and DNN. Each algorithm was trained with their parameters optimised, and the performance of the proposed model was tested and evaluated. The experimental results show that the prediction model achieved good performance in predicting the attack targets. The neural network had the best prediction performance in predicting twenty-two attack targets with 100% accuracy, indicating that the proposed model is accurate and effective.