bluuebunny/crossref_metadata_2025 huggingface dataset:
“Wrestling with Apartheid”: South Africa–US Amateur Wrestling Relations, Rebel Tours, and the Anti-Apartheid Movement, 1960–1991
Authors: Snyders Hendrik
Published: July 2021

From the onset, South African amateur wrestling, under the auspices of the SA Amateur Wrestling Union and its successors, was organized along racial lines and, under apartheid, it continued to cater exclusively to white amateurs. By 1970, it was suspended from the International Amateur Wrestling Federation. Denied participation in international competition, it resorted to rebel and boycott-busting tours involving a number of sympathetic countries and individuals in Europe, the Americas, and the Far East. Organized mostly clandestinely, it succeeded in offering international competition to the South African national wrestling team for almost two decades. One program, the Oregon Wrestling Cultural Exchange, was particularly strong. This US-based program generated strong opposition from the Amateur Athletics Association, the International Wrestling Federation, and several anti-apartheid organizations. It survived until the end of the 1980s, when the USA Comprehensive Anti-Apartheid Act (1986) and the campaigns of the anti-apartheid movement closed it down.
Circuit mechanisms for the chemical modulation of cortex-wide network interactions and behavioral variability
Authors: Pfeffer Thomas , Ponce-Alvarez Adrian , Tsetsos Konstantinos , Meindertsma Thomas , Gahnström Christoffer Julius , van den Brink Ruud Lucas , Nolte Guido , Engel Andreas Karl , Deco Gustavo , Donner Tobias Hinrich
Published: July 2021

Catecholamines and acetylcholine have dissociable effects on large-scale cortical network activity and behavior.
Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks
Authors: Rozum Jordan C. , Gómez Tejeda Zañudo Jorge , Gan Xiao , Deritei Dávid , Albert Réka
Published: July 2021

Fast analysis of attractor commitment in networks of stochastic switches answers a 50-year-old attractor scaling question.
Polycomb-group recruitment to a
Drosophila
target gene is the default state that is inhibited by a transcriptional activator
Authors: Ghotbi Elnaz , Ye Piao , Ervin Taylor , Kum Anni , Benes Judith , Jones Richard S.
Published: July 2021

Polycomb-group proteins are recruited to a target gene by default and do not require assistance from transcription factors.
Structural insights into the mechanism of human NPC1L1-mediated cholesterol uptake
Authors: Hu Miaoqing , Yang Fan , Huang Yawen , You Xin , Liu Desheng , Sun Shan , Sui Sen-Fang
Published: July 2021

Structures of NPC1L1 reveal how NPC1L1 senses the cholesterol level by conformational changes of the sterol-sensing domain.
Observation of triplet superconductivity in CoSi
2
/TiSi
2
heterostructures
Authors: Chiu Shao-Pin , Tsuei C. C. , Yeh Sheng-Shiuan , Zhang Fu-Chun , Kirchner Stefan , Lin Juhn-Jong
Published: July 2021

Conductance spectra and magnetoresistance hystereses point to topological p-wave superconductivity in CoSi
2
/TiSi
2
junctions.
Vitrification of octonary perylene mixtures with ultralow fragility
Authors: Hultmark Sandra , Cravcenco Alex , Kushwaha Khushbu , Mallick Suman , Erhart Paul , Börjesson Karl , Müller Christian
Published: July 2021

Mixtures of similar molecules can display an ultralow fragility, which facilitates the design of strong organic glass formers.
Incidence of injury in adult elite women’s football: a systematic review and meta-analysis
Authors: Mayhew Lawrence , Johnson Mark I , Francis Peter , Lutter Christoph , Alali Ali , Jones Gareth
Published: July 2021

Aim

To estimate the incidence of injury in adult elite women’s football and to characterise the nature and anatomical location of injuries.

Design

Systematic review and meta-analysis.

Data sources

Combinations of the key terms were entered into the following electronic databases (PubMed, SPORTDiscus, Science Direct and Discover) from inception to May 2021.

Eligibility criteria for selecting studies

(1) Used a prospective cohort design; (2) captured data on elite adult women players; (3) reported injury incidence by anatomical site; (4) captured data of at least one season or national team tournament; (5) included a definition of injury; and (6) written in English.

Results

The search identified 1378 records. Twelve studies published between 1991 and 2018 were included in our review and sampled 129 teams. In domestic club football, injury incidence rate was estimated to be 5.7/1000 hours (total), 19.5/1000 hours (match) and 3.1/1000 hours (training). In tournament, football match incidence was estimated to be 55.7/1000 hours. The knee (22.8%; 368/1822) was the most common site of injury in domestic club football. The ankle (23.7%, 105/443) was the most common site of injury in tournament football. Ligament sprains were the most common type of injury (27.8%), followed by muscle strains (19.1%). Severn studies (58%) had a high risk of bias associated with exposure definition and measurement and considerable heterogeneity exists between the included studies (I2=49.7%–95%).

Summary/conclusion

Ligament sprains occur more frequently in adult elite women football players. We advise caution in interpretating point estimates of the incidence of injury due to high statistical heterogeneity. Standardising injury reporting and the accurate recording of match and training exposure will overcome such limitations.

PROSPERO registration number

CRD42019130407.su
Thrombopoietin receptor agonists for acquired thrombocytopenia following anti-CD19 CAR-T-cell therapy: a case report
Authors: Baur Rebecca , Jitschin Regina , Kharboutli Soraya , Stoll Andrej , Völkl Simon , Büttner-Herold Maike , Schmidt Daniela , Rösler Wolf , Mackensen Andreas , Mougiakakos Dimitrios
Published: July 2021

Chimeric antigen receptor (CAR)-modified T-cells targeting CD19 represent a promising therapy for relapsed or refractory (r/r) lymphoma and leukemia. The most common adverse events are immune related and include cytokine release syndrome and neurotoxicity. However, early and late hematological toxicity has emerged as a substantial clinical hurdle leading among others to an increased risk for infections or bleeding. The underlying pathophysiology remains elusive and supportive measures comprise stem cell support or the use of growth factors. Here, we report a 66-year-old woman with r/r diffuse large B-cell lymphoma that received anti-CD19 CAR-T-cells achieving a complete metabolic remission. At month 3 after adoptive cell transfer, the patient still exhibited a grade 3 anemia and a grade 4 thrombocytopenia. The latter required regular platelet transfusions. Bone marrow smear revealed hypocellularity without dysplasia. Despite reduced megakaryopoiesis, immature platelet fraction was elevated indicating an at least partially consumptive underlying component. Based on the successful use of Romiplostim, a thrombopoietin receptor-agonist, in aplastic anemia and immune thrombocytopenia, we treated our patient accordingly. Platelet count (and hemoglobin levels) increased and the patient remains transfusion-free. Taken together, our therapeutic approach could represent a novel strategy for managing CAR-T-cell-related hematotoxicity but, self-evidently, requires further controlled clinical studies.
Oral SMEDDS promotes lymphatic transport and mesenteric lymph nodes target of chlorogenic acid for effective T-cell antitumor immunity
Authors: Ye Jun , Gao Yue , Ji Ming , Yang Yanfang , Wang Zhaohui , Wang Baolian , Jin Jing , Li Ling , Wang Hongliang , Xu Xiaoyan , Liao Hengfeng , Lian Chunfang , Xu Yaqi , Li Renjie , Sun Tong , Gao Lili , Li Yan , Chen Xiaoguang , Liu Yuling
Published: July 2021

Background

Mesenteric lymph nodes (MLNs) are critical draining lymph nodes of the immune system that accommodate more than half of the body’s lymphocytes, suggesting their potential value as a cancer immunotherapy target. Therefore, efficient delivery of immunomodulators to the MLNs holds great potential for activating immune responses and enhancing the efficacy of antitumor immunotherapy. Self-microemulsifying drug delivery systems (SMEDDS) have attracted increasing attention to improving oral bioavailability by taking advantage of the intestinal lymphatic transport pathway. Relatively little focus has been given to the lymphatic transport advantage of SMEDDS for efficient immunomodulators delivery to the MLNs. In the present study, we aimed to change the intestinal lymphatic transport paradigm from increasing bioavailability to delivering high concentrations of immunomodulators to the MLNs.

Methods

Chlorogenic acid (CHA)-encapsulated SMEDDS (CHA-SME) were developed for targeted delivery of CHA to the MLNs. The intestinal lymphatic transport, immunoregulatory effects on immune cells, and overall antitumor immune efficacy of CHA-SME were investigated through in vitro and in vivo experiments.

Results

CHA-SME enhanced drug permeation through intestinal epithelial cells and promoted drug accumulation within the MLNs via the lymphatic transport pathway. Furthermore, CHA-SME inhibited tumor growth in subcutaneous and orthotopic glioma models by promoting dendritic cell maturation, priming the naive T cells into effector T cells, and inhibiting the immunosuppressive component. Notably, CHA-SME induced a long-term immune memory effect for immunotherapy.

Conclusions

These findings indicate that CHA-SME have great potential to enhance the immunotherapeutic efficacy of CHA by activating antitumor immune responses.
Clinical and immunologic implications of COVID-19 in patients with melanoma and renal cell carcinoma receiving immune checkpoint inhibitors
Authors: Switzer Benjamin , Haanen John , Lorigan Paul C , Puzanov Igor , Turajlic Samra
Published: July 2021

The clinical and immunologic implications of the SARS-CoV-2 pandemic for patients with cancer receiving systemic anticancer therapy have introduced a multitude of clinical challenges and academic controversies. This review summarizes the current evidence, discussion points, and recommendations regarding the use of immune checkpoint inhibitors (ICIs) in patients with cancer during the SARS-CoV-2 pandemic, with a focus on patients with melanoma and renal cell carcinoma (RCC). More specifically, we summarize the theoretical concepts and available objective data regarding the relationships between ICIs and the antiviral immune response, along with recommended clinical approaches to the management of melanoma and RCC patient cohorts receiving ICIs throughout the course of the COVID-19 pandemic. Additional insights regarding the use of ICIs in the setting of current and upcoming COVID-19 vaccines and broader implications toward future pandemics are also discussed.
#3117 Fregoli syndrome in primary and secondary psychosis: a case level meta-analysis
Authors: Teixeira-Dias Maria , Dadwal Amber Kaur , Blackman Graham
Published: July 2021

Objectives/Aims

Fregoli syndrome is a rare delusion characterised by the misidentification of an individual, typically of someone who the patient has an emotional link towards. The pathoaetiology of Fregoli syndrome remains largely a mystery, however, it has been described in patients experiencing either a primary or secondary (organic) psychosis. We sought to compare the neuropsychiatric features of Fregoli syndrome in primary and secondary psychosis.

Methods

A patient-level meta-analysis was conducted. Five databases were searched for any descriptions of Fregoli syndrome. The patients and the psychotic episodes details alongside the co-occurring neuropsychiatric features and treatment responses were extracted. A risk of bias assessment was carried by scoring the methodological quality of all case studies. Random-effects models were used to pool the data and odds ratios and 95% confidence intervals were estimated for each of the neuropsychiatric features extracted between primary and secondary psychoses groups.

Results

A total of 119 patients (62 with primary psychosis, 50 with secondary psychosis and 7 with mixed or unknown aetiology) with Fregoli syndrome were identified in the English literature. Persecutory features were more likely to occur in patients with primary Fregoli syndrome (OR = 0.26, 95% CI[0.10;0.67], p < 0.01). In addition, Fregoli syndrome in the context of a first-episode psychosis (OR = 11.00, 95% CI [2.45;49.39], p < 0.01) and in the presence of neuroimaging abnormalities (OR = 20.19, 95% CI [4.36; 93.47], p < 0.01) was significantly associated with secondary aetiology. Patients in the secondary psychosis group (n=14) showed more right hemisphere lesions than patients in the primary psychosis group (n=1), however this trend was not significant (p = 0.10). Furthermore, no statistical differences between psychoses groups were found for the demographic, clinical and neurophysiological features analysed.

Conclusions

This is the first meta-analysis investigating the features of Fregoli syndrome in primary and secondary psychosis.Findings suggest that secondary causes of Fregoli syndrome are associated with a first-episode of psychosis and that neuroimaging abnormalities, particularly in the right hemisphere, are associated with a secondary organic cause.
8 Clinical update on delirium
Authors: MacLullich Alasdair MJ
Published: July 2021

Delirium affects more than 20% of older people in the acute hospital. It is has multiple adverse outcomes including increased length of stay, loss of independence, and increased mortality. The importance of distress in delirium, affecting both patients and carers, has emerged as a core issue in the care of patients with delirium. Additionally, recent research has shown that delirium is associated with a higher risk of new onset dementia as well as acceleration of existing dementia.

In this lecture the following topics will be covered: current diagnostic criteria for delirium; updates in understanding of terminology including appropriate use of the terms delirium and acute encephalopathy; epidemiology including the relationship between delirium and future dementia risk; a summary of current understanding of pathophysiology including delirium-dementia relationships; clinical care including detection (distinguishing between episodic and inpatient monitoring tools; treatment; prevention; future directions in clinical care and research.
Linear optical properties of a linear chain of interacting gold nanoparticles
Authors: Kheirandish Asef , Javan Nasser Sepehri , Mohammadzadeh Hosein
Published: July 2021

In a Drude-like model for the conduction electrons of metal nanoparticles (MNPs) in a periodic linear chain, considering dipole-dipole interactions of adjacent particles, an analytical expression is derived for each particle permittivity for two different polarizations of incident light: parallel with and perpendicular to the chain line. A numerical analysis is carried out for a chain including 10 identical gold nanoparticles (NPs) for two different sizes of NPs and two different host media: air and glass. It is shown that in the parallel case of polarization, interaction of NPs leads to a substantial increase in the extinction cross section and the redshift of the surface plasmon resonance (SPR) wavelength. In comparison with the linear properties of a single NP, the second and penultimate particles have the most increase in the extinction cross section and SPR wavelength displacement while the first and last particles experience the least variations due to the mutual interactions. For the perpendicular polarization, inversely, the dipolar coupling causes a decrease in extinction cross section of all particles and the blue-shift of SPR wavelength. For the parallel polarization, the absolute values of the real and imaginary parts of complex permittivity of each MNP decrease in comparison with the single particle case while they increase for the perpendicular state of polarization.
Infrared problem in perturbative quantum field theory
Authors: Duch Paweł
Published: July 2021

We propose a mathematically rigorous construction of the scattering matrix and the interacting fields in models of relativistic perturbative quantum field theory with massless fields and long-range interactions. We consider quantum electrodynamics and a certain model of interacting scalar fields in which the standard definition of the scattering matrix is not applicable because of the infrared problem. We modify the Bogoliubov construction using the ideas of Dollard, Kulish and Faddeev. Our modified scattering matrix and modified interacting fields are constructed with the use of the adiabatic limit which is expected to exist in arbitrary order of perturbation theory. In the paper, we prove this assertion in the case of the first- and the second-order corrections to the modified scattering matrix and the first-order corrections to the modified interacting fields. We study the physical properties of our construction. We conclude that the electrons and positrons are always surrounded by irremovable clouds of photons. Moreover, the physical energy-momentum operators do not coincide with the standard ones and their joint spectrum does not contain the mass hyperboloid.
Theoretical investigation of ternary semiconductors half-Heusler RhTaZ (Z = Si, Ge and Sn) for thermoelectric applications
Authors: Boudjeltia Mohammed Amine , Aziz Zoubir , Terkhi Sabria , Bennani Mohammed Abderrahim , Khandy Shakeel Ahmad , Bouadjemi Bouabdellah , Benidris Mansour , Bentata Samir
Published: July 2021

The structural, electronic, elastic, thermodynamic and thermoelectric properties of RhTaZ (Z = Si, Ge and Sn) half-Heusler materials have been studied using density functional theory. We have found that the compounds studied can be experimentally synthesized. Also, RhTaZ (Z = Si, Ge and Sn) alloys exhibit a semiconductor behavior following the Slater–Pauling rule. The elastic properties calculated confirm that our compounds are mechanically stable. Using Debye’s quasi-harmonic model, the thermodynamic properties of these half-Heusler alloys were investigated. For the study of thermoelectric properties, the semi-classical Boltzmann theory, as implemented in the BoltzTraP code, has been used. The high values obtained from the figure of merit for RhTaZ (Z = Si, Ge and Sn) compounds suggest that they are promising candidates for thermoelectric applications at low and high temperatures.
Improving the electrical properties of TiOx Schottky-type diode with an extra ZrO2 insulating layer
Authors: Fu Liping , Song Xiaoqiang , Li Yonggang , Wu Zewei , Fan Xiaolong , Gao Xiaoping
Published: July 2021

Titanium oxide has been considered a promising candidate for Schottky-type diode application. In this paper, an alternative approach for improving electrical properties of TiO[Formula: see text]-based Schottky-type diode has been demonstrated. Compared with the Ag/TiO[Formula: see text]/Ti structure Schottky-type diode, by embedding an extra ZrO2 insulating layer between the Ag/TiO[Formula: see text] interface, an extremely high rectifying ratio of 109 can be obtained in the Ag/ZrO2/TiO[Formula: see text]/Ti structure device. The improvement of the electrical properties in the Ag/ZrO2/TiO[Formula: see text]/Ti structure device can be attributed to the localized formation of Ag metal conductive filaments in ZrO2 layer after switching on.
Cognitive Robotics on 5G Networks
Authors: Lv Zhihan , Qiao Liang , Wang Qingjun
Published: July 2021

Emotional cognitive ability is a key technical indicator to measure the friendliness of interaction. Therefore, this research aims to explore robots with human emotion cognitively. By discussing the prospects of 5G technology and cognitive robots, the main direction of the study is cognitive robots. For the emotional cognitive robots, the analysis logic similar to humans is difficult to imitate; the information processing levels of robots are divided into three levels in this study: cognitive algorithm, feature extraction, and information collection by comparing human information processing levels. In addition, a multi-scale rectangular direction gradient histogram is used for facial expression recognition, and robust principal component analysis algorithm is used for facial expression recognition. In the pictures where humans intuitively feel smiles in sad emotions, the proportion of emotions obtained by the method in this study are as follows: calmness accounted for 0%, sadness accounted for 15.78%, fear accounted for 0%, happiness accounted for 76.53%, disgust accounted for 7.69%, anger accounted for 0%, and astonishment accounted for 0%. In the recognition of micro-expressions, humans intuitively feel negative emotions such as surprise and fear, and the proportion of emotions obtained by the method adopted in this study are as follows: calmness accounted for 32.34%, sadness accounted for 34.07%, fear accounted for 6.79%, happiness accounted for 0%, disgust accounted for 0%, anger accounted for 13.91%, and astonishment accounted for 15.89%. Therefore, the algorithm explored in this study can realize accuracy in cognition of emotions. From the preceding research results, it can be seen that the research method in this study can intuitively reflect the proportion of human expressions, and the recognition methods based on facial expressions and micro-expressions have good recognition effects, which is in line with human intuitive experience.
Pre-Trained Convolutional Neural Networks for Breast Cancer Detection Using Ultrasound Images
Authors: Masud Mehedi , Hossain M. Shamim , Alhumyani Hesham , Alshamrani Sultan S. , Cheikhrouhou Omar , Ibrahim Saleh , Muhammad Ghulam , Rashed Amr E. Eldin , Gupta B. B.
Published: July 2021

Volunteer computing based data processing is a new trend in healthcare applications. Researchers are now leveraging volunteer computing power to train deep learning networks consisting of billions of parameters. Breast cancer is the second most common cause of death in women among cancers. The early detection of cancer may diminish the death risk of patients. Since the diagnosis of breast cancer manually takes lengthy time and there is a scarcity of detection systems, development of an automatic diagnosis system is needed for early detection of cancer. Machine learning models are now widely used for cancer detection and prediction research for improving the successive therapy of patients. Considering this need, this study implements pre-trained convolutional neural network based models for detecting breast cancer using ultrasound images. In particular, we tuned the pre-trained models for extracting key features from ultrasound images and included a classifier on the top layer. We measured accuracy of seven popular state-of-the-art pre-trained models using different optimizers and hyper-parameters through fivefold cross validation. Moreover, we consider Grad-CAM and occlusion mapping techniques to examine how well the models extract key features from the ultrasound images to detect cancers. We observe that after fine tuning, DenseNet201 and ResNet50 show 100% accuracy with Adam and RMSprop optimizers. VGG16 shows 100% accuracy using the Stochastic Gradient Descent optimizer. We also develop a custom convolutional neural network model with a smaller number of layers compared to large layers in the pre-trained models. The model also shows 100% accuracy using the Adam optimizer in classifying healthy and breast cancer patients. It is our belief that the model will assist healthcare experts with improved and faster patient screening and pave a way to further breast cancer research.
The Complexity of Approximately Counting Retractions to Square-free Graphs
Authors: Focke Jacob , Goldberg Leslie Ann , Živný Stanislav
Published: July 2021

A
retraction
is a homomorphism from a graph
G
to an induced subgraph
H
of
G
that is the identity on
H
. In a long line of research, retractions have been studied under various algorithmic settings. Recently, the problem of approximately counting retractions was considered. We give a complete trichotomy for the complexity of approximately counting retractions to all square-free graphs (graphs that do not contain a cycle of length 4). It turns out there is a rich and interesting class of graphs for which this problem is complete in the class #BIS. As retractions generalise homomorphisms, our easiness results extend to the important problem of approximately counting homomorphisms. By giving new #BIS-easiness results, we now settle the complexity of approximately counting homomorphisms for a whole class of non-trivial graphs that were previously unresolved.
Energy-collision-aware Minimum Latency Aggregation Scheduling for Energy-harvesting Sensor Networks
Authors: Chen Quan , Cai Zhipeng , Cheng Lianglun , Gao Hong , Li Jianzhong
Published: July 2021

The emerging energy-harvesting technology enables charging sensor batteries with renewable energy sources, which has been effectively integrated into Wireless Sensor Networks (EH-WSNs). Due to the limited energy-harvesting capacities of tiny sensors, the captured energy remains scarce and differs greatly among nodes, which makes the data aggregation scheduling problem more challenging than that in energy-abundant WSNs. In this article, we investigate the Minimum Latency Aggregation Scheduling (MLAS) problem in EH-WSNs. First, we identify a new kind of collision in EH-WSNs, named as energy-collision, and design several special structures to avoid it during data aggregation. To reduce the latency, we try to choose the parent adaptively according to nodes’ transmission tasks and energy-harvesting ability, under the consideration of collisions avoidance. By considering transmitting time, residual energy, and energy-collision, three scheduling algorithms are proposed under protocol interference model. Under physical interference model, several approximate algorithms are also designed by taking account of the interference from the nodes several hops away. Finally, the theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency.
Approximate Counting of
k
-Paths: Simpler, Deterministic, and in Polynomial Space
Authors: Lokshtanov Daniel , BjÖrklund Andreas , Saurabh Saket , Zehavi Meirav
Published: July 2021

Recently, Brand et al. [STOC 2018] gave a
randomized
mathcal O(4

k

m
ε
-2
-time exponential-space algorithm to approximately compute the number of paths on
k
vertices in a graph
G
up to a multiplicative error of 1 ± ε based on exterior algebra. Prior to our work, this has been the state-of-the-art. In this article, we revisit the algorithm by Alon and Gutner [IWPEC 2009, TALG 2010], and obtain the following results:

• We present a
deterministic
4

k
+
O
(√
k
(log
k
+log
2
ε
-1
))

m
-time
polynomial-space
algorithm. This
matches
the running time of the best known deterministic polynomial-space algorithm for
deciding
whether a given graph
G
has a path on
k
vertices.

• Additionally, we present a
randomized
4

k
+mathcal O(log
k
(log
k
+logε
-1
))

m
-time
polynomial-space
algorithm. Our algorithm is simple—we only make elementary use of the probabilistic method.

Here,
n
and
m
are the number of vertices and the number of edges, respectively. Additionally, our approach extends to approximate counting of other patterns of small size (such as
q
-dimensional
p
-matchings).
Securely Sharing Randomized Code That Flies
Authors: Jelesnianski Christopher , Yom Jinwoo , Min Changwoo , Jang Yeongjin
Published: July 2021

Address space layout randomization was a great role model, being a light-weight defense technique that could prevent early return-oriented programming attacks. Simple yet effective, address space layout randomization was quickly widely adopted. Conversely, today only a trickle of defense techniques arebeing integrated or adopted mainstream. As code reuse attacks have evolved in complexity, defenses have strived to keep up. However, to do so, many have had to take unfavorable tradeoffs like using background threads or protecting only a subset of sensitive code. In reality, these tradeoffs were unavoidable steps necessary to improve the strength of the state of the art. In this article, we present
Mardu
, an on-demand system-wide runtime re-randomization technique capable of scalable protection of application as well as shared library code that most defenses have forgone. We achieve code sharing with diversification by implementing reactive and scalable rather than continuous or one-time diversification. Enabling code sharing further removes redundant computation like tracking and patching, along with memory overheads required by prior randomization techniques. In its baseline state, the code transformations needed for
Mardu
security hardening incur a reasonable performance overhead of 5.5% on SPEC and minimal degradation of 4.4% in NGINX, demonstrating its applicability to both compute-intensive and scalable real-world applications. Even when under attack,
Mardu
only adds from less than 1% to up to 15% depending on application size and complexity.
Report on the CyCAT winter school on fairness, accountability, transparency and ethics (FATE) in AI
Authors: Kleanthous Styliani , Otterbacher Jahna , Bates Jo , Giunchiglia Fausto , Hopfgartner Frank , Kuflik Tsvi , Orphanou Kalia , Paramita Monica L. , Rovatsos Michael , Shulner-Tal Avital
Published: July 2021

The first FATE Winter School, organized by the Cyprus Center for Algorithmic Transparency (CyCAT) provided a forum for both students as well as senior researchers to examine the complex topic of Fairness, Accountability, Transparency and Ethics (FATE). Through a program that included two invited keynotes, as well as sessions led by CyCAT partners across Europe and Israel, participants were exposed to a range of approaches on FATE, in a holistic manner. During the Winter School, the team also organized a hands-on activity to evaluate a tool-based intervention where participants interacted with eight prototypes of bias-aware search engines. Finally, participants were invited to join one of four collaborative projects coordinated by CyCAT, thus furthering common understanding and interdisciplinary collaboration on this emerging topic.
Simplicity in mechanism design
Authors: Li Shengwu
Published: July 2021

This is an annotated reading list about simplicity in mechanism design.
The Impact of Experienced and Expressed Emotion on Legal Factfinding
Authors: Salerno Jessica M.
Published: July 2021

Judges and jurors are asked to comb through horrific evidence of accidents and crimes when choosing verdicts and punishment. These factfinders are likely to experience and express intense emotions as a result. A review of social, cognitive, moral, and legal psychological science illuminates how experienced and expressed emotions in legal settings can unconsciously bias even the most well-intentioned, diligent factfinder's decision-making processes in prejudicial ways. Experiencing negative emotions creates motivation to blame and punish—instigating blame validation processes to justify guilty/liability verdicts and harsher punishments. The review also examines how emotion expression can impugn legal actors’ credibility when it violates factfinders’ (often unrealistic) expectations for appropriate emotion in legal contexts. It considers misguided and promising interventions to help factfinders regulate emotional responses, advocating limiting emotional evidence as much as possible and, when not possible, helping factfinders reframe how they think about it and remain aware of their potential biases.
Ins and Outs of the TCA Cycle: The Central Role of Anaplerosis
Authors: Inigo Melissa , Deja Stanisław , Burgess Shawn C.
Published: July 2021

The reactions of the tricarboxylic acid (TCA) cycle allow the controlled combustion of fat and carbohydrate. In principle, TCA cycle intermediates are regenerated on every turn and can facilitate the oxidation of an infinite number of nutrient molecules. However, TCA cycle intermediates can be lost to cataplerotic pathways that provide precursors for biosynthesis, and they must be replaced by anaplerotic pathways that regenerate these intermediates. Together, anaplerosis and cataplerosis help regulate rates of biosynthesis by dictating precursor supply, and they play underappreciated roles in catabolism and cellular energy status. They facilitate recycling pathways and nitrogen trafficking necessary for catabolism, and they influence redox state and oxidative capacity by altering TCA cycle intermediate concentrations. These functions vary widely by tissue and play emerging roles in disease. This article reviews the roles of anaplerosis and cataplerosis in various tissues and discusses how they alter carbon transitions, and highlights their contribution to mechanisms of disease.
Remembering the Past to See the Future
Authors: Rust Nicole C. , Palmer Stephanie E.
Published: July 2021

In addition to the role that our visual system plays in determining what we are seeing right now, visual computations contribute in important ways to predicting what we will see next. While the role of memory in creating future predictions is often overlooked, efficient predictive computation requires the use of information about the past to estimate future events. In this article, we introduce a framework for understanding the relationship between memory and visual prediction and review the two classes of mechanisms that the visual system relies on to create future predictions. We also discuss the principles that define the mapping from predictive computations to predictive mechanisms and how downstream brain areas interpret the predictive signals computed by the visual system.
The Impact of Micro Porous Layer on Liquid Water Evolution inside PEMFC using Lattice Boltzmann Method
Authors: Sepe M. , Satjaritanun P. , Zenyuk I. V. , Tippayawong N. , Shimpalee S.
Published: July 2021

Proton exchange membrane fuel cells (PEMFCs) require a gas diffusion layer to aid in fuel transport to the catalyst sites. A microporous layer (MPL) is often added to the GDL to improve liquid saturation inside gas diffusion media. In this work, the lattice Boltzmann method was applied to four GDL samples with the addition of an MPL. Three injection orientations were used to study liquid evolution through the samples. Each orientation used four different injection pressures, ranging from 5,000 Pa to 8,000 Pa. Saturation data for GDL samples with and without an MPL were compared. Results showed that when adding an MPL, liquid tends to distribute laterally under the MPL until pressure is reached to allow liquid to travel through the cracks of the MPL surface and into the GDL geometry. A more uniform saturation distribution across the sample is seen when comparing both types of GDLs. The outcomes of this work will help research that requires knowledge of the internal liquid transport through gas diffusion media for PEMFC application.
(Invited) Carbon Nanotubes Cloaked in Synthetic Polymers: Aqueous Dispersion, Characterization, and Applications
Authors: Budhathoki-Uprety Januka , Dewey Hannah , Sultana Nigar , Chen Yu , Jones Jaron
Published: July 2021

Surface chemistry plays a crucial role in interactions of carbon nanotubes in the biological environment. Biomimetic functionalities on nanotubes could facilitate effective nano-bio interactions enabling nanoscale biological probes, sensors, and imaging agents. Synthetic polymers that facilitate aqueous solubility, biocompatibility and molecular recognition via biomimicry are highly preferred for multifunctional carbon nanotube-based biological probes. In this talk, we will introduce carbon nanotubes cloaked in synthetic mimics of biopolymers and uses of those nanoscale probes in optical sensing of target biomolecules.
(Invited) Bioelectronics with Nanocarbons
Authors: Cohen-Karni Tzahi
Published: July 2021

We focus on developing a new class of nanoscale materials for the investigation of biological entities at multiple length scales, from the molecular level to complex cellular networks. Our highly flexible bottom-up nanomaterials synthesis capabilities allow us to form unique hybrid-nanomaterials. Recently, we have demonstrated highly controlled synthesis of 3D out-of-plane single- to few-layer fuzzy graphene (3DFG) on a Si nanowire (SiNW) mesh template. By varying graphene growth conditions, we control the size, density, and electrical properties of the NW templated 3DFG (NT-3DFG). This flexible synthesis inspires formation of complex hybrid-nanomaterials with tailored optical and electrical properties to be used in biosensing, and energy-related research. The exceptional synthetic control and flexible assembly of nanomaterials provide powerful tools for fundamental studies and applications in life science and open up the potential to seamlessly merge either nanomaterials-based platforms or unique nanosensor geometries and topologies with cells, fusing nonliving and living systems together.
(Invited) Biomimetic Nanocomposites for Implantable Devices
Authors: Kotov Nicholas A.
Published: July 2021

Materials with difficult-to-attain combination of multiple properties - mechanical, electrical, optical, chemical, transport, and biological – represent the quintessential bottleneck implantable and in particularly neuroprosthetic devices. Nanocomposites with molecular, nano-, meso-, and microscale levels of structural engineering can address these requirement, which can be demonstrated on the basis of layered biomimetic nanocomposites from nanoparticles, nanoshells, and carbon nanotubes. Besides mechanical robustness making possible their implantation, the biomimetic nanocomposites can exceed charge injection capacity and other key electrochemical characteristics of gold, IrOx and other materials used currently for neural stimulation. Small dimensions of the nanocomposite electrodes afford marked reduction of the scar tissue formation around implants. Photoactive multilayer from semiconductor particles were used to grow neuron precursor cells on them. It was found that light adsorbed in the nanoparticle layers results in the electrical excitation of the neurons making this system a functional analog of retina. Cartilage-like nanocomposites from aramid nanofibers also provide the long-term corrosion-resistant protection for a wide range of neuroprosthetic devices. New strides toward the design of the protective coatings and other nanomaterials for implantable devices using graph theory (GT) will be described.
(Invited) Imaging and Modulating Brain Activity in the Second Near-Infrared Window with Carbon and Polymeric Nanomaterials
Authors: Wu Xiang , Rommelfanger Nicholas Joseph , Hong Guosong
Published: July 2021

Optical approaches to image and modulate brain activity are limited in their penetration depth in live animals, owing to the strong scattering and absorption of photons in the visible spectrum. Carbon nanotubes and carbon-based polymers, in contrast, afford unique optical properties in the second near-infrared window (NIR-II window, 1000-1700 nm) with reduced scattering and absorption by the brain. In this talk, I will present my lab's latest work on the imaging and modulation of brain activity with carbon nanotubes and carbon-based polymeric nanoparticles in the live mouse brain. Specifically, the NIR-II window enables through-scalp imaging of brain vasculature and modulation of deep-brain neural activity in freely behaving animals via a minimally invasive, implant-free, and tether-free optical interface.
(Invited) Single-Walled Carbon Nanotubes As Optical Probes for Imaging and Biosensing
Authors: Pan Jing , Du Yancheng , Choi Jong Hyun
Published: July 2021

Single-walled carbon nanotubes (SWCNT) are exceptionally photostable fluorophores that emit in the near-infrared range. Their novel physical and chemical properties make them particularly appealing as optical probes for microscopy and spectroscopy. The π-electron rich side wall of SWCNT allows various biopolymers to be conjugated through π-π stacking, enabling novel applications in biology and medicine. In particular, oligonucleotides (DNA or RNA) have been widely used to functionalize SWCNT due to its specific base-pairing properties and programmability. Here we demonstrate the use of DNA-SWCNT hybrid nanomaterial in fundamental biophysics research and biomolecular sensing applications. In the first system, we show SWCNT can be used as a photo-stable imaging probe for optically tracking DNA walker's transport characteristics. DNA walkers are synthetic nanosystems that exploit the structural specificity and functional diversity of oligonucleotides to mimic intracellular protein motors. We integrated a DNA walker system onto SWCNT and demonstrated transportation of quantum dots along SWCNT track. We used localization microscopy and single-particle tracking to record the displacement time series of multiple walkers, which is then used to build the statistical distribution of speed, displacement and walking turnover time. The statistical characteristics of the system help extract time averaged and ensemble averaged walker kinetics, which provide biochemical and biophysical insights about the system. In the second system, we demonstrate using aptamer-SWCNT as a novel sensor architecture for biomolecular detection. We non-covalently functionalized SWCNT with porphyrin binding aptamers, which retains aptamer's target specificity and nanotube's optical property. We discovered the photoluminescence of aptamer-SWCNT is selectively quenched upon binding to heme, an iron-containing porphyrin present in diverse biological processes. The aptamer-SWCNT complex also serves as a quencher for the intrinsic fluorescence of porphyrins. We propose the two optical transduction signatures are induced by specific binding of aptamer to heme and non-specific adsorption of other porphyrin species on the side wall of SWCNT. Using these two properties, we developed a sensing mechanism for four porphyrin species present in the biosynthetic pathway, and demonstrated multiplexed porphyrin detection in blood plasma. Our work shows that SWCNT is a useful optical material for both fundamental biomolecular engineering research and biomedical applications.
Immobilization of Protein Probes on Graphene Field-Effect Transistors for Biomolecular Sensing
Authors: Bazan Claudia M. , Wilhelm Brian T. , Smith Matthew J. , Bouilly Delphine
Published: July 2021

The development of biosensor arrays able to detect specific protein interactions is highly needed to precisely dissect fundamental biological systems and to broaden the scope of biomarker detection, especially to refine diagnostics of subtyped diseases such as cancer. Graphene-based field-effect transistor sensors (GFETs) are a promising emerging technology for such biomolecular sensing applications: their atomically-thin surface provides label-free sensitivity to biomolecules via direct electrostatic interactions, and their small footprint enables compact, rapid and parallelized assays. The selectivity of GFET sensors, however, requires functionalization of the graphene surface with a layer of bio-recognition species (“probe molecules”). In this presentation, we will describe our recent progress in immobilizing proteins as probe molecules on graphene field-effect transistors, specifically (1) monoclonal antibodies against a biomarker specific to MLL-translocated acute myeloid leukemia and (2) small Ras GTPase proteins regulated by various effector proteins. First, we will describe our GFET sensor design, based on on-chip arrays of GFETs made from CVD-grown graphene, mounted with a multi-channel delivery flow-cell enabling parallel assays on sub-ensembles of sensors. We will then present our investigation of protein immobilization on graphene. We found that antibodies and small proteins can spontaneously adhere to the graphene surface, but this adhesion is partially reversible under solution flow. To create stable anchor groups at the graphene surface which can then capture the protein probes, we propose to use covalent chemistry on the graphene surface. In particular, we developed a protocol based on electrochemically-driven aryldiazonium chemistry to increase the rate of formation and the density of anchor groups on the graphene surface. Using time-resolved electrical measurements, we observed a specific electrical signal associated with the irreversible immobilization of protein probes on the graphene surface. Finally, we will discuss the use of such protein-functionalized GFETs for the detection of specific probe-target interactions, for applications in fundamental biophysics and cancer diagnostics.
(Invited) A Wearable Optical Microfibrous Biomaterial with Encapsulated Nanosensors Enables Wireless Monitoring of Oxidative Stress
Authors: Safaee Mohammad Moein , Gravely Mitchell , Roxbury Daniel
Published: July 2021

In an effort to facilitate personalized medical approaches, the continuous and noninvasive monitoring of biochemical information using wearable technologies can enable a detailed understanding of an individual’s physiology. Reactive oxygen species (ROS) are a class of oxygen-containing free radicals which function in a wide range of biological processes. In wound healing applications, the continuous monitoring of ROS through a wearable diagnostics platform is essential for the prevention of chronicity and pathogenic infection. Here, a versatile one-step procedure is utilized to fabricate optical core-shell microfibrous textiles incorporating single-walled carbon nanotubes (SWCNTs) for the real-time optical monitoring of hydrogen peroxide concentrations in wounds. The environmentally sensitive and non-photobleachable fluorescence of SWCNTs enables continuous analyte monitoring without a decay in signal over time. The existence of multiple chiralities of SWCNTs emitting near-infrared fluorescence with narrow bandwidths allows a ratiometric signal readout invariant to the excitation source distance and exposure time. The individual fibers encapsulate the SWCNT nanosensors for at least 21 days without apparent loss in structural integrity. Moreover, the microfibrous textiles can be utilized to spatially resolve peroxide concentrations on a wound surface using a camera and can be integrated into commercial wound bandages without being altered or losing their optical properties.
(Invited) In Vivo and Ex Vivo Biomarker Quantification Via Single-Walled Carbon Nanotube Near-Infrared Fluorescence
Authors: Williams Ryan M.
Published: July 2021

Optical nanosensors hold the promise of rapid, minimally-invasive longitudal monitoring of analytes within a patient or at the bedside. Such devices will allow for informed clinical intervention based on changes in disease state profiles. We are designing nanosensors based on the optical properties of single-walled carbon nanotubes (SWCNT) for use in both in vivo and ex vivo formats. SWCNT fluorescence is in the ‘tissue-transparent’ near-infrared spectrum, allowing for fluorescence measurements through biological tissue and fluids. Further, SWCNT fluorescence is photostable and responds rapidly, allowing for multiple measurements over time. We are engineering SWCNT-based sensors such that their fluorescence emission responds to multiple cancer biomarkers and inflammatory proteins. Various deployment formats include semipermeable implantable membranes, injectable hydrogel materials, and chip-based devices. Within each device, we are comparing sensor response with its physicochemical properties to optimize sensor functionality. Finally, we are deploying each sensor device in patient serum, other clinical tissues, and in live animal models of disease. For each, we are using custom-built near-infrared probe spectroscopy with rapid point-and-detect functionality. We expect these translational sensor devices to have potential as research tools or clinical diagnostics to detect disease at early stages, evaluate disease response to treatment, or monitor disease progression. These aims will allow physicians to make rapid, informed decisions on patient prognosis and treatment.