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Internet of Things (IoT) techniques have been employed in many areas, e.g., vehicles, smart home, and medicine. Among the applications of IoTs, the Internet of Vehicles (IoV) is one of the most popular techniques. IoVs are protected by public key cryptographic systems, such as RSA and ECC. However, such systems are vulnerable to quantum computer attacks. Thus, we improve the security of IoV-based post-quantum signatures, which can resist quantum computer attacks. The key operations are divisions in a finite field. Hence, we improve the security of IoV-based post-quantum signatures with division by employing systolic architectures. We propose a systolic architecture for computing division in composite fields. After that, we improve the IoT security-based post-quantum signatures with systolic divisions. We test and verify our design on a Field-Programmable Gate Array (FPGA); the experimental results confirm our estimates. Furthermore, the optimized method proposed can be further applied to various applications like solving system of linear equations and cryptographic applications for IoT security.

PDF file - 85K, Relationship between TP53 (A) or KRAS (B) gene status and TAK 960 concentration producing EC50 values. Each data point represents a mean concentration producing 50% efficacy (EC50) value for TAK 960 in an individual cell line.

PDF file - 144K, Comparison of dosing regimens.

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Polo-like kinase 1 (PLK1) is a serine/threonine protein kinase involved in key processes during mitosis. Human PLK1 has been shown to be overexpressed in various human cancers, and elevated levels of PLK1 have been associated with poor prognosis, making it an attractive target for anticancer therapy. TAK-960 [4-[(9-cyclopentyl-7,7-difluoro-5-methyl-6-oxo-6,7,8,9-tetrahydro-5H-pyrimido[4,5-b][1,4]diazepin-2-yl)amino]-2-fluoro-5-methoxy-N-(1-methylpiperidin-4-yl) benzamide] is a novel, investigational, orally bioavailable, potent, and selective PLK1 inhibitor that has shown activity in several tumor cell lines, including those that express multidrug-resistant protein 1 (MDR1). Consistent with PLK1 inhibition, TAK-960 treatment caused accumulation of G2–M cells, aberrant polo mitosis morphology, and increased phosphorylation of histone H3 (pHH3) in vitro and in vivo. TAK-960 inhibited proliferation of multiple cancer cell lines, with mean EC50 values ranging from 8.4 to 46.9 nmol/L, but not in nondividing normal cells (EC50 >1,000 nmol/L). The mutation status of TP53 or KRAS and MDR1 expression did not correlate with the potency of TAK-960 in the cell lines tested. In animal models, oral administration of TAK-960 increased pHH3 in a dose-dependent manner and significantly inhibited the growth of HT-29 colorectal cancer xenografts. Treatment with once daily TAK-960 exhibited significant efficacy against multiple tumor xenografts, including an adriamycin/paclitaxel-resistant xenograft model and a disseminated leukemia model. TAK-960 has entered clinical evaluation in patients with advanced cancers. Mol Cancer Ther; 11(3); 700–9. ©2011 AACR.

PDF file - 130K, Anti-tumor activity of TAK-960 in MV4-11luc disseminated leukemia model.

The blood-brain barrier (BBB) plays a critical role in preventing harmful endogenous and exogenous substances from penetrating the brain. Optimal brain penetration of small molecule CNS drugs is characterized by a high unbound brain/plasma ratio (Kp,uu). While various medicinal chemistry strategies and in silico models have been reported to improve BBB penetration, none were developed to predict Kp,uu directly. We describe a physics-based computational approach, solvation free energy calculations (energy of solvation or E-sol), to predict Kp,uu. Prospective application of this method to internal CNS drug discovery programs highlighted the utility and accuracy of this new method, which showed a categorical accuracy of 79% and a R2 of 0.61 from a linear regression model.

The generation frequency of grid-connected units determines the power supply reliability of the grid and primary frequency regulation, as the first guarantee to stabilize the grid frequency is affected by the category of generating units and operation mode and lacks systematic real-time optimization and monitoring means. This paper takes a 300MW sub-critical heating unit as the research object, and researches, and analyzes three aspects of signal homologation, multi-dimensional optimization, and intelligent decision-making to establish the evaluation model of the primary frequency regulation capability of the unit. The evaluation accuracy of the assessment model reaches 83%, develops the control platform based on autonomous controllable PLC, realizes intelligent dynamic control and the replacement of traditional optimization technology means, also improves the qualification rate of primary frequency regulation by about 23.2%.

This paper is concerned with the outer exponential synchronization of the drive-response complex dynamical networks subject to time-varying delays. The dynamics of nodes is complex valued, the interactions among of the nodes are directed, and the two coupling matrices in the drive system and the response system are also different. The intermittent pinning control is proposed to achieve outer exponential synchronization in the aperiodical way. Some novel sufficient conditions are derived to guarantee outer exponential synchronization of the considered complex-valued complex networks by using the Lyapunov functional method. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed control protocols.

Histone demethylase LSDl (KDMlA) belongs to the flavin adenine dinucleotide (FAD) dependent family of monoamine oxidases and is vital in regulation of mammalian biology. Dysregulation and overexpression of LSD1 are hallmarks of a number of human diseases, particularly cancers that are characterized as morphologically poorly differentiated. As such, inhibitors of LSD1 have potential to be beneficial as a cancer therapy. The most clinically advanced inhibitors of LSDl are covalent inhibitors derived from tranylcypromine (TCP). Herein, we report the discovery of a novel series of reversible and selective LSDl inhibitors. Exploration of structure-activity relationships (SARs) and optimization of ADME properties resulted in the identification of clinical candidate CC-90011. CC-90011 exhibits potent on-target induction of cellular differentiation in acute myeloid leukemia (AML) and small cell lung cancer (SCLC) cell lines, and antitumor efficacy in patient-derived xenograft (PDX) SCLC models. CC-90011 is currently in phase 2 trials in patients with first line, extensive stage SCLC (ClinicalTrials.gov identifier: NCT03850067).

Human islet amyloid polypeptide (hIAPP, also known as amylin) is a co-secreting protein of insulin in human pancreatic β-cells. It is encapsulated in vesicles and secreted out of the cells with insulin. hIAPP can promote insulin secretion and regulate blood glucose homeostasis in the body under the normal physiological conditions. However, hIAPP misfolding or excessive accumulation can cause toxic effects on the β cells, which in turn affect cell function, resulting in type 2 diabetes mellitus (T2DM) for the affected individuals. In order to eliminate the excessive accumulation of hIAPP in the cell and to maintain its normal synthetic function, we have adopted a new protein degradation technology called Trim-Away, which can degrade the target protein in a short time without affecting the mRNA transcription and translation synthesis function of the target protein. First, we overexpressed hIAPP in the rat insulinoma cells (INS1) to simulate its excessive accumulation and analyzed its effect in INS1 cells by measuring the release of LDH (lactate dehydrogenase), CCK8 activity and PI-Annexin V positive ratio. Results showed that excessive accumulation of hIAPP caused β cell apoptosis. Second, real-time quantitative PCR analysis and ELISA detection showed that the synthesis and secretion of insulin were hindered. We used Trim-Way technology to specifically eliminate the excessive accumulation of hIAPP protein in hIAPP overexpressing INS1 cells. Cell activity experiments confirmed that clearance of hIAPP reduced the cell death phenotype. Further ELISA experiments confirmed that INS1 cells restored insulin secretion ability. This study examined the toxic effect of hIAPP excessive accumulation in INS1 cells and demonstrated the cytotoxicity clearance effect of Trim-Way technology in pancreatic β-cells. Our research has provided a new strategy for using Trim-Away technology for treatment of diabetes.人胰岛淀粉样多肽(human islet amyloid polypeptide, hIAPP)又称胰淀素(Amylin),是胰岛β细胞中胰岛素的共分泌蛋白,与胰岛素共同包裹在囊泡中被分泌出细胞。正常生理条件下,hIAPP有助于胰岛素分泌并调节机体血糖平衡;但其蛋白错误折叠或过量积累则会对细胞造成毒性,进而影响β细胞功能,导致机体罹患2型糖尿病(type 2 diabetes mellitus, T2DM)。为了清除细胞内过度积累的hIAPP,且不影响其正常的合成功能,本研究选用一种新的蛋白质降解技术——Trim-Away,该技术可以在短时间内降解目标蛋白质,且不会对靶蛋白的mRNA转录、翻译等功能产生影响。首先在大鼠(

Among Internet of Things (IoTs), cloud-based IoTs help retain the confidentiality of both device-to-cloud and cloud-to-device messages by setting up individual identities and credentials for each IoT devices. As recently been emphasized by two American institutes, National Institute of Standards and Technology (NIST) and National Security Agency (NSA), cloud-based IoTs that use RSA and ECC signatures are insecure under quantum computer attacks. To ensure the security in the cloud-based IoTs under quantum computer attacks, there is a critical need for implementations of new quantum-resistance signature systems, such as Unbalanced Oil and Vinegar (UOV), for making the cloud-based IoTs more secure and reliable. In order to analyze the security of UOV for cloud-based IoTs, we present an efficient algorithm based on side channel analysis of UOV, which combines inducing faults and Hamming distance power analysis. We implement UOV signature schemes on Sakura-G FPGA board via using Verilog-HDL code and Xilinx ISE software, where the power collection uses a 350 MHz Keysights oscilloscope. Based on the experimental results, we successfully recover all the secret keys of UOV signature, which shows that we should protect UOV and related signatures against side channel attacks when they are adopted in cloud-based IoTs.

This paper presents the exponential synchronization of complex dynamical networks, in which the dynamics of nodes is complex-valued, the interactions among of the nodes are directed, and subject to time-varying delays. The aperiodically intermittent pinning control is proposed to achieve synchronization. Based on the Lyapunov functional method, complex-valued differential equations, stability theory, matrix theory and modern control technique, some novel sufficient conditions are derived to guarantee exponential synchronization of the proposed complex-valued dynamical directed networks. To illustrate the effectiveness of the theoretical results, some numerical examples are finally given.

The Internet of Medical Things (IoMTs) are the group of medical devices connected to Internet, to perform the processes and services that support healthcare. The amount of data handled by medical devices grows exponentially, which means higher exposure of personal sensitive data. RSA, ECC and, other related public key cryptographic systems with countermeasures of power analysis and fault analysis, e.g., random masking, are often adapted by medical devices for guaranteing security and privacy. However, Shor algorithm has proven that they are not secure to quantum computer attacks. Fortunately, there exists a few quantum-resistant public key cryptographic schemes, e.g., Rainbow. To ensure end-to-end service delivery in the IoMTs under quantum attacks, there is a critical need for research into new designs and evaluation for the hardware security of new quantum-resistance cryptographic systems, e.g., rainbow, to make the medical devices more secure and reliable. Therefore, we present a physical analysis model of Rainbow by combining fault analysis and differential power analysis. The proposed model is implemented on cloud computing platform. Based on the experimental results, we successfully recover all the secret keys of Rainbow signature, which shows the importance of protecting multivariate signature with countermeasures on medical devices.

Multivariate signature belongs to Multivariate-Quadratic-Equations Public Key Cryptography (MPKC), which is secure to quantum computer attacks. Compared with RSA and ECC, it is required to speed up multivariate signature implementations. A high-speed hardware architecture for signature generations of a multivariate scheme is proposed in this paper. The main computations of signature generations of multivariate schemes are additions, multiplications, inversions, and solving systems of linear equations (LSEs) in a finite field. Thus, we improve the finite field multiplications via using composite field expression and design a finite field inversion via using binary trees. Besides, we improve solving LSEs in a finite field based on a variant algorithm of Gauss-Jordan elimination and use the XOR gates to compute additions. We implement the high-speed hardware architecture based on the above improvements on an Altera Stratix Field-Programmable Gate Array (FPGA), which shows that it takes only 90 clock cycles and 0.9 μs to generate a multivariate signature. The comparison shows that the hardware architecture is much faster than other implementations.

In order to improve MQ cryptographic systems on Internet of Things (IoTs) devices, we propose an efficient hardware architecture of Gaussian Elimination in finite fields where area usage is more of a priority. In order to validate our design and verify its effectiveness, an experiment is carried out by using TSMC-0.18 µ m standard cell CMOS Application Specific Integrated Circuit (ASIC), which shows that our design is well suit for MQ cryptographic systems.

Secure storage devices are a good example of the Internet of Things (IoTs), which require secure access control mechanisms via using the prominent pubic key cryptographic systems, e.g. RSA, ECC and related systems. However, quantum computer is in a position to attack RSA, ECC and other signature algorithms adopted by many storage devices. Therefore, storage security is facing severe threats. In this paper, an efficient hardware architecture based on multivariate scheme for storage devices is proposed. Multivariate scheme belongs to multivariate public key cryptography (MPKC), which uses affine transformations and central map transformations during cryptographic operations. The advantage of adopting multivariate scheme is that multivariate scheme is immune to quantum computer attack. The efficient hardware architecture is composed of processor module, cryptographic module, storage module, display module, power module, keyboard module, export module and terminal module (off-chip). We implement the hardware architecture on the methodology of TSMC-0.18 μm standard cell CMOS Application Specific Integrated Circuit. The implementation results show that the architecture based on multivariate scheme is very efficient and well suit for storage devices.

Introduction: MALT1 (mucosa-associated lymphoid tissue lymphoma translocation protein 1) is a key mediator of the NF-κB signaling pathway, the main driver of a subset of B-cell lymphomas and functions by forming a complex with CARMA1 and BCL10 to mediate antigen receptor-induced lymphocyte activation. MALT1 is considered a potential therapeutic target for several subtypes of non-Hodgkin B-cell lymphomas and chronic lymphocytic leukemia (CLL). Previously, we described the discovery of novel and potent MALT1 inhibitors with anti-proliferative effects in non-Hodgkin B-cell lymphoma cells. Here, we highlight the strong anti-tumor activity of our MALT1 inhibitors across multiple tumor models and the combination potential with agents including standard-of-care. Results: Novel small molecule MALT1 inhibitors were identified using Schrodinger's proprietary physics-based free energy perturbation (FEP+) modeling technology. These molecules demonstrate strong MALT1 protein binding affinity, potent inhibition of MALT1 enzymatic activity and anti-proliferative activity in the activated B-cell (ABC) subtype of diffuse large B cell lymphoma (DLBCL) cell lines such as OCI-LY3 and OCI-LY10. In combination with approved agents, these inhibitors demonstrate strong combination potential with Bruton's tyrosine kinase (BTK) inhibitors such as ibrutinib in ABC-DLBCL cell lines. In ABC-DLBCL CDX models, our representative MALT1 inhibitor induces tumor regression as a single agent and complete tumor regression in combination with ibrutinib. Our representative MALT1 inhibitor, when tested in LY2298 PDX models, demonstrates similar results. In addition, our representative MALT1 inhibitor was explored in a CDX model derived from a Mantle cell lymphoma REC-1 cell line, and demonstrates strong anti-tumor activity of ~78% tumor growth inhibition (TGI) as a single agent. Conclusions: Schrodinger's novel, potent MALT1 protease small molecule inhibitors are efficacious in in vitro B-cell lymphoma cell proliferation assays and in in vivo B-cell lymphoma xenograft models. These data suggest that targeting MALT1 may expand therapeutic options for patients with selected B-cell lymphomas, such as ABC-DLBCL, with the possibility of expanding into other B-cell lymphomas such as MCL. Furthermore, these small molecule MALT1 inhibitors demonstrate potential in combination with BTKi to overcome drug-induced resistance in patients with relapsed/refractory B-cell lymphomas. Taken together, the data presented here strongly underscore the therapeutic potential of our MALT1 inhibitor and support further evaluation in clinical trials. Disclosures Weiss: Schrodinger: Current Employment; ARTham Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Blockchain is a distributed and append-only data management system maintained by many nodes from Peer-to-Peer (P2P) networks, where one of the most important and successful applications is Bitcoin. In blockchain P 2 P networks, consensus algorithms are playing a key role and take a lot of time. For example, Bitcoin uses Proof-of-Work (PoW) consensus algorithm, which takes 60 minutes to acknowledge a new transaction. Compared with the traditional data management technology, blockchain systems are very inefficient. Thus, it is very crucial to improve the blockchain consensus. We present threshold digital signature techniques to exploit the blockchain consensus mechanism. First, we propose a threshold signature scheme based on NP-hard problem, i.e., solving quadratic equations in a finite field, which is considered to be secure against quantum computer attacks and traditional attacks. Second, we further propose an efficient blockchain consensus algorithm based on the new threshold signature scheme. Third, we build a new blockchain system based on the consensus algorithm. The analysis of the blockchain system shows that the efficiency and security is must better than current blockchain systems.

The diffusion of selenite (labeled with 75Se) in compacted Beishan granite (BsG) was investigated using the in-diffusion capillary method at pH values from ∼2.0 to ∼11.0 under oxic and anoxic conditions. The results indicate that the apparent diffusion coefficient (Da) values of selenite in BsG always reached the minimum at approximately pH 5. Unexpectedly, the Da values under oxic conditions are nearly one order of magnitude lower than those under the anoxic conditions. Further characterization reveals the existence of redox-sensitive Fe(II)-containing components, which can be responsible for the great difference in Da values. Fe(2p) X-ray photoelectron spectroscopy (XPS) results show that more Fe(III)-oxyhydroxide coating is formed on the granite’s surface under aerobic conditions than is formed under anaerobic conditions. Correspondingly, Se(3d) spectra indicate that more selenium is sorbed under oxic conditions, and the sorbed amount always reached the maximum at pH values from ∼4 to ∼5. A linear combination fit of X-ray absorption near edge structure (XANES) spectroscopy data revealed that Se(0) was formed under anoxic condition and that selenite preferred to form inner-sphere complexes with Fe(III)-oxyhydroxide. Overall, this study indicates that natural Fe-bearing minerals can greatly attenuate selenite diffusion and the retardation would be enhanced under aerobic conditions.

Smart Connected Health Systems (SCHSs) belong to health systems that provide services of health care remotely. They provide the doctors with access to electronic medical records with the aid of medical sensors, smart wearable devices and smart medical instruments. Although SCHSs have many applications in the area of health care, securing massive amount of valuable and sensitive data of the patients and preserving the privacy are challenging. User authentication based on public key cryptographic techniques is playing a crucial role in SCHSs for protecting the privacy of patients. However, quantum computers will break such techniques. Rainbow signature is one of the candidates of the next generation of cryptographic algorithms which can resist attacks on quantum computers. However, it is vulnerable to Differential Power Analysis (DPA) attacks, which is based on information gained from the cryptographic implementations. We present techniques to exploit the countermeasures to protect Rainbow against DPA attacks. We propose a variant of Rainbow with resistance to DPA attacks. First, we take a random vector to randomize the power consumption of private keys during computing the first affine transformation; Second, random variables are adopted during computing central map transformation; Third, we take two random vectors during computing the second affine transformation to randomize the power consumption of private keys. We analyze the efficiency and implement the scheme on hardware. Compared with the related implementations, our scheme is efficient and suitable for signature generations on hardware. Besides, we propose a secure authentical scheme based on the implementation for protecting record of patients in SCHSs.

With the rapid growth of high-resolution remote sensing image-based applications, one of the fundamental problems in managing the increasing number of remote sensing images is automatic object detection. In this paper, we present a fusion feature-based deep learning approach to detect objects in high-resolution remote sensing images. It employs fine-tuning from ImageNet as a pre-training model to address the challenge of it lacking a large amount of training datasets in remote sensing. Besides, we improve the binarized normed gradients algorithm by multiple weak feature scoring models for candidate window selection and design a deep fusion feature extraction method with the context feature and object feature. Experiments are performed on different sizes of high-resolution optical remote sensing images. The results show that our model is better than regular models, and the average detection accuracy is 8.86% higher than objNet.

Environmental scientists and geoscientists working in different fields regard the reactivity of calcite and corresponding changes in its trace elemental- or isotopic composition from diametrically opposed points of view. As one extreme, calcite based environmental remediation strategies rely on the fast recrystallization of calcite and the concurrent uptake and immobilization of pollutants. Paleo-ecological investigations denote the other extreme, and rely on the invariability of calcite composition over geological periods of time. We use long-term radiotracer experiments to quantify recrystallization rates of seven types of calcite powder with diverse morphology and particle size distribution. On the one hand our results demonstrate the long-term metastability of calcite with equilibrated crystal surfaces even at isotopic dis-equilibrium. On the other hand, we document the extremely high reactivity and interfacial free energy of freshly ground, rough calcite. Our results indicate that bulk calcite recrystallization is an interfacial free energy driven Ostwald-ripening process, in which particle roughness effects dominate over the effect of crystal habitus and particle size. We confirm that the dynamic equilibrium exchange of crystal constituents between kink sites involves an activation barrier of about 25 kJ/mol. At room temperature the equilibrium exchange is limited to a near surface region and proceeds at a rate of (3.6 ± 1.4)·10

This present work aims to functionalize poly(amidoamine) (PAMAM) dendrimers with various reported adhesive peptides, including Arg-Gly-Asp (RGD), Tyr-Ile-Gly-Ser-Arg (YIGSR), and Ile-Lys-Val-Ala-Val (IKVAV) for enhancing cell responses. The RGD, YIGSR, or IKVAV functionalized PAMAM coated substrate could promote cell adhesion of bone marrow mesenchymal stem cells (BMSCs) within 1 h after incubation. The neurite differentiation and proliferation of pheochromocytoma (PC12) cells were also significantly enhanced after culturing on the peptide functionalized PAMAM dendrimers for two and four days. This peptide functionalized PAMAM dendrimers are considered as the potential candidates for various tissue engineering applications.

The histone demethylase LSD1 is a key enzyme in the epigenetic regulation of gene transcription. Here we present our efforts to discover small molecule reversible inhibitors of LSD1 as an attractive approach to treat hematologic malignancies and certain solid tumors. Using structure-based drug design, we designed and synthesized a novel series of heteroaromatic imidazole inhibitors that demonstrate potent inhibition of the demethylase activity and low nanomolar cell-based activity. This novel LSD1 inhibitor series was further optimized by attenuating the hERG inhibition and improving oral bioavailability.

As the use of Internet, computers and mobile devices expands, a learning management system for college students has become necessary. Therefore, we design an efficient learning management system based on cloud computing for programming learning, which can advance student learning and interacting. We divide the learning management system into three platforms, i.e. SaaS learning platform, PaaS learning platform and IaaS learning platform. SaaS learning platform provides lesson system, learning system, examining system, document system, forum system and programming system for programming learning. PaaS learning platform provides VS 2015 Community, C-free, Eclipse, SQL Server, Oracle, IIS, Apache for programming learning. IaaS learning platform provides network infrastructure, computing infrastructure, storage infrastructure for programming learning. By integrating the designs of three learning platforms, we implement our designs on OpenStack cloud computing system, by using Microsoft ASP. Net (version 4.0) and SQL Server (version 2008). The experimental results show that the learning management system based on cloud computing for programming learning is very efficient and provides learning services on SaaS, PaaS, IaaS platforms for computer major students.

Some nodes may perform in selfish way in opportunistic networking activities to save their own resources. Once selfish nodes become more, how they will affect the whole networking system is an interesting research question. In this paper, we analyze the selfish behaviors for several popular routing protocols in opportunistic network. Also we made some simulations to check the influence of varying the degree of cooperation. Besides, we also study some strategies in MobiCent in preventing selfish behavior. The experiment result shows encouraging signal that MobiCent and other strategies are useful to prevent selfish behaviors.

Many Chinese cities have been experiencing severe pollution. To reduce the environmental impacts of transport pollution and purse sustainable developments of society, many cites in China have adopted transport policies that primarily aim to reduction in ownership and usage of motor vehicles and promote use of public transport. The primary solution should be the development of mass public transit systems, e.g. public bike rental systems. Public bike rental systems have received increasing attention in recent years with initiatives to increase public transport usage and lessen the environmental impacts. However, most of the universities in China are located in the suburbs. The limited coverage of public bike rental systems and transportation network offers college students limited access to public transit systems. We design an efficient mobile system for bike sharing on campus, with the aim of improving travel conditions for students at institutions of higher education. The bike sharing system includes two parts, i.e. client and server. Client is designed based on Android system and server is designed based on Openstack cloud computing system. The bike sharing system can bring information of bike sharing and entertainment together from diverse sources on campus in a uniform way. The bike sharing system provides a consistent look and feel with access control and procedures for multiple applications and databases of bike sharing and entertainment. We divide the bike sharing system into five functional modules, i.e. login module, lessor module, lessee module and administrator module. By integrating the designs of four modules, we use Eclipse and MySQL to implement the bike sharing system based on Android.

Knowledge of the geochemical behavior of selenium and strontium is critical for the safe disposal of radioactive wastes. Goethite, as one of the most thermodynamically stable and commonly occurring natural iron oxy-hydroxides, promisingly retains these elements. This work comprehensively studies the adsorption of Se(IV) and Sr(II) on goethite. Starting from electrokinetic measurements, the binary and ternary adsorption systems are investigated and systematically compared via batch experiments, EXAFS analysis, and CD-MUSIC modeling. Se(IV) forms bidentate inner-sphere surface complexes, while Sr(II) is assumed to form outer-sphere complexes at low and intermediate pH and inner-sphere complexes at high pH. Instead of a direct interaction between Se(IV) and Sr(II), our results indicate an electrostatically driven mutual enhancement of adsorption. Adsorption of Sr(II) is promoted by an average factor of 5 within the typical groundwater pH range from 6 to 8 for the concentration range studied here. However, the interaction between Se(IV) and Sr(II) at the surface is two-sided, Se(IV) promotes Sr(II) outer-sphere adsorption, but competes for inner-sphere adsorption sites at high pH. The complexity of surfaces is highlighted by the inability of adsorption models to predict isoelectric points without additional constraints.