Reviewerly/exHarmony huggingface dataset:
A Biogeochemical study of Pandanus candelabrum in Liberia: A potential geobotanical indicator for kimberlite pipes in tropical terranes

Pandanus is recently recognized as a new geobotanical indicator for kimberlite diatremes in Liberia. The plant also grows in non-kimberlite terranes making it critical to determine the differences, similarities or contrasts between the chemical nutrient uptake of elements into the tissues (roots, fronds, bark and trunk) of the plant from substrates of fertile kimberlite and those of non-economic regional country rock. A random sampling survey was adopted in which 20 soils and 59 Pandanus tissues of roots, fronds trunks, and bark were collected over a kimberlite pipe in NW Liberia. In addition, 9 soils and 27 Pandanus samples covering the equivalent botanical tissues, except for trunk, were obtained over three granodiorite gneiss, non-kimberlite locations. A total of 5,865 analyses for major and trace elements including REE were obtained by Inductively Coupled Plasma Mass Spectrometry on Pandanus candelabrum and their soil hosts. Major Mg and trace elements of Co, Cr, Ni, Ba, Cs, Nb, Rb, Sr, Zr and REEs are enriched in the kimberlitic eluvium compared to soils from granodiorite gneisses. Diagnostic Cr, Ni, Ba, Rb, Sr, Zr and REE in Pandanus tissues on the kimberlite pipe have distinctive concentrations making the plant a new biogeochemical tool in the exploration for kimberlites in tropical cratonic terranes.
SDAN-MD: Supervised dual attention network for multi-stage motion deblurring in frontal-viewing vehicle-camera images

Motion blur in images usually distorts the information of objects, thus degrading the performance of semantic segmentation. However, there is no previous research on improving the segmentation performance by restoring the frontal-viewing vehicle-camera images taken under motion blur. Therefore, this study proposes a supervised dual attention network for multi-stage motion deblurring (SDAN-MD) for this task. In SDAN-MD, a supervised dual attention module (SDAM) is proposed, which adopts the supervised spatial and channel attention mechanisms to provide a supervisory signal of ground truth. In addition to Charbonnier loss and edge loss, we use perceptual loss utilizing Euclidean distance based on feature maps obtained from the segmentation network. Experiments were conducted with the motion blurred databases from the two open databases of road scene, Cambridge driving Labeled Video Database (CamVid) and Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI).The results show that the proposed SDAN-MD achieves 92.89% and 87.27% pixel accuracies in semantic segmentation using these two databases, respectively, outperforming the state-of-the-art methods.
Improving Gender-Related Fairness in Sentence Encoders: A Semantics-Based Approach

Abstract The ever-increasing number of systems based on semantic text analysis is making natural language understanding a fundamental task: embedding-based language models are used for a variety of applications, such as resume parsing or improving web search results. At the same time, despite their popularity and widespread use, concern is rapidly growing due to their display of social bias and lack of transparency. In particular, they exhibit a large amount of gender bias, favouring the consolidation of social stereotypes. Recently, sentence embeddings have been introduced as a novel and powerful technique to represent entire sentences as vectors. We propose a new metric to estimate gender bias in sentence embeddings, named bias score . Our solution leverages semantic importance of words and previous research on bias in word embeddings, and it is able to discern between neutral and biased gender information at sentence level. Experiments on a real-world dataset demonstrate that our novel metric can identify gender stereotyped sentences. Furthermore, we employ bias score to detect and then remove or compensate for the more stereotyped entries in text corpora used to train sentence encoders, improving their degree of fairness. Finally, we prove that models retrained on fairer corpora are less prone to make stereotypical associations compared to their original counterpart, while preserving accuracy in natural language understanding tasks. Additionally, we compare our experiments with traditional methods for reducing bias in embedding-based language models.
Simulation of agricultural digital economy development and policy support system based on resource sensitivity index

The development of science and technology has also led to the progress of rural digital economy. In China, the construction of new countryside has always been an important part of economic development. The application of big data technology in rural areas can not only promote the development of rural economy, but also improve the results of environmental protection. Using the matching coefficient method of agricultural water and soil environmental characteristics, it match the rural water and soil environmental characteristics and the impact of the water environment in the autonomous region. An indispensable driving force in the process, agricultural digitalization will update the rural economic development model, weaken the barriers to the dual structure of urban and rural areas, stabilize agricultural production, promote sustainable rural development, and promote rural economic development. The current government policy support, the urgent need for new development momentum for rural economic development, and the advancement of changes in the lifestyle of urban and rural residents are promoting high-quality development of the rural economy. At the same time, we are facing challenges such as the lack of local network coverage, the lack of logistics, sales systems, and the lack of talents with digital skills. Expanding rural network coverage, optimizing rural logistics and distribution, promoting the development of agricultural big data, and strengthening the development of digital human resources are important ways for agricultural digitalization to promote rural economic development. The research focus of this paper is the parallel development of rural digital economy and environmental protection under the big data economy, and its application in the current agricultural development can achieve a win–win situation between man and nature.
A new pathway for considering trigger factors based on parallel-serial connection models and displaying the relationships of causal factors in low-probability events

To determine the effect size of observed factors considering trigger factors based on parallel-serial models and to explore how multiple factors can be related to the result of complex events for low-probability events with binary outcomes.A low-probability event with a true binary outcome can be explained by a trigger factor. The models were based on the parallel-serial connection of switches; causal factors, including trigger factors, were simplified as switches. Effect size values of an observed factor for an outcome were calculated as SAR = (Pe-Pn)/(Pe + Pn), where Pe and Pn represent percentages in the exposed and nonexposed groups, respectively, and SAR represents standardized absolute risk. The influence of trigger factors is eliminated by SAR. Actual data were collected to obtain a deeper understanding of the system.SAR values of < 0.25, 0.25-0.50, and > 0.50 indicate low, medium, and high effect sizes, respectively. The system of data visualization based on the parallel-serial connection model revealed that at least 7 predictors with SAR > 0.50, including a trigger factor, were needed to predict schizophrenia. The SAR of the HLADQB1*03 gene was 0.22 for schizophrenia.It is likely that the trigger factors and observed factors had a cumulative effect, as indicated by the parallel-serial connection model for binary outcomes. SAR may allow better evaluation of the effect size of a factor in complex events by eliminating the influence of trigger factors. The efficiency and efficacy of observational research could be increased if we are able to clarify how multiple factors can be related to a result in a pragmatic manner.
Improving Language Ability Through The Method Of Playing With Letters Flashcards Media

This study aimed to improve language skills through the method of playing with letter flashcards in group A children at TK Handayani Tiga. This study was conducted as a professional capability strengthening of teachers, which was carried out in two cycles. The subject of professional capability strengthening of teachers was carried out in two cycles. This study consisted of four stages, namely planning, implementing, observing, and reflecting. The subjects of strengthening were the Group A students of TK Handayani Tiga, with 20 children. Data collection in this strengthening was carried out using the technique of playing with picture cards or flashcards while studying. There were also several other techniques, namely conversation, observation, performance, assignments, and work results. The results showed that (1) there was an increase in the average percentage of student learning activeness of 20% (including the criteria of being quite active) in cycle I increased to 60% in cycle II. There was an increase in the percentage of 95%, including moderate criteria. Based on the results, it can be concluded that playing activities with the media of letter flashcards can improve language skills in group A of TK Handayani Tiga.
On Non-uniform Security for Black-Box Non-interactive CCA Commitments

We obtain a black-box construction of non-interactive CCA commitments against non-uniform adversaries. This makes black-box use of an appropriate base commitment scheme for small tag spaces, variants of sub-exponential hinting PRG (Koppula and Waters, Crypto 2019) and variants of keyless sub-exponentially collision-resistant hash function with security against non-uniform adversaries (Bitansky, Kalai and Paneth, STOC 2018 and Bitansky and Lin, TCC 2018). All prior works on non-interactive non-malleable or CCA commitments without setup first construct a “base” scheme for a relatively small identity/tag space, and then build a tag amplification compiler to obtain commitments for an exponential-sized space of identities. Prior black-box constructions either add multiple rounds of interaction (Goyal, Lee, Ostrovsky and Visconti, FOCS 2012) or only achieve security against uniform adversaries (Garg, Khurana, Lu and Waters, Eurocrypt 2021). Our key technical contribution is a novel tag amplification compiler for CCA commitments that replaces the non-interactive proof of consistency required in prior work. Our construction satisfies the strongest known definition of non-malleability, i.e., CCA2 (chosen commitment attack) security. In addition to only making black-box use of the base scheme, our construction replaces sub-exponential NIWIs with sub-exponential hinting PRGs, which can be obtained based on assumptions such as (sub-exponential) CDH or LWE.
Encouraging Data Literacy via an Open Academic Digital Platform

The aim of this paper was to find out if members of an academic online community felt empowered to form collaborative relationships with their peers, sharing knowledge and experiences and more importantly increasing their knowledge on the subject data. We were able to assess the perception on the topic of data literacy based on the information gathered through a research action approach. According to the data, the participants engaged in mutual support during online meetings and answering questions about the relationship about the topic and their experiences. Although it was clear that during the time of the pandemic, the participants prioritized the topics that were most urgent for them, we still managed to achieve the objective of increasing the knowledge of data for the students engaged. For them it was clear the necessity to align data with social issues. For future studies it is necessary to think about the creation of interdisciplinary courses where the teaching of data is closer to the reality of the students.
Caveat Implementor! Key Recovery Attacks on MEGA

MEGA is a large-scale cloud storage and communication platform that aims to provide end-to-end encryption for stored data. A recent analysis by Backendal, Haller and Paterson (IEEE S &P 2023) invalidated these security claims by presenting practical attacks against MEGA that could be mounted by the MEGA service provider. In response, the MEGA developers added lightweight sanity checks on the user RSA private keys used in MEGA, sufficient to prevent the previous attacks. We analyse these new sanity checks and show how they themselves can be exploited to mount novel attacks on MEGA that recover a target user's RSA private key with only slightly higher attack complexity than the original attacks. We identify the presence of an ECB encryption oracle under a target user's master key in the MEGA system; this oracle provides our adversary with the ability to partially overwrite a target user's RSA private key with chosen data, a powerful capability that we use in our attacks. We then present two distinct types of attack, each type exploiting different error conditions arising in the sanity checks and in subsequent cryptographic processing during MEGA 's user authentication procedure. The first type appears to be novel and exploits the manner in which the MEGA code handles modular inversion when recomputing $$u=q^{-1} \bmod p$$ . The second can be viewed as a small subgroup attack (van Oorschot and Wiener, EUROCRYPT 1996, Lim and Lee, CRYPTO 1998). We prototype the attacks and show that they work in practice. As a side contribution, we show how to improve the RSA key recovery attack of Backendal-Haller-Paterson against the unpatched version of MEGA to require only 2 logins instead of the original 512. We conclude by discussing wider lessons about secure implementation of cryptography that our work surfaces.
On the Hardness of the Finite Field Isomorphism Problem

The finite field isomorphism $$(\textsf{FFI})$$ problem was introduced in PKC’18, as an alternative to average-case lattice problems (like $$\textsf{LWE}$$ , $$\textsf{SIS}$$ , or $$\textsf{NTRU}$$ ). As an application, the same paper used the $$\textsf{FFI}$$ problem to construct a fully homomorphic encryption scheme. In this work, we prove that the decision variant of the $$\textsf{FFI}$$ problem can be solved in polynomial time for any field characteristics $$q= \varOmega (\beta n^2)$$ , where $$q,\beta ,n$$ parametrize the $$\textsf{FFI}$$ problem. Then we use our result from the $$\textsf{FFI}$$ distinguisher to propose polynomial-time attacks on the semantic security of the fully homomorphic encryption scheme. Furthermore, for completeness, we also study the search variant of the $$\textsf{FFI}$$ problem and show how to state it as a q-ary lattice problem, which was previously unknown. As a result, we can solve the search problem for some previously intractable parameters using a simple lattice reduction approach.
Reverse Firewalls for Oblivious Transfer Extension and Applications to Zero-Knowledge

In the setting of subversion, an adversary tampers with the machines of the honest parties thus leaking the honest parties' secrets through the protocol transcript. The work of Mironov and Stephens-Davidowitz (EUROCRYPT'15) introduced the idea of reverse firewalls (RF) to protect against tampering of honest parties' machines. All known constructions in the RF framework rely on the malleability of the underlying operations in order for the RF to rerandomize/sanitize the transcript. RFs are thus limited to protocols that offer some structure, and hence based on public-key operations. In this work, we initiate the study of efficient Multiparty Computation (MPC) protocols in the presence of tampering. In this regard, The key idea of our work is to demonstrate that correlated randomness may be obtained in an RF-friendly way without having to rerandomize the entire transcript. This enables us to avoid expensive public-key operations that grow with the circuit-size.
Endemic Oblivious Transfer via Random Oracles, Revisited

The notion of Endemic Oblivious Transfer (EOT) was introduced by Masny and Rindal (CCS’19). EOT offers a weaker security guarantee than the conventional random OT; namely, the malicious parties can fix their outputs arbitrarily. The authors presented a 1-round UC-secure EOT protocol under a tailor-made and non-standard assumption, Choose-and-Open DDH, in the RO model. In this work, we systematically study EOT in the UC/GUC framework. We present a new 1-round UC-secure EOT construction in the RO model under the DDH assumption. Under the GUC framework, we propose the first 1-round EOT construction under the CDH assumption in the Global Restricted Observable RO (GroRO) model proposed by Canetti et al. (CCS’14). We also provide an impossibility result, showing there exist no 1-round GUC-secure EOT protocols in the Global Restricted Programmable RO (GrpRO) model proposed by Camenisch et al. (Eurocrypt’18). Subsequently, we provide the first round-optimal (2-round) EOT protocol with adaptive security under the DDH assumption in the GrpRO model. Finally, we investigate the relations between EOT and other cryptographic primitives. As side products, we present the first 2-round GUC-secure commitment in the GroRO model as well as a separation between the GroRO and the GrpRO models, which may be of independent interest.
How to Compress Encrypted Data

We study the task of obliviously compressing a vector comprised of n ciphertexts of size $$\xi $$ bits each, where at most t of the corresponding plaintexts are non-zero. This problem commonly features in applications involving encrypted outsourced storages, such as searchable encryption or oblivious message retrieval. We present two new algorithms with provable worst-case guarantees, solving this problem by using only homomorphic additions and multiplications by constants. Both of our new constructions improve upon the state of the art asymptotically and concretely. Our first construction, based on sparse polynomials, is perfectly correct and the first to achieve an asymptotically optimal compression rate by compressing the input vector into $$\mathcal {O}({t \xi })$$ bits. Compression can be performed homomorphically by performing $$\mathcal {O}({n \log n})$$ homomorphic additions and multiplications by constants. The main drawback of this construction is a decoding complexity of $$\varOmega (\sqrt{n})$$ . Our second construction is based on a novel variant of invertible bloom lookup tables and is correct with probability $$1-2^{-\kappa }$$ . It has a slightly worse compression rate compared to our first construction as it compresses the input vector into $$\mathcal {O}({\xi \kappa t /\log t})$$ bits, where $$\kappa \ge \log t$$ . In exchange, both compression and decompression of this construction are highly efficient. The compression complexity is dominated by $$\mathcal {O}({n \kappa /\log t})$$ homomorphic additions and multiplications by constants. The decompression complexity is dominated by $$\mathcal {O}({\kappa t /\log t})$$ decryption operations and equally many inversions of a pseudorandom permutation.
Exploration of Transformational Leadership in Innovation—The Case of the Lebanese Banking Sector

Perceived as the driving force of organizational performance, innovation has become today the major challenge of all institutions. Based on leadership theories, the objective of this study is to analyze the contribution of the components of transformational leadership to the development of different types of innovation within the banking sector in Lebanon. Exploiting a qualitative approach based on semi-structured interviews conducted with seven senior executives occupying key positions in five major commercial banks in Lebanon, our research confirms the essential role of intellectual stimulation and inspirational motivation of transformational leadership in the banking innovation, while the other two dimensions, the idealized influence and individualized consideration, play a very limited role in the banking sector. This study allows us to better understand the role of each of the transformational leadership dimensions in order to promote and escort innovation in the banking sector.
Data Security Strategies in Digital Health Services: A Bibliometric Analysis

An increasing occurrence of facts that threaten public health, such as the COVID-19 pandemic, is driving the adoption of digital technologies, generating a large volume of data, and making the management, protection, and confidentiality of this information challenging. This paper aimed to carry out a bibliometric analysis to map data security strategies and tools in telehealth services and digital health. To this end, an exploratory study was conducted by collecting and analyzing secondary data from the Web of Science. This paper contributes to digital health providers by pointing out vulnerabilities, potentials, and trends in privacy and security of health care systems.
Identifying Behavioral Norms within Teams

Interactions among teams and people is considered normal within society. Defining and being able to identify traits that may assist in the improvement of a team, is the aim of this paper. There are two subgroups of behavioral norms or traits that will be explored. Communication norms can be defined as the way members of a group interact or provide information to each other (Dyer & Dyer, 2020). Task norms can be defined as how things are accomplished. The exploration of these domains and potential ways to systematically improve people and groups, is essential to the success of an organization.
NanoGRAM: Garbled RAM with $$\widetilde{O}(\log N)$$ Overhead

We propose a new garbled RAM construction called NanoGRAM, which achieves an amortized cost of $$\widetilde{O}(\lambda \cdot (W \log N + \log ^3 N))$$ bits per memory access, where $$\lambda $$ is the security parameter, W is the block size, and N is the total number of blocks, and $$\widetilde{O}(\cdot )$$ hides $${\textsf{poly}} \log \log $$ factors. For sufficiently large blocks where $$W = \varOmega (\log ^2 N)$$ , our scheme achieves $$\widetilde{O}(\lambda \cdot W \log N)$$ cost per memory access, where the dependence on N is optimal (barring $${\textsf{poly}} \log \log $$ factors), in terms of the evaluator’s runtime. Our asymptotical performance matches even the interactive state-of-the-art (modulo $${\textsf{poly}} \log \log $$ factors), that is, running Circuit ORAM atop garbled circuit, and yet we remove the logarithmic number of interactions necessary in this baseline. Furthermore, we achieve asymptotical improvement over the recent work of Heath et al. (Eurocrypt ’22). Our scheme adopts the same assumptions as the mainstream literature on practical garbled circuits, i.e., circular correlation-robust hashes or a random oracle. We evaluate the concrete performance of NanoGRAM and compare it with a couple of baselines that are asymptotically less efficient. We show that NanoGRAM starts to outperform the naïve linear-scan garbled RAM at a memory size of $$N = 2^9$$ and starts to outperform the recent construction of Heath et al. at $$N = 2^{13}$$ . Finally, as a by product, we also show the existence of a garbled RAM scheme assuming only one-way functions, with an amortized cost of $$\widetilde{O}(\lambda ^2 \cdot (W \log N + \log ^3 N))$$ per memory access. Again, the dependence on N is nearly optimal for blocks of size $$W = \varOmega (\log ^2 N)$$ bits.