Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Impact of Perceived Risk on User’s Mobile Payment Adoption

The actual adoption rate of mobile payment in Taiwan is lower than expected. In order to understand the impact of perceived risk on users’ mobile payment adoption, this study identified five main factors and eighteen sub-factors through a literature review and an expert questionnaire and then used an AHP questionnaire to find out the decision weights of these factors. The weights of the five main factors from high to low are perceived usefulness, perceived ease of use, facilitating conditions, perceived risk, and social influence. The top six sub-factors are system stability, convenience, transaction speed, user interface, transaction flexibility, and system performance, which belong to perceived usefulness and perceived ease of use, respectively. In addition, this study adopts Fuzzy AHP to analyze the moderate impact of perceived risk on other main factors. The results show that when the importance of perceived usefulness reaches medium to high and perceived ease of use reaches a high level, the negative impact of perceived risk can be more effectively reduced. Therefore, this study suggests that service providers should strengthen the most important sub-factors of perceived usefulness and perceived ease of use to reduce the negative impact and increase the adoption rate of mobile payment services.
Increased risk of SARS-CoV-2 reinfection associated with emergence of the Omicron variant in South Africa 2021-12-01

Objective To examine whether SARS-CoV-2 reinfection risk has changed through time in South Africa, in the context of the emergence of the Beta, Delta, and Omicron variants Design Retrospective analysis of epidemiological surveillance data Setting Line list data on SARS-CoV-2 with specimen receipt dates between 04 March 2020 and 27 November 2021, collected through South Africa’s National Notifiable Medical Conditions Surveillance System Participants 2,796,982 individuals with laboratory-confirmed SARS-CoV-2 who had a positive test result at least 90 days prior to 27 November 2021. Individuals having sequential positive tests at least 90 days apart were considered to have suspected reinfections.
Increased risk of SARS-CoV-2 reinfection associated with emergence of the Omicron variant in South Africa 2021-12-01

Objective To examine whether SARS-CoV-2 reinfection risk has changed through time in South Africa, in the context of the emergence of the Beta, Delta, and Omicron variants Design Retrospective analysis of routine epidemiological surveillance data Setting Line list data on SARS-CoV-2 with specimen receipt dates between 04 March 2020 and 27 November 2021, collected through South Africa’s National Notifiable Medical Conditions Surveillance System Participants 2,796,982 individuals with laboratory-confirmed SARS-CoV-2 who had a positive test result at least 90 days prior to 27 November 2021. Individuals having sequential positive tests at least 90 days apart were considered to have suspected reinfections.
A recombineering based approach for

Functional analysis of mammalian genes in vivo is primarily achieved through analysing knockout mice. Now that the sequencing of several mammalian genomes has been completed, understanding functions of all the genes represents the next major challenge in the post-genome era. Generation of knockout mutant mice has currently been achieved by many research groups but only by making individual knockouts, one by one. New technological advances and the refinements of existing technologies are critical for genome-wide targeted mutagenesis in the mouse. We describe here new recombineering reagents and protocols that enable recombineering to be carried out in a 96-well format. Consequently, we are able to construct 96 conditional knockout targeting vectors simultaneously. Our new recombineering system makes it a reality to generate large numbers of precisely engineered DNA constructs for functional genomics studies.
La cartographie et la télédétection comme système de suivi- évaluation des TGRNR. Exemple de site d'application : la commune de Didy, région d'Alaotra-Mangoro, Madagascar

La teledetection est un outil permettant de produire, a l'aide d'images satellitaires, une carte d'occupation du sol. Ce qui est plus interessant est de pouvoir le faire a differentes dates. Elle permet ainsi d'effectuer, par exemple, un systeme de suivi-evaluation des Transferts de Gestion des Ressources Naturelles Renouvelables (TGRNR). Un site d'application a ete considere dans le cadre d'une etude menee par le Laboratoire de Geophysique de l'Environnement et Teledetection de l'Institut et Observatoire de Geophysique d'Antananarivo (IOGA) afin d'evaluer l'efficacite du programme de transfert de la gestion forestiere aux communautes de base locales. C'est le cas de la commune de Didy, dans la region d'Alaotra-Mangoro, situee dans la partie Centre-Nord de Madagascar. Les images multispectrales Landsat acquises a differentes dates ont ete tout d'abord soumises a des corrections atmospheriques puis classifiees chacune a l'aide des algorithmes de classification adaptes au type d'image disponible. L'analyse et la comparaison des cartes d'occupation du sol issues des images classifiees (post-classification) permettent d'apporter des informations pertinentes de suivi-evaluation des TGRNR. L'analyse et la detection des changements pourraient etre plus poussees en interpretant les matrices de transition et les cartes de changement.
P R O O

OnFebruary6,2023,twolargeearthquakesoccurredneartheTurkishtownofKahramanmaraş. Themomentmagnitude(Mw)7.8mainshockruptureda310km-longsegmentoftheleft-lateralEastAnatolian Fault,propagatingthroughmultiplereleasingstep-overs.TheMw7. 6aftershockinvolvednearbyleft-lateral strike-slipfaultsoftheEastAnatolianFaultZone,causinga150km-longrupture.Weuseremote-sensingob-servationstoconstrainthespatialdistributionofcoseismicslipforthesetwoeventsandtheFebruary20
Monitoring corn and soybean crop development by remote sensing techniques

A system for spectrally monitoring the stages of crop development for corn and soybeans based upon red and photographic infrared spectral radiances is proposed. The red and photographic infrared spectral radiance, highly correlated with the green leaf area index or green leaf biomass, enable nondestructive monitoring of the crop canopy throughout the growing season. Five distinct periods are apparent which are related to crop development for corn and soybeans.
Revista Mexicana de I ngeniería Q uímica CELLULASES AND XYLANASES PRODUCTION BY Penicillium citrinum CGETCR USING COFFEE PULP IN SOLID STATE FERMENTATION PRODUCCI

This work reports, for the ﬁrst time, the use of co ﬀ ee pulp residue to the expression of cellulolytic and xylanolytic enzymes by the native fungus Penicillium citrinum CGETCR by solid-state fermentation (SSF). Co ﬀ ee is one of the most important drinks in the world producing several residues such as co ﬀ ee pulp, which is considered a contaminant if not properly disposed. This residue causes damage to the fauna from rivers due to its composition including tannins, pH 3.5, (1-4%) ca ﬀ eine, polyphenolic compound, ochratoxin A, the presence of the latter three have toxic or nephrotoxic e ﬀ ects on higher animals. For these reasons, a study on the use of these residues to obtain high-added value products as enzymes of biotechnological interest, was performed. The enzyme production was optimized using the response surface methodology in a composite central design to study pH, moisture and fermentation time using endoglucanase activity as the response variable. The enzymatic activities found were β -glucosidases, endoglucanases, exoglucanases and xylanases which were able to function under acidic (4.0-5.5) and basic (7.5-8.0) conditions. Additionally, protein extract was used on agroindustrial residues as substrate to evaluate reducing sugar production. exoglucanasas y xilanasas las cuales fueron capaces de funcionar bajo condiciones de acidez (4.0-5.5) y basicidad (7.5-8.0). Adicionalmente, el extracto enzim´atico se us´o sobre residuos agroindustriales para evaluar la producci´on de az´ucares simples. Palabras clave : superﬁcie de respuesta, hidr ´ olisis enzim ´ atica, compuestos fen ´ olicos, fermentaci ´ on en estado s ´ olido, sacariﬁcaci ´ on de residuos agroindustriales.
Loneliness among Older People: Results from the Swedish Study on Aging and Care -Blekinge

Objectives: To investigate the prevalence and predictors of loneliness in older people (aged 78+) over a six- year period. Method: The sample (n=828) was drawn from the Swedish National Study on Aging and Care and the respondents were followed up at three and six years. Data were collected by means of structural interviews with supplementary questionnaires. Results: Half of the respondents reported that they felt lonely sometimes or more often. Women, widows/-ers living alone were more prone to report loneliness. Both independent associated factors and predictors were identified showing that loneliness is associated with and predicted by both physical and psychosocial outcomes. Discussion: Loneliness is common among older people and seems to be a steady state affected mainly by psychological and psychosocial factors such as personality, satisfaction with life, risk of depression, lack of friends and loss of spouse. Psychosocial interventions targeting emotional loneliness and social isolation are suggested.
Low Resource Domain Subjective Context Feature Extraction via Thematic Meta-learning

— The volume of the data is directly proportional to the model's accuracy in data analytics for any particular domain. Once a developing field or discipline becomes apparent, the scarcity of the data volume becomes a challenging proponent for the correctness of a model and prediction. In the proposed state-of-the-art, a transitive empirical method has been used within the same contextual domain to extract features from a low-resource part via a heterogeneous field with factual data. Even though an example of text processing has been used for brevity, it is not limited. The success rate of the proposed model is 78.37%, considering model performance. But when considering human subject matter experts, the accuracy is 81.2%.
SOLVABILITY OF CONTROL PROBLEM FOR A NONLOCAL NEUTRAL STOCHASTIC FRACTIONAL INTEGRO-DIFFERENTIAL INCLUSION WITH IMPULSES

This paper considers a class of neutral impulsive stochastic integro-diﬀerential inclusion with nonlocal conditions involving the Caputo fractional derivative of order 1 < α < 2 in a Hilbert space. A new set of suﬃcient conditions for the approximate controllability of semilinear fractional stochastic systems is derived utilizing solution operator, stochastic analysis, fractional calculus and ﬁxed point theorem for a multivalued operator under the assumption that the corresponding linear system is approximately controllable. An example is provided to illustrate the derived theory at the end of the paper.
on Usable Privacy

Operational Technology (OT) refers to systems that control and monitor industrial processes. Organisations that use OT can be found in many sectors, including water and energy, and often operate a n critical infrastructure. These organisations have been under a digitalisation process, which along with increasing regulatory pressures have necessitated changes in their cybersecurity practices. The lack of internal resources has often compelled these organisations to turn to external consultancy to enhance their security. Given the differences between OT and Information Technology (IT) security practices and that OT cybersecurity is still in its infancy, developing a security culture in OT environments remains a challenge, with little research investigating this topic. We have conducted 33 interviews with professionals with a security related role working in various OT sectors in the UK, on the subject of security culture development. Our analysis indicates three key organisational barriers to the development of a security culture: governance structures, lack of communication between functions, and the lack of OT cybersecurity expertise. Subsequently, the role of consultants and security solution vendors in overcoming these barriers through consultancy is demonstrated. We therefore argue that these stakeholders play a crucial part in the development of security culture in OT and conclude with recommendations for these organisations.
First results of tomographic SAR inversion on "reduced" flight-track simulated polarimetric data

In this paper, the tomographic inversion of Synthetic Aperture Radar polarimetric data and, in particular, the problem of reconstructing forest parameters is addressed. The forest is described by two layers, the first one accounting for the forest canopy and the second one for the ground, and the problem of determining its parameters is cast as an optimization one. Preliminary results on simulated data are shown.
Phone call while riding among delivery workers: The Application of the Theory of Planned Behavior

With the rapid growth of online food delivery services, the population of delivery workers has reached 13 million in China. Most of them use electric bicycles (e-bikes) as their primary transportation tool. On the other hand, mobile phone call (MPC), as the primary and most effective communication method for delivery workers, induces distracted riding and threatens traffic safety. Although MPC has been extensively investigated in driving-related research, MPC among delivery workers has not yet been investigated. In this study, a questionnaire based on the theory of planned behavior has been designed to investigate social-psychological factors leading to MPC among delivery workers. 150 delivery workers participated in this study. The structural equation model method was adopted to analyze the data. The results show that injunctive norm is positively associated with MPC behaviors; but descriptive norm is negatively associated with MPC behaviors, potentially because of the selective perception phenomenon.
Development of an Artificial Intelligence Model for Analyzing the Relationship between Imaging Features and Glucocorticoid Sensitivity in Idiopathic Interstitial Pneumonia

High-resolution CT (HRCT) imaging features of idiopathic interstitial pneumonia (IIP) patients are related to glucocorticoid sensitivity. This study aimed to develop an artificial intelligence model to assess glucocorticoid efficacy according to the HRCT imaging features of IIP. The medical records and chest HRCT images of 150 patients with IIP were analyzed retrospectively. The U-net framework was used to create a model for recognizing different imaging features, including ground glass opacities, reticulations, honeycombing, and consolidations. Then, the area ratio of those imaging features was calculated automatically. Forty-five patients were treated with glucocorticoids, and according to the drug efficacy, they were divided into a glucocorticoid-sensitive group and a glucocorticoid-insensitive group. Models assessing the correlation between imaging features and glucocorticoid sensitivity were established using the k-nearest neighbor (KNN) algorithm. The total accuracy (ACC) and mean intersection over union (mIoU) of the U-net model were 0.9755 and 0.4296, respectively. Out of the 45 patients treated with glucocorticoids, 34 and 11 were placed in the glucocorticoid-sensitive and glucocorticoid-insensitive groups, respectively. The KNN-based model had an accuracy of 0.82. An artificial intelligence model was successfully developed for recognizing different imaging features of IIP and a preliminary model for assessing the correlation between imaging features and glucocorticoid sensitivity in IIP patients was established.
High-Level Functional Properties of Bit-Level Programs: Formal Specifications and Automated Proofs

In a computer program, basic functionalities may be implemented using bit-wise operations. This can be motivated by the need to be close to the underlying architecture, or the need of efficiency, both in term of time and memory space. If one wants to formally specify the expected behavior of such a low-level program, it is desirable that the specification should be at a more abstract level. Formally proving that a low-level code conforms to a higher-level specification is challenging, because of the gap between the different levels of abstraction. Our approach to address this challenge is to design a rich formal theory of fixed-sized bit-vectors, which on the one hand allows a user to write abstract specifications close to the human---or mathematical---level of thinking, while on the other hand permits a close connection to decision procedures and tools for bit-vectors, as they exist in the context of the Satisfiability Modulo Theory framework. This approach is implemented in the Why3 environment for deductive program verification, and also in its front-end environment SPARK for the development of safety-critical Ada programs. We report on several case studies used to validate our approach experimentally.
Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi-Information Fusion

Due to the complexity of the structure and process of large-scale petrochemical equipment, different fault characteristics are mixed and present multiple couplings and ambiguities, leading to the difficulty in identifying composite faults in rotating machinery. This paper proposes a composite faults diagnosis method for rotating machinery of the large unit based on evidence theory and multi-information fusion. The evidence theory and multi-information fusion method mainly deal with multisource information and conflict information, synthesize multiple uncertain information, and obtain synthetic information from multiple data sources. To detect faults in rotating machinery, the dimensionless index ranges of composite faults are first used to form a feature set as the reference. Then, a two-sample distribution test is applied to compare the known fault samples with the tested fault samples, and the maximum statistical distance is used. Finally, the multiple maximum statistical distances are fused by evidence theory and identifying fault types based on the fusion result. The proposed method was applied to the large petrochemical unit simulation experiment system, the results of which showed that our proposed method could accurately identify composite faults and provide maintenance guidance for composite fault diagnosis.
TELKOMNIKA Telecommunication Computing Electronics and Control

Md. Tofael Ahmed, Maqsudur Rahman, Shafayet Nur, Abu Zafor Muhammad Touhidul Islam, Dipankar Das Department of Information and Communication Technology, Comilla University, Comilla, Bangladesh Department of Computer Science & Engineering, Port City International University, Chattogram, Bangladesh Department of Electrical and Electronics Engineering, University of Rajshahi, Rajshahi, Bangladesh Department of Information and Communication Engineering, University of Rajshahi, Rajshahi, Bangladesh
HIS-EBG Unit Cells for Pattern and Frequency Reconfigurable Dual Band Array Antenna

The incorporation of Electromagnetic Band Gap (EBG) unit cells, a type of metamaterials, with a dual band array antenna is proposed. By configuring the band gap of EBG cells accordingly, the pattern of the array antenna is successfully reconfigured at lower band of 2.4 GHz while maintaining the pattern at higher band of 5.8 GHz. Three pattern directions have been achieved: initial radiation pattern, 349-degree shift and 11-degree shift of the H-field. The array antenna is also frequency reconfigurable by suppressing the radiation pattern of the antenna in four different EBG cells configurations. In pattern shifting mode, the realized gain of the antenna is satisfactorily maintained and is comparable with the standalone of dual band array antenna with the range of gains from 5.08 dBi to 6.14 dBi and 7.83 dBi at 5.8 GHz.
On the Scalability of Testing the Crash Consistency of PM Systems

Persistent memory (PM) technologies [4, 8] can provide durability with latencies comparable to DRAM. Such characteristics bridge the gap between traditional memory and storage, and have inspired many PM-based optimizations in both user-level applications [5, 19] and operating system (OS) kernels [17, 21]. While Intel is winding down its Optane PM business, it is expected that vendor-neutral CXL-based PMs will continuously evolve and trigger new system optimizations [1, 6, 3]. Unfortunately, building correct PM-based systems is challenging: writes to PM need to be carefully ordered and persisted to avoid inconsistent or unrecoverable states upon crashes, which is non-trivial given the subtle behavior of modern cache and memory subsystem [14, 15, 7, 16, 10, 20]. To address the challenge, many testing tools have been proposed [12, 11, 13]. Nevertheless, most of them focus on user-level PM applications, leaving the OS kernel and the potential dependencies unexplored. In fact, one recent study shows that there are various PM-related issues at the kernel level [18], which calls for tool support for full systems. Notably, Kalbfleisch et al. proposed the VINTER [11] framework recently which can support full-system testing and have been applied to test multiple kernel-level PM file systems (e.g., NOVA [17], PMFS [2]). While promising, our experiments on VINTER exposed a scalability challenge in (at least) three aspects as follows: First, writes to the target PM file system can easily overwhelm VINTER. As shown in Table 1, we apply three small workloads on NOVA which generates three different sizes of writes (i.e., 256, 256*4, and 256*20 bytes). It took VINTER about 1 hour 45 minutes (‘1h 45m’) to complete the test under the 256*4 workload; and with 256*20 bytes of write, VINTER cannot finish within 12 hours. Further analysis shows that among the three core phases of VINTER (i.e., record, replay, test), both the replay and test phases are the bottlenecks. Second, VINTER cannot scale to typical PM appliWrites (Bytes) Total Runtime Runtime for Each Phase Record Replay Test 256 6m 47s 8s 5m 1m 39s 256*4 1h 45m 16s 55m 42s 48m 30s 256*20 21s >12h -
IoT based Smart Home Cyber-Attack Detection and Defense

: As the adoption of Internet of Things (IoT) devices in smart homes continues to increase, so does the risk of cyber-attacks targeting these interconnected devices. This paper proposes an IoT-based smart home cyber-attack detection and defense system that aims to enhance the security and privacy of smart home environments. The proposed system leverages machine learning algorithms and network traffic analysis techniques to detect and classify various types of cyber-attacks targeting IoT devices within the smart home network. By monitoring the communication patterns and data flows between devices, abnormal behaviors indicative of cyber-attacks can be identified in the real-time. Furthermore, the system incorporates a defense mechanism that can automatically respond to detected attacks, such as isolating compromised devices from the network, blocking malicious traffic, or alerting homeowners about potential threats. Additionally, the system allows homeowners to configure security policies and access control rules to further customize the defense mechanisms based on their preferences. To validate the effectiveness of the proposed system, a prototype implementation is developed and evaluated using a realistic smart home environment. The results demonstrate the system's ability to accurately detect and mitigate various cyber-attacks, including malware infections, unauthorized access attempts, and data exfiltration. Overall, the IoT-based smart home cyber-attack detection and defense system provides an effective solution for safeguarding smart home environments against cyber threats. Combining advanced machine learning techniques with proactive defense mechanisms; it enables homeowners to maintain a secure and protected IoT ecosystem within their homes.