Miracle-dz/UniFAR-FTUs huggingface dataset:
Materials processing technology for the integration of effective Ge p-i-n photodetectors on Si for Si microphotonics

We present a technology for the integration of high performance near-infrared Ge P-I-N photodetectors on Si for Si microphotonics. High quality Ge epilayers were grown on Si by a two-step ultrahigh-vacuum / chemical-vapor-deposition (UHV/CVD) process. Two-step UHV/CVD allows the epitaxial growth of Ge on Si without islanding. Threading-dislocations in Ge epilayers were reduced by cyclic thermal annealing. The reduction of threading-dislocations can be understood in terms of thermal stress induced dislocation glide and reactions. We found that sessile threading-dislocations are not permanent and can be removed.
STRUCRUAL OPTIMIZATION FOR THE DESIGN OF COMPLIANT THERMAL ACTUATORS BASED ON THE LEVEL SET METHOD

Compliant mechanisms are a new type of mechanism, designed to be flexible in order to achieve a specified motion as a mechanism. Such mechanisms can function as compliant thermal actuators in Micro-Electro Mechanical Systems (MEMS) by intentionally designing configurations that exploit thermal expansion effects in elastic material when appropriate portions of the mechanism structure are heated. Compliant thermal actuators of this type have been designed using a trial and error approach, but creating high performance actuators this way is difficult. Topology optimization [1] is a highly flexible structural optimization method, allowing changes not only in shape but also in the topology of target structures, and it can yield high performance structural configurations. Sigmund [2] successfully used topology optimization in the design of compliant thermal actuators, however numerical problems such as grayscales and hinges [3], [4] are often encountered. The level set based structural optimization method [5], [6] is a new structural optimization method where target structural configurations are implicitly represented using the level set function, and optimal configurations are obtained by updating the level set function governed by the Hamilton-Jacobi Equation, based on shape
SCADA Protocol Obfuscation: A Proactive Defense Line in SCADA Systems

: This paper describes a defensive approach referred to as SCADA protocol obfuscation. Such an approach counters network attacks which remotely exploit vulnerabilities in target SCADA systems through malicious messages structured in compliance with an actually used SCADA protocol. SCADA protocol obfuscation is built in the form of a proactive structural intervention which we defined upon information provided by a new conceptual structure called attack requirements trees. An attack requirements tree is a structured means of providing conditions which must hold for a given attack to be feasible. The root node of this tree is the attack itself, while each other node is an attack requirement. We built the attack requirements tree for a SCADA protocol-based attack and identified a node whose denial could make such an attack unfeasible. This node represents the requirement that attack messages should be built according to the SCADA protocol in use, therefore we decided to introduce diversity into a SCADA protocol in order to deny to the attacker the knowledge required for building correct attack messages. While a strong cryptographic algorithm would accomplish this task, we had to investigate another solution as common SCADA field devices such as PLC's or RTU's have limited computational power. Consequently they have considerable difficulties running strong cryptographic algorithms. In this paper we propose SCADA protocol obfuscation as a candidate solution and describe it as applied to the Modbus TCP/IP protocol.
Non-Woven Infection Prevention Fabrics Coated with Biobased Cranberry Extracts Inactivate Enveloped Viruses Such as SARS-CoV-2 and Multidrug-Resistant Bacteria

The Coronavirus Disease (COVID-19) pandemic is demanding the rapid action of the authorities and scientific community in order to find new antimicrobial solutions that could inactivate the pathogen SARS-CoV-2 that causes this disease. Gram-positive bacteria contribute to severe pneumonia associated with COVID-19, and their resistance to antibiotics is exponentially increasing. In this regard, non-woven fabrics are currently used for the fabrication of infection prevention clothing such as face masks, caps, scrubs, shirts, trousers, disposable gowns, overalls, hoods, aprons and shoe covers as protective tools against viral and bacterial infections. However, these non-woven fabrics are made of materials that do not exhibit intrinsic antimicrobial activity. Thus, we have here developed non-woven fabrics with antimicrobial coatings of cranberry extracts capable of inactivating enveloped viruses such as SARS-CoV-2 and the bacteriophage phi 6 (about 99% of viral inactivation in 1 min of viral contact), and two multidrug-resistant bacteria: the methicillin-resistant Staphylococcus aureus and the methicillin-resistant Staphylococcus epidermidis. The morphology, thermal and mechanical properties of the produced filters were characterized by optical and electron microscopy, differential scanning calorimetry, thermogravimetry and dynamic mechanical thermal analysis. The non-toxicity of these advanced technologies was ensured using a Caenorhabditis elegans in vivo model. These results open up a new prevention path using natural and biodegradable compounds for the fabrication of infection prevention clothing in the current COVID-19 pandemic and microbial resistant era.
A complete solution to the harmonic elimination problem

The problem of eliminating harmonics in a switching converter is considered. That is, given a desired fundamental output voltage, the problem is to find the switching times (angles) that produce the fundamental while not generating specifically chosen harmonics. In contrast to the well known work of Patel and Hoft (1973, 1974) and others, here all possible solutions to the problem are found. This is done by first converting the transcendental equations that specify the harmonic elimination problem into an equivalent set of polynomial equations. Then, using the mathematical theory of resultants, all solutions to this equivalent problem can be found. In particular, it is shown that there are new solutions that have not been previously reported in the literature. The complete solutions for both unipolar and bipolar switching patterns to eliminate the 5th and 7th harmonics are given. Finally, the unipolar case is again considered where the 5th 7th, 11th, and 13th harmonics are eliminated along with corroborative experimental results.
Locating Performance Regression Root Causes in the Field Operations of Web-Based Systems: An Experience Report

Software developers usually rely on in-house performance testing to detect performance regressions and locate their root causes. Such performance testing is typically resource and time-consuming, making it impractical to conduct when the software is delivered in fast-paced release cycles. On the other hand, the operational data generated in the field environment provides rich information about the performance of a software system and its runtime activities. Therefore, this work explores the idea of leveraging the readily-available field operational data to locate the root causes of performance regression instead of running expensive performance tests. However, due to the ever-changing workloads from the end users and the noise from the field, directly analyzing performance metrics such as response time of the system may not be able to help locate the root causes of performance regressions. In this paper, we report our experience of designing and adopting an approach that automatically locates the root causes of performance regressions while the software systems are deployed and running in the field. First, our approach uses black-box performance models to capture the relationship between the performance of a system and its runtime activities. Then, our approach analyzes the performance models and uses statistical techniques to suggest the problematic system runtime activities (i.e., the root causes) that are related to a performance regression. Our evaluation considered three open-source projects and one industrial product. In the three open-source systems, we find that our approach can successfully locate the root causes of all arbitrarily injected synthetic performance regressions. Our approach has successfully detected and located the root causes of three performance regressions in an industry system and it has been adopted by our industrial partner and used in practice on a daily basis over a 12-month period. In addition, we share the challenges that we encountered during the design and adoption of our approach, how we address those challenges, and the lessons that we learned during the process. We believe that our novel approach together with our documented experience can benefit practitioners and researchers who wish to leverage the field-operation data of a software system to conduct performance assurance activities.
Neural Incremental Speech Recognition Toward Real-Time Machine Speech Translation

SUMMARY Real-time machine speech translation systems mimic human interpreters and translate incoming speech from a source language to the target language in real-time. Such systems can be achieved by performing low-latency processing in ASR (automatic speech recognition) module before passing the output to MT (machine translation) and TTS (text-to-speech synthesis) modules. Although several studies recently proposed sequence mechanisms for neural incremental ASR (ISR), these frameworks have a more complicated training mechanism than the standard attention-based ASR because they have to decide the incremental step and learn the alignment between speech and text. In this paper, we propose attention-transfer ISR (AT-ISR) that learns the knowledge from attention-based non-incrementalASR fora lowdelay end-to-endspeechrecognition. ISRcomes with a trade-oﬀ between delay and performance, so we investigate how to reduce AT-ISR delay without a signiﬁcant performance drop. Our ex-periment shows that AT-ISR achieves a comparable performance to the non-incremental ASR when the incremental recognition begins after the speech utterance reaches 25% of the complete utterance length. Additional experiments to investigate the eﬀect of ISR on translation tasks are also performed. The focus is to ﬁnd the optimum granularity of the output unit. The results reveal that our end-to-end subword-level ISR resulted in the best translation quality with the lowest WER and the lowest uncovered-word rate.
What Is on the Menu?—A Quantitative Analysis on Label Format among (Potential) Restaurant Guests and Restaurant Owners

About 20% of energy intake in the Netherlands is consumed out-of-home. Eating out-of-home is associated with higher energy intake and poorer nutrition. Menu labeling can be considered a promising instrument to improve dietary choices in the out-of-home sector. Effectiveness depends on the presentation format of the label and its attractiveness and usability to restaurant guests and restaurant owners. This exploratory study investigated which menu labeling format would be mostly appreciated by (a) (potential) restaurant guests (n386) and (b) the uninvestigated group of restaurant owners (n41) if menu labeling would be implemented in Dutch full-service restaurants. A cross-sectional survey design was used to investigate three distinct menu labeling formats: a simple health logo; (star) ranking and calorie information. Questionnaires were used as study tool. Ranking has been shown to be the most appreciated menu labeling format by both (potential) restaurant guests and owners. Statistical analysis showed that label preference of potential restaurant guests was significantly associated with age, possibly associated with level of education, and not associated with health consciousness. In summary, we found that ranking is the most appreciated menu label format according to both (potential) restaurant guests and restaurant owners, suggesting it to be a promising way to improve healthy eating out-of-home.
Electrospun Antibacterial Nanomaterials for Wound Dressings Applications

Chronic wounds are caused by bacterial infections and create major healthcare discomforts; to overcome this issue, wound dressings with antibacterial properties are to be utilized. The requirements of antibacterial wound dressings cannot be fulfilled by traditional wound dressing materials. Hence, to improve and accelerate the process of wound healing, an antibacterial wound dressing is to be designed. Electrospun nanofibers offer a promising solution to the management of wound healing, and numerous options are available to load antibacterial compounds onto the nanofiber webs. This review gives us an overview of some recent advances of electrospun antibacterial nanomaterials used in wound dressings. First, we provide a brief overview of the electrospinning process of nanofibers in wound healing and later discuss electrospun fibers that have incorporated various antimicrobial agents to be used in wound dressings. In addition, we highlight the latest research and patents related to electrospun nanofibers in wound dressing. This review also aims to concentrate on the importance of nanofibers for wound dressing applications and discuss functionalized antibacterial nanofibers in wound dressing.
Fuzzy logic controller in a packaging plant

This paper deals with the analysis of a controller used to synchronize two parallel belt conveyors in a packaging plant. A first conveyor carries the products, while the second delivers the packages. The insertion is obtained by a proper mechanical action. The control system is based on a ‘hybrid’ fuzzy logic controller, whose parameters are optimized by using an advanced ‘operational’ genetic algorithm. ‘Hybrid’ means that a conventional fuzzy logic controller is integrated with a set of special rules needed to solve particular situations characterizing the system. An important constraint is given, since the physical structure of the existing control system is to be kept unchanged. It is shown that the controller efficiently governs the belt conveyors when: (a) the distances between goods and the relative packages become higher than a certain value; (b) the performance of the electrical engine deteriorates during working time; and also (c) interference phenomena occur between consecutive good‐package couples. Copyright ©2003 John Wiley & Sons, Ltd.
Effect of a restaurant hygienic grade certificate program on consumer choices

BACKGROUND/OBJECTIVES The recent coronavirus disease 2019 pandemic has brought to light issues regarding personal and environmental cleanliness. Individuals may have concerns about cleanliness at food service establishments when they consume food prepared at a restaurant. In Korea, a new restaurant hygienic certificate system was implemented in 2017. The effect of this new system has not been evaluated. SUBJECTS/METHODS This study investigated consumers' perceptions of these new certificates using the protection motivation theory (PMT). An online survey was conducted to collect data and then exploratory factor analysis, analysis of variance, and multiple regression tests were run. RESULTS The results of this study indicate that 3 different certificates had significant differences in threat (P < 0.001) and benefit (P < 0.001) perception. However, experience with a foodborne illness from a restaurant did not effect on the PMT variables. In addition, the 3-tier certificate did not motivate consumers to protect themselves against foodborne illnesses, while previous experiences of foodborne illness (P < 0.05), coping (P < 0.001), and benefits (P < 0.01) affected this protection motivation. CONCLUSIONS This study suggests that consumers were not influenced by different certificate levels regarding their motivation to protect themselves from foodborne illnesses. Therefore, an improved plan should be initiated to clarify the meaning of these certificates. The results of this study can help the application and development of a new system for future adaptations.
Physiotherapy Rehabilitation in Post Operative Tibia- Fibula Fracture with External Fixators

Introduction: A tibia - fibula fracture occurs when a fall or trauma to the lower extremities puts more tension on the bones than they can tolerate. Diaphyseal tibial fractures are the most common long bone fracture. Lower extremity Tibia and fibula fractures are examples of fractures. Tibial shaft fractures are most typically associated with a history of severe trauma. The tibia is the most commonly fractured bone in the lower extremity. The bone's shaft is in the middle Fibula fractures are usually, but not always, accompanied by tibial shaft fractures. Case Presentation: At the previous 15 days, a 49-year-old male patient accounted in a hospital with a road traffic accident. Discussion: The physiotherapy was given to this patient for muscle energy technique resulting in a high degree of range of motion in the lower extremity, reduce pain, and improves flexibility and strength. Conclusion: Physiotherapy has a significant effect on pain, strength, and range of motion. The result of this case report specifies that it may be effective for pain relief, improvement in strength, and functional ability.
Augmented Reality for Managerial Tasks: Review and Implications for Engineering and Operations Management

Abstract Augmented Reality (AR) has advanced rapidly, and a breadth of applications can be found in industry. While research suggests that these tools are effective in improving operational or worker performance, applications related to engineering and operations management functions, such as monitoring work practices and process control, are less common and reportedly experience additional challenges due to the nature of these tasks. This article reviews research focused on AR applications for management-related tasks exploring progress in this area, identifying key challenges, and defining opportunities for future research. Augmented Reality technology has the potential to support engineering and operations management by creating Immersive Performance Environments; however, there are many challenges to the successful adoption of this technology that must be overcome to bring the potentially powerful benefits of this technology to practice.
Scalable and Efficient Tasking for Dynamic Sensor Networks

Sensor networks including opportunistic networks of sensor-equipped smartphones as well as networks of embedded sensors can enable a wide range of applications including environmental monitoring, smart grids, intelligent transportation, and healthcare. In most real-world applications, to meet end-user requirements, the network operator needs to define and update the sensors’ tasks dynamically, such as updating the parameters for sensor data collection or updating the sensors’ code. Tasking sensor networks is necessary to reduce the effort in programming sensor networks. However, it is challenging due to dynamics and scale in terms of number of nodes, number of tasks, and sensing regions of the networks. In addition, tasking sensor networks must also be efficient in terms of bandwidth, latency, energy consumption, and memory usage. This dissertation identifies and addresses the problems of scalability and efficiency in tasking sensor networks. The first challenge in tasking sensor networks is to define a mechanism that represents multiple tasks and sensor groups efficiently taking into account the heterogeneity and mobility of sensors deployed over a large geographical region. Another challenge in tasking sensor networks in general, and embedded sensor networks in particular, is to design protocols that can not only efficiently disseminate tasks but also maintain a consistent view of the task to be performed among inherently unreliable and resource-limited sensors.
Estimating cumulative incidence rate on interval censored data in an illness-death model.

ESTIMATING CUMULATIVE INCIDENCE RATE ON INTERVAL CENSORED DATA IN AN ILLNESS-DEATH MODEL Chen Qian March 31, 2021 Phase IV clinical trials are designed to monitor long-term side effects caused over time by the medical treatment. For instance, in advanced primary cancer treatment, childhood cancer survivors are often at risk of developing undesired events, such as cardiotoxicity, during their adulthood. Such problems could be due to their cancer or the treatment they received for their cancer such as radiation or intensive chemotherapy. Cardiotoxicity can be diagnosed with electrophysiology with measurements of fraction shortening, afterload, etc. Often the primary focus of a study could be on estimating the cumulative incidence (CI) of a particular outcome of interest such as cardiotoxicity. However, it is not possible to evaluate patients on a continuous basis and often this information is collected through cross-sectional surveys by following patients longitudinally. This leads to interval censored data since the exact time of the onset of toxicity is not known. This dissertation consists of three projects related to the estimation of cumulative incidence rates on interval censored data in an illness-death model. In the first project, missing observation problem in the current status data is discussed. An imputation method is proposed to handle such issue. The second project introduces v a new method for estimating transition intensity probabilities using semi-parametric with EM (expectation-maximization) approach in a special case two-state model. A logit relationship for the treatment intensities in the two groups is proposed. In the third project, the cumulative incidence rates are evaluated using the maximum likelihood estimation approach in a complete three-state illness-death model in which death is incorporated as competing risk.
Examining Energy and Environment Issues in Non-ferrous Metallurgy in the Light of Industrial Metabolism

This paper examines the dissipative nature of non-ferrous metals industry against the idea of industrial metabolism that encompasses, for the sake of sustainable development, values, ideas such as Materials Flow Analysis, Environmental Impact Analysis, Estimation of Environmental Footprint etc. Although the industry is now far away from the dream of „green‟ technologies, it is discussed that a beginning has to be made now by analyzing present day processes critically from the iewpoint of materials and energy flow and this should be a mandatory part of Corporate Social Responsibility.
Recent developments in people screening using terahertz technology: seeing the world through terahertz eyes

Terahertz radiation, which lies between microwave and infrared, has been shown to have the potential to use very low levels of this non-ionising radiation to detect and identify objects, such as weapons and explosives, hidden under clothing. This paper describes recent work on the development of prototype systems using terahertz to provide new capabilities in people screening. In particular, it explores how hyperspectral terahertz imaging and the use of both specularly reflected and scattered terahertz radiation can enhance the detection of threat objects.