Miracle-dz/UniFAR-FTUs huggingface dataset:
Directional Multiport Ambient RF Energy-Harvesting System for the Internet of Things

Ambient radio-frequency (RF) energy harvesting can extract energy from RF signals in the ambient environment and has potential for applications in the Internet of Things. However, the power density of the ambient RF energy is low and therefore methods to maximize the average <italic>output direct current (dc) power</italic> are required. In this work we show that average <italic>output dc power</italic> in ambient RF energy harvesting is nonlinearly dependent on antenna directivity and linearly dependent on antenna port number. To maximize average <italic>output dc power</italic> it is therefore necessary to utilize directional multiport rectennas. To demonstrate the enhancements possible, the design for a directional 4-port pixel patch rectenna system to harvest ambient RF energy from the GSM-1800 frequency band is provided. The design has an average antenna size for each port of <inline-formula> <tex-math notation="LaTeX">$0.3\lambda \times 0.3\lambda $ </tex-math></inline-formula>, and realized gains of 5.5 dBi. Measurement results show that the proposed rectenna can increase average output dc power by up to 6.2 and 4.5 dB compared to omnidirectional and directional single-port rectenna designs of similar size, respectively. Measurement in a real ambient environment is also conducted, showing that the proposed rectenna can achieve an output dc power of <inline-formula> <tex-math notation="LaTeX">$11.2~\mu \mathrm {W}$ </tex-math></inline-formula> which is five times higher than the two reference rectennas.
Assessing the Ocean Surface Current Impact on Scatterometer (C- and Ku-Bands) and Altimeter (Ka-Band) Derived Winds in the Bay of Bengal

A 2-year data set from Indian Space Research Organizations (ISRO’s) scatterometer mission (SCATSAT-1) has been used to investigate the impact of ocean surface current on the derived winds in the Bay of Bengal. For this purpose, wind speed residuals obtained between Ku-band SCATSAT-1 and buoy were regressed with buoy measured ocean surface currents. Results show a good agreement between wind residuals and surface current under stable air–sea interaction conditions for the region signifying a considerable impact of currents on the radar backscatter. A further analysis was carried out to ascertain the quantitative impact of currents on the C-band ASCAT derived winds and Ka-band SARAL/AltiKa derived wind speed. This study showed that impact of surface current is much higher on Ka-band altimeter-derived wind speed when compared to C-band and Ku-band scatterometer-derived wind speed. The correlation coefficient so obtained is found to be −0.34 in the case of Ka-band and nearly −0.26 for C-band and Ku-band scatterometer-derived winds. Higher correlation magnitude in the case of Ka-band suggests that surface current impact is slightly more for Ka-band when compared to C- and Ku-bands. These statistics suggest that wind speed retrieved from radar systems are indeed current relative and not fixed earth relative. Basin scale analysis for the Bay of Bengal indicates that surface current feedback in the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) flux formulation results in 5%–15% reduction in the mechanical energy input to the ocean.
The complete mitochondrial genome sequence of Acentrogobius caninus (Gobiiformes: Gobiidae)

Abstract At present, only several species of genus Acentrogobius were described and information of mitochondrial DNA were also just focused on two species. Here, the complete mitochondrial genome of Acentrogobius caninus was completely sequenced by high throughput sequencing method. The complete mitochondrial genome was 16,614 bp in length, consisted of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, 1 large non-coding control region, and 1 light-strand replication origin. Overall base composition values for the mitochondrial genome were 28.24, 29.20, 16.77, and 25.79% for A, C, G, and T, respectively. The gene arrangement is identical to those in typical fishes. Phylogenetic tree based on 13 protein-coding genes shows that three species of genus Acentrogobiu did not cluster into one clade.
Agrobacterium rhizogenes-transformed roots of Astragalus membranaceus (Fisch. Ex Link) Bunge as a source of valuable secondary metabolites

In this study the results of agrobacterial transformation of Astragalus membranaceus (Fisch. Ex Link) Bunge, a medicinal plant from Mongolia and China with a wide spectrum of pharmacological action were presented. As explants for transformation, in vitro derived microshoots as well as hypocotyls, cotyledons and primary shoots isolated from seedlings were used. The most effective from two tested Agrobacterium rhizogenes strains (A4-RT, 15834 SWISS) was 15834 SWISS, causing the transformation of various types of explants, including primary shoots as a more responsive type. The optimal co-cultivation time of explants with bacterial suspension (48 hours) and the highest transformation rate of primary shoots (36.4%) were established. PCR analysis confirmed the transgenic nature of the roots transformed with strain 15834 SWISS and the absence of bacterial contamination.
Pinpointing Software Inefficiencies With Profiling

Complex code bases with several layers of abstractions have abundant ine ciencies that a↵ect the performance. These ine ciencies arise due to various causes such as developers’ inattention to performance, inappropriate choice of algorithms and ine cient code generation among others. To eliminate the redundancies, lots of work have been done during compiling phase. However, not all redundancies can be easily detected or eliminated with compiler optimization passes due to limited optimization scopes, and execution contexts act as severe deterrents to static program analysis. There are also profiling tools which can reveal how resources are used. However, they can hardly distinguish whether the resource are worth fully used. More profiling tools are in need to diagnose resource wastage and pinpoint ine ciencies. We have developed three tools to pinpoint di↵erent types of ine ciencies in di↵erent granularity. We build Runtime Value Numbering (RVN), a dynamic fine-grained profiler to pinpoint and quantify redundant computations in an execution. It is based on the classical value numbering technique but works at runtime instead of compile time. We developed RedSpy–a fine-grained profiler to pinpoint and quantify value redundancies in program executions. Value redundancy may happen over time at same locations or in adjacent locations, and thus it has temporal and spatial locality. RedSpy identifies both temporal and spatial value locality. Furthermore, RedSpy is capable of identifying values that are approximately the same, enabling optimization opportunities in HPC codes that often use floating point computations. RVN and RedSpy are both instrumentation based tools. They provide comprehensive result while introducing high space and time overhead. Our lightweight framework, Witch, samples consecutive accesses to the same memory location by exploiting two ubiquitous hardware features: the performance monitoring units (PMU) and debug registers. Witch performs no instrumentation. Hence, witchcraft—tools built atop Witch—can detect a variety of software ine ciencies while introducing negligible slowdown and insignificant memory consumption and yet maintaining accuracy comparable to exhaustive instrumentation tools. Witch allowed us to scale our analysis to a large number of code bases. All the tools work on fully optimized binary executable and provide insightful optimization guidance by apportioning redundancies to their provenance–source lines and full calling contexts. We apply RVN, RedSpy and Witch on programs that were optimization targets for decades and guided by the tools, we were able to eliminate redundancies that resulted in significant speedups.
Coexistence Analysis Between 5G NR and TVRO in C-Band

This work reports a coexistence analysis between 5G New Radio (5G NR) and Satellite Television Receive Only (TVRO) in C-Band. The coexistence experiments to detect 5G NR interference in TVRO systems are based on the two following approaches: broadcast of analog and digital TV channels, received by a 1.7 meters parabolic antenna pointed to the Star One C2 geostationary satellite from Embratel; 100 MHz-bandwidth 5G NR link at 3.55 GHz with two printed log periodic antennas. The performance analysis has been carried out as a function of the TV channel quality signal, by means of varying the 5G power level at vertical polarization. Measured spectra of either radiofrequency (RF) and intermediate frequency (IF) signals are presented for demonstrating a probable interference problem due to the installation of 5G base stations close to TVRO user homes. For instance, there are still 22 million TVRO users in Brazil and 120 million homes attended by C-Band satellites in United States for radio and TV services. Finally, two efficient technological solutions are proposed and theoretically validated, using SF.1486 ITU-R recommendation, for mitigating 5G NR interference to TVRO and their results are properly compared to other techniques reported in literature.
Clinical investigation and genetic analysis of a peripheral sclerocornea pedigree

Abstract Background Sclerocornea is a rare congenital disorder characterized with opacification of the cornea. Here we report a non-consanguineous Chinese family with multiple peripheral sclerocornea patients spanning across three generations inherited in an autosomal dominant manner. Methods This is a retrospective case series of a peripheral sclerocornea pedigree. Comprehensive ophthalmic examinations were conducted and assessed on 14 pedigree members. Whole exome sequencing was used to identify the genetic alterations in the affected pedigree members. Lymphoblastoid cell lines (LCLs) were established using blood samples from the family members. Functional tests were performed with these cell lines. Results Six affected and eight unaffected members of a family with peripheral sclerocornea were examined. All affected individuals showed features of scleralization over the peripheral cornea of both eyes. Mean horizontal and vertical corneal diameter were found significantly decreased in the affected members. Significant differences were also observed on mean apex pachymetry between affected and unaffected subjects. These ophthalmic parameters did not resemble that of cornea plana. A RAD21C1348T variant was identified by whole-exome sequencing. Although this variant causes RAD21 R450C substitution at the separase cleavage site, cells from peripheral sclerocornea family members had no mitosis and ploidy defects. Conclusions We report a family of peripheral sclerocornea with no association with cornea plana. A RAD21 variant was found co-segregating with peripheral sclerocornea. Our results suggest that RAD21 functions, other than its cell cycle and chromosome segregation regulations, could underline the pathogenesis of peripheral sclerocornea.
Toward Uncovering Patterns of Certification Internalization

The number and variety of information systems (IS) certifications have increased continuously as the use of information technology has diversified and expanded. IS certifications are neutral third-party attestations of specific system characteristics and management principles to prove compliance with requirements. The reasons for organizations to adopt IS certifications are diverse, such as fostering learning and improvement, or demonstrating regulatory compliance. However, because of organizations’ diverse motivations to adopt certifications, organizations also differ in their degree of internalizing the certification. In particular, superficial, ceremonial adoption and a lack of internalization of certifications become critical issues harming the certification’s reputation and effectiveness. This short paper reports on preliminary findings from a qualitative study on the development of a data protection certification. Based on unique access to case companies throughout the certification attestation process, our research will provide insights into how motivations for adoption impact the internalization processes of organizations.
Detection and possible elimination of the first recorded population of the zebra mussel (Dreissena polymorpha) in Portugal from a reservoir

The zebra mussel, Dreissena polymorpha, has strong economic and environmental effects within a wide range of habitats, including reservoirs, and there is a need to monitor in advance of an arrival so that an elimination might be possible. We report the establishment of the zebra mussel in the Alfundão Reservoir, a small reservoir in south Portugal, 190 km away from the closest known population in Spain. The area has been monitored using suspended ropes since 2016, and during October 2019, mussels of 5–43.8 mm shell length were recorded for the first time in the Alfundão reservoir. The shallow lined reservoir was then chlorinated and drained. To date, this treatment appears to have been successful in eliminating this population. It is unknown how this mussel arrived, since the reservoir area has a surrounding exclusion zone.
Safety analysis of simultaneous cranioplasty and ventriculoperitoneal shunt placement.

AIM In this study, we investigated the safety of combined cranioplasty (CP) and ventriculoperitoneal shunt (VPS) placement. Furthermore, we investigated whether the sequence of these procedures affects the postoperative complication rates associated with staged CP and VPS placement. MATERIAL AND METHODS We retrospectively investigated patients who developed communicating hydrocephalus after decompressive craniectomy and subsequently underwent VPS placement and CP at the hospital at which this study was performed between January 2009 and December 2019. Patients were categorized into group 1 (simultaneous CP and VPS placement) and group 2 (CP and VPS placement performed separately). Group 2 was subcategorized into subgroup 2a (CP performed before VPS placement) and subgroup 2b (VPS placement performed before CP). The Student's t and Chi square tests were used to analyze intergroup differences. RESULTS This study included 86 patients; 22 in group 1 and 64 in group 2 (24 patients in subgroup 2a and 40 patients in subgroup 2b). No statistically significant difference was observed in the overall complication rates between groups 1 and 2 (36.4% vs. 28.1%, P=0.591). However, the incidence of infections was significantly higher in group 1 than in group 2 (22.7% vs. 4.7%, P=0.024). Subgroup analysis showed that the overall complication rate was signiﬁcantly lower in subgroup 2a than in subgroup 2b (12.5% vs. 37.5%, P=0.031). CONCLUSION Simultaneous CP and VPS placement is associated with a high incidence of infections. Moreover, compared with initial CP, initial VPS placement is associated with a significantly higher risk of overall complications in patients who undergo a staged procedure.
Failure Prediction of Hard Disk Drives Based on Adaptive Rao–Blackwellized Particle Filter Error Tracking Method

Active failure prediction of hard disk drives (HDDs) is critical to prevent data loss and spare parts replacement decisions. Existing methods for failure predictions of HDDs always used a binary classifier to distinguish the healthy or failed HDDs and cannot address the problem of variable degradation states. In this article, an adaptive error tracking method is proposed for the HDD failure prediction. This method regards the extracted degradation feature as time serials and uses a state filter to estimate the real-time HDD's health status. Then, the HDD failure online prediction is achieved according to the alarm threshold determined by the adaptive error tracking. The degradation of an HDD is described by a first-order Markov hybrid jump degradation model, and the advanced Rao–Blackwellized particle filter algorithm, together with the expectation-maximization (EM) algorithm, is derived to estimate the model parameters adaptively. Finally, to verify the effectiveness of the proposed method, an accelerated degradation test (ADT) based on the vibration was carried out. And the data from ADT and real data center show that the proposed method performs much better than the previous methods, such as Kalman filter, SVM, MD, and recurrent neural network (RNN) based methods, with respect to failure prediction and the alarm distance, which helps to backup data and optimize maintenance decision costs for users.
A Fault Diagnosis and Postfault Reconfiguration Scheme for Interleaved Boost Converter in PV-Based System

To utilize the solar photovoltaic (PV) energy efficiently, dc–dc converters are widely used in both grid-connected and stand-alone systems. Among the various topologies, interleaved dc–dc boost converter offers the benefit of modularity, high power density, and high efficiency along with reduced input current ripple to the PV panel, thereby improving its power extraction efficiency. Open-circuit faults in any of the semiconductor switches of interleaved boost converter could lead to unequal loading on the healthy phases and increase in ripple current that reduces the extraction efficiency of the PV system. To address this issue, a new fault detection and localization scheme is proposed in this article. The proposed scheme utilizes the switching-frequency-based harmonic component for fault detection and localization. Once the fault is localized, a postfault restoration and control strategy is also proposed to ensure equal current sharing among the remaining healthy modules within their maximum current rating and minimize the input current ripple in the PV panel. Detailed simulations are carried out to show the effectiveness of the proposed approach. A laboratory prototype of the interleaved converter is built to validate the proposed approach and experimental test results are provided.
Dietary periodisation for health and performance in world-class endurance athletes

Periodisation – defined as the systematic planning and sequencing of training blocks across macro, meso and micro cycles of training and racing as a means to optimise athletic adaptation and performance – has been implemented by coaches to athletes across most sports for several decades. Similarly to training, nutrition should also be periodised to support training and racing goals. For example, the diets of endurance athletes may move along the spectrum from low to high energy availability (EA) or low to high carbohydrate (CHO) availability (e.g. body composition management with brief periods of low EA or CHO vs optimised adherence to sports nutrition guidelines via high energy and CHO availability). Despite robust evidence behind current guidelines, the literature lacks systematic information on the knowledge and implementation of periodised nutrition strategies across various levels of training and racing by world class endurance athletes. Another popular dietary approach – chronic or long-term ketogenic low-CHO, high fat (LCHF) diet – has become popular among some athletes and scientists as a means to enhance endurance performance and to support health. Notably, current literature does not support the former claim of enhanced performance, and the majority of existing evidence in favour of the latter claim comes from research in clinical populations (such as obesity, cancer, and epilepsy). Since endurance athletes are at an especially high risk for low bone mineral density (BMD) and stress fractures, and as available evidence suggests that both acute low EA and CHO availability may have independent and negative effects on bone modelling process in active individuals, this is an important topic that has been largely unexplored in the literature to-date. Therefore, this thesis will investigate dietary periodisation approaches in elite endurance athletes as well as the effects of low energy and low CHO availability on direct and indirect outcomes of markers of bone modelling and bone health in this population.
Secrecy Outage Minimization for Wireless-Powered Relay Networks With Destination-Assisted Cooperative Jamming

To solve security vulnerability and energy scarcity problems in relay, we propose two secure relaying protocols, power splitting-based relaying (PSR) and time switching-based relaying (TSR), in a wireless-powered relay network with destination-assisted cooperative jamming. In these protocols, the relay adaptively controls the amount of energy harvested from the received signals using PS or TS policy, considering information leakage to the eavesdropper. We first prove the convexity of the secrecy outage probability with respect to the PS ratio (<inline-formula> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula>) and TS ratio (<inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>), and then derive the closed-form expressions of the optimal <inline-formula> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> for minimizing secrecy outage under the signal-to-noise ratio (SNR) assumption. Numerical results reveal that the proposed PSR and TSR protocols using the derived <inline-formula> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> can achieve near-optimal performance in terms of secrecy outage. It is observed that the optimal <inline-formula> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> do not depend on the eavesdropping channels in a high SNR regime such that the near-optimal secrecy outage can be achieved practically without knowledge of the eavesdropper location. Furthermore, intensive simulations reveal that it is advantageous to allocate more power to energy harvesting for PSR, whereas more time to signal processing for TSR to minimize secrecy outage.
Deep Reinforcement Learning for Smart City Communication Networks

Smart city communication networks hold the promise of harnessing the Internet of Things, smart devices, intelligent energy grids, autonomous cars, and many other data architectures to improve quality of life for every citizen. As time and progress have gradually shifted this concept from an idea into a reality, the possibilities for what services a smart city might provide have exploded. Along with that expansion, the number of devices that may need to be supported across a communications network has multiplied enormously. However, existing congestion control protocols are not equipped to support this higher requirement for network performance. New protocols are needed to provide higher data throughputs, reduce queuing delays and packet loss, and maintain stable and reliable communications pathways. The end-to-end congestion control protocol presented in this article does all these things. Called high throughput congestion control (HTCC), the framework takes full advantage of reinforcement learning and a fast growth algorithm to adaptively control the bytes in flight across the network's links to suit the prevailing network conditions. The result is a protocol that not only finds the optimal tradeoff between throughput, latency, and packet loss, but also significantly speeds up the learning process to avoid wasting network resources, use all free bandwidth and maximize network utilization. A comprehensive set of experiments with HTCC and six state-of-the-art protocols—Copa, PCC Vivace, PCC-Allegro, TCP Cubic, TaoVA-100x, and FillP-Sheep—demonstrate that, in most conditions, HTCC is able to make the best tradeoff between throughput, delay, and loss rate.