Miracle-dz/UniFAR-FTUs huggingface dataset:
By his words alone: the economic consequences of Rodrigo Duterte

Philippine President Rodrigo Duterte has gained worldwide notoriety for his foul-mouthed statements, particularly for his threats directed towards the nation’s largest businesses and their powerful owners. Such pronouncements, which may be mistaken for shifts in government policy, may inadvertently provoke the business sector to react negatively. This paper examines whether President Duterte's negative business-related pronouncements have an appreciable effect on the Philippine Stock Exchange Index (PSEi). We apply an interrupted time series model on PSEi data for the period June 30, 2016 until December 31, 2019 to determine Duterte’s impact on stock prices under six different intervention scenarios. Specifically, we test different classifications of business pronouncements— initial business pronouncements, anti-oligarch statements, personal attacks, and combinations of the three. The results show a significant relationship between Duterte’s negative business-related pronouncements on the PSEi closing price, with the biggest changes occurring during the first times he brought up a particular issue or addressed a certain personality. We aggregated the losses for the period 2018-2019 resulting from these pronouncements. For the five pronouncements, we estimate the combined losses to rise from ₱1 million on the day they were made to ₱47 million within five days and, as the market continues to adjust, up to ₱441 million within ten days.
BLOCKCHAIN: A NON-TECHNICAL PRIMER FOR MARKETING ACADEMICS

ABSTRACT In the ongoing march of industrial evolution there comes along technologies that have the power to transform businesses as we know it. The Internet revolutionized business/marketing in the nineties and today and bockchain has the potential to do the same for commercial transactions. Blockchain is a peer-to-peer model that can speed up processes resulting in robust tracking and reducing costs of transactions. Given the implications of this far-reaching technology, it is essential for marketing students to understand its significance in the conduct of marketing activities. Consequently, it is imperative that faculty comprehend aspects of the technology and its applications in marketing to integrate them in marketing courses. The purpose of the paper is to enlighten marketing faculty on the concept of blockchain in a non-technical manner along with highlighting its applications in marketing that can be imparted through their courses. To do so, the paper is structured around three research questions relating to (a) understanding the idea of blockchain technology; (b) expounding on the importance of the technology in marketing applications; and (c) illustrating how marketing faculty can integrate the concepts and application in marketing courses.
China quality award and the market value of the firm

Quality has always been an important factor affecting the competitive advantages and financial performance of firms. Some research has examined the impacts of Malcolm Baldrige Award and European Quality Award announcements on the market value of winners. However, the effect of the China Quality Award on firm market value has rarely been studied and has not been fully elucidated. On the basis of 85 China Quality Award announcements, this study explores whether winners show significant abnormal stock returns on the award announcement day using an event study. Some firm characteristics, such as ownership type, industry type, registered address, first time winning the award or not, and whether related firms won the awards are further considered. A market adjustment model is also adopted to re-estimate the short-term market reaction to test the robustness of our findings. It is found that China Quality Award winners do not show a significant market reaction for the full sample in the short term. However, the China Quality Award has brought significantly positive benefits to firms located in eastern China, first-time winners, and firms winning the award themselves. The long-term stock price performance is significantly positive. The findings may expand the research on the relationship between quality awards and firm market value in various institutional contexts.
Measuring Circular Supply Chain Risk: A Bayesian Network Methodology

The world is facing economic, as well as social, crisis due totheCOVID-19 pandemic. Implementing sustainable practices is one of the possible ways to address these issues. Adopting circular oriented techniques throughout the supply chain not only guarantees economic profitability, but also provides an edge to the organization in the market of fierce global competition. The concept of implementing circularity in the supply chain is novel and dynamic in nature, and it involves certain risk. In this study, a Bayesian Network methodology is adopted to analyze how the risk propagation takes place in a circular supply chain network of an automobile organization. The circular supply chain network consists of a group of manufacturers, retailers and recyclers, located in the Delhi–NCR region. Economic, environmental, social, technological, waste management, agile vulnerability, and risk of cannibalization are the major risk categories that were identified through an extensive literature review. Further, the impact of risk on the performance of the circular supply chain is analyzed by considering performance parameters such as lost sales, impact on supply chain revenue, and inventory holding cost. Risk exposure index is incorporated into the study to analyze the vulnerability of each node. The findings of the study reveal that the reverse side of the circular supply chain can be a source of risk propagation during the implementation of the circularity concept. This work is carried out under a single industry domain. In the future, risk propagation analysis can be examined in the supply chain of other sectors. The findings of the study can assist the supply chain managers and the risk experts to focus on the areas that are more vulnerable to risk.
Expanding SAR-based probabilistic deforestation detections using deep learning

In this work, we leverage deep learning to reproduce and expand Synthetic Aperture Radar (SAR) based deforestation detections generated using a probabilistic Bayesian model. Our Bayesian updating deforestation detections leverage SAR backscatter and InSAR coherence to perform change detection on forested areas and detect deforestation regardless of cloud cover. However, this model does not capture all deforestation events and is better suited to near-real time alerting than accurate forest loss acreage estimates. Here, we use SAR based probabilistic detections as deforested labels and Sentinel-2 optical composites as input features to train a neural network to differentiate deforested patches at various stages of regrowth from native forest. The deep learning model predictions demonstrate excellent recall of the original Bayesian label, and low precision due to providing better coverage of deforestation and detecting deforested patches not included in the imperfect Bayesian labels. These results provide an avenue to improve existing deforestation models, specifically with regards to their ability to quantify deforested acreage.
Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set

Artificial intelligence (AI) and machine learning algorithms are changing many facets of our lives and have great potential for disease diagnosis. In this Plenary Paper, Matek et al describe training a convolutional neural network model using 171 374 bone marrow cytology images from 945 patients with various hematological diseases before validating its accuracy in classifying single cells in an independent set of 627 images. The system can automatically classify 22 classes of bone marrow leukocytes, and with further improvements, it may bring AI-aided diagnosis of bone marrow biopsy specimens closer to fruition.
Unique insight into protein-DNA interactions from single molecule atomic force microscopy

Protein-DNA interactions are pivotal for many essential biological processes. Atomic force microscopy (AFM) imaging of protein-DNA systems involved in DNA target site search, identification, and processing by proteins has contributed invaluable information to our understanding of the underlying mechanisms. The single molecule 3D resolution of AFM enables us to uncover stoichiometries and conformational properties of protein-DNA complexes. Its molecular resolution places AFM at the interface between the atomic resolution achievable by crystallography and the comparably poor (typically > hundred nanometers) spatial resolution of optical microscopy. Furthermore, the transient character of protein interactions with nonspecific DNA sites, for example during their target site search renders these complexes difficult to resolve by standard ensemble methods. Here, we review current applications and capabilities of as well as novel advances in AFM imaging in protein-DNA interaction studies.
Patient Blood Management in der Chirurgie

▶ Abb. 2 Grafische Zusammenfassung der Ergebnisse aus Meybohm et al. [2] (Quelle: Meybohm P, Herrmann E, Steinbicker AU et al. Patient Blood Management is Associated With a Substantial Reduction of Red Blood Cell Utilization and Safe for Patientʼs Outcome: A Prospective, Multicenter Cohort Study With a Noninferiority Design. Ann Surg 2016; 264: 203– 211; https://journals.lww.com/annalsofsurgery). [rerif] Chirurgische Eingriffe sind oftmals mit einem hohen Blutverlust assoziiert, der zu einer erhöhten postoperativen Komplikationsrate führen kann. Patient Blood Management (PBM) ist ein evidenzbasiertes multimodales Konzept, welches unter Berücksichtigung modernster medizinischer Erkenntnisse zur Steigerung der Patientensicherheit eingesetzt wird.
Flying Among Stars: Jamming-Resilient Channel Selection for UAVs Through Aerial Constellations

Wireless communication between an unmanned aerial vehicle (UAV) and the ground base station is susceptible to adversarial jamming. In such situations, it is important for the UAV to indicate a new channel to the BS. This paper describes a method of creating spatial codes that map the chosen channel to the location of the UAVs in space, wherein the latter physically traverses the space from a given so called ”constellation points” to another. These points create patterns in the sky, analogous to modulation constellations in classical wireless communications, and are detected at the BS through a millimeter-wave radar sensor. A constellation point represents a distinct n-bit field mapped to a specific channel, allowing simultaneous frequency switching at both ends without any RF transmissions. The main contributions of this paper are: (i) We conduct experimental studies to demonstrate how such constellations may be formed using COTS UAVs and mmWave sensors, (ii) We develop a theoretical framework that maps a desired constellation design to error and band switching time, including multi-user scenario-specific challenges, (iii) We compare our approach against current FHSS technology and (iv) We experimentally demonstrate jamming resilient communications and validate system goodput for links formed by UAV-mounted software defined radios.
Diagnosis and Management of Hyperammonemia in Newborns: Is It Still a Challenge?

Background: Hyperammonaemia is a serious cause of mortality and morbidity duringin the neonatal period, regardless of the aetiology. Quickly differentiatingon between inherited metabolic diseases (IMDs) and other causes is important in terms of for treatment and prognosis. We This study aimed to determine the diagnostic and prognostic differences between IMD- and non-IMD-related causes with based on a literature review. Methods: Clinical and laboratory data of newborns treated for hyperammonaemia between 2016 and 2019 were evaluated retrospectively. Results: Hyperammonaemia was detected in 60 out of 1963 (3%) patients, and 25% of these patients were diagnosed with IMD. The most common non-IMD etiologies were sepsis (31.6%) and prematurity (31.6%). Significant differences were detected between the two groups inregarding gestational age (P=0.001) and birth weight (P=0.005)were detected (p=0.001 and p=0.005, respectively). Moreover, another significant difference was observed between the two groups in terms of glutamine (P=0.004), alanine (P=0.004), and citrulline (P=0.001) levels and as well as the proportions of glutamine to arginine (G/A)P=0.001), citrulline (G/CP=0.0001), ornithine (G/OP=0.003), and alanine (G/A) (P=0.003). Conclusion: Metabolic screening tests should be performed to rapidly diagnose hyperammonaemia. In addition to the diagnosing diagnosis of IMDs, it can promptly differentiate non-metabolic causes.
Evaluation Model of Operation State Based on Deep Learning for Smart Meter

The operation state detection of numerous smart meters is a significant problem caused by manual on-site testing. This paper addresses the problem of improving the malfunction detection efficiency of smart meters using deep learning and proposes a novel evaluation model of operation state for smart meter. This evaluation model adopts recurrent neural networks (RNN) to predict power consumption. According to the prediction residual between predicted power consumption and the observed power consumption, the malfunctioning smart meter is detected. The training efficiency for the prediction model is improved by using transfer learning (TL). This evaluation uses an accumulator algorithm and threshold setting with flexibility for abnormal detection. In the simulation experiment, the detection principle is demonstrated to improve efficient replacement and extend the average using time of smart meters. The effectiveness of the evaluation model was verified on the actual station dataset. It has accurately detected the operation state of smart meters.
Rising housing costs and income poverty among the elderly in Germany

Abstract Housing costs have been increasing rapidly in Germany in recent years. Given the importance of housing for the elderly, one may expect many to be forced to dedicate ever-larger shares of their income to housing costs. Using longitudinal data from the German Socio-Economic Panel (GSOEP), we examine how changes in housing costs between 1996 and 2017 have affected income poverty among Germany’s over-65s. Our results reveal that higher costs have indeed contributed to increased income poverty in old age in that period. Our pooled probit regression models as applied to Germany’s elderly show that increased housing costs mean tenants, homeowners with outstanding mortgages, single-person households and people with migration background all suffer a higher risk of poverty, while the risk remains lower for outright homeowners. Since the relative income position of the elderly is expected to further deteriorate in future, our study suggests a need for policy action to avoid a worsening in figures for old-age income poverty in Germany.
The Malaysian Garden Concept Design Branding: Whose Role is it Anyway?

Two decades ago, Malaysian leaders had expressed their desire to have a garden design concept that can represent Malaysia. This study explores the Malaysian Garden Concept (MGC) branding from the perspectives of experts recognized by the National Landscape Department (NLD). This study applies a qualitative research method, in which researchers have interviewed respondents using specific effective techniques. The MGC is meant for public parks and designed for all uses but has some significant issues. The finding found that intensive promotion, marketing, and advertising can help implement the concept of Malaysian Garden in the future. Keywords: Malaysian Garden; National Identity; Landscape Architecture; Concept Branding eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4. 2914
DETERMINATION OF DIFFERENT OPTICAL PROPERTIES FOR CUBIC TITANIUM DIOXIDE: AN AB – INITIO APPROACH

This paper presents an analysis of optical properties of cubic titanium dioxide (TiO2) using Orthogonalized Linear Combinations of Atomic Orbitals (OLCAO) basis set under the framework of Density Functional Theory (DFT). Many optical properties such as refractive index, extinction coefficient, reflectivity, absorption coefficient, photoconductivity, and loss coefficient have been studied and analyzed thoroughly. From the analysis of optical properties, it is seen that, cubic TiO2 supports interband transition between states. Reflectivity of pyrite structure TiO2 lies within IRvisible – UV region due to which it qualifies for coating industry. Furthermore, the results are compared with previous theoretical as well as with experimental results. It is found that DFT based simulation produces results which are close approximation to experimental results.
Missbrauch und Abhängigkeit von Benzodiazepinen und Z-Drugs

ZUSAMMENFASSUNG Missbrauch und Abhängigkeit von Sedativa und Hypnotika sind klinisch häufig (Prävalenz ca. 2%), insbesondere von Benzodiazepinen und Non-Benzodiazepin-Hypnotika (Z-Drugs). Beide Substanzgruppen haben ältere und weit toxischere Sedativa und Hypnotika wie Barbiturate und Meprobamat zu Recht verdrängt. Benzodiazepine wie Z-Drugs entfalten ihre Wirkung über den inhibitorischen GABA-Rezeptor und können beide eine erhebliche Toleranz induzieren, was klinisch zu Dosissteigerungen, physischer und psychischer Abhängigkeit, Kontrollverlust sowie Entzugssymptomen führen kann. Prädisponierende Faktoren sind neben dem Geschlecht, Frauen sind häufiger betroffen, vor allem psychiatrische und psychosomatische Erkrankungen, insbesondere Angst und Schlafstörungen, aber auch psychosomatische Störungen und chronische Schmerzerkrankungen. Besonders häufig und lange werden Benzodiazepine älteren Patienten verschrieben, entgegen aller Leitlinienempfehlungen. Therapeutisch gesichert ist, dass bei Benzodiazepinabhängig-keit ein langsames Ausschleichen über viele Wochen, manchmal sogar Monate notwendig ist. Ansonsten können erhebliche Entzugserscheinungen inklusive epileptischen Anfällen, Psychosen und Delire auftreten. Das Entzugssyndrom bei Sedativa und Hypnotika ist sehr vielgestaltig mit Depression, Agitation, innerer Unruhe und Perzeptions-und Schlafstörungen als häufigen Symptomen. Die übrige Therapie ist pragmatisch und richtet sich nach den zugrunde liegenden psychischen Störungen und Entzugssymptomen. Im Wesentlichen werden Antidepressiva eingesetzt. Kurzzeitinterventionen werden empfohlen. Psychotherapeutisch haben sich Psychoedukation, kognitive Verhaltenstherapie oder motivationale Therapien bewährt.
The effect of the natural antioxidants catalase and epigallocatechin added after thawing on the quality of dromedary camel spermatozoa

The objective of this study was to evaluate the effect of adding two natural antioxidants (Catalase and Epigallocatechin) to the thawing media on the quality of cryopreserved dromedary camel spermatozoa post-thaw. Also, an indirect measure of ROS production was performed by measuring malondialdehyde (MDA) production (a product of oxidative damage) post-thaw. Ejaculates from 6 adult dromedary camel males (3 ejaculates/male) were included in this study. Ejaculates were obtained using an artificial vagina, frozen in liquid nitrogen vapour (1 cm above the liquid) for 15 min and then plunged into liquid nitrogen for storage. Samples were thawed at 60 oC for 10 s. Semen evaluation was performed immediately after thawing and 3 aliquots were prepared: control, catalase and epigallocatechin. Semen samples where then evaluated for total motility, progressive motility, kinematics (Computer Assisted Sperm Analysis, CASA), acrosome integrity and membrane integrity at 1.5 and 3h post-thaw. The MDA concentration was measured 3 hours after thawing in the different treatments. Significantly (p<0.05) better values were obtained for the catalase group compared to the epigallocatechin or control groups for total motility (TM) and progressive motility (PM) and some kinematic parameters. None of the treatments showed any significant effect on vitality (VIT) or acrosome damage (AD) after thawing. For MDA production 3h after thawing, no significant effect could be demonstrated for the different treatments and no significant male effect was found. A significant difference was found between males regarding TM, PM and some kinematic parameters, as well as for VIT and AD after thawing. In conclusion, according to this study, addition of catalase to the thawing media can prove beneficial for the survival of dromedary camel sperm following cryopreservation by improving post-thaw sperm quality. The beneficial effects of addition of antioxidants in the cryopreservation media suggest that ROS are likely to be important contributors to the reduced viability of spermatozoa following cryopreservation.
Adherence to Antibiotic Stewardship Program Associated with Shorter Course of Treatment and Fewer Adverse Events

Group Name: NorthShore University HealthSystem Background: Prolonged antibiotic use has been attributed to an increased incidence of adverse drug events (ADEs). Cessation of unnecessary antibiotics would decrease length of treatment and may help prevent these adverse events. We evaluated whether an antibiotic stewardship intervention aimed at stopping unnecessary antibiotic usage would both shorten the duration of treatment and reduce ADEs. Methods: At NorthShore University HealthSystem, a 4-hospital, 832-bed system, we identified patients who were started on empiric antibiotics during a hospital admission between May 2, 2016, and June 30, 2018. Within 24 hours of antibiotic initiation, an infectious disease (ID) physician reviewed each patient chart. If the patient was unlikely to have a symptomatic bacterial infection, the ID physician left a note in the electronic medical record (EMR) recommending antibiotic cessation. Two physician reviewers retrospectively reviewed whether the treatment team accepted these recommendations and assessed potential ADEs for 30 days after the recommendation through inpatient and outpatient notes in the EMR. These ADEs were defined using previously published criteria. If the 2 reviewers disagreed on the presence of an ADE, an ID physician acted as the tie breaker. We compared the number of antibiotic days and the number of ADEs between cases in which the recommendations were followed and cases in which they were not. Results: We reviewed 168 cases: 78 (46.43%) followed recommendations and 90 (53.57%) did not. There were no significant differences in baseline patient characteristics between the 2 groups. There was a significant difference in total ADEs between the 2 groups: in 6 cases (7.69%) the recommendations were followed, and 21 (23.33%) they were not followed (P = .011). There was also a significant difference in antibiotic days between cases in which recommendations were followed (1.40 days) versus those in which they were not followed (1.99 days) (p < 0.001). Conclusions: Antibiotic-associated adverse events can cause harm to patients and increase healthcare costs, particularly when used for patients who are unlikely to have a bacterial infection. An antibiotic stewardship program to identify patients in an EMR who are unlikely to benefit from antibiotic use can decrease the length of total antibiotic usage and help prevent adverse events. Funding: No Disclosures: None Table 1.